Short-term displacement prediction for newly established monitoring slopes based on transfer learning

This study makes a significant progress in addressing the challenges of short-term slope displacement prediction in the Universal Landslide Monitoring Program,an unprecedented disaster mitigation program in China,where lots of newly established monitoring slopes lack sufficient historical deformation data,making it difficult to extract deformation patterns and provide effective predictions which plays a crucial role in the early warning and forecasting of landslide hazards.A slope displacement prediction method based on transfer learning is therefore proposed.Initially,the method transfers the deformation patterns learned from slopes with relatively rich deformation data by a pre-trained model based on a multi-slope integrated dataset to newly established monitoring slopes with limited or even no useful data,thus enabling rapid and efficient predictions for these slopes.Subsequently,as time goes on and monitoring data accumulates,fine-tuning of the pre-trained model for individual slopes can further improve prediction accuracy,enabling continuous optimization of prediction results.A case study indicates that,after being trained on a multi-slope integrated dataset,the TCN-Transformer model can efficiently serve as a pretrained model for displacement prediction at newly established monitoring slopes.The three-day average RMSE is significantly reduced by 34.6%compared to models trained only on individual slope data,and it also successfully predicts the majority of deformation peaks.The fine-tuned model based on accumulated data on the target newly established monitoring slope further reduced the three-day RMSE by 37.2%,demonstrating a considerable predictive accuracy.In conclusion,taking advantage of transfer learning,the proposed slope displacement prediction method effectively utilizes the available data,which enables the rapid deployment and continual refinement of displacement predictions on newly established monitoring slopes.

A Real-Time System for Monitoring Distant Dynamic Displacement of Structures

Based on digital image processing technique, a real-time system is developed to monitor and detect the dynamic displacement of engineering structures. By processing pictures with a self-programmed software, the real-time coordinate of an object in a certain coordinate system can be obtained, and further dynamic displacement data and curve of the object can also be achieved. That is, automatic gathering and real-time processing of data can be carried out by this system simultaneously. For this system, first, an untouched monitoring technique is adopted, which can monitor or detect objects several to hundreds of meters apart; second, it has flexible installation condition and good monitoring precision of sub-millimeter degree; third, it is fit for dynamic, quasi-dynamic and static monitoring of large engineering structures. Through several tests and applications in large bridges, good reliability and dominance of the system is proved.

3D Microdisplacement Monitoring of Large Aircraft Assembly with Automated In Situ Calibration

Three-dimensional(3D)microdisplacement monitoring plays a crucial role in the assembly of large aircraft.This paper presents a broadly applicable high-precision online 3D microdisplacement monitoring method and system based on proximity sensors as well as a corresponding in situ calibration method,which can be applied under various extreme working conditions encountered in the aircraft assembly process,such as compact and obstructed spaces.A 3D monitoring model is first established to achieve 3D microdisplacement monitoring based only on the one-dimensional distances measured by proximity sensors,which concerns the extrinsic sensor parameters,such as the probe base point(PBP)and the unit displacement vector(UDV).Then,a calibration method is employed to obtain these extrinsic parameters with high precision by combining spatial transformation principles and weighted optimization.Finally,calibration and monitoring experiments performed for a tailplane assembly process are reported.The calibration precision for the PBP is better than±10 lm in the X and Y directions and±2 lm in the Z direction,and the calibration precision for the UDV is better than 0.07°.Moreover,the accuracy of the 3D microdisplacement monitoring system can reach±15 lm.In general,this paper provides new insights into the modeling and calibration of 3D microdisplacement monitoring based on proximity sensors and a precise,efficient,and low-cost technical means for performing related measurements in compact spaces during the aircraft assembly process.

Study and application of monitoring plane displacement of a similarity model based on time-series images

In order to compensate for the deficiency of present methods of monitoring plane displacement in similarity model tests,such as inadequate real-time monitoring and more manual intervention,an effective monitoring method was proposed in this study,and the major steps of the monitoring method include:firstly,time-series images of the similarity model in the test were obtained by a camera,and secondly,measuring points marked as artificial targets were automatically tracked and recognized from time-series images.Finally,the real-time plane displacement field was calculated by the fixed magnification between objects and images under the specific conditions.And then the application device of the method was designed and tested.At the same time,a sub-pixel location method and a distortion error model were used to improve the measuring accuracy.The results indicate that this method may record the entire test,especially the detailed non-uniform deformation and sudden deformation.Compared with traditional methods this method has a number of advantages,such as greater measurement accuracy and reliability,less manual intervention,higher automation,strong practical properties,much more measurement information and so on.

