灰色马尔柯夫链方法在设备故障预测中的应用初探

Application of Grey Markov Forecasting Model to Machine ′s Fault Forecast

将灰色马尔柯夫预测模型应用于设备运行状态的预测，实践证明，这种预测方法兼有灰色ＧＭ（１，１）预测和马尔柯夫概率矩阵预测的优点，尤其适用于随机波动性较大的数据列的预测。这一应用拓广了灰色预测的应用范围。对轴承振动的预测结果表明，该预测模型的预测精度是令人满意的。

WT5”BZ〗This paper presents a Grey Markov forecasting model which is initially and successfully applied to the prediction of operational conditions of machines.The results show that the method has the merits of both grey GM(1,1) forecast and Markov probability matrix forecast, and would expand the applicative scope of grey forecast. In particular,the Grey Markov forecasting model is suited for data sequences with heavy random fluctuation.The forecasted results of bearing′s vibration show that the forecasting precision of the model is satisfactory.