A Mahalanobis Distance Measurement Method to Analyze Current Waveform for Determining the Motor’s Quality Types

This study proposes a Mahalanobis Distance Measurement (MDM) method to analyze current waveform for determining the motor’s quality types. The MDM method consists of three major stages: (i) the preprocessing stage which is for enlarging motor current waveforms’ amplitude and eliminating noises, and includes signal amplitude amplifier, filter circuit (eliminating noises), and analog-to-digital converter (ADC) parts, (ii) the qualitative features stage which is for qualitative feature selection on motor current waveforms, and (iii) the classification stage which is for determining motor quality types using the MDM method. It can recognize defective motors and their defective types in less than 0.5 second. In the experiment, the total classification accuracy (TCA) was approximately 99.03% in average. The proposed method has the advantages of good detection results, no complex mathematic computations, hi-speed, and hi-reliability.

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Acoustic Distance Measurement Method Using 2ch Microphones Measurable from 0m Based on Phase Interference and Removal of DC Component

IEEJ Transactions on Electronics Information and Systems ◽

10.1541/ieejeiss.135.1349 ◽

2015 ◽

Vol 135 (11) ◽

pp. 1349-1350

Author(s):

Kazuhiro Suzuki ◽

Noboru Nakasako ◽

Masato Nakayama ◽

Toshihiro Shinohara ◽

Tetsuji Uebo

Keyword(s):

Measurement Method ◽

Distance Measurement ◽

Phase Interference ◽

Dc Component

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Acoustic Distance Measurement Method Based on Phase Interference Using Calibration and Whitening Processing in Real Environments

IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences ◽

10.1587/transfun.e94.a.1638 ◽

2011 ◽

Vol E94-A (8) ◽

pp. 1638-1646 ◽

Cited By ~ 3

Author(s):

Masato NAKAYAMA ◽

Shimpei HANABUSA ◽

Tetsuji UEBO ◽

Noboru NAKASAKO

Keyword(s):

Measurement Method ◽

Distance Measurement ◽

Phase Interference

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Feature selection of the armature winding broken coils in synchronous motor using genetic algorithm and mahalanobis distance

Archives of Metallurgy and Materials ◽

10.2478/v10172-012-0091-7 ◽

2012 ◽

Vol 57 (3) ◽

pp. 829-835 ◽

Cited By ~ 1

Author(s):

Z. Głowacz ◽

J. Kozik

Keyword(s):

Genetic Algorithm ◽

Feature Selection ◽

Mahalanobis Distance ◽

Distance Measure ◽

Synchronous Motor ◽

Medical Diagnostics ◽

Motor Current ◽

Feature Spaces ◽

Multidimensional Feature Spaces ◽

Selection Of

The paper describes a procedure for automatic selection of symptoms accompanying the break in the synchronous motor armature winding coils. This procedure, called the feature selection, leads to choosing from a full set of features describing the problem, such a subset that would allow the best distinguishing between healthy and damaged states. As the features the spectra components amplitudes of the motor current signals were used. The full spectra of current signals are considered as the multidimensional feature spaces and their subspaces are tested. Particular subspaces are chosen with the aid of genetic algorithm and their goodness is tested using Mahalanobis distance measure. The algorithm searches for such a subspaces for which this distance is the greatest. The algorithm is very efficient and, as it was confirmed by research, leads to good results. The proposed technique is successfully applied in many other fields of science and technology, including medical diagnostics.

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