Fault Mechanism Analysis Research Articles

Complex system fault diagnosis based on interpretive structural model

To realize the fault diagnosis of complex systems, a fault diagnosis method for complex systems based on the explanatory structural model is proposed. According to the fault mechanism analysis, the fault association matrix of system elements is established. The explanatory structural model is applied to transform the fault association relationship of complex systems into an intuitive hierarchical structural model through matrix transformation, so as to realize the structuring and hierarchical propagation of system faults. The PageRank algorithm is introduced to evaluate the influence and impact of system element faults. According to the influence and impact of the same-layer components and the fault transmission logic, the main cause of system fault transmission is clarified, which provides a basis for fault diagnosis. Finally, a specific application is carried out with a certain device as an example to verify the effectiveness of the method.

Dynamic modeling and analysis of rolling bearing faults under time-varying excitations considering defect deformation

Fault mechanism analysis is one of the methods in fault diagnosis, and the dynamic modeling of rolling bearing faults plays a crucial role in studying fault mechanisms. Existing dynamic fault models only consider the impact of fault size and bearing speed on the impact force, providing an incomplete description of the impact force. In order to more accurately describe the dynamic fault model of impact forces, this paper focuses on the deep groove ball bearing with outer race faults. Factors such as defect deformation, speed, and fault size are considered, and an instantaneous impact force excitation function is proposed. Based on this proposed excitation function, a dynamic model for the outer race fault of deep groove ball bearings is established. Finally, through simulation and experimental comparison, the results indicate that the fault characteristic frequencies and their harmonics of the model in this paper are closer to the actual fault characteristic frequencies, reducing the error by 1 to 2 Hz. Therefore, the model proposed in this paper is more effective and accurate, providing a more precise rolling bearing fault model for the study of fault mechanisms.

A Mechanism and Data Hybrid-Driven Method for Main Circuit Ground Fault Diagnosis in Electrical Traction System

Ground faults can be caused by abnormal grounding of several different modules in the electrical traction drive system, leading to vulnerable train operation. Therefore, rapid and accurate diagnosis of ground faults is of great significance to improve safety and reliability of electric locomotives and electric multiple units (EMU). This paper proposes a mechanism and data hybrid driven method to diagnose the ground faults. Firstly, according to ground fault mechanism analysis, characteristic variables are constructed and several fault features are extracted by using signals selected from existing control system. Secondly, according to historical data, the probability membership function associated with fault features and typical ground fault types is established offline by fuzzy logic theory. Then, the probability information of fault features is fused using Dempster-Shafer (D-S) evidence theory and a decision-making method based on the basic probability number is applied to classify faults. Finally, field experiments are performed and the results show that compared with canonical correlation analysis (CCA) based method and on-board fault diagnosis method, the proposed method has better performance in the presence of large measurement noise and transient condition changes, and it is also promising for practical applications.

Fault Coupling Analysis and Reliability Assessment of Actuation System Based on Bond Graph Model

In this paper, a new degradation model of the more electrical aircraft (MEA) actuation system is proposed. The bond graph model is used to build the dissimilar redundancy actuation system model, taking into account the degradation behavior (wear, fatigue, aging) of components in the system operation and the fault coupling phenomenon caused by the accumulation of dissipated energy in space and time, and a fault coupling degradation model of the actuation system is established with clear mechanism support. Through the fault mechanism analysis, various fault types are injected into the bond graph model of the actuation system, and the simulation results are compared. The influence of fault propagation on system output is analyzed, the system’s reliability is assessed, and the performance evaluation of the actuation system is realized while taking the fault coupling mechanism into account.

Failure Analysis and Improvement of Check Valve Reverse Cut-off Seal

Given the failure of reverse cut-off seal performance in the test process of the check valve, the fault location and mechanism analysis were carried out, and the improvement measures were proposed and verified by the test. It is analyzed that the main reason for the failure is the unreasonable design of the moving pair and the welding position of the check valve, which makes the sealing pair cannot fit effectively after the welding of the check valve, leading to the failure of the reverse cut-off seal. By controlling the ratio of the length of the guide surface to the diameter of the guide surface to 1.25, and controlling the distance between the welding position and the sealing pair to 10mm, the failure problem of the reverse cut-off seal of the check valve caused by the unreasonable design of the moving pair and the weld position is successfully solved. The effectiveness of the improved scheme of the check valve is verified by the test.

