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Displacement Identification by Computer Vision for ConditionMonitoring of Rail Vehicle Bearings
Southwest Jiaotong University.
Southwest Jiaotong University.
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics, Rail Vehicles. KTH, School of Engineering Sciences (SCI), Centres, The KTH Railway Group.ORCID iD: 0000-0001-7393-569X
Southwest Jiaotong University.
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2021 (English)In: Sensors, E-ISSN 1424-8220, Vol. 21, no 6, article id 2100Article in journal (Refereed) Published
Abstract [en]

Bearings of rail vehicles bear various dynamic forces. Any fault of the bearing seriouslythreatens running safety. For fault diagnosis, vibration and temperature measured from the bogieand acoustic signals measured from trackside are often used. However, installing additional sensingdevices on the bogie increases manufacturing cost while trackside monitoring is susceptible toambient noise. For other application, structural displacement based on computer vision is widelyapplied for deflection measurement and damage identification of bridges. This article proposesto monitor the health condition of the rail vehicle bearings by detecting the displacement of boltson the end cap of the bearing box. This study is performed based on an experimental platform ofbearing systems. The displacement is monitored by computer vision, which can image real-timedisplacement of the bolts. The health condition of bearings is reflected by the amplitude of thedetected displacement by phase correlation method which is separately studied by simulation. Toimprove the calculation rate, the computer vision only locally focuses on three bolts rather thanthe whole image. The displacement amplitudes of the bearing system in the vertical direction arederived by comparing the correlations of the image’s gray-level co-occurrence matrix (GLCM). Forverification, the measured displacement is checked against the measurement from laser displacementsensors, which shows that the displacement accuracy is 0.05 mm while improving calculation rate by68%. This study also found that the displacement of the bearing system increases with the increase inrotational speed while decreasing with static load

Place, publisher, year, edition, pages
MDPI, 2021. Vol. 21, no 6, article id 2100
National Category
Vehicle Engineering
Research subject
Engineering Mechanics
Identifiers
URN: urn:nbn:se:kth:diva-291672DOI: 10.3390/s21062100ISI: 000652733700001PubMedID: 33802714Scopus ID: 2-s2.0-85102579553OAI: oai:DiVA.org:kth-291672DiVA, id: diva2:1538071
Note

QC 20210710

Available from: 2021-03-17 Created: 2021-03-17 Last updated: 2022-06-25Bibliographically approved

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Liu, Zhendong

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