Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213337
Zhiyu Peng, Ruiyun Qi
For hypersonic flight vehicles (HFVs), this article designs an adaptive fault-tolerant controller to achieve full-state constraints. Firstly, integral barrier Lyapunov function (iBLF) is applied on the parameterized longitudinal model to ensure that the flight path angle (FPA), the angle of attack (AOA), and the pitch rate in the constraint interval, and the problem of “differential expansion” of is avoided because of the introduction of the dynamic surface method. Then, aiming at the unknown fault of the rudder surface, the fault-tolerant controller structure is designed. Finally, it is proved using Lyapunov theory that the proposed method can ensure the closed-loop stability of the system. Also, a simulation is provided to show the effectiveness of the iBLF -based backstepping method.
{"title":"Adaptive Fault-tolerant Controller for Hypersonic Flight Vehicle with State Constraints Using Integral Barrier Lyapunov Function","authors":"Zhiyu Peng, Ruiyun Qi","doi":"10.1109/SAFEPROCESS45799.2019.9213337","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213337","url":null,"abstract":"For hypersonic flight vehicles (HFVs), this article designs an adaptive fault-tolerant controller to achieve full-state constraints. Firstly, integral barrier Lyapunov function (iBLF) is applied on the parameterized longitudinal model to ensure that the flight path angle (FPA), the angle of attack (AOA), and the pitch rate in the constraint interval, and the problem of “differential expansion” of is avoided because of the introduction of the dynamic surface method. Then, aiming at the unknown fault of the rudder surface, the fault-tolerant controller structure is designed. Finally, it is proved using Lyapunov theory that the proposed method can ensure the closed-loop stability of the system. Also, a simulation is provided to show the effectiveness of the iBLF -based backstepping method.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116405939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213426
Zifeng Gong, H. Jadoon, Deqing Huang, N. Qin, Lei Ma
This paper considers the digital realization of fault diagnosis (FD) and fault tolerant control (FTC) method for both catenary current and DC-link voltage sensor of the PWM rectifier under high switching frequency. A novel state observer is designed, which plays a key role in the FD and FTC algorithms and facilitates their digital implementation. The FD algorithm consists of residual calculation and comparison between residuals and the corresponding thresholds. The FTC technique is realized by control system reconfiguration that replaces the wrong measured value with output of the state observer. Results of simulation experiments confirm the feasibility and superiority of the proposed method.
{"title":"Fault Diagnosis and Tolerant Control for Sensors of PWM Rectifier Under High Switching Frequency","authors":"Zifeng Gong, H. Jadoon, Deqing Huang, N. Qin, Lei Ma","doi":"10.1109/SAFEPROCESS45799.2019.9213426","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213426","url":null,"abstract":"This paper considers the digital realization of fault diagnosis (FD) and fault tolerant control (FTC) method for both catenary current and DC-link voltage sensor of the PWM rectifier under high switching frequency. A novel state observer is designed, which plays a key role in the FD and FTC algorithms and facilitates their digital implementation. The FD algorithm consists of residual calculation and comparison between residuals and the corresponding thresholds. The FTC technique is realized by control system reconfiguration that replaces the wrong measured value with output of the state observer. Results of simulation experiments confirm the feasibility and superiority of the proposed method.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117143373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213416
Enhua Hu, Cunren Zhu, Chunmei Li
With the faster and faster development of urban rail transit, the scheduling of the operation has become increasingly tight. In light of this background, higher demands on the reliability and maintainability of metro signaling equipment were proposed. At present, the switch machine, which contributes the highest failure rate in the operation of urban rail transit lines, has caught the attention of the maintenance companies, since its failure and disrepair may directly affect the punctuality and the occurrence of accidents. When the switch malfunctioned or operated abnormally, some differences will be revealed on the curve. Consequently, important evidence for the normal operation of the switch machine is whether the characteristic curve of the switch is displayed normally. On the basis of understanding the characteristics of common failures, analyzing the characteristic curve for normal operations of the switch machine can contribute to the proactive determination of whether there might be an impending fault with the machine; or the quicker localization and diagnosis of the cause after the failure.
