Fault Diagnosis of Axle Box Bearing with Acoustic Signal Based on Chirplet Transform and Support Vector Machine
نویسندگان
چکیده
Acoustic fault diagnosis technology equipment is non-contact, and the acoustic signal easy to access. However, it difficult extract feature information of with low signal-to-noise ratio (SNR). In this paper, a model (FDM) axle box bearing based on Chirplet transform (CT) support vector machine (SVM) established diagnose signal. The availability verified by comparing vibration acceleration results, correctness utilizing open database Western Reserve University. acoustic-vibration comprehensive experiment platform (AVEP) investigate accuracy. results suggest that, FDM, accuracy stability are not as good when number samples small under single condition; similar that enough multiple condition, which provides reference for application in engineering future.
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ژورنال
عنوان ژورنال: Shock and Vibration
سال: 2022
ISSN: ['1875-9203', '1070-9622']
DOI: https://doi.org/10.1155/2022/9868999