Fault mechanism analysis and diagnosis for closed-loop drive system of industrial robot based on nonlinear spectrum

To solve the problem of nonlinear characteristics neglecting and fault mechanism analysis lacking in fault diagnosis research, a new method of fault mechanism analysis and diagnosis based on nonlinear spectrum is proposed. Firstly, based on the Permanent Magnet Synchronous Motor (PMSM) model of robot, the first 4-order spectrums based on nonlinear output frequency response function (NOFRF) in different states are obtained by batch calculation method. Secondly, the high-frequency spectrum distribution rule of NOFRF spectrum in different states are analyzed. Finally, in the closed-loop simulation environment of robot, the identification method based on data-driven is adopted for NOFRF spectrum calculation to verify power loss fault of PMSM. Meanwhile, the fault diagnosis experiment is also carried out. The experimental results indicate that the key characteristics distribution rule of NOFRF spectrums in the real environment is consistent with the theoretical analysis results, and compared with the traditional fault feature extraction methods by output signal, the diagnosis with fault feature of NOFRF spectrum for industrial robot closed-loop drive system has the highest accuracy, which verifies the validity of NOFRF spectrum as the fault feature.

Study on Fault Detection of Plastic Micro-Drive System: An Experimental Analysis of Grille Controller

Plastic micro-drive systems are used in an increasing number of applications in manufacturing industries. The operational status of the plastic micro-drive system directly affects the performance of the host system. However, the fault diagnosis of the plastic micro-drive system remains a challenge due to its miniaturization. In this paper, a fault-detection study using the electrical-parameter analysis method is proposed for the grille controller, which provides a basis for typical plastic micro-drive systems. The structure and working principle of grille controllers are analyzed, and typical faults are summarized. Then, the fault-mechanism analysis of typical faults is presented, and the identification indicators of faults are developed. A strategy of fault-feature frequency extraction based on the improved reconstruction method of empirical-mode decomposition (EMD) is proposed. Finally, the experimental results reveal that the proposed indicators and method demonstrate high accuracy for the grille-controller fault detection.

Analysis of the Regularity and Mechanism of Fault Activation Caused by Deep Continuous Mining of Shizishan Copper Mine, China

In order to study the law and mechanism of fault activation induced by deep continuous mining, this paper takes the fault activation caused by underground mining of Shizishan Copper Mine as the research object. On the basis of field investigation and theoretical analysis of fault activation, the law and mechanism of fault group activation induced by deep continuous mining in the Shizishan mining area are analyzed in detail based on the three-dimensional discrete element method software 3DEC. The results show that the fault effect of rock movement in the footwall of the main orebody in the mine area is obvious. The en echelon steep dipping fault group in the footwall of the goaf will move each fault block in the direction of the goaf and slip along the fault plane when the balance between mining and gravity is disrupted. The fault activation has a domino effect in time and space, and the mechanism of this effect is revealed. The research results have great significance for the deep mining area development, mining alignment arrangement, and disaster prevention and control caused by fault activation.

Application of comprehensive diagnosis technology in fault analysis of 35kV box transformer in wind farm

Using on-line monitoring means to monitor the state quantity of power equipment is the trend of equipment diagnosis and evaluation, but it is usually difficult to accurately judge the hidden dangers of equipment by using a single means. This paper puts forward the transformer comprehensive on-line monitoring technology, which can effectively identify the equipment faults through multi state quantity and long-time comprehensive analysis. The relevant achievements are applied to the fault analysis of 35kV box-type transformer in a wind farm. The qualitative classification of fault category is realized by integrating three state quantities: temperature, oil color spectrum and iron core grounding current; Through disassembly inspection, the effectiveness of the integrated on-line monitoring system is proved; The analysis of fault mechanism is realized by using finite element electromagnetic field calculation. The technology of transformer comprehensive diagnosis in this paper has a very important reference for the defect analysis of transformer equipment.

Fault data expansion method of permanent magnet synchronous motor based on Wasserstein-generative adversarial network

Aiming at the characteristics of non-smooth, non-linear, multi-source heterogeneity, low density of value and unevenness of fault data collected by the online monitoring equipment of permanent magnet synchronous motor (PMSM), and the difficulty of fault mechanism analysis, this paper proposes a method of PMSM data expansion based on the improved generative adversarial network. First, use the real fault data of the motor to train the model to obtain a mature and stable generative countermeasure network. Secondly, use the generative countermeasure network model to test the remaining data and generate pseudo samples. Finally, use the two-dimensional data analysis method and the time-domain analysis method to generate validity analysis of samples. Aiming at the characteristics of unbalanced motor data, the data expansion method of inter-turn short-circuit faults is carried out based on the data expansion method of the improved generative countermeasure network, and the two-dimensional data analysis method and the time-domain analysis method are used for analysis. The experimental results show that the improved Wasserstein-Generative Adversarial Network (W-GAN) has a better ability to generate fake data, which provides a data basis for the mechanism analysis and machine fault diagnosis of PMSMs. Data analysis results show that the improved W-GAN effectively solves the problem of poor convergence of GAN.

