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The defects diagnosis and pattern classification are presented in this paper. Morphological pattern spectrum describes the shape characteristics of the inspected signal based on the morphological opening operation with multi-scale structuring elements. The pattern spectrum entropy and the barycenter scale location of the spectrum curve are extracted as the feature vector presenting different defects...
We address the issue of classification problems in the following situation: test data include data belonging to unlearned classes. To address this issue, most previous works have taken two-stage strategies where unclear data are detected using an anomaly detection algorithm in the first stage while the rest of data are classified into learned classes using a classification algorithm in the second...
Electric transformers play an important role in the electrical power system, and there is a strong demand on their reliable and safe operation. Support vector machine (SVM) based classification gives a promising approach for fault diagnostics of electric transformers. But the standard method for N-class SVMs (there are many types of electrical transformer fault) doesn't present an easy solution. The...
In fault pattern recognition field, the real-time online fault diagnosis is a new requirement especially from the high-speed machines, and also the magnificent researching direction. The precision and speed of the classification are important research issues in fault pattern recognition for this kind of intelligent fault diagnosis. Although many improved ANN (artificial neural net) methods have been...
A reliable and precise classification of breast cancer is essential for successful diagnosis. Discrimination methods, including mahalanobis distance, Fisher rules and support vector machine, are applied for the classification of breast cancer diagnosis. This article compares the performance of different discrimination methods
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