模糊规则集在发动机故障诊断中的应用

Fuzzy Rule Sets Approach to Engine Fault Diagnosis

基于模糊规则集度量，提出了一种故障诊断系统。提取模糊规则分两步实现：（1）由训练样本自适应形成超球子空间，可望解决高维空间的识别问题：（2）计算每个子空间上模糊规则的信任度。对模糊规则的概念进行了拓展，以便解决模糊规则之间的矛盾。仿真研究表明：模糊规则集度量可以用于液体火箭发动机的故障诊断。

Based on the fuzzy measuring of fuzzy rule sets, a scheme system used for fault diagnosis is proposed in this paper. The extraction of fuzzy rules invo1ves two steps:(1) the whole space of the trained data is adaptively divided into subspaces in the form of hypersphere. It is probable to solve the problems of recognition in the high dimension space.(2) A fuzzy rule in each subspace is generated and confidence of each fuzzy rule calculated.We extend the conception of the traditional fuzzy rule for the purpose of resolving the contadictions among the generated fuzzy rules. The simulation research has shown that the fuzzy measuring of the fuzzy rule sets can be used for the fault diagnosis of the liquid rocket engine.