کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
386860 660892 2008 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Decision-level fusion based on wavelet decomposition for induction motor fault diagnosis using transient current signal
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Decision-level fusion based on wavelet decomposition for induction motor fault diagnosis using transient current signal
چکیده انگلیسی

In this paper, we propose and implement a decision-level fusion model by combining the information of multi-level wavelet decomposition for fault diagnosis of induction motor using transient stator current signal. Firstly, the start-up transient current signals are collected from different faulty motors. Then signal preprocessing is conducted containing smoothing and subtracting to reduce the influence of line frequency in transient current signals. Next, we employ discrete wavelet transform technique to decompose the preprocessed signals into different frequency ranges of products, and then features are extracted from decomposed detail components. Finally, two decision-level fusion strategies, Bayesian belief fusion and multi-agent fusion, are employed. That is, fault features are classified using several classifiers and generated decisions are fused using a specific fusion algorithm. The proposed approach is evaluated by an experiment of fault diagnosis for induction motors. Experiment results show that excellent diagnosis performance can be obtained.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 35, Issue 3, October 2008, Pages 918–928
نویسندگان
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