Application of instantaneous phase detection technology based on laser displacement sensor in fault diagnosis of spur gear of rotation vector reducer

Aiming at the problem of a spur gear fault of the rotation vector (RV) reducer in industrial robots, an instantaneous phase detection technology based on eccentric modulation and laser displacement sensor is proposed. Taking the RV-20E reducer as the object, through the analysis of the RV reducer gear fault mechanism, an RV reducer fault diagnosis test bed is developed to simulate the actual operating conditions of the RV reducer of industrial robot. The instantaneous phase information of the RV reducer is collected, and the adaptive permutation entropy is used to process the instantaneous phase data, which can judge the gear fault type quickly and effectively. The test results show that the fault diagnosis test bench based on this detection technology can effectively and quantitatively judge the fault type of the spur gear of the RV reducer.

Fault Mechanism Analysis of Irreversible Demagnetization Due to the Dynamic Eccentricity of IPMSM for EV Traction

The dynamic eccentricity fault (DEF) of the interior permanent magnet synchronous motor (IPMSM) is mainly caused by external mechanical shock. In the case of DEF, an unbalanced magnetic force occurs because the length of the air gap is not constant. Noise and vibration of the motor occur due to unbalanced magnetic force. In addition, since the length of the air gap is not constant, the distribution of magnetic flux density is distorted, and iron loss is increased. As the iron loss increases, the temperature rises, and an irreversible demagnetization fault (IDF) of the permanent magnet occurs due to overheating. Therefore, in this paper, the fault mechanism of IDF due to DEF of IPMSM for electric vehicle (EV) traction is analyzed. Initially, the magnetic flux density and iron loss characteristics according to the healthy condition and DEF condition are analyzed using the finite element method (FEM). Then, the detailed iron loss analysis is performed based on the phase current waveform measured through the load test of the motor. Finally, the fault mechanism of IDF due to DEF was verified through an electric-axle load test on a manufactured motor having eccentricity.

DC-side faults mechanism analysis and causes location for two-stage photovoltaic grid connected inverters

Due to the deep coupling of the DC faults for the two-stage photovoltaic (PV) inverters, it is very difficult to determine the specific causes of DC faults. In terms of this issue, the fault mechanism of different causes is analysed and the obvious fault features are selected to locate the causes. Furthermore, a complete set of fault diagnosis process is proposed for DC overvoltage and undervoltage faults. An experimental platform for PV power generation system is used to simulate the deterioration of operating conditions and obtains various fault data. The results show that the correctness of fault mechanism analysis and the effectiveness of the proposed diagnosis process.

Early Fault Diagnosis of Shaft Crack Based on Double Optimization Maximum Correlated Kurtosis Deconvolution and Variational Mode Decomposition

Aiming at the problem that the vibration energy of shaft crack early weak fault is small and the feature extraction was difficult, the fault diagnosis method of cuckoo search, maximum correlation kurtosis deconvolution and variational mode decomposition (CS-MCKD-VMD) was proposed to diagnose the early weak fault of shaft cracks. Firstly, considering the periodic characteristics of fault signal, MCKD was used to highlight the fault signal, and the kurtosis correlation of deconvolution signal processed by MCKD were enhanced. Then, VMD could be used to decompose the harmonic signal, and VMD was used to process the deconvolution signal to generate some intrinsic mode functions (IMF), and the correlation coefficient method was used to calculate the components with the maximum correlation. At the same time, in order to improve the correlation of parameters in MCKD and VMD, CS was used to optimize the parameters to reduce the error of human selection. Thirdly, the optimal component was calculated by the fast spectral kurtosis (FSK), and the envelope spectrum was obtained by filtering the optimal component with the parameters obtained. Finally, the simulation and experimental results show that the transfer frequency and its 2 and 3 times frequency were prominent in the envelope spectrum, which was consistent with the analysis of shaft crack fault mechanism, Therefore, it was proved that the CS-MCKD-VMD method can effectively extract the early weak fault features of shaft cracks.

