基于概率模型算法的设备运行状态分析

从设备状态动态变化的本质出发，采用概率神经网络方法构建设备状态概率模型，描述设备从正常到故障的全过程．通过对神经网络结构的分析和主要模型参数的计算，以设备运行历史数据作为网络样本点，在模型数据预处理的基础上建立了设备的概率模型，该模型能较好地反映机械设备的运行状态，通过现场数据的分析，证明了该模型的合理性和正确性．

Analysis of Equipment Running Condition Based on the Probabilistic Model Arithmetic

Based on the essence of dynamic evolution of equipment condition,according to probabilistic neural networks(PNN),a probability model of equipment condition is adopted to describe the whole process of equipment evolution from normal to fault in the paper.By analyzing Neural Network construction,calculating the main model parameter and using the machine history data as the network sample,we establish the probability model of machine with the pretreatment model data as a basis.The machine equipment condition is well reflected by the probability model.The reasonability and correctness of the model are proved by analyzing the machine history data.