Noise source identification of high-speed motion mechanism of textile equipment based on equivalent source method

Yang, Xu; Angang, Li; Sheng, Xiaowei; Zhang, Ziyu

doi:10.1080/00405000.2019.1702488

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…3 In particular, the noise from motor and transmission abnormal have a medium and high frequency spectrum, close to the sensitive frequency band of human ear to noise, which has a remarkable impact on the whole vehicle acoustic comfort. 4,5 There are passive and active ways to control interior noise, among which passive control measures such as sound absorption and sound insulation can reduce decibel to meet the existing noise limit requirement (GB/T 25982-2010), but it is difficult to effectively regulate vehicle sound quality. 4,6,7 This is because sound quality improvement not only need to reduce the sound pressure level in a certain frequency domain, but also fully consider other psycho-acoustic objective characteristics, such as loudness and roughness.…”

Section: Introductionmentioning

confidence: 99%

Active noise control modeling for an electric bus driving position and its effect on sound quality

Zhang,

Peng,

Chen

et al. 2024

Noise & Vibration Worldwide

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Current electric bus has become an important public transport for people in China, and its interior sound quality directly affects the driver’s physical and mental health for a long working time and the comprehensive performance of the vehicle. Therefore, it is an inevitable and urgent trend to research electric bus interior sound quality. Aiming at the problem of subjective uncomfortable auditory sensation caused by different speeds, the noise signals near the driver’s ears were collected under two constant speed conditions. On the basis of principle analysis of feed-forward adaptive control system, the primary and secondary path transfer functions were presented using Simulink module in MATLAB to construct three active noise control models for an electric bus based on least mean square (LMS), normalized LMS (NLMS) and filtered-x LMS (FxLMS). Numerical simulation results indicate that the established control models are convergent, and four acoustic parameters are effectively reduced after controls to achieve the effect of improving the sound quality.

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