The study focuses on the stability control measures for mining roadways in fault zones of deep mines,using Daqiang Coal Mine as a case study.The control system under consideration,referred to as"pre-splitting cut...The study focuses on the stability control measures for mining roadways in fault zones of deep mines,using Daqiang Coal Mine as a case study.The control system under consideration,referred to as"pre-splitting cutting roof+NPR anchor cable"(PSCR-NPR),is subjected to scrutiny through theoretical analysis,numerical modelling,and field trials.Furthermore,a comprehensive analysis is undertaken to evaluate the stability control mechanism of this particular technology.The study provides evidence that the utilization of deep-hole directional energy-concentrated blasting facilitates the attainment of directional roof cutting in roadways.The aforementioned procedure leads to the formation of a uniform structural surface on the roof of the roadway and causes modifications in the surrounding geological formation.The examination of the lateral abutment pressure and shear stress distribution,both prior to and subsequent to roof cutting,indicates that the implementation of pre-splitting techniques leads to a noteworthy reduction in pressure.The proposition of incorporating the safety factor Q for roof cutting height is suggested as a method to augment comprehension of the pressure relief phenomenon in the field of engineering.The analysis of numerical simulation has indicated that the optimal pressure relief effect of a mining roadway in a fault area is attained when the value of Q is 1.8.The NPR anchor cable exhibits noteworthy characteristics,including a high level of prestress,continuous resistance,and substantial deformation.After the excavation of the roadway,a notable reduction in radial stress occurs,leading to the reinstatement of the three-phase stress state in the surrounding rock.This restoration is attributed to the substantial prestress exerted on the radial stress.The termination point of the NPR anchor cable is strategically positioned within a stable rock formation,allowing for the utilization of the mechanical characteristics of the deep stable rock mass.This positioning serves to improve the load-bearing capacity of the surrounding rock.The mining roadway within the fault region of Daqiang Coal Mine is outfitted with the PSCR-NPR technology.The drop in shear stress experienced by the rock surrounding the roadway is estimated to be around 30%,whilst the low-stress region of the mining roadway extends by a factor of approximately 5.5.The magnitude of surface displacement convergence experiences a decrease of approximately 45%-50%.The study’s findings provide useful insights regarding the stable of mining roadway in characterized by fault zones.展开更多
To minimize negative effects of geostress distribution on mining safety near the fault areas, the UPM40 triaxial geostress testing system was introduced to conduct in-situ geostress measurements at three sites and nin...To minimize negative effects of geostress distribution on mining safety near the fault areas, the UPM40 triaxial geostress testing system was introduced to conduct in-situ geostress measurements at three sites and nine points by the borehole stress-relief method. The results of strain?confining pressure curves show that rock masses at the three measuring sites exhibit comprehensive linear elasticity in spite of various fissures or cracks within rocks. Horizontal and vertical stress components distribute discrepantly near the fault areas, and the maximum lateral pressure coefficient is as high as 6.15. The maximum principle stress ranges from 8.01 to 14.93 MPa, and stress directions are in the range of N78.07°W?N17.55°W. Geostresses near fault areas are dominated by the horizontal tectonic stresses, while the lower values, compared to those under similar geological conditions are due to stress release by the fault. Additionally, the fault and shear stress nearby are partially responsible for asymmetric elongation and southwesterly migration of orebodies.展开更多
The Qinghai Nanshan fault is a larger fault in the Northeastern Xizang Plateau.In previous studies,its movement characteristics are mainly investigated with geological and seismic observations,and the tectonic transfo...The Qinghai Nanshan fault is a larger fault in the Northeastern Xizang Plateau.In previous studies,its movement characteristics are mainly investigated with geological and seismic observations,and the tectonic transformation role of the fault on its east is not yet clear.This study uses data fusion to obtain denser GPS observations near the Qinghai Nanshan fault.Based on tectonic characteristics,we establish a block model to investigate the fault slip rate,locking degree,and slip deficit.The results show that the Qinghai Nanshan fault slip rate is characterized by sinistral and convergent movement.Both the sinistral and convergent rates display a decreasing trend from west to east.The locking degree and slip deficit are higher in the western segment(with an average of about 0.74 and 1.1 mm/a)and lower in the eastern segment.Then,we construct a strain rate field using GPS observations to analyze the regional strain characteristics.The results indicate that along the fault,the western segment shows a larger shear strain rate and negative dilation rate.Regional earthquake records show that the frequency of earthquakes is lower near the fault.The joint results suggest that the western segment may have a higher earthquake risk.In addition,the insignificant fault slip rate in the eastern segment may indicate that it does not participate in the tectonic transformation among the Riyueshan,Lajishan,and West Qinling faults.展开更多
The study of sedimentary mélanges holds pivotal importance in understanding orogenic processes and unveiling geodynamic mechanisms.In this study,we present findings on zircon U-Pb isotopes and whole-rock elementa...The study of sedimentary mélanges holds pivotal importance in understanding orogenic processes and unveiling geodynamic mechanisms.In this study,we present findings on zircon U-Pb isotopes and whole-rock elemental data concerning the recently uncovered Zongzhuo Formation sedimentary mélanges within the Dingri area.Field observations reveal the predominant composition of the Zongzhuo Formation,characterized by a matrix of sandstone-mudstone mixed with sand-conglomerates within native blocks exhibiting soft sediment deformation.Moreover,exotic blocks originating from littoral-neritic seas display evidence of landslide deformation.Our study identifies the depositional environment of the Zongzhuo Formation in Dingri as a slope turbidite fan,with its provenance traced back to the passive continental margin.Notably,this contrasts with the Zongzhuo Formation found in the Jiangzi-Langkazi area.Based on existing data,we conclude that the Zongzhuo Formation in the Dingri area was influenced by the Dingri-Gamba fault and emerged within a fault basin of the passive continental margin due to Neo-Tethys oceanic subduction during the Late Cretaceous period.Its provenance can be attributed to the littoral-neritic sea of the northern Tethys Himalaya region.This study holds significant implications for understanding the tectonic evolution of Tethys Himalaya and for reevaluating the activity of the Dingri-Gamba fault,as it controls the active deposition of the Zongzhuo Formation.展开更多
