Rui Zhang, Jiyan Yi, Hanlin Guan, Yao Xiao, Wangfang Tao, Yan Ren
{"title":"Fault diagnosis of pump truck waterproof valves using multi-sensor high-dimensional time-domain feature expansion map","authors":"Rui Zhang, Jiyan Yi, Hanlin Guan, Yao Xiao, Wangfang Tao, Yan Ren","doi":"10.1177/16878132241245894","DOIUrl":null,"url":null,"abstract":"The master cylinder of most pump trucks is equipped with a waterproof valve, whose purpose is to prevent water from the tank from entering the master cylinder. Once waterproof valve fails to failure, the waterproof valve at the main cylinder can only be supported by a BS seal (this seal is very easy to fail), which results in oil emulsification and pollution of the hydraulic system. Therefore, a fault diagnosis method combining a multi-sensor high-dimensional time-domain feature expansion map (MHTFEM) with an attentional convolutional capsule network (ACCN) is proposed. In this method, the raw vibration signals acquired by all sensors are first preprocessed to generate a high-dimensional feature matrix. Then the different high-dimensional feature matrices are stitched, expanded and generated into grayscale images, followed by randomly dividing the training set and the testing set. Finally, the training set is brought into the ACCN for training and the testing set is brought into the network model for fault type identification. A test bench was built to confirm the effectiveness of the method for waterproof valve fault diagnosis. This provides a method to achieve intelligent fault diagnosis of construction machinery to ensure its reliability.","PeriodicalId":7357,"journal":{"name":"Advances in Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Mechanical Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1177/16878132241245894","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The master cylinder of most pump trucks is equipped with a waterproof valve, whose purpose is to prevent water from the tank from entering the master cylinder. Once waterproof valve fails to failure, the waterproof valve at the main cylinder can only be supported by a BS seal (this seal is very easy to fail), which results in oil emulsification and pollution of the hydraulic system. Therefore, a fault diagnosis method combining a multi-sensor high-dimensional time-domain feature expansion map (MHTFEM) with an attentional convolutional capsule network (ACCN) is proposed. In this method, the raw vibration signals acquired by all sensors are first preprocessed to generate a high-dimensional feature matrix. Then the different high-dimensional feature matrices are stitched, expanded and generated into grayscale images, followed by randomly dividing the training set and the testing set. Finally, the training set is brought into the ACCN for training and the testing set is brought into the network model for fault type identification. A test bench was built to confirm the effectiveness of the method for waterproof valve fault diagnosis. This provides a method to achieve intelligent fault diagnosis of construction machinery to ensure its reliability.
期刊介绍:
Advances in Mechanical Engineering (AIME) is a JCR Ranked, peer-reviewed, open access journal which publishes a wide range of original research and review articles. The journal Editorial Board welcomes manuscripts in both fundamental and applied research areas, and encourages submissions which contribute novel and innovative insights to the field of mechanical engineering