{"title":"Failure Recognition for Switch Machines Based on Machine Learning","authors":"Enhua Hu, Cunren Zhu, Chunmei Li","doi":"10.1109/SAFEPROCESS45799.2019.9213416","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213416","url":null,"abstract":"With the faster and faster development of urban rail transit, the scheduling of the operation has become increasingly tight. In light of this background, higher demands on the reliability and maintainability of metro signaling equipment were proposed. At present, the switch machine, which contributes the highest failure rate in the operation of urban rail transit lines, has caught the attention of the maintenance companies, since its failure and disrepair may directly affect the punctuality and the occurrence of accidents. When the switch malfunctioned or operated abnormally, some differences will be revealed on the curve. Consequently, important evidence for the normal operation of the switch machine is whether the characteristic curve of the switch is displayed normally. On the basis of understanding the characteristics of common failures, analyzing the characteristic curve for normal operations of the switch machine can contribute to the proactive determination of whether there might be an impending fault with the machine; or the quicker localization and diagnosis of the cause after the failure.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117164105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213318
An Liu, Shaolin Hu, Ming Wang, Jianguo Song
In view of the big noises and performance degradation on tracking process with a set of ground system of TTC (Tracking, Telemetering, and Command), it is difficult to diagnose and identify the abnormal conditions problems. A method for establishing a low rank analysis model is present. Through the tracking of historical data, a mathematical model of low rank decomposition is established. Furthermore, the anomaly monitoring and identification of tracking process can be carried out more accurately through the establishment of maximum variance statistic control line. According to the projection of statistics, the influence variables of abnormal occurrence are separated and achieve abnormal separation and alarm. The multi-loop tracking data for a satellite by actual tracking can be analyzed to show that his method can effectively eliminate the influence of measurement noise in tracking process, effectively identify abnormal land realize abnormal separation and alarm.
针对一套TTC (tracking, Telemetering, and Command)地面系统在跟踪过程中存在较大的噪声和性能下降，异常工况问题的诊断和识别较为困难。提出了一种建立低秩分析模型的方法。通过对历史数据的跟踪，建立了低秩分解的数学模型。此外，通过建立最大方差统计控制线，可以更准确地进行跟踪过程的异常监测和识别。根据统计投影，分离异常发生的影响变量，实现异常分离和报警。通过对某卫星实际跟踪的多环跟踪数据进行分析，表明该方法能有效消除跟踪过程中测量噪声的影响，有效识别异常土地，实现异常分离和报警。
{"title":"Health Supervision Based on Low Rank Analysis for Aerospace Tracking","authors":"An Liu, Shaolin Hu, Ming Wang, Jianguo Song","doi":"10.1109/SAFEPROCESS45799.2019.9213318","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213318","url":null,"abstract":"In view of the big noises and performance degradation on tracking process with a set of ground system of TTC (Tracking, Telemetering, and Command), it is difficult to diagnose and identify the abnormal conditions problems. A method for establishing a low rank analysis model is present. Through the tracking of historical data, a mathematical model of low rank decomposition is established. Furthermore, the anomaly monitoring and identification of tracking process can be carried out more accurately through the establishment of maximum variance statistic control line. According to the projection of statistics, the influence variables of abnormal occurrence are separated and achieve abnormal separation and alarm. The multi-loop tracking data for a satellite by actual tracking can be analyzed to show that his method can effectively eliminate the influence of measurement noise in tracking process, effectively identify abnormal land realize abnormal separation and alarm.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125974713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213434
Yueyue Meng, W. Shangguan, B. Cai, Junzhen Zhang
On-board equipment is the core component of Train Control System. It is of great significance to perform the fault prediction of on-board equipment in order to improve the safety of the train. This paper proposes a fault prediction method based on Grey-Elman neural network(Grey-ENN) for 300T on-board equipment. Firstly, through the statistics and analysis of the AE-log data of on-board equipment, the operation states evaluation and division have been completed. Secondly, the GSM-SVM (Support Vector Machine is optimized by Grid Search Method) model has been used to recognize operation states, followed by verifying the validity of the equivalent failure rate. The experiment results show that the fault states can be distinguished based on GSM-SVM with the accuracy of 93.4%. Finally, a joint fault prediction model has been employed to accomplish the complete prediction of serious and emergency faults with overall prediction accuracy of 86%, which verifies the feasibility and effectiveness of the Grey-Enn prediction method, and fault prediction result has certain guiding significance for maintenance decision.
