Sensor fault diagnosis based on auto associative neural network

XU Yue; ZHU Wei-xing

doi:10.13873/j.1000-97872007.04.021

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Sensor fault diagnosis based on auto associative neural network

更新时间：2025-09-11

- Sensor fault diagnosis based on auto associative neural network
- Issue 4, Pages: 94-96(2007)
- 作者机构：
  
  1. 江苏大学电气信息工程学院
  2. 江苏大学电气信息工程学院,江苏,镇江,212013
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872007.04.021
  CLC： TP183;TP277
- Published：2007
- 稿件说明：
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[1]许跃,朱伟兴.基于自联想神经网络的传感器故障诊断[J].传感器与微系统,2007(04):94-96.

XU Yue, ZHU Wei-xing. Sensor fault diagnosis based on auto associative neural network[J]. 2007, (4): 94-96.
[1]许跃,朱伟兴.基于自联想神经网络的传感器故障诊断[J].传感器与微系统,2007(04):94-96. DOI： 10.13873/j.1000-97872007.04.021.

XU Yue, ZHU Wei-xing. Sensor fault diagnosis based on auto associative neural network[J]. 2007, (4): 94-96. DOI： 10.13873/j.1000-97872007.04.021.

摘要

提出一种基于自联想神经网络（AANN）的新算法用于系统中传感器故障诊断。阐述了AANN的结构和算法。具体说明了搜寻2个故障传感器和恢复信号的方法。用改进的AANN诊断有噪声情况下传感器跳变故障并恢复信号。本方法有易实现、结构简单的优点

仿真结果表明:本方法是可行的。

Abstract

A novel algorithm based on auto associative neural networks（AANN）is given for sensor failure diagnosis.The structure and algorithm of AANN are presented.The approach is proposed for searching two faulty sensors and estimating their real value.Enhanced AANN is used to diagnose sensor drift failure and recover their signals.The method is easy to realize and has simple structure.The simulation results show the method works well.

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references

BP神经网络用于传感器故障诊断的仿真研究 [J]. 曹曦,苏明,黄善衡. 上海铁道大学学报 . 2000(06)

基于改进鲁棒自联想神经网络的传感器故障诊断新方法 [J]. 张晨,韩月秋,陶然. 仪器仪表学报 . 1999(02)

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