Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213386
Zhi-wen Chen, Zhuo Chen, Tao Peng, Ketian Liang, Chunhua Yang, Xu Yang
Fault detection is critical to ensure the safe operation of high speed trains. One class support vector machine (OCSVM) and one class minimax probability machine (OCMPM) are two domain-based single class classification methods and commonly used for fault detection. This paper systematically analyzes their training and detecting complexity, principle of optimization and hyperparameter influence of both methods, and compares their performance on motor and sensor fault data from the simulated traction control system of the high speed train. It shows that OCMPM achieves higher fault detection rate than OCSVM given the same false alarm rate. But OCMPM is unfeasible used for real-time fault detection when the training dataset is large.
{"title":"A comparison of OCMPM and OCSVM in motor and sensor fault detection for traction control system","authors":"Zhi-wen Chen, Zhuo Chen, Tao Peng, Ketian Liang, Chunhua Yang, Xu Yang","doi":"10.1109/SAFEPROCESS45799.2019.9213386","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213386","url":null,"abstract":"Fault detection is critical to ensure the safe operation of high speed trains. One class support vector machine (OCSVM) and one class minimax probability machine (OCMPM) are two domain-based single class classification methods and commonly used for fault detection. This paper systematically analyzes their training and detecting complexity, principle of optimization and hyperparameter influence of both methods, and compares their performance on motor and sensor fault data from the simulated traction control system of the high speed train. It shows that OCMPM achieves higher fault detection rate than OCSVM given the same false alarm rate. But OCMPM is unfeasible used for real-time fault detection when the training dataset is large.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"26 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":"126376102","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/SAFEPROCESS45799.2019.9213417
Zhichao Li, Tianzhen Wang, Milu Zhang, Yide Wang, D. Diallo
In recent years, more and more attention has been paid to marine current turbines (MCTs). Attachments on blades will influence the system operation by causing imbalance and it is essential to monitor its working state, repair or replace the faulty blade (s) to reduce its damages. Imbalance fault detection of MCTs using electric signals has many superiorities compared with traditional vibration-based method. However, there are some shortcomings in using decomposition method to weaken the influence of waves and turbulence. This paper proposes a method to detect the imbalance fault of MCTs using voltage signal. In this proposed method, the instantaneous voltage frequency and average voltage frequency is calculated through Hilbert transform (HT). Meanwhile, the imbalance fault frequency is extracted by using the cubic spline interpolation. Finally, the wavelet transform (WT) method is used to detect whether there is a blade imbalance fault. The effectiveness of this method is verified by theoretical analysis, simulation results and experimental results.
{"title":"An Imbalance Fault Detection Method for MCTs Using Voltage Signal","authors":"Zhichao Li, Tianzhen Wang, Milu Zhang, Yide Wang, D. Diallo","doi":"10.1109/SAFEPROCESS45799.2019.9213417","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213417","url":null,"abstract":"In recent years, more and more attention has been paid to marine current turbines (MCTs). Attachments on blades will influence the system operation by causing imbalance and it is essential to monitor its working state, repair or replace the faulty blade (s) to reduce its damages. Imbalance fault detection of MCTs using electric signals has many superiorities compared with traditional vibration-based method. However, there are some shortcomings in using decomposition method to weaken the influence of waves and turbulence. This paper proposes a method to detect the imbalance fault of MCTs using voltage signal. In this proposed method, the instantaneous voltage frequency and average voltage frequency is calculated through Hilbert transform (HT). Meanwhile, the imbalance fault frequency is extracted by using the cubic spline interpolation. Finally, the wavelet transform (WT) method is used to detect whether there is a blade imbalance fault. The effectiveness of this method is verified by theoretical analysis, simulation results and experimental results.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"21 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":"126746747","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/SAFEPROCESS45799.2019.9213359
Yanwen Wang, Maoyin Chen, Donghua Zhou
In this paper, a novel part mutual information based quality-related component analysis (PMIQCA) method is presented to detect quality-related faults and reduce the interference alarms. The low-dimensional subspace of process variables can be found, which reflects real-time changes in quality. The detection rates of quality-unrelated faults can be reduced while the detection rates of faults that are related to quality are increased. The basic idea is to select the most relevant process variables and principal components (PCs) with the maximal part mutual information (PMI) for each iteration, so as to build a more accurate supervisory relations between process variables and quality. Afterwards, two appropriate statistics are established for quality-related fault detection. Finally, the Tennessee Eastman Process (TEP) is carried out to demonstrate the effectiveness of PMIQCA.
