矿用带式输送机在线监测与故障诊断系统设计

Design of on-Line Monitoring and Fault Diagnosis System for Mining Belt Conveyor

为了提高井下运输效率,提出了一种基于小波包分解和支持向量机相结合的方法的带式输送机在线监测与故障诊断系统设计思路和方案。首先,为了减少传感器数量,采用一个加速度传感器采集多个托辊的振动信号,通过对振动信号进行小波包分解和提取各频带能量作为特征;然后,利用这些特征训练支持向量机,以实现对托辊故障的检测;最后设计了带式输送机在线监测与故障诊断系统并进行试验。通过现场试验发现,在有限数量的传感器下该系统可以完成在线监测与故障诊断,对提高井下运输效率具有重要意义。

In order to improve the efficiency of underground transportation,this paper proposes a method combining wavelet packet decomposition and support vector machine to carry out on-line monitoring and fault diagnosis of belt conveyor.Because the number of rollers may be large,in order to reduce the number of sensors,an acceleration sensor is used to collect the vibration signals of multiple rollers.The vibration signal is decomposed by wavelet packet decomposition,and the energy of each frequency band is extracted as the feature.Then,these features are used to train the support vector machine to realize the detection of the roller fault.Firstly,the proposed fault diagnosis method is tested on the test bench,and then the on-line monitoring and fault diagnosis system of belt conveyor is designed.Through the field test,it is found that the position of the fault roller can be located under a limited number of sensors,which is of great significance to the operation of the actual belt conveyor.