Recently,intelligent fault diagnosis based on deep learning has been extensively investigated,exhibiting state-of-the-art performance.However,the deep learning model is often not truly trusted by users due to the lack...Recently,intelligent fault diagnosis based on deep learning has been extensively investigated,exhibiting state-of-the-art performance.However,the deep learning model is often not truly trusted by users due to the lack of interpretability of“black box”,which limits its deployment in safety-critical applications.A trusted fault diagnosis system requires that the faults can be accurately diagnosed in most cases,and the human in the deci-sion-making loop can be found to deal with the abnormal situa-tion when the models fail.In this paper,we explore a simplified method for quantifying both aleatoric and epistemic uncertainty in deterministic networks,called SAEU.In SAEU,Multivariate Gaussian distribution is employed in the deep architecture to compensate for the shortcomings of complexity and applicability of Bayesian neural networks.Based on the SAEU,we propose a unified uncertainty-aware deep learning framework(UU-DLF)to realize the grand vision of trustworthy fault diagnosis.Moreover,our UU-DLF effectively embodies the idea of“humans in the loop”,which not only allows for manual intervention in abnor-mal situations of diagnostic models,but also makes correspond-ing improvements on existing models based on traceability analy-sis.Finally,two experiments conducted on the gearbox and aero-engine bevel gears are used to demonstrate the effectiveness of UU-DLF and explore the effective reasons behind.展开更多
Mobile Edge Computing(MEC)is a technology designed for the on-demand provisioning of computing and storage services,strategically positioned close to users.In the MEC environment,frequently accessed content can be dep...Mobile Edge Computing(MEC)is a technology designed for the on-demand provisioning of computing and storage services,strategically positioned close to users.In the MEC environment,frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery,ultimately enhancing the quality of the user experience.However,due to the typical placement of edge devices and nodes at the network’s periphery,these components may face various potential fault tolerance challenges,including network instability,device failures,and resource constraints.Considering the dynamic nature ofMEC,making high-quality content caching decisions for real-time mobile applications,especially those sensitive to latency,by effectively utilizing mobility information,continues to be a significant challenge.In response to this challenge,this paper introduces FT-MAACC,a mobility-aware caching solution grounded in multi-agent deep reinforcement learning and equipped with fault tolerance mechanisms.This approach comprehensively integrates content adaptivity algorithms to evaluate the priority of highly user-adaptive cached content.Furthermore,it relies on collaborative caching strategies based onmulti-agent deep reinforcement learningmodels and establishes a fault-tolerancemodel to ensure the system’s reliability,availability,and persistence.Empirical results unequivocally demonstrate that FTMAACC outperforms its peer methods in cache hit rates and transmission latency.展开更多
Electrolysis tanks are used to smeltmetals based on electrochemical principles,and the short-circuiting of the pole plates in the tanks in the production process will lead to high temperatures,thus affecting normal pr...Electrolysis tanks are used to smeltmetals based on electrochemical principles,and the short-circuiting of the pole plates in the tanks in the production process will lead to high temperatures,thus affecting normal production.Aiming at the problems of time-consuming and poor accuracy of existing infrared methods for high-temperature detection of dense pole plates in electrolysis tanks,an infrared dense pole plate anomalous target detection network YOLOv5-RMF based on You Only Look Once version 5(YOLOv5)is proposed.Firstly,we modified the Real-Time Enhanced Super-Resolution Generative Adversarial Network(Real-ESRGAN)by changing the U-shaped network(U-Net)to Attention U-Net,to preprocess the images;secondly,we propose a new Focus module that introduces the Marr operator,which can provide more boundary information for the network;again,because Complete Intersection over Union(CIOU)cannot accommodate target borders that are increasing and decreasing,replace CIOU with Extended Intersection over Union(EIOU),while the loss function is changed to Focal and Efficient IOU(Focal-EIOU)due to the different difficulty of sample detection.On the homemade dataset,the precision of our method is 94%,the recall is 70.8%,and the map@.5 is 83.6%,which is an improvement of 1.3%in precision,9.7%in recall,and 7%in map@.5 over the original network.The algorithm can meet the needs of electrolysis tank pole plate abnormal temperature detection,which can lay a technical foundation for improving production efficiency and reducing production waste.展开更多
With drilling and seismic data of Transtensional(strike-slip)Fault System in the Ziyang area of the central Sichuan Basin,SW China plane-section integrated structural interpretation,3-D fault framework model building,...With drilling and seismic data of Transtensional(strike-slip)Fault System in the Ziyang area of the central Sichuan Basin,SW China plane-section integrated structural interpretation,3-D fault framework model building,fault throw analyzing,and balanced profile restoration,it is pointed out that the transtensional fault system in the Ziyang 3-D seismic survey consists of the northeast-trending F_(I)19 and F_(I)20 fault zones dominated by extensional deformation,as well as 3 sets of northwest-trending en echelon normal faults experienced dextral shear deformation.Among them,the F_(I)19 and F_(I)20 fault zones cut through the Neoproterozoic to Lower Triassic Jialingjiang Formation,presenting a 3-D structure of an“S”-shaped ribbon.And before Permian and during the Early Triassic,the F_(I)19 and F_(I)20 fault zones underwent at least two periods of structural superimposition.Besides,the 3 sets of northwest-trending en echelon normal faults are composed of small normal faults arranged in pairs,with opposite dip directions and partially left-stepped arrangement.And before Permian,they had formed almost,restricting the eastward growth and propagation of the F_(I)19 fault zone.The F_(I)19 and F_(I)20 fault zones communicate multiple sets of source rocks and reservoirs from deep to shallow,and the timing of fault activity matches well with oil and gas generation peaks.If there were favorable Cambrian-Triassic sedimentary facies and reservoirs developing on the local anticlinal belts of both sides of the F_(I)19 and F_(I)20 fault zones,the major reservoirs in this area are expected to achieve breakthroughs in oil and gas exploration.展开更多
Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend o...Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.展开更多
Deep learning(DL) is progressively popular as a viable alternative to traditional signal processing(SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis methods dif...Deep learning(DL) is progressively popular as a viable alternative to traditional signal processing(SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis methods difficult to be trusted and understood by industrial users. In addition, the extraction of weak fault features from signals with heavy noise is imperative in industrial applications. To address these limitations, inspired by the Filterbank-Feature-Decision methodology, we propose a new Signal Processing Informed Neural Network(SPINN) framework by embedding SP knowledge into the DL model. As one of the practical implementations for SPINN, a denoising fault-aware wavelet network(DFAWNet) is developed, which consists of fused wavelet convolution(FWConv), dynamic hard thresholding(DHT),index-based soft filtering(ISF), and a classifier. Taking advantage of wavelet transform, FWConv extracts multiscale features while learning wavelet scales and selecting important wavelet bases automatically;DHT dynamically eliminates noise-related components via point-wise hard thresholding;inspired by index-based filtering, ISF optimizes and selects optimal filters for diagnostic feature extraction. It’s worth noting that SPINN may be readily applied to different deep learning networks by simply adding filterbank and feature modules in front. Experiments results demonstrate a significant diagnostic performance improvement over other explainable or denoising deep learning networks. The corresponding code is available at https://github. com/alber tszg/DFAWn et.展开更多