{"title":"Part Mutual Information Based Quality-related Component Analysis for Fault Detection","authors":"Yanwen Wang, Maoyin Chen, Donghua Zhou","doi":"10.1109/SAFEPROCESS45799.2019.9213359","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213359","url":null,"abstract":"In this paper, a novel part mutual information based quality-related component analysis (PMIQCA) method is presented to detect quality-related faults and reduce the interference alarms. The low-dimensional subspace of process variables can be found, which reflects real-time changes in quality. The detection rates of quality-unrelated faults can be reduced while the detection rates of faults that are related to quality are increased. The basic idea is to select the most relevant process variables and principal components (PCs) with the maximal part mutual information (PMI) for each iteration, so as to build a more accurate supervisory relations between process variables and quality. Afterwards, two appropriate statistics are established for quality-related fault detection. Finally, the Tennessee Eastman Process (TEP) is carried out to demonstrate the effectiveness of PMIQCA.","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":"128112333","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/SAFEPROCESS45799.2019.9213345
Ran Li, Yang Liu
A hybrid dimension reduction algorithm based on feature selection and kernel principal component analysis (KPCA) is proposed in this paper to better realize the classification of the planetary gearbox faults. Firstly, in order to reduce the redundancy of some unnecessary features in the sample to a greater extent and the complexity of the kernel matrix calculation, a multi-criterion feature selection method is used to eliminate the irrelevant features. Secondly, through KPCA, the nonlinear principal component of the selected features is built. Then, fault is recognized by put the feature subset into the SVM classification. The proposed algorithm is applied to a planetary gearbox fault diagnosis experiment, and the experimental results show that the proposed algorithm outperforms the ones which employ feature selection or KPCA separately.
{"title":"Fault Diagnosis for the Planetary Gearbox Based on a Hybrid Dimension Reduction Algorithm","authors":"Ran Li, Yang Liu","doi":"10.1109/SAFEPROCESS45799.2019.9213345","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213345","url":null,"abstract":"A hybrid dimension reduction algorithm based on feature selection and kernel principal component analysis (KPCA) is proposed in this paper to better realize the classification of the planetary gearbox faults. Firstly, in order to reduce the redundancy of some unnecessary features in the sample to a greater extent and the complexity of the kernel matrix calculation, a multi-criterion feature selection method is used to eliminate the irrelevant features. Secondly, through KPCA, the nonlinear principal component of the selected features is built. Then, fault is recognized by put the feature subset into the SVM classification. The proposed algorithm is applied to a planetary gearbox fault diagnosis experiment, and the experimental results show that the proposed algorithm outperforms the ones which employ feature selection or KPCA separately.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"28 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":"134293234","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/SAFEPROCESS45799.2019.9213390
Zixin An, Hao Yang, B. Jiang
In this paper, based on the small-gain theorem of large-scale interconnected systems, we study the convergence performance of nonlinear interconnected systems with cycles, and establish a safely reconfigurable condition for the control law of each subsystem, which is applied to design fault-tolerant control (FTC) schemes. Both individual and cooperative FTC methods are presented in this paper by redesigning the controller of each subsystem and adjusting the interconnected gain between subsystems to ensure that the trajectories of states do not exceed the given safety bound.
