Abstract
Due to the complexity of the coupling between the active noise control (ANC) controller and secondary path estimator, performance analysis of the system becomes particularly difficult. At present, the performance analysis of the system is often based on the fact that the secondary path tends to be stable, and the secondary path fitting error is minimal. However, in the early stage of system operation, or when the secondary path changes suddenly, the secondary path fitting error is significant, which easily causes divergence of the system control. It is still unable to guarantee the step-size bounds of convergence stability. Therefore, factor decomposition was used to analyze the mean weight behavior in this study. This strategy emphasizes the influence of secondary path modeling (SPM) error. The mean square behavior was evaluated using the energy conservation relationship. According to the established theoretical model, the convergence condition of the system was derived and the upper bound of step size suitable for all stages of system operation was obtained. The simulation and experimental results show that the ANC system is quite stable and robust under extreme conditions and has an obvious noise reduction effect in a specific range of open space, which can reach about 20 dB noise reduction.
Highlights
Noise control methods mainly include passive and active control strategies [1,2,3].Passive noise control improves ambient acoustic performance by absorbing materials and changing the shape of the structure in conjunction with the environment [4]
The simulation and experimental results show that the system is quite stable under extreme conditions and has a noticeable noise reduction effect in a specific range of open space, which provides a basis for the active noise control (ANC) system design
Offline secondary path modeling (SPM) was performed before running the ANC filter
Summary
Secondary Path Modeling Based on Factor Decomposition and Application in Open Space. Featured Application: According to the established theoretical model, this study deduces the convergence conditions of the system and obtains the step-size bound suitable for all stages of system operation. The simulation and experimental results show that the system has excellent stability and robustness under extreme conditions; it has a pronounced noise reduction effect for different noise signals and establishes a quiet space. These results have practical guiding significance for other follow-up work, such as variable step size and auxiliary noise power scheduling strategy, as well as the creation of quiet space. Based on Factor Decomposition and Application in Open Space.
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