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Nowadays, power quality detecting devices have some problems in the applications. The low cost and the multi-function have been the main contradiction. For these, this paper designs a dual-core power quality detecting system based on the latest TI's OMAP-L138 chip, which has both ARM and DSP core. With the high-speed ADS8556 chip, the system achieves real-time data acquisition, processing and analysis...
Transformer fault diagnosis based on relevance vector machine (RVM) is proposed. The advantages of the RVM over the support vector machine (SVM) are probabilistic predictions, automatic estimations of parameters, and the possibility of choosing arbitrary kernel functions. Most importantly, RVM is capable of comparable classification accuracy to SVM, but with fewer relevance vectors (RVs) and higher...
Grinding production rate (GPR) is a vital index of grinding process. Getting accurate and timely information of GPR is the premise of enhancing grinding efficiency and conducting optimization control. However, for complexity of grinding process, there is no effective method to on-Line predict GPR. On the basis of soft sensor principle, a new sCheme that applying improved mixed-kernel support vector...
Research on various eco-environmental sounds is very important for people to understand a particular area. However, eco-environmental sounds have many specific properties such as the diversity, high background noise and non-stationary structure which make many traditional audio features hard to characterize them accurately. In this paper, a novel feature extraction technique based on Matching Pursuit...
Support Vector Machine (SVM) is based on statistical learning theory which developed from the common machine learning. It is an effective tool to deal with limited samples. This paper proposes a model of the dissolved gas analysis (DGA) of transformer based on Multi-class SVM. Firstly, with the combination of SVM multi-class classification methods one-versus-rest (1-v-r) and one-versus-one (1-v-1),...
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