机械科学与技术2018，Vol.37Issue(3)：391-395,5.DOI:10.13433/j.cnki.1003-8728.2018.0310
内燃机振动时频图像的编码特征提取与诊断
Coding Feature Extraction and Diagnosis of I.C.Engine Vibration Time-frequency Images
摘要
Abstract
According to the problems of parameter selection and feature extraction for vibration diagnosis of traditional internal combustion (I.C) engine,a new fault diagnosis method is discussed.The method based on S-transformation and Module Two Dimensional Principal Components Analysis (M-2DPCA) is proposed to carry out fault diagnosis of I.C.engine valve mechanism.First of all,the method transfers cylinder surface vibration signals of I.C.engine into images through S-transform.Second extracting the optimized projection vectors from the general distribution G which is obtained by all sample sub-images,so that vibration spectrum images can be modularized using M-2DPCA.At last,these features matrix obtained from images project will served as the enters of nearest neighbor classifier,it is used to achieve fault types' division.The method is applied to the diagnosis example of the vibration signal of the valve mechanism eight operating modes,recognition rate up to 94.17％;the effectiveness of the proposed method is proved.关键词
S变换/M-2DPCA/最近邻分类器/故障诊断Key words
S-transform/M-2DPCA/nearest neighbor classifier/fault diagnosis分类
能源科技引用本文复制引用
张世雄,蔡艳平,石林锁,牟伟杰..内燃机振动时频图像的编码特征提取与诊断[J].机械科学与技术,2018,37(3):391-395,5.基金项目
国家自然科学基金项目(51405498)、陕西省自然科学基金项目(2013JQ8023)及中国博士后基金项目(2015M582642)资助 （51405498）
