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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| Format: | Article |
| Language: | Chinese |
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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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| _version_ | 1839651652691296256 |
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| author | Liu Xuejie Li Guofu Ren Lu |
| author_facet | Liu Xuejie Li Guofu Ren Lu |
| author_sort | Liu Xuejie |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-a2bf2df11c2044cba70d6005979aec1d |
| institution | Matheson Library |
| issn | 0258-7998 |
| language | zho |
| publishDate | 2024-02-01 |
| publisher | National Computer System Engineering Research Institute of China |
| record_format | Article |
| series | Dianzi Jishu Yingyong |
| spelling | doaj-art-a2bf2df11c2044cba70d6005979aec1d2025-06-26T02:12:08ZzhoNational Computer System Engineering Research Institute of ChinaDianzi Jishu Yingyong0258-79982024-02-01502545910.16157/j.issn.0258-7998.2342083000163479Surface roughness detection based on spindle motor current signalLiu Xuejie0Li Guofu1Ren Lu2College of Mechanical Engineering and Mechanics，Ningbo University，Ningbo 315211， ChinaCollege of Mechanical Engineering and Mechanics，Ningbo University，Ningbo 315211， ChinaCollege of Mechanical Engineering and Mechanics，Ningbo University，Ningbo 315211， ChinaWorkpiece 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.http://www.chinaaet.com/article/3000163479spindle motor current signalwavelet packet decompositionrandom forestthe total harmonic distortionsurface roughness |
| spellingShingle | Liu Xuejie Li Guofu Ren Lu Surface roughness detection based on spindle motor current signal Dianzi Jishu Yingyong spindle motor current signal wavelet packet decomposition random forest the total harmonic distortion surface roughness |
| title | Surface roughness detection based on spindle motor current signal |
| title_full | Surface roughness detection based on spindle motor current signal |
| title_fullStr | Surface roughness detection based on spindle motor current signal |
| title_full_unstemmed | Surface roughness detection based on spindle motor current signal |
| title_short | Surface roughness detection based on spindle motor current signal |
| title_sort | surface roughness detection based on spindle motor current signal |
| topic | spindle motor current signal wavelet packet decomposition random forest the total harmonic distortion surface roughness |
| url | http://www.chinaaet.com/article/3000163479 |
| work_keys_str_mv | AT liuxuejie surfaceroughnessdetectionbasedonspindlemotorcurrentsignal AT liguofu surfaceroughnessdetectionbasedonspindlemotorcurrentsignal AT renlu surfaceroughnessdetectionbasedonspindlemotorcurrentsignal |