Distributed fiber optic sensors for tunnel monitoring:A state-of-the-art review

Distributed fiber optic sensors(DFOSs)possess the capability to measure strain and temperature variations over long distances,demonstrating outstanding potential for monitoring underground infrastructure.This study presents a state-of-the-art review of the DFOS applications for monitoring and assessing the deformation behavior of typical tunnel infrastructure,including bored tunnels,conventional tunnels,as well as immersed and cut-and-cover tunnels.DFOS systems based on Brillouin and Rayleigh scattering principles are both considered.When implementing DFOS monitoring,the fiber optic cable can be primarily installed along transverse and longitudinal directions to(1)measure distributed strains by continuously adhering the fiber to the structure’s surface or embedding it in the lining,or(2)measure point displacements by spot-anchoring it on the lining surface.There are four critical aspects of DFOS monitoring,including proper selection of the sensing fiber,selection of the measuring principle for the specific application,design of an effective sensor layout,and establishment of robust field sensor instrumentation.These four issues are comprehensively discussed,and practical suggestions are provided for the implementation of DFOS in tunnel infrastructure monitoring.

基于DMS传输平台的CTCS3-300H ATP车载设备数据无线下载及分析系统设计

针对CTCS3-300H型ATP车载设备日常运维存在的数据下载接口多、数据下载时间长、缺少智能化分析手段等问题,设计一套基于动态监测系统(DMS)传输平台的ATP车载设备数据无线下载及分析系统。通过车载端的ATP数据无线下载单元实现对300H型ATP车载设备各关键单元数据的实时采集、存储、检索及传输;利用既有DMS传输平台中的无线传输通道实现车载设备数据的无线下载;通过部署于地面的ATP日志分析工作站和智能诊断分析终端,实现ATP车载设备数据分类存储、故障报警、故障数据自动下载、车载数据智能诊断分析和历史故障的查询统计。该系统不仅可有效提高运维数据分析效率,降低车载故障对现场运营的影响,还可提升运维数据的时效性和可追溯性,从而全面提高300H型ATP车载设备的运维效率及运维质量。

DMS与ATP智能分析系统融合方案研究

列控车载设备动态监测系统(DMS)和ATP智能分析系统都用于ATP设备的日常运行维护,二者功能各不相同,但在架构设计、JRU记录数据采集、故障触发逻辑等方面存在一定的耦合。从现场实际应用需求出发,详细分析二者融合的必要性,分别提出车载设备、地面服务器和用户终端的集成融合方案。其中,除200H型ATP可以直接在DMS车载设备上扩展外,其他型号ATP都需要新增独立的ATP智能分析车载设备。建议将DMS地面服务器和ATP智能分析系统服务器合二为一,并可以分阶段逐步对DMS客户端与ATP智能分析系统客户端进行融合。在ATP智能分析系统大规模安装部署前,从总体角度研究2个系统融合方案,能够在降低系统成本的同时,提高现场设备的可维护性,对于后续实现ATP设备全生命周期智能运维管理,具有重要的现实意义和参考价值。

基于物联网和弱反射光栅阵列的地质灾害监测系统设计与应用

我国是世界上地质灾害类型最多、地质灾害最严重的国家之一,而雨量监测和形变监测在地质灾害监测中发挥着越来越重要的作用,因此确保地质灾害监测系统的长期运行以及在降雨期间的稳定运行尤为重要。文中基于STM32微控制器、LORA模块、4G模块设计了一款物联网数据采集控制板,并结合压电式雨量传感器、拉绳位移传感器研制了雨量智能监测仪、裂缝位移智能监测仪;结合物联网数据采集控制板和弱反射光栅阵列传感技术构建了基于物联网的弱反射光栅地质灾害监测系统,实现了对地质灾害体的定时监测和降雨期间的自动监测;最后将雨量智能监测仪、裂缝位移智能监测仪和弱反射光栅地质灾害监测系统应用于桐梓县大河镇新场火车站新场滑坡、崩塌的监测实验中。监测数据表明,弱反射光栅监测系统测得传感光缆41#弱反射光栅传感段的位移变化达5 mm,在其附近的位移监测仪也测到有位移变化,可有效实现对地质灾害的定时监测和降雨期间的自动监测。

Embedded Remote Monitoring System of Agricultural Environment Based on DSP

Agricultural environmental remote monitoring,data collection and network transmission are the development directions of modern agriculture.The embedded video remote monitoring system is designed with DSP processor DM642,which can collect the video signal of agricultural environment and biological information,as well as complete the extraction of video signal and network transmission.This system can be applied to the agro-ecological and environmental resources monitoring,agricultural disaster monitoring and warning and other digital agricultures.

