基于频段振动烈度和ARIMA的煤矿减速机状态预测

振动信号反映设备运行的状态,为了能够对设备的运行状态进行有效监控和预报,采用了频段振动烈度分析和ARIMA建模的方法。通过监控各个频段的振动烈度值,能够全面了解设备的状态。根据各个频段的变化趋势,选择处于上升阶段的频段进行ARIMA建模与状态预测。并讨论了如何处理现场数据的非平稳性以及模型类型判别方法,构建合适的时间序列模型。

Study on Coal Gear Box Status Predictive Method Based on Band Vibration Severity and ARIMA

Vibration signals reflect the status of equipment.Vibration severity analysis and ARIMA modeling approach is used to effectively monitor and forecast the status of the equipment.The status of the equipment could be understood by monitoring the value of each band.According to the trends of each band,the rising ones are chosen to do ARIMA modeling and forecast the status.It's discussed that how to handle n on-stationary nature of field data and the discrimination of model type in order to construct a suitable...