As one of the main controlling factors of oil and gas accumulation,faults are closely related to the distribution of oil and gas reservoirs.Studying how faults control petroliferous basins is particularly important.In...As one of the main controlling factors of oil and gas accumulation,faults are closely related to the distribution of oil and gas reservoirs.Studying how faults control petroliferous basins is particularly important.In this work,we investigated the plane positions of major faults in the China seas and its adjacent areas using the normalized vertical derivative of the total horizontal derivative(NVDR-THDR)of the Bouguer gravity anomaly,the fusion results of gravity and magnetic anomalies,and the residual Bouguer gravity anomaly.The apparent depths of major faults in the China seas and its adjacent areas were inverted using the Tilt-Euler method based on the Bouguer gravity anomaly.The results show that the strikes of the faults in the China seas and its adjacent areas are mainly NE and NW,followed by EW,and near-SN.Among them,the lengths of most ultra-crustal faults are in the range of 1000–3000 km,and their apparent depths lie between 10 km and 40 km.The lengths of crustal faults lie between 300 km and 1000 km,and their apparent depths are between 0 km and 20 km.According to the plane positions and apparent depths of the faults,we put forward the concept of fault influence factor for the first time.Based on this factor,the key areas for oil and gas exploration were found as follows:the east of South North China Basin in the intracontinental rift basins;the southeast region of East China Sea Shelf Basin,the Taixinan and Qiongdongnan basins in the continental margin rift basins;Zhongjiannan Basin in the strike-slip pull-apart basins;the Liyue,Beikang,and the Nanweixi basins in the rifted continental basins.This work provides valuable insights into oil and gas exploration,mineral resource exploration,and deep geological structure research in the China seas and its adjacent areas.展开更多
On August 6,2023,a magnitude MW5.5 earthquake struck Pingyuan County,Dezhou City,Shandong Province,China.This event was significant as no large earthquakes had been recorded in the region for over a century,and no act...On August 6,2023,a magnitude MW5.5 earthquake struck Pingyuan County,Dezhou City,Shandong Province,China.This event was significant as no large earthquakes had been recorded in the region for over a century,and no active fault had been previously identified.This study collects 1309 P-wave arrival times and 866 S-wave arrival times from 74 seismic stations less than 200 km to the epicenter to constrain the spatial distribution of the mainshock and its 125 early aftershocks by the double difference earthquake relocation method,and selects 864 P-waveforms from 288 stations located within 800 km of the epicenter to constrain the focal mechanism solution of the mainshock through centroid moment tensor inversion.The relocation and the inversion indicate,the Pingyuan MW5.5 earthquake was caused by a rupture on a buried fault,likely an extensive segment of the Gaotang fault.This buried fault exhibited a dip of approximately 75°to the northwest,with a strike of 222°,similar to the Gaotang fault.The rupture initiated at the depth of 18.6 km and propagated upward and northeastward.However,the ground surface was not broken.The total duration of the rupture was~6.0 s,releasing the scalar moment of 2.5895×1017 N·m,equivalent to MW5.54.The moment rate reached the maximum only 1.4 seconds after the rupture initiation,and the 90%scalar moment was released in the first 4.6 s.In the first 1.4 seconds of the rupture process,the rupture velocity was estimated to be 2.6 km/s,slower than the local S-wave velocity.As the rupture neared its end,the rupture velocity decreased significantly.This study provides valuable insights into the seismic characteristics of the Pingyuan MW5.5 earthquake,shedding light on the previously unidentified buried fault responsible for the seismic activity in the region.Understanding the behavior of such faults is crucial for assessing seismic hazards and enhancing earthquake preparedness in the future.展开更多
The angle α between the fault strike and the axial direction of the roadway produces different damage characteristics. In this paper, the research methodology includes theoretical analyses, numerical simulations and ...The angle α between the fault strike and the axial direction of the roadway produces different damage characteristics. In this paper, the research methodology includes theoretical analyses, numerical simulations and field experiments in the context of the Daqiang coal mine located in Shenyang, China. The stability control countermeasure of "pre-splitting cutting roof + NPR anchor cable"(PSCR-NPR) is simultaneously proposed. According to the different deformation characteristics of the roadway, the faults are innovatively classified into three types, with α of type I being 0°-30°, α of type II being 30°-60°, and α of type III being 60°-90°. The full-cycle stress evolution paths during mining roadway traverses across different types of faults are investigated by numerical simulation. Different pinch angles α lead to high stress concentration areas at different locations in the surrounding rock. The non-uniform stress field formed in the shallow surrounding rock is an important reason for the instability of the roadway. The pre-cracked cut top shifted the high stress region to the deep rock mass and formed a low stress region in the shallow rock mass. The high prestressing NPR anchor cable transforms the non-uniform stress field of the shallow surrounding rock into a uniform stress field. PSCR-NPR is applied in the fault-through roadway of Daqiang mine. The low stress area of the surrounding rock was enlarged by 3-7 times, and the cumulative convergence was reduced by 45%-50%. It provides a reference for the stability control of the deep fault-through mining roadway.展开更多
On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage ...On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage and substantial economic loss. In this study, we established a coseismic landslide database triggered by Luding Ms 6.8 earthquake, which includes 4794 landslides with a total area of 46.79 km^(2). The coseismic landslides primarily consisted of medium and small-sized landslides, characterized by shallow surface sliding. Some exhibited characteristics of high-position initiation resulted in the obstruction or partial obstruction of rivers, leading to the formation of dammed lakes. Our research found that the coseismic landslides were predominantly observed on slopes ranging from 30° to 50°, occurring at between 1000 m and 2500 m, with slope aspects varying from 90° to 180°. Landslides were also highly developed in granitic bodies that had experienced structural fracturing and strong-tomoderate weathering. Coseismic landslides concentrated within a 6 km range on both sides of the Xianshuihe and Daduhe fault zones. The area and number of coseismic landslides exhibited a negative correlation with the distance to fault lines, road networks, and river systems, as they were influenced by fault activity, road excavation, and river erosion. The coseismic landslides were mainly distributed in the southeastern region of the epicenter, exhibiting relatively concentrated patterns within the IX-degree zones such as Moxi Town, Wandong River basin, Detuo Town to Wanggangping Township. Our research findings provide important data on the coseismic landslides triggered by the Luding Ms 6.8 earthquake and reveal the spatial distribution patterns of these landslides. These findings can serve as important references for risk mitigation, reconstruction planning, and regional earthquake disaster research in the earthquake-affected area.展开更多