{"title":"Fault Prediction Method of the On-board Equipment of Train Control System Based on Grey-ENN","authors":"Yueyue Meng, W. Shangguan, B. Cai, Junzhen Zhang","doi":"10.1109/SAFEPROCESS45799.2019.9213434","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213434","url":null,"abstract":"On-board equipment is the core component of Train Control System. It is of great significance to perform the fault prediction of on-board equipment in order to improve the safety of the train. This paper proposes a fault prediction method based on Grey-Elman neural network(Grey-ENN) for 300T on-board equipment. Firstly, through the statistics and analysis of the AE-log data of on-board equipment, the operation states evaluation and division have been completed. Secondly, the GSM-SVM (Support Vector Machine is optimized by Grid Search Method) model has been used to recognize operation states, followed by verifying the validity of the equivalent failure rate. The experiment results show that the fault states can be distinguished based on GSM-SVM with the accuracy of 93.4%. Finally, a joint fault prediction model has been employed to accomplish the complete prediction of serious and emergency faults with overall prediction accuracy of 86%, which verifies the feasibility and effectiveness of the Grey-Enn prediction method, and fault prediction result has certain guiding significance for maintenance decision.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128654035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213314
Rongyi Yan, H. Xia, Tongtong Liang, Xiao He
Intermittent faults (IFs) in practical processes are characterized by non-determinability, repeatability and unpredictability, which brings an enormous challenge to the diagnosis of IFs. In this paper, the detection and estimation problem of intermittent actuator faults for a class of linear stochastic systems is investigated. In order to determine the appearing (dis-appearing) time before the subsequent disappearing (appearing) time, an observer-type detection filter is designed by utilizing a geometric approach. Based on the moving horizon technique, the output of the observer is applied to generate a novel residual, which is more sensitive to the appearing (disappearing) time of the IF. Then, two hypothesis tests are proposed to determine all the appearing time and disappearing time, respectively. Moreover, an estimation algorithm is provided for the magnitude of the IF. Finally, a simulation example on an unmanned arial vehicle system is given to illustrate the effectiveness of the proposed scheme.
{"title":"Detecting and Estimating Intermittent Actuator Faults in Linear Stochastic Systems","authors":"Rongyi Yan, H. Xia, Tongtong Liang, Xiao He","doi":"10.1109/SAFEPROCESS45799.2019.9213314","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213314","url":null,"abstract":"Intermittent faults (IFs) in practical processes are characterized by non-determinability, repeatability and unpredictability, which brings an enormous challenge to the diagnosis of IFs. In this paper, the detection and estimation problem of intermittent actuator faults for a class of linear stochastic systems is investigated. In order to determine the appearing (dis-appearing) time before the subsequent disappearing (appearing) time, an observer-type detection filter is designed by utilizing a geometric approach. Based on the moving horizon technique, the output of the observer is applied to generate a novel residual, which is more sensitive to the appearing (disappearing) time of the IF. Then, two hypothesis tests are proposed to determine all the appearing time and disappearing time, respectively. Moreover, an estimation algorithm is provided for the magnitude of the IF. Finally, a simulation example on an unmanned arial vehicle system is given to illustrate the effectiveness of the proposed scheme.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129830248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213330
Dewen Zhu, Dongsheng Du, Haoshuang Chen, Runting Wen
This paper deal with the problem of the fault detection (FD) filter design for continuous-time switched systems with actuator faults. The actuator faults and the unknown disturbances of the system are set in finite frequency domain. By using the switched Lyapunov function and the average dwell-time (ADT) techniques, efficient conditions are obtained, which can realize the residual signal sensitive to the fault and robust to the unknown disturbances. In the design of fault detection filter, we use Linear matrix inequalities (LMIs) conditions to guarantee the finite frequency H∞ and $H$ - performance index. Finally, a practical example is provided and simulation results are conducted to demonstrate the effectiveness of the proposed approach.
{"title":"Actuator Fault Detection Filter Design for Continuous-time Switched Systems in Finite Frequency Domain","authors":"Dewen Zhu, Dongsheng Du, Haoshuang Chen, Runting Wen","doi":"10.1109/SAFEPROCESS45799.2019.9213330","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213330","url":null,"abstract":"This paper deal with the problem of the fault detection (FD) filter design for continuous-time switched systems with actuator faults. The actuator faults and the unknown disturbances of the system are set in finite frequency domain. By using the switched Lyapunov function and the average dwell-time (ADT) techniques, efficient conditions are obtained, which can realize the residual signal sensitive to the fault and robust to the unknown disturbances. In the design of fault detection filter, we use Linear matrix inequalities (LMIs) conditions to guarantee the finite frequency H∞ and $H$ - performance index. Finally, a practical example is provided and simulation results are conducted to demonstrate the effectiveness of the proposed approach.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130077776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213353
Bin Li, Xiaoguang Chen, Zhixin Wang, Shulin Tan
Rails are the foundation of rail transport, and any defects of the rails may directly affect the running state of the train or even lead to major safety incidents. However, the existing algorithms for rail crack detection are too expensive and difficult to perform on-line real-time monitoring. In this paper, we propose a method based on vibration signal for rail crack detection, which fits the vibration signal in the healthy rail and the cracked rail by least squares method. The transmission mode of vibration signal in the healthy rail and the cracked rail can be constructed, and the transmission mode can be used to distinguish the difference between the two types of rail on the higher harmonics. On this basis, the crack type of the cracked rail can be further distinguished. Using this method, we have established a rail crack detection system, which achieves a good on-line detection of cracks, and we discuss the reliability and safety of its on-line use in the future.
