基于自组织特征映射网络的采煤机故障诊断

Fault Diagnosis of Shearer based on Self-organizing Feature Mapping Network

针对采煤机日常运行中各类故障难以诊断的问题,以MG300/700-WD型交流电牵引采煤机为研究对象,通过提取采煤机的故障特征信息,并结合相关样本数据,提出了一种基于自组织特征映射(SOM)网络的采煤机故障诊断模型。经Matlab仿真测试,采用SOM网络进行采煤机故障诊断具有一定的可行性和实用性。

Aiming at the problem that it is difficult to diagnose all kinds of faults in the daily operation of shearer, taking the MG300/700-WD type AC electric haulage shearer as the research object, by extracting the fault feature information of shearer and combining with relevant sample data, a shearer fault diagnosis model based on self-organizing feature map(SOM) network is proposed. Through the Matlab simulation test, it is feasible and practical to use SOM network to diagnose the fault of shearer.