Surface roughness detection based on spindle motor current signal
Workpiece waste is usually caused by delayed detection of surface roughness. A rapid surface roughness detection classification based on the current signal of the spindle motor is proposed for the first time. The current signals of the spindle motor under different surface roughness processing condi...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | Chinese |
| Published: |
National Computer System Engineering Research Institute of China
2024-02-01
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| Series: | Dianzi Jishu Yingyong |
| Subjects: | |
| Online Access: | http://www.chinaaet.com/article/3000163479 |
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| Summary: | Workpiece waste is usually caused by delayed detection of surface roughness. A rapid surface roughness detection classification based on the current signal of the spindle motor is proposed for the first time. The current signals of the spindle motor under different surface roughness processing conditions are collected through experiments, and the current signals are decomposed into different frequency bands through wavelet packet decomposition. The current signals of different frequency bands are evaluated by the energy characteristics and the margin factors, and the low correlation frequency bands are filtered. Then the features are screened through random forest to reduce the redundancy of features. The total harmonic distortion feature achieves built-up edge detection during the machining process. The workpiece surface roughness detection accuracy is as high as 95%. And the detection time is within 2 seconds. Spindle current signal analysis basically achieves fast and accurate detection of workpiece surface roughness. |
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| ISSN: | 0258-7998 |