标题:Differential Equation-Based Prediction Model for Early Change Detection in Transient Running Status
作者:Wen, Xin; Chen, Guangyuan; Lu, Guoliang; Liu, Zhiliang; Yan, Peng
作者机构:[Wen, Xin; Chen, Guangyuan; Lu, Guoliang; Yan, Peng] Shandong Univ, Key Lab High Efficiency & Clean Mech Manufacture, Natl Demonstrat Ctr Expt Mech En 更多
通讯作者:Lu, GL;Lu, Guoliang
通讯作者地址:[Lu, GL]Shandong Univ, Key Lab High Efficiency & Clean Mech Manufacture, Natl Demonstrat Ctr Expt Mech Engn Educ, MOE,Sch Mech Engn, Jinan 250061, Sha 更多
来源:SENSORS
出版年:2019
卷:19
期:2
DOI:10.3390/s19020412
关键词:prediction model; early change detection; differential equation; machine; running status
摘要:Early detection of changes in transient running status from sensor signals attracts increasing attention in modern industries. To achieve this end, this paper presents a new differential equation-based prediction model that can realize one-step-ahead prediction of machine status. Together with this model, an analysis of continuous monitoring of condition signal by means of a null hypothesis testing is presented to inspect/diagnose whether an abnormal status change occurs or not during successive machine operations. The detection operation is executed periodically and continuously, such that the machine running status can be monitored with an online and real-time manner. The effectiveness of the proposed method is demonstrated using three representative real-engineering applications: external loading status monitoring, bearing health status monitoring and speed condition monitoring. The method is also compared with those benchmark methods reported in the literature. From the results, the proposed method demonstrates significant improvements over others, which suggests its superiority and great potentials in real applications.
收录类别:EI;SCOPUS;SCIE
资源类型:期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060373489&doi=10.3390%2fs19020412&partnerID=40&md5=ed635ddb1450a84d0c84159f7d6adb89
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