Nonlinear self-adaptive active noise reduction system and noise reduction method thereof

An active noise reduction and self-adaptive technology, used in active noise control, sounding equipment, instruments, etc.

Pending Publication Date: 2020-12-08
南京时保联信息科技有限公司
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Problems solved by technology

[0006] The purpose of the present invention is to overcome the problem that the nonlinear active noise reduction system in the prior art can take into account both real-time and fitting capabilities for nonlinear characteristics

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  • Nonlinear self-adaptive active noise reduction system and noise reduction method thereof
  • Nonlinear self-adaptive active noise reduction system and noise reduction method thereof
  • Nonlinear self-adaptive active noise reduction system and noise reduction method thereof

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Embodiment Construction

[0057] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0058] Such as Figure 1-3 As shown, a nonlinear adaptive active noise reduction system is characterized in that it includes a sound signal unit 1, an electrical signal unit 2, an anti-noise source 3 and a target noise reduction area unit 4

[0059] The sound signal unit 1 is used for collecting and transmitting the noise signal sent by the noise...

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Abstract

The invention discloses a nonlinear self-adaptive active noise reduction system and a noise reduction method thereof. The nonlinear self-adaptive active noise reduction system is characterized in thatthe algorithm structure comprises a self-adaptive filter for filtering a sound signal, a feedback elimination filter for eliminating sound feedback, a secondary path estimation filter for calculatingan error sound signal, a primary path estimation filter, an off-line path identification algorithm used for off-line estimation of a required filter, and an iterative algorithm used for updating theself-adaptive filter in real time. According to the method, an offline path identification method based on a wavelet function, nonlinear adaptive filtering based on a radial basis function and a meanclustering center selection algorithm are adopted, the virtual acoustic sensor technology is combined, the problem that the effect is not ideal when a traditional FxLMS algorithm faces nonlinear noiseis solved, and therefore pollution of the nonlinear noise is effectively reduced.

Description

technical field [0001] The invention relates to the technical field of noise processing, in particular to a nonlinear adaptive active noise reduction system and a noise reduction method thereof. Background technique [0002] With the rapid development of modern industry and the continuous improvement of people's requirements for the quality of life, the problem of environmental pollution has attracted more and more attention. Among them, noise pollution, water pollution, and air pollution are regarded as the three major pollutions worldwide. Noise pollution, like other pollution, exists widely in all aspects of our lives. Noise can be divided into high-intensity and low-intensity. Low-intensity noise is generally not harmful to people's physical and mental health, but high-intensity noise can easily affect people's physical and mental health and make people depressed. , physical and mental fatigue, memory loss, and even cause disease after prolonged exposure. There are fo...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10K11/178
CPCG10K2210/3028G10K2210/30391G10K11/17854
Inventor 梁瑞宇沈雨论王青云丁帆
Owner 南京时保联信息科技有限公司
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