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Technical Briefs

Commutation Sparking Image Monitoring for DC Motor

[+] Author and Article Information
Fei Hu

Department of Precision Machinery and Precision Instrumentation,  University of Science and Technology of China, Hefei, Anhui, 230026, P. R. Chinafeihu@mail.ustc.edu.cn

Qingbo He

Department of Precision Machinery and Precision Instrumentation,  University of Science and Technology of China, Hefei, Anhui, 230026, P. R. Chinaqbhe@ustc.edu.cn

Jianping Wang

Department of Precision Machinery and Precision Instrumentation,  University of Science and Technology of China, Hefei, Anhui, 230026, P. R. Chinawjp@ustc.edu.cn

Zhigang Liu

Department of Precision Machinery and Precision Instrumentation,  University of Science and Technology of China, Hefei, Anhui, 230026, P. R. Chinaliuzg@ustc.edu.cn

Fanrang Kong1

Department of Precision Machinery and Precision Instrumentation,  University of Science and Technology of China, Hefei, Anhui, 230026, P. R. Chinakongfr@ustc.edu.cn

1

Corresponding author

J. Manuf. Sci. Eng 134(2), 024501 (Apr 04, 2012) (6 pages) doi:10.1115/1.4005796 History: Received October 31, 2010; Revised December 30, 2011; Published March 30, 2012; Online April 04, 2012

As one of the most important parameters in evaluating the status of a DC motor, commutation spark has been widely used in condition monitoring and fault diagnosis. A new approach using image processing techniques on the commutation spark has been proposed. Advantageous over other methods using partial spark information, the details about the motor condition can be comprehensively retained and extracted from the sparking images. The sparking images were obtained by the cameras, which were fixed at the certain sites in DC motor beforehand. The images were processed through the sparking image preprocessing, segmentation, enhancement, and feature extraction. Comparing the characteristic parameters of the sparking image with the result of the subjective grading, the relationship between the parameters and the sparking grades had been analyzed to monitor the DC motor. The effectiveness had been demonstrated by application examples.

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Copyright © 2012 by American Society of Mechanical Engineers
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Figures

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Figure 1

Distribution of the brushes and image probes

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Figure 2

Systemic flow diagram of sparking monitoring

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Figure 3

Sparking image processing

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Figure 4

Processing background images by averaging multiple images (a) Histogram of a single background image; (b) histogram of the averaged background images

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Figure 5

Sparking at grade 1.25: (a) Raw image and (b) image after segmentation

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Figure 6

Sparking at grade 1.5: (a) Raw image and (b) image after segmentation

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Figure 7

Sparking at grade 2: (a) Raw image and (b) image after segmentation

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Figure 8

Sparking at grade 3: (a) Raw image and (b) image after segmentation

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