采煤机振动信号采集和识别系统设计研究

Design and Research on Vibration Signal Acquisition and Identification System of Shearer

针对采煤机电机转子容易产生故障的问题,设计了一种利用振动信号诊断电机运行状况的方法。首先设计了信号采集硬件,使用STM32采集与处理振动信号,并将信号远传至服务器,然后设计了振动信号故障识别与分类算法,使用信号频谱能量距提取信号的类别特征,使用训练完成的基于VGG16的改进算法对特征进行分类,最后进行实验,结果表明故障分类平均正确率可达95.97%。为采煤机电机的故障识别和分类提供了一套高效的方法。

Aiming at the problem that the motor rotor of shearer is prone to failure, a method of using vibration signal to diagnose the running condition of motor is designed. Firstly, the signal acquisition hardware is designed, the vibration signal is collected and processed by STM32, and the signal is transmitted to the server remotely. Then, the vibration signal fault identification and classification algorithm is designed, the signal spectral energy distance is used to extract the category features of the signal, and the trained improved algorithm based on VGG16 is used to classify the features. Finally, the experiment is carried out, the results show that the average accuracy of fault classification can reach95.97%. It provides a set of efficient methods for fault identification and classification of shearer motor.