THE SURVEILLANCE OF LARGE ROTATING MACHINERY VIA ARTIFICIAL NEURAL NETWORKS

陈岳东; 屈梁生

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THE SURVEILLANCE OF LARGE ROTATING MACHINERY VIA ARTIFICIAL NEURAL NETWORKS

更新时间：2025-12-16

- THE SURVEILLANCE OF LARGE ROTATING MACHINERY VIA ARTIFICIAL NEURAL NETWORKS
- CIESC Journal Issue 1, (1993)
- 作者机构：
  
  西安交通大学机械工程系,西安交通大学机械工程系西安710049,西安,710049
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Online First：25 February 1993，
  
  Published：25 February 1993
- 稿件说明：
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陈岳东, 屈梁生. THE SURVEILLANCE OF LARGE ROTATING MACHINERY VIA ARTIFICIAL NEURAL NETWORKS[J]. CIESC Journal, 1993, (1).
DOI：

陈岳东, 屈梁生. THE SURVEILLANCE OF LARGE ROTATING MACHINERY VIA ARTIFICIAL NEURAL NETWORKS[J]. CIESC Journal, 1993, (1). DOI：

摘要

Abstract

In recent years

artificial neural networks(ANNs) have been successfully used in many fields. In order to improve the accuracy of surveillance and diagnosis for large rotating machinery in chemical processes

first

the time domain signal is transformed into featuressuited for the learning of neural network

then

ANN(BP) is used to extract the features of the field vibrational signal. By means of the features extraced

it is easy to monitor the vibration situation of a machinery unit. Checking with practical vibration data has proved this method to be satisfactory.

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