Multi-layered Nonnegative Matrix Factorization Based on PCA for the Foreign Object Detection in Electricity Meters

摘要：

　　Foreign object detection is an important part ofquality control of electricity meters.An automatic detection device is developed based on acoustic identification.In order to suppress background noise interference,we design a novel sound separation algorithm to separate the mixed sound signals to obtain the target source signal produced by foreign objects.Firstly,the improved principal-component-analysis-based multi-layered nonnegative matrix factorization(PMNMF)is used to separate sound signals.Secondly,the SVM is used to classify and identify sound signals.A suppot vector machine(SVM)as the classifier is used to compare the PMNMF algorithm with the basic NMF algorithm.The results indicate that the sound data pre-processed with the improved NMF algorithm results in a significantly higher identification rate up to about 95%.

作者: Zhang Jin Ou Xi Yang Wu Jian Ou Xi Zhou You Ji Chang

作者单位: State Grid ChongQing Electric Power Science Research Institute,ChongQing,401120,China Sichuan Fude Robot Co,Ltd,Sichuan,621000,China

会议类型: 国际会议

会议名称: 2018 International Symposium on Water System Operations(ISWRSO 2018)(2018年水资源系统及调度国际研讨会)

会议地点: 北京

会议语种:英文

页码: 1-5

在线出版日期: 2018-10-12（万方平台首次上网日期，不代表论文的发表时间）