| Application on Extracting Feature in State Monitoring and Fault Diagnosis |
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| 作者姓名： | CAI Jing zhi |
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| 摘 要： | With the development and application of information and internet and virtual instrument technology ,the virtual globular company based on internet arises .To study remote state monitoring, remote fault detection and diagnosis about large scale, complicated and integrative equipment become very important. In the whole fault diagnosis system , the detecting ,data acquisition is original ,processing; transform and extracting features with the signal detected is a key factor. The theories and methods used in mechanical fault diagnosis is stated. The application of signal process and its feature extracting methods is introduced which are time domain, frequency domain and time frequency domain analysis, in state monitoring and fault diagnosis with its signal analysis. The processing method of random time variant special signal is given also.
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| 关 键 词： | feature extracting state monitoring fault diagnosis signal process |
| 修稿时间： | 2002/12/20 0:00:00 |
Application on Extracting Feature in State Monitoring and Fault Diagnosis |
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| CAI Jing,zhi.Application on Extracting Feature in State Monitoring and Fault Diagnosis[J].Storage & Process,2003(4):93-95. |
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| Authors: | CAI Jing zhi |
| |
| Abstract: | With the development and application of information and internet and virtual instrument technology ,the virtual globular company based on internet arises .To study remote state monitoring, remote fault detection and diagnosis about large scale, complicated and integrative equipment become very important. In the whole fault diagnosis system , the detecting ,data acquisition is original ,processing; transform and extracting features with the signal detected is a key factor. The theories and methods used in mechanical fault diagnosis is stated. The application of signal process and its feature extracting methods is introduced which are time domain, frequency domain and time frequency domain analysis, in state monitoring and fault diagnosis with its signal analysis. The processing method of random time variant special signal is given also. |
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| Keywords: | feature extracting state monitoring fault diagnosis signal process |
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