一种应用于故障诊断中的高效推理算法

针对经典联合树推理算法的信息传播共享和推理时间等问题, 提出一种高效联合树推理算法. 该算法基于获得的证据信息和查询节点对原始的网络结构化简, 然后在化简后的网络结构上进行联合树推理. 在信息传递过程中, 该算法可以实现不同证据下的信息共享. 经仿真验证, 高效联合树算法能够在保证准确率的同时, 以更短的时间作出诊断推理. 基于现场收集的数据, 建立水泥回转窑故障诊断系统模型并应用改进的算法实现了精准且快的故障诊断.

An effective inference algorithm for fault diagnosis

Aiming at information propagation shared, inference time and other issues in classic junction tree inference algorithm, an effective junction tree algorithm is presented. Based on evidence information obtained and query nodes, the original structure of a Bayesian network is simplified, and then the junction tree algorithm is used for inference on the simplified structure. During the information propagation, the effective junction tree algorithm can achieve information shared between different evidence variables. The result of simulations shows that the improved algorithm can guarantee high precision at the same time, and do the diagnosis and reasoning in a short period of time. Based on data collected in the field, a fault diagnosis model is built for the cement rotary kiln, and the effective junction tree algorithm is applied to the fault diagnosis of cement rotary, achieving a faster and accurate fault diagnosis.