{"title":"Safe Reconfigurability of a Class of Nonlinear Interconnected Systems","authors":"Zixin An, Hao Yang, B. Jiang","doi":"10.1109/SAFEPROCESS45799.2019.9213390","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213390","url":null,"abstract":"In this paper, based on the small-gain theorem of large-scale interconnected systems, we study the convergence performance of nonlinear interconnected systems with cycles, and establish a safely reconfigurable condition for the control law of each subsystem, which is applied to design fault-tolerant control (FTC) schemes. Both individual and cooperative FTC methods are presented in this paper by redesigning the controller of each subsystem and adjusting the interconnected gain between subsystems to ensure that the trajectories of states do not exceed the given safety bound.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"311 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":"133345268","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/SAFEPROCESS45799.2019.9213410
Qing Wang, X. Liang, Maopeng Ran, Chaoyang Dong
The paper investigate the fault-tolerant attitude control for the rigid spacecraft attitude system with external disturbances and actuator faults simultaneously. Firstly, an iterative learning-based observer is proposed, which can estimate the actuator faults with high precise even in presence of the disturbance. Then, employing the estimate informations of the designed observer, a sliding-mode fault-tolerant control scheme is designed to guarantee stability of the closed-loop system and reject to the external disturbance. Finally, the simulation results are given to validate the effectiveness of the proposed approaches.
{"title":"Observer-based Sliding Mode Fault-Tolerant Control for Spacecraft Attitude System with Actuator Faults","authors":"Qing Wang, X. Liang, Maopeng Ran, Chaoyang Dong","doi":"10.1109/SAFEPROCESS45799.2019.9213410","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213410","url":null,"abstract":"The paper investigate the fault-tolerant attitude control for the rigid spacecraft attitude system with external disturbances and actuator faults simultaneously. Firstly, an iterative learning-based observer is proposed, which can estimate the actuator faults with high precise even in presence of the disturbance. Then, employing the estimate informations of the designed observer, a sliding-mode fault-tolerant control scheme is designed to guarantee stability of the closed-loop system and reject to the external disturbance. Finally, the simulation results are given to validate the effectiveness of the proposed approaches.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"11 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":"130795578","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/SAFEPROCESS45799.2019.9213354
Yanqiang Zhai, N. Zhong, Zhenhai Zhang
A fault detection and identification (FDI) method based on mixed logic dynamic(MLD) model for three-phase inverter using single current sensor is proposed in this paper. Single current sensor is used to measure and reconstruct the output currents of a three-phase inverter. A MLD model of the inverter is further established to estimate the output current in real-time under different fault conditions. The estimated currents and the measured currents can be compared and residuals between them can also be calculated in real-time to detect and locate the faults. Compared with existing FDI methods, method proposed in this paper can reduce the uncertainty brought by current sensors by using single current sensor, and improve the accuracy of fault diagnosis by using mixed logic model of the inverter. Simulation results show the effectiveness of the FDI method.
{"title":"A Fault Detection and Identification Method Based on Mixed Logic Dynamic Model for Three-phase Inverter Using Single Current Sensor","authors":"Yanqiang Zhai, N. Zhong, Zhenhai Zhang","doi":"10.1109/SAFEPROCESS45799.2019.9213354","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213354","url":null,"abstract":"A fault detection and identification (FDI) method based on mixed logic dynamic(MLD) model for three-phase inverter using single current sensor is proposed in this paper. Single current sensor is used to measure and reconstruct the output currents of a three-phase inverter. A MLD model of the inverter is further established to estimate the output current in real-time under different fault conditions. The estimated currents and the measured currents can be compared and residuals between them can also be calculated in real-time to detect and locate the faults. Compared with existing FDI methods, method proposed in this paper can reduce the uncertainty brought by current sensors by using single current sensor, and improve the accuracy of fault diagnosis by using mixed logic model of the inverter. Simulation results show the effectiveness of the FDI method.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"398 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":"124510863","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/SAFEPROCESS45799.2019.9213369
Fei Wang, Liangguang Zheng, Chengrui Zhao
The platinum resistance temperature sensors, which are widely applied in high speed trains, have the disadvantage of unreliable performance which usually causes train delay. This paper presents a reliable high-speed train axle temperature monitoring system based on fluorescent optical fiber temperature sensor, which has the advantages of accurate temperature measurement, good versatility, simple principle, and low cost. The fluorescent decay effect is used to measure the temperature, and the optical fiber is used to transfer the fluorescent signal in order to overcome the failure of insulation, water, and electromagnetic interference (EMI). The system shows high accuracy and reliability in the type test, and will be used on the track engineering vehicle to get a real test.
