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Doppler effect reduction based on microphone arrays for wayside acoustic defective bearing diagnosis

机译:基于麦克风阵列的多普勒效应降低,用于路边声学缺陷轴承诊断

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The wayside Acoustic Defective Bearing Detector (ADBD) system plays an important role to maintain the safety of the railway transport. Due to the system acquired acoustic signal from a passing train by stationary microphones, it should be noted that the acquired signal is severely distorted by the Doppler Effect, which is an obstacle for defective bearings detection. This paper proposes a hardly needing prior knowledge method, called angle interpolation resampling (AIR) based on a microphone array, to remove the Doppler distortion embedded in the acoustic signal, and verifies it by means of simulation case and experiment case. The results indicate that the proposed AIR method has the superior performance in removing the Doppler distortion and has obvious advantages for ADBD system.
机译:路边声学缺陷轴承检测器(ADBD)系统在维护铁路运输的安全性方面起着重要作用。由于系统通过固定麦克风从经过的火车上获取了声音信号,因此应注意,所获取的信号会由于多普勒效应而严重失真,这是轴承故障检测的障碍。本文提出了一种几乎不需要的先验知识方法,即基于麦克风阵列的角度插值重采样(AIR),以消除嵌入在声信号中的多普勒失真,并通过仿真案例和实验案例对其进行验证。结果表明,所提出的AIR方法在消除多普勒失真方面具有优越的性能,对ADBD系统具有明显的优势。

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