Development of an Expert System to Diagnose Rotor Vibration Problems
碩士 === 國立交通大學 === 機械工程研究所 === 85 === In this thesis, an expert system to diagnose rotating machinery vibration problems is developed to achieve the goal of diagnosis automation. The underlying expert system includes the following three modules: (1) Main architecture of the expert system. (2)...
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ndltd-TW-085NCTU34890382015-10-13T17:59:39Z http://ndltd.ncl.edu.tw/handle/39485646901123494870 Development of an Expert System to Diagnose Rotor Vibration Problems 專家系統在轉子振動診斷之研究 Lin, Wei-Yao 林為瑤 碩士 國立交通大學 機械工程研究所 85 In this thesis, an expert system to diagnose rotating machinery vibration problems is developed to achieve the goal of diagnosis automation. The underlying expert system includes the following three modules: (1) Main architecture of the expert system. (2) vibrational signal processing. (3) Rules for diagnosis. The main architecture of the expert system consists of manmachine interface, data-base, rule-base and inference machine. The inference machine performs three inference mechanisms, i.e., the symbol inference, certainty factor inference and fuzzy inference. The second module will execute the job of extracting the features from the specific data of vibration signal. The holospectra and spectra are adopted for feature extraction in vibrational signal analysis. The third module is the essence in our expert system where the diagnosis rules should be carefully built according to the research results reported in refereed literature and knowledge from the in-field expertise in that particular domain. The final expert system is tested by using the simulation of vibration data in rotating machinery. Furthermore, it is noted that the parameters and rules for diagnosis in the expert system should be updated based on the results from a series of experiments with the hope that it will become more and more intelligent and accurate. Lee, An-Chen 李安謙 1997 學位論文 ; thesis 84 zh-TW |
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碩士 === 國立交通大學 === 機械工程研究所 === 85 === In this thesis, an expert system to diagnose rotating machinery vibration problems is developed to achieve the goal of diagnosis automation. The underlying expert system includes the following three modules:
(1) Main architecture of the expert system.
(2) vibrational signal processing.
(3) Rules for diagnosis.
The main architecture of the expert system consists of manmachine interface, data-base, rule-base and inference machine. The inference machine performs three inference mechanisms, i.e., the symbol inference, certainty factor inference and fuzzy inference. The second module will execute the job of extracting the features from the specific data of vibration signal. The holospectra and spectra are adopted for feature extraction in vibrational signal analysis. The third module is the essence in our expert system where the diagnosis rules should be carefully built according to the research results reported in refereed literature and knowledge from the in-field expertise in that particular domain. The final expert system is tested by using the simulation of vibration data in rotating machinery. Furthermore, it is noted that the parameters and rules for diagnosis in the expert system should be updated based on the results from a series of experiments with the hope that it will become more and more intelligent and accurate.
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author2 |
Lee, An-Chen |
author_facet |
Lee, An-Chen Lin, Wei-Yao 林為瑤 |
author |
Lin, Wei-Yao 林為瑤 |
spellingShingle |
Lin, Wei-Yao 林為瑤 Development of an Expert System to Diagnose Rotor Vibration Problems |
author_sort |
Lin, Wei-Yao |
title |
Development of an Expert System to Diagnose Rotor Vibration Problems |
title_short |
Development of an Expert System to Diagnose Rotor Vibration Problems |
title_full |
Development of an Expert System to Diagnose Rotor Vibration Problems |
title_fullStr |
Development of an Expert System to Diagnose Rotor Vibration Problems |
title_full_unstemmed |
Development of an Expert System to Diagnose Rotor Vibration Problems |
title_sort |
development of an expert system to diagnose rotor vibration problems |
publishDate |
1997 |
url |
http://ndltd.ncl.edu.tw/handle/39485646901123494870 |
work_keys_str_mv |
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