Affiliations: [a] School of Electrical Engineering, Tiangong University, Tianjin, China | [b] School of Electrical Engineering and Automation, Tianjin University of Technology, Tianjin, China | [c] State Key Laboratory of Power Grid Environmental Protection, Wuhan, China
Correspondence:
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Corresponding author: Lihua Zhu, School of Electrical Enineering, Tiangong University, Tianjin 300387, China. E-mail: zhulihua@tiangong.edu.cn
Abstract: Active noise reduction system is widely used in production and life because of its good noise reduction effect in low frequency band, easy installation, high practicability and good economy. This paper focused on the compilation of active noise reduction algorithms and the overall system debugging, and explored the factors that affected the active noise reduction. In order to realize the software part of the active noise reduction system, the LMS adaptive filtering algorithm was written and non-linearity function and auxiliary machine learning algorithm was used. Then the hardware system was built for the overall joint debugging of software and hardware. Combined with the practical application background of electrical equipment engineering, the influence of the angle, number of speakers and the distance from electrical equipment on the noise reduction effect were studied. The results showed the overall noise reduction in the experiment was about 6 dB, which proved that the active noise reduction system proposed in this paper is effective.
Keywords: Active noise reduction, adaptive filtering, LMS, influence of noise reduction
