Abstract：Focusing on the problem of analog electronic circuit fault diagnosis and location, a novel hybrid fault dictionaries(FDs) based on the one-against-rest support vector machines classifier (SVC) is presented. Firstly, the Euclidean distances between the testing sample and all fault centroids are calculated. Secondly, the signal analysis mechanism is employed for the SVC and the fault can be located accurately by the designed algorithm. The presented method avoids some unnecessary calculations; hence the testing time needed is reduced significantly. Compared to the conventional SVC, such as one-against-rest SVC and one-against-one SVC, the proposed method is simple and fast, also, the performance of this classifier is near or even superior to its counterparts. The simulated and physical experiments validate the presented method.
崔江, 王友仁. 一种新颖的基于混合故障字典方法的模拟故障诊断策略[J]. 电工技术学报, 2013, 28(4): 272-278.
Cui Jiang, Wang Youren. A Novel Strategy of Analog Fault Diagnosis Based on Hybrid Fault Dictionaries. Transactions of China Electrotechnical Society, 2013, 28(4): 272-278.
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2013, Vol. 28 
