Subway rail fastener vibration signal detection device and health assessment method

The invention discloses a vibration signal detection device for an urban subway rail fastener. The vibration signal detection device comprises a piezoresistor, an amplifying and filtering circuit, anA/D conversion circuit, a processor and a display. The method for evaluating the health condition of...

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Hauptverfasser: ZHENG YINGJIE, SUN JIANG, SHI ZHANGHAI, WANG FUSHENG, GE XINGLAI, MA ZHIYUAN
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creator ZHENG YINGJIE
SUN JIANG
SHI ZHANGHAI
WANG FUSHENG
GE XINGLAI
MA ZHIYUAN
description The invention discloses a vibration signal detection device for an urban subway rail fastener. The vibration signal detection device comprises a piezoresistor, an amplifying and filtering circuit, anA/D conversion circuit, a processor and a display. The method for evaluating the health condition of the rail fastener comprises the following steps of S1, establishing a database of rail fastener vibration signals; S2, collecting vibration signals generated when rail fasteners on a plurality of subway rails work; S3, establishing a BP neural network model; S4, respectively training to obtain a healthy vibration signal BP neural network model, a sub-healthy vibration signal BP neural network model and a dangerous vibration signal BP neural network model; and S5, identifying the type of the vibration signal, and displaying an identification result on a display screen. According to the method, the detected electric signals are screened through the BP neural network, the health condition of the specific rail fastener
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The vibration signal detection device comprises a piezoresistor, an amplifying and filtering circuit, anA/D conversion circuit, a processor and a display. The method for evaluating the health condition of the rail fastener comprises the following steps of S1, establishing a database of rail fastener vibration signals; S2, collecting vibration signals generated when rail fasteners on a plurality of subway rails work; S3, establishing a BP neural network model; S4, respectively training to obtain a healthy vibration signal BP neural network model, a sub-healthy vibration signal BP neural network model and a dangerous vibration signal BP neural network model; and S5, identifying the type of the vibration signal, and displaying an identification result on a display screen. 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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
MEASUREMENT OF MECHANICAL VIBRATIONS OR ULTRASONIC, SONIC ORINFRASONIC WAVES
MEASURING
PHYSICS
TESTING
title Subway rail fastener vibration signal detection device and health assessment method
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