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• W2361281632 abstract "Real-time and exact sampling of suspension state in Middle-Low speed maglev train(LMSMT) is a basal part with great importance,which depends upon the state of sensors mostly.To ensure the dependability of the sensors,the system has been designed redundantly and the control algorithm has been improved.However,fault of the sensors cannot be detected on-line,which affects stability of the whole suspension frame and even becomes a menace in the safety of the train.This paper introduces a fault detection method of position sensors based on adaptive filter,which identifies fault state of each sensor by analyzing the relativity of the signal difference between each sensor.By analyzing the simulated signal and experimenting,it is confirmed that the proposed method can be applied in fault detection of position sensors efficiently." @default.
• W2361281632 created "2016-06-24" @default.
• W2361281632 creator A5014726262 @default.
• W2361281632 date "2010-01-01" @default.
• W2361281632 modified "2023-09-26" @default.
• W2361281632 title "Fault Detection of Position Sensors in LMSMT" @default.
• W2361281632 hasPublicationYear "2010" @default.
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