Simulation Research of Fault Model of Detecting Rotor Dynamic Eccentricity in Brushless DC Motor Based on Motor Current Signature Analysis

基于Ansoft／Maxwell设置动态偏心故障，建立求解电机电感和磁链的有限元模型，通过仿真，证明了将感应电机动态偏心故障的特征频率经过简化后，同样适用于无刷直流电动机。基于Ansoft／Simplorer建立无刷直流电动机系统的仿真模型。在电机稳态运行下，对定子电流进行傅里叶分析，研究并建立基于定子电流监测动态偏心故障的仿真模型：动态偏心故障与特征频率的关系、动态偏心故障程度与特征频率幅值的关系。进而研究了无刷直流电动机稳态运行时转速波动对偏心故障监测的影响。仿真结果表明，转子偏心程度加大，特征频率的幅值增加。

Improvements of corner frequency and scaling factor for stochastic finite-fault modeling

In this paper, three existing source spectral models for stochastic finite-fault modeling of ground motion were reviewed. These three models were used to calculate the far-field received energy at a site from a vertical fault and the mean spectral ratio over 15 stations of the Northridge earthquake, and then compared. From the comparison, a necessary measure was observed to maintain the far-field received energy independent of subfault size and avoid overestimation of the long- period spectra/level. Two improvements were made to one of the three models （i.e., the model based on dynamic comer frequency） as follows： （i） a new method to compute the subfault comer frequency was proposed, where the subfault comer frequency is determined based on a basic value calculated from the total seismic moment of the entire fault and an increment depending on the seismic moment assigned to the subfault; and （ii） the difference of the radiation energy from each suhfault was considered into the scaling factor. The improved model was also compared with the unimproved model through the far-field received energy and the mean spectral ratio. The comparison proves that the improved model allows the received energy to be more independent of subfault size than the unimproved model, and decreases the overestimation degree of the long-period spectral amplitude.

Coseismic fault model of the 2017 M_(W)6.5 Jiuzhaigou earthquake and implications for the regional fault slip pattern

On August 8,2017,an M_(W)6.5 earthquake occurred in Jiuzhaigou County,Sichuan Province,China,on the eastern margin of the Qinghai-Tibet Plateau.This study investigates the coseismic deformation field and fault model with ascending and descending Sentinel-1 synthetic aperture radar(SAR)images,aftershock distribution,and elastic half-space dislocation model.The regional fault slip pattern is then quantita-tively examined using the boundary element method.The results show that the ascending and descending interferometric synthetic aperture radar(InSAR)coseismic deformation fields display an overall NNW-SSE trend,with more significant deformation on the southwest side of the fault.The coseismic fault geometry is divided into NW and SE sub-faults with strikes of 162.1°and 149.3°,respectively.The coseismic fault slip is dominated by a left-lateral strike-slip movement with an average rake of-2.31°,mainly occurring at a depth of 0-13.04 km with a shape of an approximately inverted triangle.The fault slip features two peak slip zones,with a maximum of 1.39 m.The total seismic moment is 6.34×10^(18) N·m(M_(W)6.47).The boundary element calculation quantitatively indicates that the regional fault slip pattern may be mainly attributable to the changing strike and dip.The strike changes from NNWeSSE to nearly NS direction,and the dip gradually decreases from the Jiuzhaigou earthquake fault in the north to the Huya fault in the south.With these characteristics,the Huya and the Jiuzhaigou earthquake faults form the eastern boundary of the Minshan uplift zone and accommodate the accumulated deformation.

REVIEW OF HIGH LEVEL FAULT MODELING APPROACHES FOR MIXED-SIGNAL SYSTEMS

In the modern analogue design, Transistor Level Fault Simulation (TLFS) plays the im-portant part since every fault in the whole circuit has to be simulated at that level. Unfortunately, it is a very CPU intensive task even though it maintains the high accuracy. Therefore, High Level Fault Modeling (HLFM) and High Level Fault Simulation (HLFS) are required in order to alleviate the efforts of simulation. In this paper, different HLFM approaches are reviewed at the device level during last two decades. We clarify their domains of application and evaluate their strengths and current limitations. We also analyze causes of faults and introduce various test approaches.

