大型连轧机传动齿轮在线故障诊断方法研究

STUDY OF ONLINE FAULT DIAGNOSIS GEARBOX ON CONTINUOUS STRIP MILL

在大型连轧机组中 ,主传动系统的减速机、齿轮座承受着巨大的负载 ,很容易出现各种故障。采用神经网络自适应滤波方法和小波分解方法在线分析传动齿轮的振动信号 ,有效地分解出信号中由故障所引起的成分 ,准确地诊断出连轧机传动齿轮的各种故障原因 。

The gearbox of main driving system on large scale continuous strip mill usually bear huge load Adaptive neural network filter and wavelet decomposing methods used to online analyze the vibration signal of gear transformation system are introduced in this paper These methods can decompose the signal and separate the component induced by fault from gear vibration signal effectively, and then recognize the gear faults accurately and effectively These efforts will provide new and effective online fault diagnosis tools for gear transformation system of continuous strip mill