{"title":"Vibration Signal Analysis For Rail Flaw Detection","authors":"Bin Li, Xiaoguang Chen, Zhixin Wang, Shulin Tan","doi":"10.1109/SAFEPROCESS45799.2019.9213353","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213353","url":null,"abstract":"Rails are the foundation of rail transport, and any defects of the rails may directly affect the running state of the train or even lead to major safety incidents. However, the existing algorithms for rail crack detection are too expensive and difficult to perform on-line real-time monitoring. In this paper, we propose a method based on vibration signal for rail crack detection, which fits the vibration signal in the healthy rail and the cracked rail by least squares method. The transmission mode of vibration signal in the healthy rail and the cracked rail can be constructed, and the transmission mode can be used to distinguish the difference between the two types of rail on the higher harmonics. On this basis, the crack type of the cracked rail can be further distinguished. Using this method, we have established a rail crack detection system, which achieves a good on-line detection of cracks, and we discuss the reliability and safety of its on-line use in the future.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125659069","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213448
Jingxin Zhang, Maoyin Chen, Donghua Zhou
This paper proposes a process monitoring approach for dynamic systems based on Lapalacian eigenmaps. Aimed at the “out of sample” issue, we adopt radial basis function neural network instead of the traditional linear transformation, which is able to discover the accurate nonlinear functional relationship between the raw data and the low-dimensional data. Besides, in order to utilize temporal information, time-lagged embedding is employed to extract more meaningful information and dynamic characteristics. Thus, the proposed approach can be actually applied to nonlinear dynamic systems. Eventually, a numerical case demonstrates the effectiveness of the proposed approach.
{"title":"Dynamic Laplacian eigenmaps for process monitoring","authors":"Jingxin Zhang, Maoyin Chen, Donghua Zhou","doi":"10.1109/SAFEPROCESS45799.2019.9213448","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213448","url":null,"abstract":"This paper proposes a process monitoring approach for dynamic systems based on Lapalacian eigenmaps. Aimed at the “out of sample” issue, we adopt radial basis function neural network instead of the traditional linear transformation, which is able to discover the accurate nonlinear functional relationship between the raw data and the low-dimensional data. Besides, in order to utilize temporal information, time-lagged embedding is employed to extract more meaningful information and dynamic characteristics. Thus, the proposed approach can be actually applied to nonlinear dynamic systems. Eventually, a numerical case demonstrates the effectiveness of the proposed approach.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"141 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129177174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213265
Lili Guo, Wei Dong, Xinya Sun, Xingquan Ji
Direct current (DC) cable is the main current-carrying component in the DC transmission system. Its operating state is important to the stability of the metro traction power supply system. Once a fault occurs, it will not be able to supply power to the train normally and cause serious consequences. At the same time, its risk mechanism and propagation chain are complex, so it is not easy to analyze. Aiming at such characteristics, this paper proposes a dynamic risk analysis and evaluation method for metro power supply system based on fuzzy reasoning. In this paper, the risk propagation chain model of the subway DC power supply system causing the power supply system to stop power supply is studied, and the fault mechanism of DC cable breakdown is analyzed. The fuzzy probability is used to derive the risk propagation probability, and the graph theory is used to analyze the severity of the risk consequences caused by DC cable breakdown. Finally, a dynamic risk analysis and evaluation method for the DC cable breakdown risk propagation chain of the subway power supply system is established.
{"title":"A Method of Dynamic Risk Analysis and Assessment for Metro Power Supply System Based on Fuzzy Reasoning","authors":"Lili Guo, Wei Dong, Xinya Sun, Xingquan Ji","doi":"10.1109/SAFEPROCESS45799.2019.9213265","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213265","url":null,"abstract":"Direct current (DC) cable is the main current-carrying component in the DC transmission system. Its operating state is important to the stability of the metro traction power supply system. Once a fault occurs, it will not be able to supply power to the train normally and cause serious consequences. At the same time, its risk mechanism and propagation chain are complex, so it is not easy to analyze. Aiming at such characteristics, this paper proposes a dynamic risk analysis and evaluation method for metro power supply system based on fuzzy reasoning. In this paper, the risk propagation chain model of the subway DC power supply system causing the power supply system to stop power supply is studied, and the fault mechanism of DC cable breakdown is analyzed. The fuzzy probability is used to derive the risk propagation probability, and the graph theory is used to analyze the severity of the risk consequences caused by DC cable breakdown. Finally, a dynamic risk analysis and evaluation method for the DC cable breakdown risk propagation chain of the subway power supply system is established.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126259713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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