Seismic ground motion relationships in southern China based on stochastic finite-fault model

The characteristics of seismic ground motions in southern China are difficult to determine statistically due to a lack of strong ground motion data.In this study,a stochastic finite-fault ground motion model was adopted to simulate the seismic ground motions at bedrock for southern China,based on parameters derived from small and medium earthquakes that have occurred in the region.From these,the response spectra was estimated.A set of ground motion attenuation relationships was then developed based on simulated peak ground motions and response spectral parameters through regression,which would be applicable for use in engineering practice.Through comparisons,it was demonstrated that the proposed ground motion relationships are generally consistent with those obtained from other reported ground motion attenuation models for southern China.

Dynamic Fault Model for On-Line Evaluation of Yarn End Breakage during Ring Spinning

In this paper, a dynamic fault model is proposed to predict yarn end breakage in the spinning procedure through investigation of fault characteristics. In view of the principle that uniformity bad in raw material causes instable yarn formation, the investigation focuses on the fault characteristic existing in the dynamic tension. Analyzing the dynamic spinning system, the phenomenon of over random shock in a spinning triangle is discovered to be the main physical event prior to yarn end breakage. The fault characteristic is further confirmed by dynamic tests and signal processing, and can be used to make an approach to predicting yarn end breakage. A relative energy feature is defined for evaluating the tendency of yarn end breakage, and its effectiveness is verified by on-line monitoring tests in the laboratory. The research results show that the proposed dynamic fault model has not only an advantage in indicating the presence of fault characteristics, but also great potentials in quantitating fault in on-line spinning monitoring.

Estimation of Displacement and Extension due to Reverse Drag of Normal Faults: Forward Method

In the case of reverse drag of normal faulting, the displacement and horizontal extension are determined based on the established equations for the three mechanisms: rigid body, vertical shear and inclined shear. There are three sub-cases of basal detachment for the rigid body model: horizontal detachment, antithetic detachment and synthetic detachment. For the rigid body model, the established equations indicate that the total displacement on the synthetic base (Dt2) is the largest, that on the horizontal base (Dt1) is moderate, and that on the antithetic base (Dt3) is the smallest. On the other hand, the value of (Dt1) is larger than the displacement for the vertical shear (Dt4). The value of (Dt1) is larger than or less than the displacement for the inclined shear (Dt5) depending on the original fault dip δ0, bedding angle θ, and the angle of shear direction β. For all original parameters, the value of Dt5 is less than the value of Dt4. Also, by comparing three rotation mechanisms, we find that the inclined shear produces largest extension, the rigid body model with horizontal detachment produces the smallest extension, and the vertical shear model produces moderate extension.

基于PSModel的海上风电场全电磁暂态建模与仿真

开发有效的风机电磁暂态模型是进行海上风电并网研究的基础。根据不同生产厂家所提供的直驱风机模型,提出了一种基于厂家黑盒模型的直驱风机电磁暂态建模方法。利用厂家所提供的模型测试数据解析风机的故障响应特性,推导了不同厂家在电压故障下有功和无功功率响应表达式,包括故障期间的穿越控制过程及不同过程间的暂态切换策略。提出了加权平均压降的风电场等值方法,采用自主研发的全电磁暂态仿真软件(power system model,PSModel)对我国广东某海上风电场进行全电磁暂态建模。根据稳态潮流及暂态特性结果验证了模型可通过系统测试,且有效实现了海上风电场的全电磁暂态建模,从而为该风场接入大电网后的安全稳定分析提供了研究基础。

Review of Artificial Intelligence for Oil and Gas Exploration: Convolutional Neural Network Approaches and the U-Net 3D Model