基于DM642的视频压缩板卡的设计与实现

介绍了一种基于TI TMS320DM642的实时、4路MPEG-4视频压缩PCI板卡的设计与实现,对系统软硬件构成以及MPEG-4视频编码和优化进行了分析,试验结果表明该板卡可以实时对视频流进行压缩编码,并传输给主机,可以方便的完成本地存储或远程传输功能,为实现远程视频监控提供了有效的硬件支持。

Structural condition assessment of long-span suspension bridges using long-term monitoring data

This paper focuses on developing an online structural condition assessment technique using long-term monitoring data measured by a structural health monitoring system. The seasonal correlations of frequency-temperature and beam-end displacement-temperature for the Runyang Suspension Bridge are performed, first. Then, a statistical modeling technique using a six-order polynomial is further applied to formulate the correlations of frequency-temperature and displacement-temperature, from which abnormal changes of measured frequencies and displacements are detected using the mean value control chart. Analysis results show that modal frequencies of higher vibration modes and displacements have remarkable seasonal correlations with the environmental temperature and the proposed method exhibits a good capability for detecting the micro damage-induced changes of modal frequencies and displacements. The results demonstrate that the proposed method can effectively eliminate temperature complications from frequency and displacement time series and is well suited for online condition monitoring of long-span suspension bridges.

Prediction of landslide displacement with dynamic features using intelligent approaches

Landslide displacement prediction can enhance the efficacy of landslide monitoring system,and the prediction of the periodic displacement is particularly challenging.In the previous studies,static regression models(e.g.,support vector machine(SVM))were mostly used for predicting the periodic displacement.These models may have bad performances,when the dynamic features of landslide triggers are incorporated.This paper proposes a method for predicting the landslide displacement in a dynamic manner,based on the gated recurrent unit(GRU)neural network and complete ensemble empirical decomposition with adaptive noise(CEEMDAN).The CEEMDAN is used to decompose the training data,and the GRU is subsequently used for predicting the periodic displacement.Implementation procedures of the proposed method were illustrated by a case study in the Caojiatuo landslide area,and SVM was also adopted for the periodic displacement prediction.This case study shows that the predictors obtained by SVM are inaccurate,as the landslide displacement is in a pronouncedly step-wise manner.By contrast,the accuracy can be significantly improved using the dynamic predictive method.This paper reveals the significance of capturing the dynamic features of the inputs in the training process,when the machine learning models are adopted to predict the landslide displacement.

Stability evaluation for steep bank slope with microseismic monitoring in Three Gorges Reservoir area

Rock slide is one of the common geohazard in the Three Gorges Reservoir area, and it affects the shipping of the Yangtze River and the safety of people living on the banks. In order to investigate the internal fracturing mechanism of rock mass, distributed microseismic monitoring network was arranged with 15 three component geophones(3C geophones), deployed at borehole and out of the sliding mass in the unstable Dulong slope. Stein Unbiased Risk Estimation(SURE) method was used to noise suppression for the microseismic record, and decomposition parameters of the Continuous Wavelet Transform(CWT) were determined with maximum energy of correlation coefficient(MECC) method. The signal-to-noise ratio was tripled after the process, and source parameters are obtained with full waveform inversion. The rupture volume model was counted by the irregular grid statistics with the events’ density. It shows that the rock slide is of a small scale and composed of a single block. Moreover, the relationship among microseismicity, displacement and rainfall were discussed in the paper. The deformation rate was dramatically changed in the period of intensive events. There is a good consistency especially in the rainfall period. Although there is a time delay, continuous rainfall is more likely to cause the increase of microseismic events. The results show that the Dulong slope is a shallow rock slide in the state of creep deformation, and the rupture mechanism of the rock mass is left-lateral normal fault with shear failure. The research provides more key information for the early warning and prevention of rock slides and helps to reduce the risk of geohazards.

Sensor monitoring of a newly designed foundation pit supporting structure

A new type of pit supporting structure, which was tested and verified using the sensor monitoring technology, was presented. The new supporting structure is assembled by prefabricated steel structural units. The adjacent steel structural units are jointed with fasteners, and each steel structural unit has a certain radian and is welded by two steel tubes and one piece of steel disc. In order to test and verify the reliability of the new supporting structure, the field tests are designed. The main monitoring programs include the hoop stress of supporting structure, lateral earth pressure, and soil deformation. The monitoring data of the field tests show that the new supporting structure is convenient, reliable and safe.

Automatic prediction of time to failure of open pit mine slopes based on radar monitoring and inverse velocity method

Radar slope monitoring is now widely used across the world, for example, the slope stability radar(SSR)and the movement and surveying radar(MSR) are currently in use in many mines around the world.However, to fully realize the effectiveness of this radar in notifying mine personnel of an impending slope failure, a method that can confidently predict the time of failure is necessary. The model developed in this study is based on the inverse velocity method pioneered by Fukuzono in 1985. The model named the slope failure prediction model(SFPM) was validated with the displacement data from two slope failures monitored with the MSR. The model was found to be very effective in predicting the time to failure while providing adequate evacuation time once the progressive displacement stage is reached.

