Method for train bearing track-side acoustic diagnosis under variable speed condition

Abstract

The invention discloses a method for train bearing track-side acoustic diagnosis under a variable speed condition. The method includes the following steps that: acoustics signals emitted by a train bearing when a train passes at different speeds are acquired through microphones mounted on two sides of a track, and the acoustics signals are pre-processed; 2) 7 features such as a peak factor and variance are extracted, and the extracted 7 features, together with a vehicle speed Vs, are adopted to constitute a historical sample set with 8 feature quantities; 3) the historical sample set is adopted to train a 4-layer BP neural network; and 4) track-side acoustic signals emitted by the train bearing and a train speed at present are acquired, and the BP neural network obtained in the step 3) isadopted to perform fault diagnosis. With the method of the invention adopted, the influence of Doppler acoustic signal distortion on fault features under a variable speed condition of the train can beeliminated, and the accurate identification of the faults of the train bearing can be accurately identified under the variable speed condition; only the train speed value is required to be measured,and the required number of sensors is smaller; accurate correction can be realized without correction required, so that the amount of calculation is less; and historical data information is fully utilized, so that the reliability of diagnosis results is effectively improved.

Description

technical field [0001] The invention belongs to the field of acoustic fault diagnosis of a rail edge of a high-speed train bearing, and in particular relates to an acoustic diagnosis method of a rail edge of a train bearing under variable speed conditions. Background technique [0002] As one of the important modes of transportation, railway is playing an increasingly important role in cargo transportation and short- and medium-distance passenger transportation due to its low operating cost and large carrying capacity. As a key component of the train, the health of the train bearing has great significance and influence on the overall operation of the train and the safety of passengers. Therefore, on-line fault detection of bearings has very important practical significance. The trackside acoustic diagnosis technology uses microphones installed on both sides of the rails to collect the sound signals from the bearings when the train passes by, and uses signal processing techn...

AI Technical Summary

Problems solved by technology

The existing method is to use the Doppler distortion correction method to eliminate the Doppler distortion, but the correction process needs to obtain multiple parameters in advance, such as the vehicle speed, the vertical distance between the microphone and the sound source moving line of the bearing, and the lateral distance, and interpolation processing is required. Large amount of calculation

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