Analysis and recognition method of wear degree of roadheader cutting picks
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摘要: 为了实现掘进机截齿磨损程度的精确识别，提出了掘进机截齿磨损程度分析及识别方法，测试和提取了不同磨损程度截齿截割过程中的三向振动信号和电流信号，建立了各截割特征信号的样本证据组，采用基于修改模型的D-S组合识别模型实现了截齿磨损程度在线识别。实验结果表明，该方法能够根据多截割特征信号实现截齿磨损程度的精确识别，具有较高的识别精度和可靠性，为确定截齿的最佳维护和更换周期提供了重要依据。Abstract: In order to realize accurate identification of wear degree of roadheader cutting picks, an analysis and recognition method of wear degree of roadheader cutting picks was proposed. Three-direction vibration signal and current signal in cutting process of picks with different wear degree were tested and extracted. Sample evidence set for each cutting characteristic signal was established, and on-line recognition of wear degree of picks was realized by using D-S combination recognition model based on modified model. The experimental results show that the proposed method can accurately identify wear degree of picks according to multi cutting characteristic signals, and has high recognition precision and reliability, which provides important basis for determining the optimal maintenance and replacement period of picks.
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Keywords:
- coal mining /
- roadheader /
- cutting pick /
- wear degree /
- on-line identification /
- D-S combinatio
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期刊类型引用(3)
1. 葛利俊，刘学文，毕琳琳. 水力泵在气井排采中的应用. 设备管理与维修. 2022(18): 95-97 . 
百度学术
2. 刘磊. 煤层气精准排采监控系统. 工矿自动化. 2020(03): 89-94 . 本站查看
3. 徐启. 基于PLC的液压无杆排采系统研究. 机电工程. 2019(08): 846-850 . 百度学术
其他类型引用(1)
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