| IPCA在故障检测与分离中的应用 |
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| 引用本文： | 成成,黄道.IPCA在故障检测与分离中的应用[J].医学教育探索,2000(5):502-506. |
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| 作者姓名： | 成成 黄道 |
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| 作者单位： | 华东理工大学自动化工程中心,上海 |
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| 基金项目： | 国家科技攻关项目，上海市重点学科建设项目，863-511-854-007，B980403，， |
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| 摘 要： | 针对现有ＢＰ网络在故障诊断中存在的缺陷，提出了利用小波函数构造故障诊断神经元网络，利用变尺度算法进行网络训练，加快了网络的训练速度。并交结果运用到一个ＣＳＴＲ非稳态故障诊断的过程中，仿真实例表明，小波网络较ＢＰ网络具有更好的故障诊断能力。
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| 关 键 词： | 非稳态 故障诊断 小波网络 变尺度法 |
Fault
Detection and Diagnosis by Integrated
Principal Component Analysis |
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| Cheng Cheng,Huang Dao.Fault
Detection and Diagnosis by Integrated
Principal Component Analysis[J].Researches in Medical Education,2000(5):502-506. |
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| Authors: | Cheng Cheng Huang Dao |
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| Abstract: | In order to improve the performance of fault diagnosis systems based on BP networks, a new method based on wavelet networks is presented which incorporated an algorithm of varying scal for training networks so as to accelerate the training process. Simulation research on its application to unsteady fault diagnosis of a CSTR process has proved that it performs more effectively than that based on BP networks. |
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| Keywords: | unsteady fault diagnosis wavelet net quasi newton method CSTR |
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