掘进机截齿失效的识别和改进方案

Identification and Improvement Scheme for Cutter Failure of Tunneling Machine

在煤矿掘进机的生产中,截齿容易受到磨损从而失效,基于常规截齿失效检修的低效率不足问题,提出了截齿磨损度的识别技术。为此,在了解掘进机截齿的主要失效形式后,从截割电流信号、收集三向振动信号出发,进行掘进机截割特征数据库的构建和截割样本特征的分析。明确磨损识别定义和开展数据推理,采用基于修改模型的D-S组合识别模型,进行截齿运行实际磨损程度的在线识别。最后经过试验,能有效了解截齿的磨损度,为截齿的维护检修提供可靠的数据支撑,进一步降低截齿失效的故障率。

In the production of coal mine tunneling machines,the cutting teeth are prone to wear and failure.Based on the low efficiency of conventional cutting tooth failure maintenance,an identification technology for cutting tooth wear degree was proposed.Therefore,after understanding the main failure modes of the cutting teeth of the tunneling machine,starting from the cutting current signal and collecting the three-way vibration signal,the construction of the tunneling machine cutting feature database and the analysis of cutting sample features were carried out.Secondly,the definition of wear recognition was clarified and data inference was carried out.A modified D-S combination recognition model based on the modified model was adopted for online recognition of the actual wear degree during tooth cutting operation.Finally,after testing,it was found that the wear degree of the cutting teeth can be effectively understood,providing reliable data support for the maintenance and repair of the cutting teeth,and further reducing the failure rate of cutting teeth.