Nonintrusive power load feature recognition based on internet of things technology Online publication date: Wed, 21-Jun-2023
by Jing Liu; Di Zhao
International Journal of Autonomous and Adaptive Communications Systems (IJAACS), Vol. 16, No. 3, 2023
Abstract: In order to overcome the problems of low recognition efficiency, low information credibility and low recognition accuracy existing in the existing nonintrusive power load feature recognition methods, a nonintrusive power load feature recognition method based on internet of things technology is proposed. With the support of internet of things technology, the feature parameters of power consumption information are obtained by the Fourier transform method, and the feature parameters are fused according to the correct time sequence to realise the recognition of power consumption equipment. Based on the detection results, a nonintrusive power load feature recognition model is constructed by the C4.5 decision tree algorithm, and the nonintrusive power load feature recognition model is realised by using the nonintrusive power load feature recognition model. The experimental results show that the proposed method has high recognition efficiency, high information reliability and high recognition accuracy.
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