摘要
论文在分析现有故障诊断方法特点和局限性的基础上,对基于规则推理和案例推理的集成诊断系统的设计方案、集成机制和关键技术进行了研究。
规则获取是专家系统的“瓶颈”问题,论文采用基于粗集的数据挖掘方法进行规则获取,对属性约简的基本算法做出了改进,利用属性约减算法和启发式值约减算法,在一定程度上简化了计算,提高了约简效率。粗糙集从现有的故障诊断的数据出发,能有效地处理不完备、不一致数据,实现高效快速地提取故障诊断规则的目的。
在运用知识工程技术进行案例的表示、组织以及案例库的构建中,论文根据压缩机故障诊断领域的特点以及故障诊断专家系统的应用需求,以基于特征的故障案例表示为基础,依据故障的特征属性和内容将压缩机故障案例按照故障特征分类。在案例检索中,根据故障案例特征的层次结构,将整个案例库组织成多级分层索引结构。这种按故障特征分类,分层索引的策略思想不仅降低了案例表示、组织以及案例库的构建难度,而且极大地提高了案例检索的效率。
在上述研究工作基础上,研究建立了一个集规则诊断(RBR)和案例推理(CBR)于一体的集成智能诊断专家系统。该集成系统既可以充分利用相关的领域知识又可以利用以往的诊断经验,相互补充,从而提高诊断系统的故障分辨能力和准确性。
The article analyzes the characteristic and limitation of the applied fault diagnosis method. Based on that, a new integrated diagnosis method based on RBR (rule-based reasoning) and CBR (case-based reasoning) is presented in this paper. The design plan, integrated mechanism and key technology of the integrated diagnosis method have been developed.
A Rough sets data mining method for rule acquisition is selected to over come the shortages of some knowledge attaining methods existed before. The basic algorithm is improved by using attribute reduction and heuristic value reduction, which can simplify the calculation and enhance the efficiency of seeking the reduction in some extent. Rough sets theory can gathers the existing diagnoses data and obtains the diagnosis rule efficiently and quickly through handle incomplete and inconsistent data availably.
According to the demand of fault diagnosis expert system and the characteristic of compressor fault diagnosis, the compressor fault case is classified by characteristic and detail on the foundation of characteristic-based case expression. The multi-layered structure of the case database of the system is formed in accordance with the structure of the key characteristic which is abstracted from fault cases. The strategy of layering index and characteristic classification have reduced the complexity of case expression, the management and construction of case database, it also have enhanced the index speed and efficiency dramatically.
Based on the research above, this paper introduces an integrated fault diagnosis expert system integrated with rule-based reasoning and case-based reasoning. The integrated system can not only make use of the field knowledge but can take advantage of diagnose experience in the past, There by,it is mutually complementary to improve the accuracy and identification capability of the diagnosis System.
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