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首页> 外文会议>Asia-Pacific Power and Energy Engineering Conference;APPEEC 2009 >Fuzzy Rule Set Based Engine Fault Diagnosis
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Fuzzy Rule Set Based Engine Fault Diagnosis

机译：基于模糊规则集的发动机故障诊断

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Based on a fuzzy match method of fuzzy rule sets which are a series of fuzzy neural networks, a system framework used for the engine fault diagnosis is proposed in this paper. This fault diagnosis system consists of five parts, including the extraction of fuzzy rules, fuzzy reference rule sets, a fuzzy rule set to be detected, the fuzzy match module of fuzzy rule sets and the diagnosis logic module. The extraction of fuzzy rules involves two steps: step 1 adaptively divides the whole space of the trained data into the subspaces in the form of hypersphere, which is expected efficiently to work out the recognition questions in the high dimension space; step 2 generates a fuzzy rule in each sample subspace and calculates the membership degree of each fuzzy rule. This paper specially makes extension of the conception of the fuzzy rule for resolving the contradictions among the generated fuzzy rules. The fuzzy rule is divided into the fuzzy reference rule set and the fuzzy rule set to be detected. Many fuzzy reference rule sets are obtained by the extraction module of fuzzy rules for the offline learning, and a fuzzy rule set to be detected is online formed while the monitoring process is going on. With the beliefs estimated from the fuzzy match process of fuzzy rule sets, which indicate the existence of working classes in the plant, the diagnosis logic module can export fault detection time, fault isolation time, fault type and fault degree. The simulation researches of the fault diagnosis in a 2000N space propulsion system demonstrate the superior qualities of the fault diagnosis method on the basis of the fuzzy match of the fuzzy rule sets.
机译：基于一系列模糊神经网络的模糊规则集的模糊匹配方法，提出了一种用于发动机故障诊断的系统框架。故障诊断系统由模糊规则的提取，模糊参考规则集，待检测的模糊规则集，模糊规则集的模糊匹配模块和诊断逻辑模块五个部分组成。模糊规则的提取涉及两个步骤：步骤1将训练数据的整个空间自适应地划分为超球面形式的子空间，这有望有效地解决高维空间中的识别问题；步骤2在每个样本子空间中生成一个模糊规则，并计算每个模糊规则的隶属度。本文专门对模糊规则的概念进行了扩展，以解决所生成的模糊规则之间的矛盾。模糊规则分为模糊参考规则集和要检测的模糊规则集。脱机学习的模糊规则提取模块获得了许多模糊参考规则集，并且在进行监视过程的同时，在线形成了要检测的模糊规则集。利用逻辑规则集的模糊匹配过程估计的信念（表明工厂中存在工作类别），诊断逻辑模块可以导出故障检测时间，故障隔离时间，故障类型和故障程度。在2000N空间推进系统的故障诊断仿真研究中，基于模糊规则集的模糊匹配，证明了故障诊断方法的优越性。

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