文章基本信息

标题：Multi-layered Nonnegative Matrix Factorization Based on PCA for the Foreign Object Detection in Electricity Meters
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作者：Jin Zhang ; Yang Ou Xi ; Jian Wu 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2018
卷号：246
DOI：10.1051/matecconf/201824603008
语种：English
出版社：EDP Sciences
摘要：Foreign object detection is an important part of quality 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%.