Deep learning, especially through convolutional neural networks (CNN) such as the U-Net 3D model, has revolutionized fault identification from seismic data, representing a significant leap over traditional methods. Our review traces the evolution of CNN, emphasizing the adaptation and capabilities of the U-Net 3D model in automating seismic fault delineation with unprecedented accuracy. We find: 1) The transition from basic neural networks to sophisticated CNN has enabled remarkable advancements in image recognition, which are directly applicable to analyzing seismic data. The U-Net 3D model, with its innovative architecture, exemplifies this progress by providing a method for detailed and accurate fault detection with reduced manual interpretation bias. 2) The U-Net 3D model has demonstrated its superiority over traditional fault identification methods in several key areas: it has enhanced interpretation accuracy, increased operational efficiency, and reduced the subjectivity of manual methods. 3) Despite these achievements, challenges such as the need for effective data preprocessing, acquisition of high-quality annotated datasets, and achieving model generalization across different geological conditions remain. Future research should therefore focus on developing more complex network architectures and innovative training strategies to refine fault identification performance further. Our findings confirm the transformative potential of deep learning, particularly CNN like the U-Net 3D model, in geosciences, advocating for its broader integration to revolutionize geological exploration and seismic analysis.

A New Growth Model of Fault Attributes in a Strike-Slip Fault System in the Tarim Basin

Fault attributes generally display a consistent power–law-scaling relationship.Based on new 3 D seismic data,however,we found some exceptional fault attribute relationships of lengths(L)–throw(T)(vertical component of displacement),overlap zone length(Lo)–width(Wo)from a strike-slip fault system of the Ordovician carbonates in the Tarim Basin.The L–T relationship shows two linear segments with breakup at^40 km in fault length.This presents an exceptional throw increase in the second stage,which is attributed to a localization of vertical displacement and deformation in overlapping zones other than the different fault scales in a mature fault zone.The Lo–Wo relationship in the overlapping zones shows multiply stepped-shape patterns,suggesting multiple fault differential growth and periodic increase in fault size.Therefore,we propose a new alternative growth model of fault attributes in strike-slip fault zones,in which the overlapping zones accumulated localized displacement and deformation in the intracratonic strike-slip fault zone.

The Relationship between Fe Mineralization and Magnetic Basement Faults using Multifractal Modeling in the Esfordi and Behabad Areas(BMD), Central Iran

Multifractal modeling is a mathematical method for the separation of a high potential mineralized background from a non-mineralized background. The Concentration-Distance to Fault structures(C-DF) fractal model and the distribution of the known iron(Fe) deposits/mines seen in the Esfordi and Behabad 1:100,000 sheets from the Bafq region of central Iran are used to distinguish Fe mineralization based on their distance to magnetic basement structures and surface faults, separately, using airborne geophysical data and field surveys. Application of the C-DF fractal model for the classification of Fe mineralizations in the Esfordi and Behabad areas reveals that the main ones show a correlation with their distance from magnetic basement structures. Accordingly, the distances of Fe mineralizations with grades of Fe higher than 55%(43% < Fe ≤ 60%) are located at a distance of less than 1 km, whereas for surfacial faults with grades of 43% ≤ Fe ≤ 60%, the distances are 3162< DF ≤ 4365 m from the faults. Thus, there is a positive relationship between Fe mineralization and magnetic basement structures. Also, the proximity evidence of Precambrian high-grade Fe mineralization related to magnetic basement structures indicates syn-rifting tectonic events. Finally, this C-DF fractal model can be used for exploration of magmatic and hydrothermal ore deposits.

