华北工学院测试技术学报2000，Vol.14Issue(1)：7-11,5.
应用概率神经网络诊断自行火炮发动机的故障
Using Probabilistic Neural Network to Diagnose the Fault of Self-propelled Gun Engine
于治会1
作者信息
- 1. 沈阳新乐精密机器公司检测中心, 辽宁沈阳 110034
- 折叠
摘要
Abstract
Aim To research Probabilistic Neural Network(PNN) model, and its application to fault diagnosis. Methods Based on probability statistics theory and Bayes Classification Rule, PNN model, network structure, algorithm, and their characteristic is analyzed, and applied to fault diagnosis. An optimization method to estimate smoothing parameters is established. Results It is very good to diagnose the oil and gas fault in Self-propelled Gun Engine(SPGE) by using PNN. Conclusion Using PNN will get better effect in the field of pattern recognition and fault diagnosis.关键词
概率神经网络/Bayes 分类规则/故障诊断Key words
probability neural networks/bayes classification rule/ fault diagnosis分类
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于治会..应用概率神经网络诊断自行火炮发动机的故障[J].华北工学院测试技术学报,2000,14(1):7-11,5.
