期刊
SENSORS
卷 19, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/s19081847
关键词
surface quality monitoring; wireless sensory tool holder; feature extraction; deep forest
资金
- National Natural Science Foundation of China [51705015]
- Equipment Pre-Research Program of China [41423010301]
- National Defense Fundamental Research Foundation of China [JCKY2016601C006]
The quality of a machined surface plays a critical role in assembly performance, especially for precise matching parts, and therefore it is necessary to develop a surface quality monitoring system in the machining process. In this paper, an indirect surface quality monitoring approach is proposed with a wireless sensory tool holder. First, experimentation is conducted to collect the machining process signals from the tool holder. Then, the time domain, frequency domain and time-frequency domain features are extracted, and the deep forest algorithm is adopted to identify the surface quality, which is evaluated through the surface average parameter. Finally, the results of the experiment and the comparisons with other approaches demonstrate the effectiveness of the proposed method, which could be applied to ensure the surface quality, improve the machining efficiency and reduce the rejection rate of the machining process.
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