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| 題 名 | The Application of Artificial Neural Network on Sound-Signal Recognition for Induction Motor=類神經網路在馬達聲訊辨識上之應用 |
|---|---|
| 作 者 | 曹大鵬; 吳榮慶; | 書刊名 | Proceedings of the National Science Council : Part A, Physical Science and Engineering |
| 卷 期 | 23:1 1999.01[民88.01] |
| 頁 次 | 頁75-84 |
| 分類號 | 448.2 |
| 關鍵詞 | 類神經網路; 馬達; 聲訊辨識; Fault recognition; Artificial neural network; Feature exacting; Induction motor; |
| 語 文 | 英文(English) |
| 英文摘要 | In the past, the research on fault recognition for induction motors only concentrated on spectrum amplitudes which are based on a constant load. However, the frequency and amplitude of the spectrum analyzed under different fault conditions are also affected significantly by load variation. Hence, simply using spectrum amplitudes to recognize motor faults is not sufficient in a practical system. Both various load conditions and different types of faults will influence the spectrum structure. In order to recognize faults under various load conditions, we have to consider band shift and amplitude as two major factors. In this paper, we use band shift and amplitude techniques to solve the spectrum problem under various load conditions and different types of faults. We also use the methods of frequency axis adjustment and feature exaction to solve the band shift and amplitude variation problems respectively. After the above-mentioned procedures,efficient features are obtained. Then, we use the back propagation artificial neural network (ANN) to train and recognize fault conditions. In addition, we compare the recognition ability between the artificial neural network and traditional method. All the theories and methods used in the paper are validated by means of different experimental results on motors. |
本系統中英文摘要資訊取自各篇刊載內容。