Many locations with concentrated hydrates at vents have confirmed the presence of abundant thermogenic gas in the middle of the Qiongdongnan Basin(QDNB).However,the impact of deep structures on gasbearing fluids migra...Many locations with concentrated hydrates at vents have confirmed the presence of abundant thermogenic gas in the middle of the Qiongdongnan Basin(QDNB).However,the impact of deep structures on gasbearing fluids migration and gas hydrates distribution in tectonically inactive regions is still unclear.In this study,the authors apply high-resolution 3D seismic and logging while drilling(LWD)data from the middle of the QDNB to investigate the influence of deep-large faults on gas chimneys and preferred gasescape pipes.The findings reveal the following:(1)Two significant deep-large faults,F1 and F2,developed on the edge of the Songnan Low Uplift,control the dominant migration of thermogenic hydrocarbons and determine the initial locations of gas chimneys.(2)The formation of gas chimneys is likely related to fault activation and reactivation.Gas chimney 1 is primarily arises from convergent fluid migration resulting from the intersection of the two faults,while the gas chimney 2 benefits from a steeper fault plane and shorter migration distance of fault F2.(3)Most gas-escape pipes are situated near the apex of the two faults.Their reactivations facilitate free gas flow into the GHSZ and contribute to the formation of fracture‐filling hydrates.展开更多
Dear Editor,This letter presents a novel dynamic vision enabled contactless cross-domain fault diagnosis method with neuromorphic computing.The event-based camera is adopted to capture the machine vibration states in ...Dear Editor,This letter presents a novel dynamic vision enabled contactless cross-domain fault diagnosis method with neuromorphic computing.The event-based camera is adopted to capture the machine vibration states in the perspective of vision.展开更多
Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measur...Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measure, a principal method is designed for quantifying the detectabilities of fault detection algorithms over special datasets.展开更多
This work presents a novel wavelet-based denoising technique for improving the signal-to-noise ratio(SNR)of nonsteady vibration signals in hardware redundant systems.The proposed method utilizes the relationship betwe...This work presents a novel wavelet-based denoising technique for improving the signal-to-noise ratio(SNR)of nonsteady vibration signals in hardware redundant systems.The proposed method utilizes the relationship between redundant hardware components to effectively separate fault-related components from the vibration signature,thus enhancing fault detection accuracy.The study evaluates the proposed technique on two mechanically identical subsystems that are simultaneously controlled under the same speed and load inputs,with and without the proposed denoising step.The results demonstrate an increase in detection accuracy when incorporating the proposed denoising method into a fault detection system designed for hardware redundant machinery.This work is original in its application of a new method for improving performance when using residual analysis for fault detection in hardware redundant machinery configurations.Moreover,the proposed methodology is applicable to nonstationary equipment that experiences changes in both speed and load.展开更多
The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source domain.However,in engineering scenarios,achieving such high-quality label annotatio...The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source domain.However,in engineering scenarios,achieving such high-quality label annotation is difficult and expensive.The incorrect label annotation produces two negative effects:1)the complex decision boundary of diagnosis models lowers the generalization performance on the target domain,and2)the distribution of target domain samples becomes misaligned with the false-labeled samples.To overcome these negative effects,this article proposes a solution called the label recovery and trajectory designable network(LRTDN).LRTDN consists of three parts.First,a residual network with dual classifiers is to learn features from cross-domain samples.Second,an annotation check module is constructed to generate a label anomaly indicator that could modify the abnormal labels of false-labeled samples in the source domain.With the training of relabeled samples,the complexity of diagnosis model is reduced via semi-supervised learning.Third,the adaptation trajectories are designed for sample distributions across domains.This ensures that the target domain samples are only adapted with the pure-labeled samples.The LRTDN is verified by two case studies,in which the diagnosis knowledge of bearings is transferred across different working conditions as well as different yet related machines.The results show that LRTDN offers a high diagnosis accuracy even in the presence of incorrect annotation.展开更多
The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault lo...The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.展开更多
基金funded by the National Natural Science Foundation of China(52174096,42277174)the Fundamental Research Funds for the Central Universities(2022YJSSB03)the Scientific and Technological Projects of Henan Province(232102320238)。
文摘The study focuses on the stability control measures for mining roadways in fault zones of deep mines,using Daqiang Coal Mine as a case study.The control system under consideration,referred to as"pre-splitting cutting roof+NPR anchor cable"(PSCR-NPR),is subjected to scrutiny through theoretical analysis,numerical modelling,and field trials.Furthermore,a comprehensive analysis is undertaken to evaluate the stability control mechanism of this particular technology.The study provides evidence that the utilization of deep-hole directional energy-concentrated blasting facilitates the attainment of directional roof cutting in roadways.The aforementioned procedure leads to the formation of a uniform structural surface on the roof of the roadway and causes modifications in the surrounding geological formation.The examination of the lateral abutment pressure and shear stress distribution,both prior to and subsequent to roof cutting,indicates that the implementation of pre-splitting techniques leads to a noteworthy reduction in pressure.The proposition of incorporating the safety factor Q for roof cutting height is suggested as a method to augment comprehension of the pressure relief phenomenon in the field of engineering.The analysis of numerical simulation has indicated that the optimal pressure relief effect of a mining roadway in a fault area is attained when the value of Q is 1.8.The NPR anchor cable exhibits noteworthy characteristics,including a high level of prestress,continuous resistance,and substantial deformation.After the excavation of the roadway,a notable reduction in radial stress occurs,leading to the reinstatement of the three-phase stress state in the surrounding rock.This restoration is attributed to the substantial prestress exerted on the radial stress.The termination point of the NPR anchor cable is strategically positioned within a stable rock formation,allowing for the utilization of the mechanical characteristics of the deep stable rock mass.This positioning serves to improve the load-bearing capacity of the surrounding rock.The mining roadway within the fault region of Daqiang Coal Mine is outfitted with the PSCR-NPR technology.The drop in shear stress experienced by the rock surrounding the roadway is estimated to be around 30%,whilst the low-stress region of the mining roadway extends by a factor of approximately 5.5.The magnitude of surface displacement convergence experiences a decrease of approximately 45%-50%.The study’s findings provide useful insights regarding the stable of mining roadway in characterized by fault zones.
