摘要
传统的灰色关联度故障诊断方法,由于存在故障诊断的模式向量中参数量纲不同、数量级差异等缺点,可能导致诊断结果存在较大的误差。为此,将模糊理论的隶属函数引入到灰色关联分析法中,提出了模糊灰关联分析法,采用模糊相对隶属度对诊断参数进行了规格化处理;同时,在此基础上求得模糊灰关联度向量;最后,根据择大原则达到诊断识别的目的。通过柴油机故障诊断的实例分析,证明该方法具有简单可靠、适应性强且诊断精度高等一系列优点。
For the disadvantages of difference of parameter unit and magnitude in the diagnosis vectors, the traditional grey correlation method to fault diagnosis of diesel engine may cause the result a rather serious error. A new fuzzy grey correlation analysis method is proposed in this paper. The sequence of the object to be identified is firstly normalized using fuzzy relative subordination degree. Then a vector of fuzzy grey correlation degree is derived. At last the identification is made by the principle of choosing the maximum vector. Application of this method to diesel engine proves that it is reliable, adaptable, precise and easy to operate.
出处
《农机化研究》
北大核心
2007年第5期210-212,214,共4页
Journal of Agricultural Mechanization Research
基金
江苏省科技攻关项目(BE2006101)
关键词
能源与动力工程
故障诊断
理论研究
柴油机
灰色系统
模糊数学
关联度
energy and power engineering
fault diagnosis
theoretical research
internal construction engine
grey system
fuzzy mathematics
correlation
