佛山科学技术学院学报（自然科学版）2018，Vol.36Issue(3)：50-53,4.
基于聚类分析的空调振动信号的分类方法
Classification of air conditioning vibration signals based on cluster analysis
摘要
Abstract
In order to solve the problems existing in the detection of home appliance vibration, this paper takes the air conditioning machine as an example to extract the kurtosis index, mean square value index and correlation coefficient index of the vibration signal of the air conditioner under certain conditions as the eigenvalue of the cluster analysis. The K-means clustering analysis is used to cluster the signals and calculate the contour values of the clustering results. According to the calculated contour values, it can be seen that when the sample is divided into 10 classes, each observed contour value is greater than 0.18, indicating that it is appropriate to classify 40 samples into 10 categories.关键词
聚类分析/振动/K-均值聚类法Key words
cluster analysis/vibration/K-means clustering method分类
信息技术与安全科学引用本文复制引用
郑文炜,王宇华,刘芝庭..基于聚类分析的空调振动信号的分类方法[J].佛山科学技术学院学报（自然科学版）,2018,36(3):50-53,4.基金项目
广东省公益研究与能力建设专项资金资助项目(2015A010103017,2015B010101014) （2015A010103017,2015B010101014）
佛山市科技创新资助项目(00205371200120104) （00205371200120104）
佛山科学技术学院研究生自由探索基金资助项目 （）
