自动化学报2005，Vol.31Issue(2)：195-201,7.
PWM型VLSI神经网络在故障诊断中的应用
PWM VLSI Neural Network for Fault Diagnosis
摘要
Abstract
An improved pulse width modulation (PWM) neural network VLSI circuit for fault diagnosis is presented, which differs from the software-based fault diagnosis approach and exploits the merits of neural network VLSI circuit. A simple synapse multiplier is introduced, which has high precision, large linear range and less switching noise effects. A voltage-mode sigmoid circuit with adjustable gain is introduced for realization of different neuron activation functions. A voltage-pulse conversion circuit required for PWM is also introduced, which has high conversion precision and linearity. These 3 circuits are used to design a PWM VLSI neural network circuit to solve noise fault diagnosis for a main bearing. It can classify the fault samples directly. After signal processing, feature extraction and neural network computation for the analog noise signals including fault information,each output capacitor voltage value of VLSI circuit can be obtained, which represents Euclid distance between the corresponding fault signal template and the diagnosing signal, The real-time online recognition of noise fault signal can also be realized.关键词
Pulse signal/fault diagnosis/neural network/noise/pulse width modulation/VLSIKey words
Pulse signal/fault diagnosis/neural network/noise/pulse width modulation/VLSI分类
信息技术与安全科学引用本文复制引用
吕琛,王桂增,张泽宇..PWM型VLSI神经网络在故障诊断中的应用[J].自动化学报,2005,31(2):195-201,7.基金项目
Supported by National Natural Science Foundation (60274015) and the "863" Program of P. R. China(2002AA412420) （60274015）
