APPLICATION OF IMPROVED BP NEURON NETWORK IN CONDENSER FAULT DIAGNOSIS

ZHANG LIping; WANG Waifeng; TANG Deshan

doi:10.19666/j.rlfd.2004.03.016

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APPLICATION OF IMPROVED BP NEURON NETWORK IN CONDENSER FAULT DIAGNOSIS

更新时间：2025-09-28

- APPLICATION OF IMPROVED BP NEURON NETWORK IN CONDENSER FAULT DIAGNOSIS
- Thermal Power Generation Issue 3, Pages: 50-52(2004)
- 作者机构：
  
  1. 河海大学
  2. 国电热工研究院
  4. ,江苏,南京,210098
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.2004.03.016
  CLC： TK264.1
- Published：2004
- 稿件说明：
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ZHANG LIping, WANG Waifeng, TANG Deshan. APPLICATION OF IMPROVED BP NEURON NETWORK IN CONDENSER FAULT DIAGNOSIS[J]. Thermal power generation, 2004, (3): 50-52.
DOI：

ZHANG LIping, WANG Waifeng, TANG Deshan. APPLICATION OF IMPROVED BP NEURON NETWORK IN CONDENSER FAULT DIAGNOSIS[J]. Thermal power generation, 2004, (3): 50-52. DOI： 10.19666/j.rlfd.2004.03.016.

摘要

针对BP网络学习收敛速度慢和易陷入局部最小点的不足

提出了一种恒误差修正率控制的网络学习率自适应调整方法。将这种改进的BP网络算法应用于凝汽设备故障诊断中

在 1台 30 0MW机组上取得了实效。

Abstract

In view of low speed selflearning convergence concerning back propagation(BP) neuron network

and the said network being easily in insufficient of partial lowest points

a method of adaptive adjustment for the network selflearning rate controlled by correction rate of constant error has been put forword. This improved BP network has been used in condenser fault dragnosis

and obtaning practical effectiveness on a 300 MW unit.

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