基金Projects(50934002,51104011)supported by the National Natural Science Foundation of ChinaProject(2012BAB08B02)supported by the National Key Technologies R&D Program during the 12th Five-year Plan of China
文摘To minimize negative effects of geostress distribution on mining safety near the fault areas, the UPM40 triaxial geostress testing system was introduced to conduct in-situ geostress measurements at three sites and nine points by the borehole stress-relief method. The results of strain?confining pressure curves show that rock masses at the three measuring sites exhibit comprehensive linear elasticity in spite of various fissures or cracks within rocks. Horizontal and vertical stress components distribute discrepantly near the fault areas, and the maximum lateral pressure coefficient is as high as 6.15. The maximum principle stress ranges from 8.01 to 14.93 MPa, and stress directions are in the range of N78.07°W?N17.55°W. Geostresses near fault areas are dominated by the horizontal tectonic stresses, while the lower values, compared to those under similar geological conditions are due to stress release by the fault. Additionally, the fault and shear stress nearby are partially responsible for asymmetric elongation and southwesterly migration of orebodies.
基金supported by the National Natural Science Foundation of China(41874011,42074007)the Fundamental Research Funds for the Central Universities(2042023kfyq01)。
文摘The Qinghai Nanshan fault is a larger fault in the Northeastern Xizang Plateau.In previous studies,its movement characteristics are mainly investigated with geological and seismic observations,and the tectonic transformation role of the fault on its east is not yet clear.This study uses data fusion to obtain denser GPS observations near the Qinghai Nanshan fault.Based on tectonic characteristics,we establish a block model to investigate the fault slip rate,locking degree,and slip deficit.The results show that the Qinghai Nanshan fault slip rate is characterized by sinistral and convergent movement.Both the sinistral and convergent rates display a decreasing trend from west to east.The locking degree and slip deficit are higher in the western segment(with an average of about 0.74 and 1.1 mm/a)and lower in the eastern segment.Then,we construct a strain rate field using GPS observations to analyze the regional strain characteristics.The results indicate that along the fault,the western segment shows a larger shear strain rate and negative dilation rate.Regional earthquake records show that the frequency of earthquakes is lower near the fault.The joint results suggest that the western segment may have a higher earthquake risk.In addition,the insignificant fault slip rate in the eastern segment may indicate that it does not participate in the tectonic transformation among the Riyueshan,Lajishan,and West Qinling faults.
基金supported by the Geological Survey Project of the China Geological Survey(Grant No.DD20211547)the Basic Survey Project of the Command Center of Natural Resources Comprehensive Survey(Grant No.ZD20220508)。
文摘The study of sedimentary mélanges holds pivotal importance in understanding orogenic processes and unveiling geodynamic mechanisms.In this study,we present findings on zircon U-Pb isotopes and whole-rock elemental data concerning the recently uncovered Zongzhuo Formation sedimentary mélanges within the Dingri area.Field observations reveal the predominant composition of the Zongzhuo Formation,characterized by a matrix of sandstone-mudstone mixed with sand-conglomerates within native blocks exhibiting soft sediment deformation.Moreover,exotic blocks originating from littoral-neritic seas display evidence of landslide deformation.Our study identifies the depositional environment of the Zongzhuo Formation in Dingri as a slope turbidite fan,with its provenance traced back to the passive continental margin.Notably,this contrasts with the Zongzhuo Formation found in the Jiangzi-Langkazi area.Based on existing data,we conclude that the Zongzhuo Formation in the Dingri area was influenced by the Dingri-Gamba fault and emerged within a fault basin of the passive continental margin due to Neo-Tethys oceanic subduction during the Late Cretaceous period.Its provenance can be attributed to the littoral-neritic sea of the northern Tethys Himalaya region.This study holds significant implications for understanding the tectonic evolution of Tethys Himalaya and for reevaluating the activity of the Dingri-Gamba fault,as it controls the active deposition of the Zongzhuo Formation.
基金supported in part by the National Natural Science Foundation of China(52105116)Science Center for gas turbine project(P2022-DC-I-003-001)the Royal Society award(IEC\NSFC\223294)to Professor Asoke K.Nandi.
文摘Recently,intelligent fault diagnosis based on deep learning has been extensively investigated,exhibiting state-of-the-art performance.However,the deep learning model is often not truly trusted by users due to the lack of interpretability of“black box”,which limits its deployment in safety-critical applications.A trusted fault diagnosis system requires that the faults can be accurately diagnosed in most cases,and the human in the deci-sion-making loop can be found to deal with the abnormal situa-tion when the models fail.In this paper,we explore a simplified method for quantifying both aleatoric and epistemic uncertainty in deterministic networks,called SAEU.In SAEU,Multivariate Gaussian distribution is employed in the deep architecture to compensate for the shortcomings of complexity and applicability of Bayesian neural networks.Based on the SAEU,we propose a unified uncertainty-aware deep learning framework(UU-DLF)to realize the grand vision of trustworthy fault diagnosis.Moreover,our UU-DLF effectively embodies the idea of“humans in the loop”,which not only allows for manual intervention in abnor-mal situations of diagnostic models,but also makes correspond-ing improvements on existing models based on traceability analy-sis.Finally,two experiments conducted on the gearbox and aero-engine bevel gears are used to demonstrate the effectiveness of UU-DLF and explore the effective reasons behind.
