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Vibro-acoustic analysis and active control of low-frequency noise in high-speed elevator cabins based on psychoacoustic evaluation

作者
Rui Tian,Chufeng Zhang,Xingbao Wu
出处
期刊:Journal of Low Frequency Noise Vibration and Active Control [SAGE Publishing]
被引量:1
标识
DOI:10.1177/14613484261465705
摘要

Low-frequency noise in high-speed elevator cabins significantly impairs ride comfort. Traditional A-weighted sound pressure level (dBA) metrics inadequately capture subjective perception due to low-frequency insensitivity. This study proposes an integrated framework combining objective acoustic measurements, psychoacoustic evaluation, and active noise control (ANC) to grade sound quality satisfaction. A vibro-acoustic cabin model was developed using Computational Fluid Dynamics (CFD) and Finite Element Methods (FEM): transient aerodynamic excitation was obtained via Large Eddy Simulation (LES) of the hoistway flow field at a constant ascent speed of 10 m/s, and the resulting pulsating pressure distribution on the cabin exterior surface was applied as the primary acoustic excitation source. The model was validated against experimental measurements with an average deviation within 3 dB across key low-frequency bands (50–400 Hz). A Sound Quality Index (SQI) model was adapted from appliance standards to elevator noise, incorporating loudness, sharpness, and roughness. Psychoacoustic experiments with 110 participants established a mapping between SQI and subjective satisfaction, enabling the derivation of standardized grading thresholds. A FxLMS-based ANC system was simulated under the steady-state cruising condition, demonstrating significant improvement in both objective parameters and subjective ratings. FxLMS was selected as the baseline algorithm for its low computational complexity and stable convergence in the low-frequency range. To validate the algorithm-agnostic nature of the proposed SQI evaluation framework, a supplementary comparative simulation was conducted between FxLMS and the perceptually-motivated Active Noise Equalizer (ANE), with both algorithms achieving meaningful SQI improvements (+6.2 and +5.2 points, respectively) under identical conditions. The framework provides a practical tool for elevator noise evaluation and ANC optimization, with potential implications for the acoustic design and standardization of high-end elevator systems.

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