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作 者:Juhan WANG Ying GAO Yuan CAO Tao TANG
机构地区:[1]School of Electronics and Information Engineering,Beijing Jiaotong University,Beijing 100044,China [2]Graduate Department,China Academy of Railway Science,Beijing 100044,China [3]National Engineering Research Center of Rail Transportation Operation and Control System,Beijing Jiaotong University,Beijing 100044,China
出 处:《Chinese Journal of Electronics》2024年第1期274-281,共8页电子学报(英文版)
基 金:supported by the National Key R&D Program of China(Grant No.2021YFF0501102);the National Natural Science Foundation of China(Grant Nos.U1934219,52022010,and 52202392)。
摘 要:The pressure data of the train air braking system is of great significance to accurately evaluate its operation state.In order to overcome the influence of sensor fault on the pressure data of train air braking system,it is necessary to design a set of sensor fault-tolerant voting mechanism to ensure that in the case of a pressure sensor fault,the system can accurately identify and locate the position of the faulty sensor,and estimate the fault data according to other normal data.A fault-tolerant mechanism based on multi-classification support vector machine(SVM)and adaptive network-based fuzzy inference system(ANFIS)is introduced.Multi-classification SVM is used to identify and locate the system fault state,and ANFIS is used to estimate the real data of the fault sensor.After estimation,the system will compare the real data of the fault sensor with the ANFIS estimated data.If it is similar,the system will recognize that there is a false alarm and record it.Then the paper tests the whole mechanism based on the real data.The test shows that the system can identify the fault samples and reduce the occurrence of false alarms.
关 键 词:Multi-classification support vector machine Adaptive network-based fuzzy inference system Train air braking system Fault-tolerant voting Multi-sensors.
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