基金supported by the Innovation Fund Project of Jiangxi Normal University(YJS2022065)the Domestic Visiting Program of Jiangxi Normal University.
文摘Mobile Edge Computing(MEC)is a technology designed for the on-demand provisioning of computing and storage services,strategically positioned close to users.In the MEC environment,frequently accessed content can be deployed and cached on edge servers to optimize the efficiency of content delivery,ultimately enhancing the quality of the user experience.However,due to the typical placement of edge devices and nodes at the network’s periphery,these components may face various potential fault tolerance challenges,including network instability,device failures,and resource constraints.Considering the dynamic nature ofMEC,making high-quality content caching decisions for real-time mobile applications,especially those sensitive to latency,by effectively utilizing mobility information,continues to be a significant challenge.In response to this challenge,this paper introduces FT-MAACC,a mobility-aware caching solution grounded in multi-agent deep reinforcement learning and equipped with fault tolerance mechanisms.This approach comprehensively integrates content adaptivity algorithms to evaluate the priority of highly user-adaptive cached content.Furthermore,it relies on collaborative caching strategies based onmulti-agent deep reinforcement learningmodels and establishes a fault-tolerancemodel to ensure the system’s reliability,availability,and persistence.Empirical results unequivocally demonstrate that FTMAACC outperforms its peer methods in cache hit rates and transmission latency.
文摘Electrolysis tanks are used to smeltmetals based on electrochemical principles,and the short-circuiting of the pole plates in the tanks in the production process will lead to high temperatures,thus affecting normal production.Aiming at the problems of time-consuming and poor accuracy of existing infrared methods for high-temperature detection of dense pole plates in electrolysis tanks,an infrared dense pole plate anomalous target detection network YOLOv5-RMF based on You Only Look Once version 5(YOLOv5)is proposed.Firstly,we modified the Real-Time Enhanced Super-Resolution Generative Adversarial Network(Real-ESRGAN)by changing the U-shaped network(U-Net)to Attention U-Net,to preprocess the images;secondly,we propose a new Focus module that introduces the Marr operator,which can provide more boundary information for the network;again,because Complete Intersection over Union(CIOU)cannot accommodate target borders that are increasing and decreasing,replace CIOU with Extended Intersection over Union(EIOU),while the loss function is changed to Focal and Efficient IOU(Focal-EIOU)due to the different difficulty of sample detection.On the homemade dataset,the precision of our method is 94%,the recall is 70.8%,and the map@.5 is 83.6%,which is an improvement of 1.3%in precision,9.7%in recall,and 7%in map@.5 over the original network.The algorithm can meet the needs of electrolysis tank pole plate abnormal temperature detection,which can lay a technical foundation for improving production efficiency and reducing production waste.
基金Supported by the Key Project of National Natural Science Foundation of China(42330810).
文摘With drilling and seismic data of Transtensional(strike-slip)Fault System in the Ziyang area of the central Sichuan Basin,SW China plane-section integrated structural interpretation,3-D fault framework model building,fault throw analyzing,and balanced profile restoration,it is pointed out that the transtensional fault system in the Ziyang 3-D seismic survey consists of the northeast-trending F_(I)19 and F_(I)20 fault zones dominated by extensional deformation,as well as 3 sets of northwest-trending en echelon normal faults experienced dextral shear deformation.Among them,the F_(I)19 and F_(I)20 fault zones cut through the Neoproterozoic to Lower Triassic Jialingjiang Formation,presenting a 3-D structure of an“S”-shaped ribbon.And before Permian and during the Early Triassic,the F_(I)19 and F_(I)20 fault zones underwent at least two periods of structural superimposition.Besides,the 3 sets of northwest-trending en echelon normal faults are composed of small normal faults arranged in pairs,with opposite dip directions and partially left-stepped arrangement.And before Permian,they had formed almost,restricting the eastward growth and propagation of the F_(I)19 fault zone.The F_(I)19 and F_(I)20 fault zones communicate multiple sets of source rocks and reservoirs from deep to shallow,and the timing of fault activity matches well with oil and gas generation peaks.If there were favorable Cambrian-Triassic sedimentary facies and reservoirs developing on the local anticlinal belts of both sides of the F_(I)19 and F_(I)20 fault zones,the major reservoirs in this area are expected to achieve breakthroughs in oil and gas exploration.
基金funded by the Science and Technology Project of China Southern Power Grid(YNKJXM20210175)the National Natural Science Foundation of China(52177070).
文摘Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.
基金National Natural Science Foundation of China (Grant Nos. 51835009, 52105116)China Postdoctoral Science Foundation (Grant Nos. 2021M692557, 2021TQ0263)。
文摘Deep learning(DL) is progressively popular as a viable alternative to traditional signal processing(SP) based methods for fault diagnosis. However, the lack of explainability makes DL-based fault diagnosis methods difficult to be trusted and understood by industrial users. In addition, the extraction of weak fault features from signals with heavy noise is imperative in industrial applications. To address these limitations, inspired by the Filterbank-Feature-Decision methodology, we propose a new Signal Processing Informed Neural Network(SPINN) framework by embedding SP knowledge into the DL model. As one of the practical implementations for SPINN, a denoising fault-aware wavelet network(DFAWNet) is developed, which consists of fused wavelet convolution(FWConv), dynamic hard thresholding(DHT),index-based soft filtering(ISF), and a classifier. Taking advantage of wavelet transform, FWConv extracts multiscale features while learning wavelet scales and selecting important wavelet bases automatically;DHT dynamically eliminates noise-related components via point-wise hard thresholding;inspired by index-based filtering, ISF optimizes and selects optimal filters for diagnostic feature extraction. It’s worth noting that SPINN may be readily applied to different deep learning networks by simply adding filterbank and feature modules in front. Experiments results demonstrate a significant diagnostic performance improvement over other explainable or denoising deep learning networks. The corresponding code is available at https://github. com/alber tszg/DFAWn et.