Analytical Research on Deformation Monitoring of Large Span Continuous Rigid Frame Bridge during Operation

Based on a large span continuous rigid frame bridge in Chongqing of China, the main pier vertical displacement and deviation, the bridge deck alignment and the expansion joint deformation are analytically researched during operation. Firstly, the monitoring content and method of the large span continuous rigid frame bridge are clearly stated. Secondly, by finite element software Midas Civil, the relevant deformation values of the bridge are calculated. Thirdly, in practice, the relevant deformation values of the bridge are measured. Finally, the measured values in practice are compared with the calculated ones by the finite element software Midas Civil, finding that the former is less than the latter, and it can be concluded that the bridge is basically in the normal working condition. In this paper, the analytical research on the deformation monitoring can provide the basis for similar bridges, which has good practical significance.

Integrated real-time roof monitoring

CSIRO has recently developed a real-time roof monitoring system for under-groundcoal mines and successfully tried the system in gate roads at Ulan Mine.The systemintegrated displacement monitoring,stress monitoring and seismic monitoring in onepackage.It included GEL multianchor extensometers,vibrating wire uniaxial stress meters,ESG seismic monitoring system with microseismic sensors and high-frequency AE sensors.The monitoring system automated and the data can be automatically collected by acentral computer located in an underground nonhazardous area.The data are then transferredto the surface via an optical fiber cable.The real-time data were accessed at anylocation with an Internet connection.The trials of the system in two tailgates at Ulan Minedemonstrate that the system is effective for monitoring the behavior and stability of roadwaysduring Iongwall mining.The continuous roof displacement/stress data show clearprecursors of roof falls.The seismic data (event count and locations) provide insights intothe roof failure process during roof fall.

Numerical Simulation and Field Monitoring Analysis for Deep Foundation Pit Construction of Subway Station

To investigate the effect of deep foundation pit excavation on the stability of retaining structure, a subway stationin the city of Jinan was selected as a project, and a FLAC3D-based three dimensional model was developed fornumerical simulation. The horizontal displacement of the retaining structure, the axial force of the support, andthe vertical displacement of the column were studied and compared to the collected data from the field. The findingsindicate that when the foundation pit is excavated, the maximum deformation of the retaining structure progressivelydecreases from the top, the distortion of the retaining structure gradually rises, and the final maximumdeformation is around 17 meters deep. In each layer of support, the largest axial force support is located in thefirst reinforced concrete support;the uplift of the pit bottom caused by soil unloading plays a primary role in thevertical displacement of the column, and the column exhibits an upward trend under all construction conditions.When compared to the measured data, the generated findings are comparable and the fluctuation trend is extremelyconsistent. The findings of this article may give technical direction for the development of subway stationswith a comparable engineering basis.

Study on the Girder-End Displacement of a Suspension Bridge Based on Field Measurements

The load-response correlation is a great concern for the management and maintenance agency of bridges. Based on both the load test data and the long-term structural health monitoring data, this study aims to characterize the variation in the girder-end longitudinal displacement of a long-span suspension bridge, i.e., the Zhaoyun Bridge in Guangdong Province of China. The load test provides a valuable chance to investigate the structural deformation in high loading levels, while the structural health monitoring system records the real-time, in-site, and long-term measurements in the normal operational stage of bridges. During the load test, the movement direction of the main girder is found to depend on the relative position of the center of gravity of the girder and the loading vehicles. However, over the period of normal operation, the quasi-static displacement at the ends of the main girder along the bridge axis is dominated by the temperature variations, rather than the traffic loading. The temperature-induced deformation is considerable so it should be filtered out from the structural total responses to highlight the live load effects or the anomalies of the bridge. As a case study, the temperature-displacement baseline model of the Zhaoyun Bridge is established and then utilized to identify the erroneous measurements in the structural health monitoring system. This paper serves as a reference for the structural behavior interpretation and performance evaluation of similar bridges.

基于DMS架构的配电网施工现场安全监控系统的研究

为了实现对配电网施工现场安全监控,提出基于DMS架构的配电网施工现场安全监控系统。构建配电网施工现场安全管控的统计信息分析模型,采用DMS架构体系进行配电网施工现场安全监控的嵌入式体系构架,运用分布式信息融合方法进行配电网施工现场安全监控的过程控制,提高建配电网施工现场安全监控和管理能力。仿真结果表明,采用该方法进行配电网施工现场安全监控的过程控制能力较好,提高了对配电网施工现场安全管理和过程控制能力。