Adaptive Variational Mode Decomposition for Bearing Fault Detection

Rolling element bearings are commonly used in rotary mechanical and electrical equipment. According to investigation, more than half of rotating machinery defects are related to bearing faults. However, reliable bearing fault detection still remains a challenging task, especially in industrial applications. The objective of this work is to propose an adaptive variational mode decomposition (AVMD) technique for non-stationary signal analysis and bearing fault detection. The AVMD includes several steps in processing: 1) Signal characteristics are analyzed to determine the signal center frequency and the related parameters. 2) The ensemble-kurtosis index is suggested to decompose the target signal and select the most representative intrinsic mode functions (IMFs). 3) The envelope spectrum analysis is performed using the selected IMFs to identify the characteristic features for bearing fault detection. The effectiveness of the proposed AVMD technique is examined by experimental tests under different bearing conditions, with the comparison of other related bearing fault techniques.

Fault tolerant control with torque limitation based on fault mode for ten-phase permanent magnet synchronous motor

This paper proposes a novel fault tolerant control with torque limitation based on the fault mode for the ten-phase permanent magnet synchronous motor （PMSM） under various open-circuit and short-circuit fault conditions, which includes the optimal torque control and the torque limitation control based on the fault mode. The optimal torque control is adopted to guarantee the ripple-free electromagnetic torque operation for the ten-phase motor system under the post-fault condition. Furthermore, we systematically analyze the load capacity of the ten-phase motor system under different fault modes. And a torque limitation control approach based on the fault mode is proposed, which was not available earlier. This approach is able to ensure the safety operation of the faulted motor system in long operating time without causing the overheat fault. The simulation result confirms that the proposed fault tolerant control for the ten-phase motor system is able to guarantee the ripple-free electromagnetic torque and the safety operation in long operating time under the normal and fault conditions.

Fault mode probability factor based fault-tolerant control for dissimilar redundant actuation system

This paper presents a Fault Mode Probability Factor（FMPF） based Fault-Tolerant Control（FTC） strategy for multiple faults of Dissimilar Redundant Actuation System（DRAS）composed of Hydraulic Actuator（HA） and Electro-Hydrostatic Actuator（EHA）. The long-term service and severe working conditions can result in multiple gradual faults which can ultimately degrade the system performance, resulting in the system model drift into the fault state characterized with parameter uncertainty. The paper proposes to address this problem by using the historical statistics of the multiple gradual faults and the proposed FMPF to amend the system model with parameter uncertainty. To balance the system model precision and computation time, a Moving Window（MW） method is used to determine the applied historical statistics. The FMPF based FTC strategy is developed for the amended system model where the system estimation and Linear Quadratic Regulator（LQR） are updated at the end of system sampling period. The simulations of DRAS system subjected to multiple faults have been performed and the results indicate the effectiveness of the proposed approach.

Sliding Mode Fault Tolerant Attitude Control Scheme for Spacecraft with Actuator Faults

An active fault tolerant control scheme is investigated for the attitude control systems of spacecraft with external disturbance and actuator faults by using the sliding mode technique. Firstly,the dynamic equations and kinematic equations of spacecraft are given. For the dynamic mode of spacecraft in faulty case,a fault diagnosis component is used for fault detection and estimation by using a nonlinear observer. According to the fault estimation information obtained during the fault diagnosis,the fault tolerant control scheme is developed by adopting the backstepping sliding mode control technique. Meanwhile,the Lyapunov theory is used to analyze the stability of the closed-loop attitude systems. Finally,simulation results for the attitude dynamics models show the feasibility of the proposed fault tolerant scheme.

The Study of Overhead Line Fault Probability Model Based on Fuzzy Theory

In the background of the design and construction of Smart Grid Operation Supporting System for District Power Networks, this paper established the weighted fault probability model of the overhead line which is based on equipment operating status, utility theory and fuzzy theory. In this model, the proper membership function is adopted to describe the influence of lightning, wind speed, line ice and temperature, and the outage rate of overhead line, derived from historical statistics, is amended. Based on this model, the power supply risk analysis software is developed to calculate the online risk indicators of district grid, and provide real-time decision support information based on risk theory for scheduling operations personnel.

Adaptive sliding mode backstepping control for near space vehicles considering engine faults

A fault tolerant control methodology based adaptive sliding mode(ASM) backstepping is proposed for near space vehicle(NSV) attitude control system under engine faults. The proposed scheme combined adaptive backstepping with the sliding mode control strategy could guarantee the system’s stability and track desired signals under external disturbances and engine faults. Firstly, attitude mode description and the engine faulty model are given. Secondly, a nominal control law is designed.Thirdly, a sliding mode observer is given later in order to estimate both the information of engine faults and external disturbances. An adaptive sliding mode technology based on the previous nominal control law is developed via updating faulty parameters. Finally,analyze the system’s fault-tolerant performance and reliability through experiment simulation, which verifies the proposed design of fault-tolerant control can tolerate engine faults, as well as the strong robustness for external disturbance.