Testing content addressable memories with physical fault models

Content addressable memory （CAM） is widely used and its tests mostly use functional fault models. However, functional fault models cannot describe some physical faults exactly. This paper introduces physical fault models for write-only CAM. Two test algorithms which can cover 100% targeted physical faults are also proposed. The algorithm for a CAM module with N-bit match output signal needs only 2N＋2L＋4 comparison operations and 5N writing operations, where N is the number of words and L is the word length. The algorithm for a HIT-signal-only CAM module uses 2N＋2L＋5 comparison operations and 8N writing operations. Compared to previous work, the proposed algorithms can test more physical faults with a few more operations. An experiment on a test chip shows the effectiveness and efficiency of the proposed physical fault models and algorithms.

Robust inversion analysis of local gravity anomalies caused by geological dislocation model of faults

Theoretical analysis and practical observations show that fault dislocations can change the gravity field around the fault. Gravity changes which were caused by the repeated dislocations over a long period of time were superimposed on the Bougeur gravity anomalies. These anomalies became the evidence of historical movement of fault as well as provide a way for the study of paleo earthquakes. This paper investigates inversion methods for the geological dislocation modeling of faults using the local Bouguer's gravity anomalies. To remove the effects of the irrelevant part of gravity anomalies to fault movements, we propose the robust nonlinear inversion method and set up the corresponding algorithm. Modeling examples indicate that the Marquardt's and Baye's least squares solutions depart from the true solution due to the attraction of gross errors in the data. The more seriously the data is contaminated, the more seriously the solutions are biased. In contrast, the proposed robust Marquardt's and Baye's inversion solutions can still maintain consistency with the solution without gross errors, even though 50 percent of the data is contaminated. This indicates that the proposed robust methods are effective. Using the proposed methods, we invert the geological dislocation models of the faults around the Erhai Lake in West Yunnan. The results show that the Northern Cangdong fault and the Erhai fault are normal dip slip faults with about 4 to 5 km dislocations; and that the Southern Cangdong fault has a less dip slip compared with the former two. A satisfactory fitting between the theoretical values of the inversion solution and the actual local gravity field is achievable.

FAULT DIAGNOSIS APPROACH BASED ON HIDDEN MARKOV MODEL AND SUPPORT VECTOR MACHINE

Aiming at solving the problems of machine-learning in fault diagnosis, a diagnosis approach is proposed based on hidden Markov model （HMM） and support vector machine （SVM）. HMM usually describes intra-class measure well and is good at dealing with continuous dynamic signals. SVM expresses inter-class difference effectively and has perfect classify ability. This approach is built on the merit of HMM and SVM. Then, the experiment is made in the transmission system of a helicopter. With the features extracted from vibration signals in gearbox, this HMM-SVM based diagnostic approach is trained and used to monitor and diagnose the gearbox＇s faults. The result shows that this method is better than HMM-based and SVM-based diagnosing methods in higher diagnostic accuracy with small training samples.

Modeling of normal faulting in the subducting plates of the Tonga,Japan,Izu-Bonin and Mariana Trenches:implications for near-trench plate weakening

The plate flexure and normal faulting characteristics along the Tonga, Japan, Izu-Bonin and Mariana Trenches are investigated by combining observations and modeling of elastoplastic deformation of the subducting plate. The observed average trench relief is found to be the smallest at the Japan Trench(3 km) and the largest at the Mariana Trench(4.9 km), and the average fault throw is the smallest at the Japan Trench(113 m) and the largest at the Tonga Trench(284 m). A subducting plate is modeled to bend and generate normal faults subjected to three types of tectonic loading at the trench axis: vertical loading, bending moment, and horizontal tensional force. It is inverted for the solutions of tectonic loading that best fit the observed plate flexure and normal faulting characteristics of the four trenches. The results reveal that a horizontal tensional force(HTF) for the Japan Trench is 33%, 50% and 60% smaller than those of the Mariana, Tonga and Izu-Bonin Trenches, respectively. The normal faults are modeled to penetrate to a maximum depth of 29, 23, 32 and 32 km below the sea floor for the Tonga,Japan, Izu-Bonin and Mariana Trenches, respectively, which is consistent with the depths of relocated normal faulting earthquakes in the Japan and Izu-Bonin Trenches. Moreover, it is argued that the calculated horizontal tensional force is generally positively correlated with the observed mean fault throw, while the integrated area of the reduction in the effective elastic thickness is correlated with the trench relief. These results imply that the HTF plays a key role in controlling the normal faulting pattern and that plate weakening can lead to significant increase in the trench relief.

