Ambiguity groups detection in analog systems diagnostics using Self-Organizing Maps

Piotr Bilski

Abstract

The paper presents the application of Self- Organizing Maps (SOM) to the ambiguity groups detection in the analog system. This type of neural network is able to find dependencies in data, indicating groups of similar examples in the data set used for training the classifier or the regression machine. Various configurations of the network were implemented and compared. The ability to detect ambiguity groups was verified on the model of the induction machine. Results show the efficiency of the approach, able to identify examples difficult to distinguish by the fault detection and location scheme.

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IMEKO TC

TC10 - Measurement for Diagnostics, Optimization and Control

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