Satellite fault diagnosis method based on predictive filter and empirical mode decomposition

A novel satellite fault diagnosis scheme is presented based on the predictive filter and empirical mode composition（EMD）.First,the predictive filter is utilized to obtain the fault estimation,which is corrupted by noise.Then the EMD method is introduced to decompose the fault estimation into a finite number of intrinsic mode functions and extract the trend of faults for fault diagnosis.The proposed scheme has the ability of diagnosing both abrupt and incipient faults of the actuator in a satellite attitude control subsystem.A mathematical simulation is given to illustrate the effectiveness of the proposed scheme.

Relationships between In SAR Seismic Deformation and Fault Motion Sense,Fault Strike,and Ascending/Descending Modes

Based on the working principle of satellite radars, the earthquake deformation field measured by interferometric synthetic aperture（InSAR） is the projection of ground displacement associated with the seismogenic fault in the line of sight（LOS） of the satellite. However, LOS projections are complex, and are not only related to the ascending/descending modes and incidence angles of SAR data, but also related to the strike and motion senses of the fault. Even for the same earthquake, the LOS deformation derived from different ascending/descending data can be almost identical in one case, but quite different in another case, which makes the interpretation of InSAR seismic deformation and its comparison with field observations difficult. In this study, we undertook a quantitative analysis of the relationships between LOS observation sensitivity of InSAR and fault strike, fault motion sense, and ascending/descending modes, as well as 3D deformation fields. We studied the features and differences of the LOS deformation fields in different types of earthquakes using ascending/descending modes, with a particularly detailed analysis of the relations for a strikeslip type of earthquake. We also summarized the characteristics of LOS deformation fields of faults with different strikes and optimal observational data modes. Taking the strike-slip Yushu earthquake and the normal Gaize event as examples, we used SAR data of the ascending/descending modes to verify the results of quantitative calculations. These analyses will not only provide a more reasonable interpretation of InSAR seismic deformation fields and but also help understand the differences of seismic deformation fields revealed by data with different observational modes, therefore promoting the application of InSAR technology in seismology.

Optimal selection of tests for fault detection and isolation in multi-operating mode system

The complex systems are often in the structure of multi-operating modes, and the components implementing system functions are different under different operation modes, which results in the problems that components often fail in different operating modes, faults can be only detected in specified operating modes, tests can be available in specified operating modes,and the cost and efficiency of detecting and isolating faults are different under different operating modes and isolation levels. Aiming at these problems, an optimal test selection method for fault detection and isolation in the multi-operating mode system is proposed by using the fault pair coding and rollout algorithm. Firstly,the faults in fault-test correlation matrices under different operating modes are combined to fault-pairs, which is used to construct the fault pair-test correlation matrices under different operating modes.Secondly, the final fault pair-test correlation matrix of the multioperating mode system is obtained by operating the fault pair-test correlation matrices under different operating modes. Based on the final fault pair-test correlation matrix, the necessary tests are selected by the rollout algorithm orderly. Finally, the effectiveness of the proposed method is verified by examples of the optimal test selection in the multi-operating mode system with faults isolated to different levels. The result shows that the proposed method can effectively mine the fault detection and isolation ability of tests and it is suitable for the optimal test selection of the multi-operating mode system with faults isolated to the replacement unit and specific fault.

A New Method of Wind Turbine Bearing Fault Diagnosis Based on Multi-Masking Empirical Mode Decomposition and Fuzzy C-Means Clustering

Based on Multi-Masking Empirical Mode Decomposition (MMEMD) and fuzzy c-means (FCM) clustering, a new method of wind turbine bearing fault diagnosis FCM-MMEMD is proposed, which can determine the fault accurately and timely. First, FCM clustering is employed to classify the data into different clusters, which helps to estimate whether there is a fault and how many fault types there are. If fault signals exist, the fault vibration signals are then demodulated and decomposed into different frequency bands by MMEMD in order to be analyzed further. In order to overcome the mode mixing defect of empirical mode decomposition (EMD), a novel method called MMEMD is proposed. It is an improvement to masking empirical mode decomposition (MEMD). By adding multi-masking signals to the signals to be decomposed in different levels, it can restrain low-frequency components from mixing in highfrequency components effectively in the sifting process and then suppress the mode mixing. It has the advantages of easy implementation and strong ability of suppressing modal mixing. The fault type is determined by Hilbert envelope finally. The results of simulation signal decomposition showed the high performance of MMEMD. Experiments of bearing fault diagnosis in wind turbine bearing fault diagnosis proved the validity and high accuracy of the new method.