A Complete Analytic Model for Fault Diagnosis of Power Systems

现代大规模互联电网提高了电力系统运行的稳定性和经济性,同时也给电网的故障诊断增加了难度。对电网保护配置和断路器动作规则进行深入分析,提出一种新的电网故障诊断模型——完全解析模型,并为基于此模型的故障诊断提出一种实用有效的求解方法。在完全解析模型中,故障假说（即可疑故障设备的故障情况）与保护、断路器的动作情况及拒动和误动情况一同表示成逻辑变量,而保护配置和断路器动作规则以逻辑方程组形式进行充分表达,逻辑方程组的每个解析解对应一个故障模式（设备故障状态和保护动作、断路器跳闸状态及拒动/误动情况）,是对故障情形的完整解释。本模型对故障诊断规则和保护、断路器的动作逻辑进行完全解析,并完整保留了故障设备、保护动作和断路器跳闸之间的耦合关系,克服了已有解析模型的缺陷。算例表明,保留完整耦合关系的完全解析模型可有效提高故障诊断的准确性和容错能力。

Sandbox Modeling of the Fault-increment Pattern in Extensional Basins

Three series of sandbox modeling experiments were performed to study the fault-increment pattern in extensional basins. Experimental results showed that the tectonic action mode of boundaries and the shape of major boundary faults control the formation and evolution of faults in extensional basins. In the process of extensional deformation, the increase in the number and length of faults was episodic, and every ＇episode＇ experienced three periods, strain-accumulation period, quick fault-increment period and strain-adjustment period. The more complex the shape of the boundary fault, the higher the strain increment each ＇episode＇ experienced. Different extensional modes resulted in different fault-increment patterns. The horizontal detachment extensional mode has the ＇linear＇ style of fault-increment pattern, while the extensional mode controlled by a listric fault has the ＇stepwise＇ style of fault-increment pattern, and the extensional mode controlled by a ramp-flat boundary fault has the ＇stepwise-linear＇ style of fault-increment pattern. These fault-increment patterns given above could provide a theoretical method of fault interpretation and fracture prediction in extensional basins.

ONLINE MODEL AND ACTUATOR FAULT TOLERANT CONTROL FOR AUTONOMOUS MOBILE ROBOT

A novel fault-tolerant adaptive control methodology against the actuator faults is proposed. The actuator effectiveness factors （AEFs） are introduced to denote the healthy of actuator, and the unscented Kalman filter （UKF） is employed for online estimation of both the motion states and the AEFs of mobile robot. A square root version of the UKF is introduced to improve efficiency and numerical stability. Using the information from the UKF, the reconfigurable controller is designed automatically based on an enhancement inverse dynamic control （IDC） methodology. The experiment on a 3-DOF omni-directional mobile robot is performed, and the effectiveness of the proposed method is demonstrated.

Fault diagnosis using noise modeling and a new artificial immune system based algorithm

A new fault classification/diagnosis method based on artificial immune system (AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate, Gaussian and non-Gaussian noise generating models are applied to simulate environmental noise. The identification of noise model, known as training process, is based on the estimation of the noise model parameters by genetic algorithms (GA) utilizing real experimental features. The proposed fault classification/diagnosis algorithm is applied to the noise contaminated features. Then, the results are compared to that obtained without noise modeling. The performance of the proposed method is examined using three laboratory case studies in two healthy and damaged conditions. Finally three different types of noise models are studied and it is shown experimentally that the proposed algorithm with non-Gaussian noise modeling leads to more accurate clustering of memory cells as the major part of the fault classification procedure.