Cross-updated active noise control system based on novel algorithm for online identification of secondary channel

Abstract

The invention protects a cross-updated active noise control system based on a novel algorithm for online identification of a secondary channel. The noise control system comprises 6 modules of noise signal filtering, momentum FxLMS algorithm, white noise generator, secondary channel modeling, main channel path and third adaptive filter update module. The object of the noise control system is to solve the problem that an active noise cancellation (ANC) system has a slow convergence speed and a small noise reduction amount in indoor noise-cancellation applications. The innovation lies in the factthat the unevenness of the power spectral density of a noise signal greatly affects the convergence speed of a control filter and a modeling filter in the indoor noise-cancellation applications. Themomentum FxLMS algorithm is proposed to update the weight of the control filter, and a variable step size LMS algorithm is used to update the weight of the modeling filter. The third adaptive filter using the Newton LMS algorithm is used to eliminate an error signal and the signal related to the reference input signal, and improves the modeling accuracy of the modeling filter and the convergence speed of the entire ANC system.

Description

technical field [0001] The invention belongs to the technical field of noise elimination, and in particular relates to a research on a cross-updating active noise control system based on a new algorithm for online identification of secondary channels. Background technique [0002] The traditional noise control mainly focuses on the acoustic control of noise. The main technical means include sound absorption treatment, sound insulation treatment, use of muffler, isolation and reduction of vibration, etc. The mechanism of these noise control methods is to make noise sound waves interact with acoustic materials or structures to consume sound energy, thereby achieving the purpose of noise reduction. They belong to passive control methods and are called "passive" noise control. Generally speaking, the method of passive control is more effective for reducing medium and high frequency noise, but has little effect on reducing low frequency noise. However, active noise control (ANC)...

AI Technical Summary

Problems solved by technology

The presence of a secondary path (the path from the output of the noise control filter to the error sensor measuring the residual noise) can cause instability in the standard least mean square (LMS) algorithm, and the secondary path path is time-varying or non-linear , which in turn will lead to a decrease or divergence in the noise reduction performance of the ANC system

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