THE GROWTH MODE OF ALTUN FAULT AND IT'S DYNAMICS

A set of ENE\|trending fault which locates in the rigid Tarim massif and flexible Qilian massif in the same dynamic system of the uplift of the Qinghai—Tibetan plateau is referred to as the Altun Fault (ALF). ALF displays a linear geometry or a geometry of overlapping of linear and arcuate segments and a growth and development process of the breakdown segment\|by\|segment, connection segment\|by\|segment and propagation gradually (northeastward migration of the northeast tip, southwestward growth of the southwest tip). The formation of the Altun fault began in the middle or upper Carboniferous. It was characteristic of the sinistral strike\|slip\|thrust before Eocene, of the thrust\|sinistral strike\|slip during Oligocene—Miocene, and of the normal slip, and thrust\|sinistral strike\|slip simultaneously since Miocene.

The Altun Fault: Its Geometry, Nature and Mode of Growth

The Altun (or Altyn Tagh) fault displays a geometry of overlapping of linear and arcuate segments and shows strong inhomogeneity in time and space. It is a gigantic fault system with complex mechanical behaviours including thrusting, sinistral strike slip and normal slip. The strike slip and normal slip mainly occurred in the Cretaceous—Cenozoic and Plio-Quaternary respectively, whereas the thrusting was a deformation event that has played a dominant role since the late Palaeozoic (for a duration of about 305 Ma). The formation of the Altun fault was related to strong inhomogeneous deformation of the massifs on its two sides (in the hinterland of the Altun Mountains contractional deformation predominated and in the Qilian massif thrust propagation was dominant). The fault experienced a dynamic process of successive break-up and connection of its segments and gradual propagation, which was synchronous with the development of an overstep thrust sequence in the Qilian massif and the uplift of the Qinghai-Tibet plateau. With southward propagation of the thrust sequence and continued uplift of the plateau, the NE tip of the Altun fault moved in a NE direction, while the SW tip grew in a SW direction.

Fault Diagnosis Model Based on Feature Compression with Orthogonal Locality Preserving Projection

Based on feature compression with orthogonal locality preserving projection（OLPP）,a novel fault diagnosis model is proposed in this paper to achieve automation and high-precision of fault diagnosis of rotating machinery.With this model,the original vibration signals of training and test samples are first decomposed through the empirical mode decomposition（EMD）,and Shannon entropy is constructed to achieve high-dimensional eigenvectors.In order to replace the traditional feature extraction way which does the selection manually,OLPP is introduced to automatically compress the high-dimensional eigenvectors of training and test samples into the low-dimensional eigenvectors which have better discrimination.After that,the low-dimensional eigenvectors of training samples are input into Morlet wavelet support vector machine（MWSVM） and a trained MWSVM is obtained.Finally,the low-dimensional eigenvectors of test samples are input into the trained MWSVM to carry out fault diagnosis.To evaluate our proposed model,the experiment of fault diagnosis of deep groove ball bearings is made,and the experiment results indicate that the recognition accuracy rate of the proposed diagnosis model for outer race crack、inner race crack and ball crack is more than 90%.Compared to the existing approaches,the proposed diagnosis model combines the strengths of EMD in fault feature extraction,OLPP in feature compression and MWSVM in pattern recognition,and realizes the automation and high-precision of fault diagnosis.

Model of Fault Controlling Petroleum Accumulation in Linshang Fault Zone,Huimin Depression

Fault controlling petroleum accumulation is mainly reflected in hydrocarbon migration and sealing in accumulation periods.By fault activity rate analysis and fuzzy comprehensive sealing evaluation in different places of Linshang Fault Zone(LFZ),LFZ controlling petroleum accumulation shows a lot of spatiotemporal differences:(1) main branch of

Sliding mode observer-based fault reconstruction for uncertain descriptor linear systems

Fault detection and reconstruction of actuator faults for uncertain descriptor linear system based on a sliding mode observer was considered. The design algorithms of sliding mode observer for linear descriptor systems with faults and uncertain were given. The method uses H∞ concepts to design the observer gain such that L2 gain from the uncertainty to reconstruction error of fault was minimized.

