基于EMMD-RVM的煤矿采矿机械设备异常检测系统

Anomaly detection system for coal mine mining machinery and equipment based on EMMD-RVM

针对煤矿采矿机械设备异常特征信号是非均匀变化的,容易出现机械设备异常检测结果不精准的问题,提出了基于EMMD-RVM的煤矿采矿机械设备异常检测系统。采用4通道AD转换芯片,采集煤矿采矿机械设备异常数据。使用ZigBee传感器作为终端设备,传输电压、电流、转速红外成像和温度信号。利用传感器网络协议适配器,将不同传输信号统一传输到服务器,消除传感器网络异构性。采用EMMD极值域均值模式分解方法,引入加权平均法获取信号局部均值,分析煤矿采矿机械设备异常特征。构建RVM支持向量机模型,设计基于RVM的煤矿采矿机械设备异常检测流程。由系统应用结果可知,该系统通过采集高频分量信息,可获取精准异常检测结果,为机械设备异常检测提供一种新思路。

Aiming at the problem that the abnormal characteristic signal of coal mine mining machinery and equipment changes non-uniformly,and the results of abnormal detection of machinery and equipment are prone to inaccurate,an abnormal detection system of coal mine mining machinery and equipment based on EMMD-RVM was proposed.A 4-channel AD conversion chip was used to collect abnormal data of coal mining machinery and equipment.Use ZigBee sensors as end deviced to transmit voltage,current,rotational speed infrared imaging and temperature signals.Using the sensor network protocol adapter,the different transmission signals were uniformly transmitted to the server to eliminate the heterogeneity of the sensor network.The EMMD extreme value domain mean mode decomposition method was adopted,and the weighted average method was introduced to obtain the local mean value of the signal,and the abnormal characteristics of coal mining machinery and equipment were analyzed.The RVM support vector machine model was constructed,and the abnormal detection process of coal mining machinery and equipment based on RVM was designed.It could be seen from the system application results that the system could obtain accurate abnormal detection results by collecting high-frequency component information,which provided a new idea for abnormal detection of mechanical equipment.