{"title":"A fault diagnosis method for bogie axle box bearing based on sound-vibration multiple signal fusion","authors":"Zejun Zheng, Dongli Song, Weihua Zhang, Chen Jia","doi":"10.1016/j.apacoust.2024.110336","DOIUrl":null,"url":null,"abstract":"<div><div>The fault diagnosis method of multi-signal fusion is one of the current research trends, which can improve the reliability of diagnosis results. In this paper, the single channel signal is decomposed by multi-channel bandpass filter bank, and a new indicator value is constructed to select the optimal component. A new fusion demodulation method is constructed by using the two signal demodulation methods to extract the characteristic frequency of the single channel signal. Subsequently, the characteristic spectrum of the multi-channel signals is fused to extract the final characteristic frequency. The diagnosis method is verified by the simulation signal and the sound signal and vibration signal collected by the experiment. The results show that the proposed method can reduce the content of noise components in the characteristic spectrum, highlight the fault characteristic frequency, and reflect the superiority of the proposed method compared with other methods. This paper provides guidance for feature extraction of data fusion methods in the future, and provides an effective method for fault diagnosis and condition monitoring of bearings.</div></div>","PeriodicalId":55506,"journal":{"name":"Applied Acoustics","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Acoustics","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0003682X24004870","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ACOUSTICS","Score":null,"Total":0}
引用次数: 0
Abstract
The fault diagnosis method of multi-signal fusion is one of the current research trends, which can improve the reliability of diagnosis results. In this paper, the single channel signal is decomposed by multi-channel bandpass filter bank, and a new indicator value is constructed to select the optimal component. A new fusion demodulation method is constructed by using the two signal demodulation methods to extract the characteristic frequency of the single channel signal. Subsequently, the characteristic spectrum of the multi-channel signals is fused to extract the final characteristic frequency. The diagnosis method is verified by the simulation signal and the sound signal and vibration signal collected by the experiment. The results show that the proposed method can reduce the content of noise components in the characteristic spectrum, highlight the fault characteristic frequency, and reflect the superiority of the proposed method compared with other methods. This paper provides guidance for feature extraction of data fusion methods in the future, and provides an effective method for fault diagnosis and condition monitoring of bearings.
期刊介绍:
Since its launch in 1968, Applied Acoustics has been publishing high quality research papers providing state-of-the-art coverage of research findings for engineers and scientists involved in applications of acoustics in the widest sense.
Applied Acoustics looks not only at recent developments in the understanding of acoustics but also at ways of exploiting that understanding. The Journal aims to encourage the exchange of practical experience through publication and in so doing creates a fund of technological information that can be used for solving related problems. The presentation of information in graphical or tabular form is especially encouraged. If a report of a mathematical development is a necessary part of a paper it is important to ensure that it is there only as an integral part of a practical solution to a problem and is supported by data. Applied Acoustics encourages the exchange of practical experience in the following ways: • Complete Papers • Short Technical Notes • Review Articles; and thereby provides a wealth of technological information that can be used to solve related problems.
Manuscripts that address all fields of applications of acoustics ranging from medicine and NDT to the environment and buildings are welcome.