A Model for Visual Assessment of Fault Plane Solutions and Active Tectonics Analysis Using the Global Centroid Moment Tensor Catalog

In this study, individual fault plane solutions are developed using various methods to improve the understanding of active tectonics on a regional scale. The comparative analysis of a focal mechanism solution (FMS) has not elicited the attention of researchers. Therefore, this study aims (1) to visually analyze the fault plane solution for 20 local faults that are responsible for all the earthquakes that occurred using visualization techniques such as: fault parameters, the linked Bingham method, the ad hoc pressure (P) axis and tension (T) axis method, and the moment tensor method; (2) to identify the best method for FMS; and (3) to understand the active tectonics of a fault population. A comparative analysis of the models is systematically documented to improve the understanding of the methods. An analysis of the overall fault mechanism is conducted for the analytic determination of fault movement using fault population data from the Global Centroid Moment Tensor catalog. The approach used in this work is a newly designed method for analyzing the reliability of various techniques for fault mechanism and overall fault movement research. Findings show that for the fault mechanism analysis, the P and T axes method and the moment tensor method are better than the fault plane solution from the fault parameters and the linked Bingham method based on the input parameters, output information, model outfit, and accuracy. The moment tensor method is one of the best approaches for analyzing fault mechanism because the errors in the nine components used as input data for the modeling are negligible. Meanwhile, the P and T axes method is one of the best techniques for the overall analysis of fault movement. P and T dihedral analysis using Kamb contouring is modeled. It indicates that the overall mechanisms of compression and dilation are features at the NW–SE and E–W directions, respectively. This comprehensive and consistent analysis of the fault mechanism provides an overview of the seismotectonic settings in Sabah, Malaysia.

Application of fault propagation intensity in fault diagnosis of CNC machine tool

ABSTRACTTo realize dynamic and real-time multi-fault decoupling and diagnostic CNC machine tools, this study proposes a dynamic fault diagnosis method that is based on fault propagation intensity. Integrated fault mechanism analysis, directed graph theory, and interpretative structure model are used to construct a fault propagation hierarchical model to visually depict complex fault causality. The influence degree of component nodes and the fault influence degree of edges are calculated using PageRank and a coupling degree function. The fault propagation probability of component nodes is determined by synthesizing node fault probability. Fault propagation intensity is defined by the probability of fault propagation and edge-betweenness to characterize the behavior of fault propagation dynamically. Combined with the hierarchical fault propagation model, the critical path and node are determined. A certain type of CNC machine tool is taken as an example to carry out a specific application. Results show that the hierarchical model of system fault propagation realizes multi-fault decoupling and clarifies the process of fault propagation. The critical path is identified according to the fault propagation intensity, the deviation caused by describing the behavior of fault propagation based on a single index is avoided, and the accuracy of fault diagnosis is improved.

Simulation and analysis of single-phase grounding fault in small current grounding system

The characteristics and distribution of single-phase grounding faults in small current grounding system are not easy to capture, and it is not easy to collect and cover all possible situations in operation site. This paper builds a fault simulation model of distribution network based on PSCAD. By changing the fault location, line type, transition resistance, fault time and other factors, and combining with the analysis of fault mechanism, the factors affecting single-phase grounding faults are obtained. The impacts of fault feature distribution provide theoretical guidance for fault identification equipment function detection and so on.

Fault Mechanism Analysis for Manufacturing System Based on Catastrophe Model

Fault analysis is important in both research and industry. Current fault analysis tasks are mainly concerned with fault prediction and classification and do not focus enough on fault evolution mechanisms. In this paper, we propose a fault analysis method based on catastrophe theory for manufacturing system to improve the effectiveness and efficiency of real time monitoring of potential fault and causes analysis. The key advantages of our proposed method are (i) utilizing catastrophe theory and big data analysis to establish the fault cusp catastrophe model of manufacturing system and create the internal fault evolution mechanism of manufacturing system by the cusp catastrophe model and, (ii) with the established catastrophe model, fulfilling fault monitoring and accurate preventive control of the manufacturing system and ensuring the healthy operation of the manufacturing system.

Thermal Vacuum and Swivel Table Tests of a CMG and Fault Mechanism Analysis

AbstractThermal vacuum and swivel table tests of a control moment gyroscope (CMG) are designed and the start-up hesitation and rotation break of the CMG are analyzed. In order to study the fault me...

Research on criticality analysis method of CNC machine tools components under fault rate correlation

In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.