高速线材精轧机故障智能监测与诊断

Fault Monitor and Diagnosis Approach with Neural Networks for High-Speed Rod-Rolling Mill

在对高速线材精轧机常见故障分析研究的基础上,通过对设备振动信号的采集、处理和提取特征参数的方法,结合人工神经网络原理,对其故障进行智能监测与诊断。并通过实验研究,对相关参数进行了优化,为该方法的实际应用奠定了理论与实验基础。同时,证明了该方法的可行性和实用性。

In this paper, a fault monitor approach for high-speed rod-rolling mill is realized by collecting and analyzing its fault signals and finding out its fault characteristic parameters with the theory of neural network, This approach has been applied to DLB-7 centrifuge and therefore the technology foundation is laid for further practical application.