某线震后轨道设计方案研究

2022年1月8日门源发生6.9级地震,造成某线隧道二衬坍塌、桥梁梁体移位、接触网脱落等基础、设备严重损坏,并伴随钢轨折断、扣件脱落、道床倾斜等轨道震害,是我国高速铁路首次遭遇的强震作用下严重受灾事件。结合震后预测余滑变形量水平150~300 mm,垂向100 mm条件下,在设防区段提出一种“三孔连体套管承轨台可调式WJ-8型扣件+长枕埋入式单层道床预留切割孔”新型大调整量无砟轨道结构方案。其中,三孔连体套管承轨台可调式WJ-8型扣件在既有WJ-8型扣件基础上通过增设铁承轨台、调距块和三联套管等部件可满足单股钢轨左右位置调整量达152 mm,长枕埋入式单层道床中预留切割孔,便于在基础变形超出扣件调整范围后切割纠偏;通过对余滑变形后线路拟合获得拨距包络图,确定了大调整量无砟轨道铺设范围。

基于电流模分量特性的多端柔性直流配电网线路纵联保护

多端柔性直流配电网因在供电可靠性方面极具优势而受到广泛的关注,然而对于直流线路保护中故障的快速、可靠识别成为其急速发展所需解决的关键问题之一。因此,设计了一种利用电流模分量特性的直流线路纵联保护方法。该方法利用故障时正极电流线模分量方向来判别区内外故障,以不同故障条件下故障点正极电流零模分量平均值的差异来构造保护判据,从而判别故障类型,形成保护策略。最后,在PSCAD/EMTDC4.5上搭建了多端柔性直流配电网模型,对保护判据及关键影响要素进行了仿真分析。结果表明,该保护方法能够有选择性地快速、可靠识别区内外故障及故障类型,且具有较好的耐过渡电阻与抗噪声能力。

中性点柔性接地配电网故障相恢复电压暂态时域特征分析

配电网接地故障过零熄弧后的电压暂态恢复特性决定了系统过电压水平及电弧重燃特性,目前,中性点柔性接地配电网故障熄弧后暂态恢复电压变化机理尚不明确,为此建立柔性接地配电网接地故障暂态等值电路,理论解析故障过零熄弧后故障恢复电压的时域表达式。在此基础上,对比分析配电网谐振接地与柔性接地方式下,系统参数变化对故障相恢复电压暂态峰值与恢复速度的影响,揭示暂态时间尺度下故障相恢复电压特征随注入零序电流值与电流注入时机的变化规律,阐明通过中性点注入可控零序电流抑制故障暂态过电压的机理。在PSCAD/EMTDC仿真环境与10 kV真型配电网实验场中模拟各种运行和故障工况,仿真与真型实验结果均验证柔性接地配电网故障相恢复电压时域解析特征与变化规律的正确性。

基于避免断层激活机制的组合压裂模式研究

页岩气井多级压裂过程中的套管剪切变形问题日益严重,甚至出现了水力压裂诱发断层激活造成邻井套管变形的现象,这导致相邻水平井压裂不能顺利进行,严重影响了区块产能建设,而降低泵压及排量等现有方法对套管变形控制效果不明显。为此,基于Mohr-Coulomb准则建立了页岩气井井间断层激活评价模型,揭示了常规压裂模式下井间断层激活机理,提出了一种基于避免水力压裂诱发断层激活机制的组合压裂模式。研究结果表明:常规压裂模式下井间断层区域均会被激活,导致相邻水平井丢段;随井间距增加及水平井夹角减小,水平井丢段长度增加;通过采用拉链-顺序-同步组合压裂模式优化断层附近多井多段压裂顺序,可达到避免断层提前激活、缩短水平井丢段长度的效果。研究结果可为页岩气水平井断层激活及套管变形控制提供理论指导。

基于DCM‑PCA和GA‑BP的逆变器故障诊断

针对光伏并网三相电压型逆变器开关管的开路故障,提出深度级联模型(deep cascade mode,DCM)‒主成分分析(principal component analysis,PCA)与遗传算法(genetic algorithm,GA)优化的BP神经网络结合的故障诊断方法。首先对逆变器的开路故障进行分析和仿真,确定三相电流作为故障信号,选择22类故障状态作为诊断对象,通过以稀疏表示分类(sparse representation based classififier,SRC)为基本操作单元的深度级联模型提取故障特征,DCM根据层次学习特性将故障特征分层,再由SRC部分得到不同故障的编码系数,并采用t分布—随机近邻嵌入(t⁃distributed stochastic neighbor embedding,t⁃SNE)方法验证了DCM具有较好的特征提取能力,通过PCA降低故障特征的冗余度、保留有价值的主成分提高网络映射能力,最后将故障特征向量作为GA⁃BP神经网络的输入信号实现对故障的诊断识别。通过仿真实验得到该方法的故障诊断准确率为95.64%,与DCM⁃PCA⁃BP、FFT⁃GA⁃BP和FFT⁃BP相比准确率分别提高8.71%、20.64%、51.70%,表明该方法有更好的故障特征提取能力和故障诊断效果。