{"title":"Research on Reliable High-speed Train Axle Temperature Monitoring System based on Fluorescence Optical Fiber Sensor","authors":"Fei Wang, Liangguang Zheng, Chengrui Zhao","doi":"10.1109/SAFEPROCESS45799.2019.9213369","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213369","url":null,"abstract":"The platinum resistance temperature sensors, which are widely applied in high speed trains, have the disadvantage of unreliable performance which usually causes train delay. This paper presents a reliable high-speed train axle temperature monitoring system based on fluorescent optical fiber temperature sensor, which has the advantages of accurate temperature measurement, good versatility, simple principle, and low cost. The fluorescent decay effect is used to measure the temperature, and the optical fiber is used to transfer the fluorescent signal in order to overcome the failure of insulation, water, and electromagnetic interference (EMI). The system shows high accuracy and reliability in the type test, and will be used on the track engineering vehicle to get a real test.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"26 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":"124544597","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/safeprocess45799.2019.9213326
Bai Xingzhen, Bao Cunyu, Bo Cuimei, Cai Baigen, Cai Peipei, Cai Zhiduan, Cao Langcai, Cao Yuping, Che Haochi, Chen Maoyin, Chen Qiming, Chen Tongwen, Chen Zhiwen, Chen Zhuo, Dai Xi, Demba Diall, Deng Meng, Deng Xiaogang, Ding Shige, Ding Zhongjun, Ding Zhou, Dong Jingchao, Dong Wei, D. Lei, Du Dongsheng, Du Fei, Du Zhiyong, Fang Haidong, Fan Saite, Fang Dikai, Fan Huajing, Fang Jingzhong, Fang Yifan, Fu Qilong, Gai Wendong, Gao Bingpeng, Gao Jiajun, Gao Min, Gao Siyang, Gao Zhifeng, G. Zhiqiang, Geng Yangfeng, G. Zhiqiang, Gong Jianye, Gong Longhao, Gong Zifeng, Gu Guoxiang, Guo Jianxin, Guo Jin, Guo Shenghui, Guo Tianxu
Pub Date : 2019-07-01DOI: 10.1109/SAFEPROCESS45799.2019.9213415
L. Yin, Jianwei Liu, Pu Yang
This paper presents an interval observer-based fault detection (IOFD) scheme in UAVs formation system. Firstly, for the formation system in healthy case, the interval observer is constructed based on the known boundary information of the disturbance term and relative output estimation error. Then, the residual errors that can be used for detecting the actuator faults are developed by the output estimation error. Different from the traditional FD schemes, it is not necessary to design the threshold generators in the IOFD scheme. At last, MATLAB proves the correctness and feasibility of the IOFD scheme.
{"title":"Interval Observer-based Fault Detection for UAVs Formation with Actuator Faults","authors":"L. Yin, Jianwei Liu, Pu Yang","doi":"10.1109/SAFEPROCESS45799.2019.9213415","DOIUrl":"https://doi.org/10.1109/SAFEPROCESS45799.2019.9213415","url":null,"abstract":"This paper presents an interval observer-based fault detection (IOFD) scheme in UAVs formation system. Firstly, for the formation system in healthy case, the interval observer is constructed based on the known boundary information of the disturbance term and relative output estimation error. Then, the residual errors that can be used for detecting the actuator faults are developed by the output estimation error. Different from the traditional FD schemes, it is not necessary to design the threshold generators in the IOFD scheme. At last, MATLAB proves the correctness and feasibility of the IOFD scheme.","PeriodicalId":353946,"journal":{"name":"2019 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)","volume":"32 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":"114444995","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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