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논문 기본 정보

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한국동력기계공학회 한국동력기계공학회 학술대회 논문집 2006年度 春季學術大會 論文集
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    초록·키워드

    This paper concerns of establishing the intelligent system for faults detection and classification of induction motor using wavelet support vector machine (W-SVM). Support vector machine (SVM) is well known as an intelligent classifier with strong generalization ability. Application of non-linear SVM using kernel function is widely used for multi-class classification procedure. In this paper, building kernel function using wavelet is introduced and applied for SVM multi-class classifier. Moreover, the feature vectors for training classification routine are obtained from feature extraction and reduction using component analysis via independent component analysis (ICA) and principal component analysis (PCA). Hence, a relatively new intelligent faults detection and classification method called W-SVM is established. This method is used to induction motor for faults detection based on vibration signal. The results show that this method can well classify and separate each condition of faults in induction motor based on experimental work. Finally, it can contribute the intelligent faults detection system in the future.

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      UCI(KEPA) : I410-ECN-0101-2009-550-014957102