基金The Scientific and Technological Project of China National Offshore Oil Corporation(CNOOC)Research Institute Co.,Ltd.,under contract No.CCL2021RCPS0167KQNthe Fundamental Research Funds for the Central Universities,CHD under contract No.300102261714。
文摘As one of the main controlling factors of oil and gas accumulation,faults are closely related to the distribution of oil and gas reservoirs.Studying how faults control petroliferous basins is particularly important.In this work,we investigated the plane positions of major faults in the China seas and its adjacent areas using the normalized vertical derivative of the total horizontal derivative(NVDR-THDR)of the Bouguer gravity anomaly,the fusion results of gravity and magnetic anomalies,and the residual Bouguer gravity anomaly.The apparent depths of major faults in the China seas and its adjacent areas were inverted using the Tilt-Euler method based on the Bouguer gravity anomaly.The results show that the strikes of the faults in the China seas and its adjacent areas are mainly NE and NW,followed by EW,and near-SN.Among them,the lengths of most ultra-crustal faults are in the range of 1000–3000 km,and their apparent depths lie between 10 km and 40 km.The lengths of crustal faults lie between 300 km and 1000 km,and their apparent depths are between 0 km and 20 km.According to the plane positions and apparent depths of the faults,we put forward the concept of fault influence factor for the first time.Based on this factor,the key areas for oil and gas exploration were found as follows:the east of South North China Basin in the intracontinental rift basins;the southeast region of East China Sea Shelf Basin,the Taixinan and Qiongdongnan basins in the continental margin rift basins;Zhongjiannan Basin in the strike-slip pull-apart basins;the Liyue,Beikang,and the Nanweixi basins in the rifted continental basins.This work provides valuable insights into oil and gas exploration,mineral resource exploration,and deep geological structure research in the China seas and its adjacent areas.
基金support from the National Natural Science Foundation of China(Nos.42104043,42374081,and U2039208)the Fundamental Research Funds for the Institute of Geophysics,China Earthquake Administration(No.DQJB22R35).
文摘On August 6,2023,a magnitude MW5.5 earthquake struck Pingyuan County,Dezhou City,Shandong Province,China.This event was significant as no large earthquakes had been recorded in the region for over a century,and no active fault had been previously identified.This study collects 1309 P-wave arrival times and 866 S-wave arrival times from 74 seismic stations less than 200 km to the epicenter to constrain the spatial distribution of the mainshock and its 125 early aftershocks by the double difference earthquake relocation method,and selects 864 P-waveforms from 288 stations located within 800 km of the epicenter to constrain the focal mechanism solution of the mainshock through centroid moment tensor inversion.The relocation and the inversion indicate,the Pingyuan MW5.5 earthquake was caused by a rupture on a buried fault,likely an extensive segment of the Gaotang fault.This buried fault exhibited a dip of approximately 75°to the northwest,with a strike of 222°,similar to the Gaotang fault.The rupture initiated at the depth of 18.6 km and propagated upward and northeastward.However,the ground surface was not broken.The total duration of the rupture was~6.0 s,releasing the scalar moment of 2.5895×1017 N·m,equivalent to MW5.54.The moment rate reached the maximum only 1.4 seconds after the rupture initiation,and the 90%scalar moment was released in the first 4.6 s.In the first 1.4 seconds of the rupture process,the rupture velocity was estimated to be 2.6 km/s,slower than the local S-wave velocity.As the rupture neared its end,the rupture velocity decreased significantly.This study provides valuable insights into the seismic characteristics of the Pingyuan MW5.5 earthquake,shedding light on the previously unidentified buried fault responsible for the seismic activity in the region.Understanding the behavior of such faults is crucial for assessing seismic hazards and enhancing earthquake preparedness in the future.
基金funded by the National Natural Science Foundation of China (52174096, 52304110)the Fundamental Research Funds for the Central Universities (2022YJSSB03)the Scientific and Technological Projects of Henan Province (232102320238)。
文摘The angle α between the fault strike and the axial direction of the roadway produces different damage characteristics. In this paper, the research methodology includes theoretical analyses, numerical simulations and field experiments in the context of the Daqiang coal mine located in Shenyang, China. The stability control countermeasure of "pre-splitting cutting roof + NPR anchor cable"(PSCR-NPR) is simultaneously proposed. According to the different deformation characteristics of the roadway, the faults are innovatively classified into three types, with α of type I being 0°-30°, α of type II being 30°-60°, and α of type III being 60°-90°. The full-cycle stress evolution paths during mining roadway traverses across different types of faults are investigated by numerical simulation. Different pinch angles α lead to high stress concentration areas at different locations in the surrounding rock. The non-uniform stress field formed in the shallow surrounding rock is an important reason for the instability of the roadway. The pre-cracked cut top shifted the high stress region to the deep rock mass and formed a low stress region in the shallow rock mass. The high prestressing NPR anchor cable transforms the non-uniform stress field of the shallow surrounding rock into a uniform stress field. PSCR-NPR is applied in the fault-through roadway of Daqiang mine. The low stress area of the surrounding rock was enlarged by 3-7 times, and the cumulative convergence was reduced by 45%-50%. It provides a reference for the stability control of the deep fault-through mining roadway.
基金supported by the National Natural Science Foundation of China project (No. 42372339)the China Geological Survey Project (Nos. DD20221816, DD20190319)。
文摘On September 5, 2022, a magnitude Ms 6.8 earthquake occurred along the Moxi fault in the southern part of the Xianshuihe fault zone located in the southeastern margin of the Tibetan Plateau,resulting in severe damage and substantial economic loss. In this study, we established a coseismic landslide database triggered by Luding Ms 6.8 earthquake, which includes 4794 landslides with a total area of 46.79 km^(2). The coseismic landslides primarily consisted of medium and small-sized landslides, characterized by shallow surface sliding. Some exhibited characteristics of high-position initiation resulted in the obstruction or partial obstruction of rivers, leading to the formation of dammed lakes. Our research found that the coseismic landslides were predominantly observed on slopes ranging from 30° to 50°, occurring at between 1000 m and 2500 m, with slope aspects varying from 90° to 180°. Landslides were also highly developed in granitic bodies that had experienced structural fracturing and strong-tomoderate weathering. Coseismic landslides concentrated within a 6 km range on both sides of the Xianshuihe and Daduhe fault zones. The area and number of coseismic landslides exhibited a negative correlation with the distance to fault lines, road networks, and river systems, as they were influenced by fault activity, road excavation, and river erosion. The coseismic landslides were mainly distributed in the southeastern region of the epicenter, exhibiting relatively concentrated patterns within the IX-degree zones such as Moxi Town, Wandong River basin, Detuo Town to Wanggangping Township. Our research findings provide important data on the coseismic landslides triggered by the Luding Ms 6.8 earthquake and reveal the spatial distribution patterns of these landslides. These findings can serve as important references for risk mitigation, reconstruction planning, and regional earthquake disaster research in the earthquake-affected area.
