DAI Hai, CHEN Kean, LI Rong, et al. Judgment for adaptive active noise control convergence state[J]. Journal of Vibration Engineering. DOI: 10.16385/j.cnki.issn.1004-4523.202504003
Citation: DAI Hai, CHEN Kean, LI Rong, et al. Judgment for adaptive active noise control convergence state[J]. Journal of Vibration Engineering. DOI: 10.16385/j.cnki.issn.1004-4523.202504003

Judgment for adaptive active noise control convergence state

  • The minimum mean square error criterion is one of the best criteria currently used in adaptive active noise control algorithms. For this kind of adaptive filtering system, in actual engineering, its convergence status needs to be monitored in real time to determine external interference so that countermeasures can be taken to avoid instability in the adaptive process. This study proposes a method to determine whether the noise reduction system is divergent by judging the filter convergence status, which can accurately monitor the adaptive filter convergence status of the noise reduction system in real time. The theoretical judgment method is given, and the factors such as sound field noise size, control coefficient and sound field noise frequency that affect the convergence threshold value are simulated and analyzed, and verified in the aircraft model cabin. Simulation and test results show when the adaptive filter diverges, the system divergence can be determined in less than 0.5 s; the instability determination threshold is easy to set and has universal applicability, and can be used in different sound field environments; this method is simple and efficient in calculation, can accurately reflect the convergence status of the adaptive filter in real time, and provides a basis for judging the robustness of the active noise control system.
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