摘要
针对传统灰关联分析方法存在的问题,引入动态分辨系数和因子权重系数,提出新型灰关联分析方法。与传统灰关联分析方法相比,该方法具有两个优点:一是降低对人为确定分辨系数和权重系数的依赖性;二是提高识别结果的可靠性和准确性。最后将该方法应用于数控机床主轴故障识别中,并与传统灰关联分析方法和神经网络识别结果进行对比分析。结果显示,新型灰关联分析方法识别结果更准确可靠。
Against the problem of traditional grey relation analysis mettaoct,a novel metnoa was proposed by introducing dynamic identification and factor weight coefficient. Compared with tradition- al method, this method has two advantages： reducing the dependence of man--made identification and weight eoefficient;strengthening the reliability and veracity. Application of this method to fault recognition of NC machine tool spindle shows a better effect on the reliability and veracity over tradi- tional method and neural network, this method can also be applied to many other fields.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2013年第23期3150-3153,3219,共5页
China Mechanical Engineering
基金
国家科技重大专项(2011ZX04016-017)
关键词
故障识别
灰关联分析
动态分辨系数
因子权重系数
数控机床
fault recognition
grey relation analysis
dynamic identification coefficient
factorweight coefficient
NC machine tool