基金supported by the National Natural Science Foundation of China(42376221,42276083)Director Research Fund Project of Guangzhou Marine Geological Survey(2023GMGSJZJJ00030)+2 种基金National Key Research and Development Program of China(2021YFC2800901)Guangdong Major Project of Basic and Applied Basic Research(2020B030103003)the project of the China Geological Survey(DD20230064).
文摘Many locations with concentrated hydrates at vents have confirmed the presence of abundant thermogenic gas in the middle of the Qiongdongnan Basin(QDNB).However,the impact of deep structures on gasbearing fluids migration and gas hydrates distribution in tectonically inactive regions is still unclear.In this study,the authors apply high-resolution 3D seismic and logging while drilling(LWD)data from the middle of the QDNB to investigate the influence of deep-large faults on gas chimneys and preferred gasescape pipes.The findings reveal the following:(1)Two significant deep-large faults,F1 and F2,developed on the edge of the Songnan Low Uplift,control the dominant migration of thermogenic hydrocarbons and determine the initial locations of gas chimneys.(2)The formation of gas chimneys is likely related to fault activation and reactivation.Gas chimney 1 is primarily arises from convergent fluid migration resulting from the intersection of the two faults,while the gas chimney 2 benefits from a steeper fault plane and shorter migration distance of fault F2.(3)Most gas-escape pipes are situated near the apex of the two faults.Their reactivations facilitate free gas flow into the GHSZ and contribute to the formation of fracture‐filling hydrates.
基金supported in part by the National Key R&D Program of China (2022YFB3402100)the National Science Fund for Distinguished Young Scholars of China (52025056)。
文摘Dear Editor,This letter presents a novel dynamic vision enabled contactless cross-domain fault diagnosis method with neuromorphic computing.The event-based camera is adopted to capture the machine vibration states in the perspective of vision.
基金supported by the National Key R&D Program of China (2021YFB1715000)the National Natural Science Foundation of China (U1811461, 62022013, 12150007, 62103450, 61832003, 62272137)。
文摘Dear Editor, This letter deals with the problem of algorithm recommendation for online fault detection of spacecraft. By transforming the time series data into distributions and introducing a distribution-aware measure, a principal method is designed for quantifying the detectabilities of fault detection algorithms over special datasets.
文摘This work presents a novel wavelet-based denoising technique for improving the signal-to-noise ratio(SNR)of nonsteady vibration signals in hardware redundant systems.The proposed method utilizes the relationship between redundant hardware components to effectively separate fault-related components from the vibration signature,thus enhancing fault detection accuracy.The study evaluates the proposed technique on two mechanically identical subsystems that are simultaneously controlled under the same speed and load inputs,with and without the proposed denoising step.The results demonstrate an increase in detection accuracy when incorporating the proposed denoising method into a fault detection system designed for hardware redundant machinery.This work is original in its application of a new method for improving performance when using residual analysis for fault detection in hardware redundant machinery configurations.Moreover,the proposed methodology is applicable to nonstationary equipment that experiences changes in both speed and load.
基金the National Key R&D Program of China(2022YFB3402100)the National Science Fund for Distinguished Young Scholars of China(52025056)+4 种基金the National Natural Science Foundation of China(52305129)the China Postdoctoral Science Foundation(2023M732789)the China Postdoctoral Innovative Talents Support Program(BX20230290)the Open Foundation of Hunan Provincial Key Laboratory of Health Maintenance for Mechanical Equipment(2022JXKF JJ01)the Fundamental Research Funds for Central Universities。
文摘The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source domain.However,in engineering scenarios,achieving such high-quality label annotation is difficult and expensive.The incorrect label annotation produces two negative effects:1)the complex decision boundary of diagnosis models lowers the generalization performance on the target domain,and2)the distribution of target domain samples becomes misaligned with the false-labeled samples.To overcome these negative effects,this article proposes a solution called the label recovery and trajectory designable network(LRTDN).LRTDN consists of three parts.First,a residual network with dual classifiers is to learn features from cross-domain samples.Second,an annotation check module is constructed to generate a label anomaly indicator that could modify the abnormal labels of false-labeled samples in the source domain.With the training of relabeled samples,the complexity of diagnosis model is reduced via semi-supervised learning.Third,the adaptation trajectories are designed for sample distributions across domains.This ensures that the target domain samples are only adapted with the pure-labeled samples.The LRTDN is verified by two case studies,in which the diagnosis knowledge of bearings is transferred across different working conditions as well as different yet related machines.The results show that LRTDN offers a high diagnosis accuracy even in the presence of incorrect annotation.
基金the National Key Research and Development Program of China under Grant 2021YFB3301300the National Natural Science Foundation of China under Grant 62203213+1 种基金the Natural Science Foundation of Jiangsu Province under Grant BK20220332the Open Project Program of Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System under Grant 2022A0004.
文摘The reliable operation of high-speed wire rod finishing mills is crucial in the steel production enterprise.As complex system-level equipment,it is difficult for high-speed wire rod finishing mills to realize fault location and real-time monitoring.To solve the above problems,an expert experience and data-driven-based hybrid fault diagnosis method for high-speed wire rod finishing mills is proposed in this paper.First,based on its mechanical structure,time and frequency domain analysis are improved in fault feature extraction.The approach of combining virtual value,peak value with kurtosis value index,is adopted in time domain analysis.Speed adjustment and side frequency analysis are proposed in frequency domain analysis to obtain accurate component characteristic frequency and its corresponding sideband.Then,according to time and frequency domain characteristics,fault location based on expert experience is proposed to get an accurate fault result.Finally,the proposed method is implemented in the equipment intelligent diagnosis system.By taking an equipment fault on site,for example,the effectiveness of the proposed method is illustrated in the system.