On-board real-time railroad bearing defect detection and monitoring

被引:34
|
作者
Sneed, WH [1 ]
Smith, RL [1 ]
机构
[1] Transportat Technol Ctr Inc, Pueblo, CO 81001 USA
来源
PROCEEDINGS OF THE 1998 ASME/IEEE JOINT RAILROAD CONFERENCE | 1998年
关键词
D O I
10.1109/RRCON.1998.668098
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
For several years, the Association of American Railroads (AAR) has been developing new techniques to detect defective roller bearings as part of their new generation wayside acoustic detector program. This paper reviews thermal and vibration data collected from on-board a test train used to simulate railroad revenue service conditions during the test program. The train tests were carried out by Transportation Technology Center now known as Transportation Technology Center, Inc. (TTCI), a subsidiary of the AAR, at the Transportation Technology Center (TTC), Pueblo, Colorado in November 1996. Of all the bearing defect types to be detected, one of the most challenging is that of a bearing with a loose inner raceway commonly referred to as a spun cone. Normal roller bearings have "press fit" inner raceways that keep them from rotating or sliding about the axle. However, the spun cone bearing has lost its tight press fit and can slowly rotate about the axle journal axis. The spun cone bearing defect is suspected to be the cause of many of today's confirmed hot bearing setouts.(1) This paper compares both thermal and vibration data from bearings with no internal defects to those with spun cones, broken rollers, and water etched surfaces.
引用
收藏
页码:149 / 153
页数:5
相关论文
共 50 条
  • [1] On-board and real-time expert control
    MorizetMahoudeaux, P
    IEEE EXPERT-INTELLIGENT SYSTEMS & THEIR APPLICATIONS, 1996, 11 (04): : 71 - 81
  • [2] Real-time Java for on-board systems
    ETH-Zentrum, Institut für Automatik, Physikstr. 3, 8092 Zürich, Switzerland
    Eur Space Agency Spec Publ ESA SP, 1600, 509 (336-347):
  • [3] Real-Time Human Detection and Gesture Recognition for On-Board UAV Rescue
    Liu, Chang
    Sziranyi, Tamas
    SENSORS, 2021, 21 (06) : 1 - 21
  • [4] ON-BOARD REAL-TIME FAILURE-DETECTION AND DIAGNOSIS OF AUTOMOTIVE SYSTEMS
    DEBENITO, CD
    JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 1990, 112 (04): : 769 - 773
  • [5] AMARO-An On-Board Ship Detection and Real-Time Information System
    Willburger, Katharina
    Schwenk, Kurt
    Brauchle, Joerg
    SENSORS, 2020, 20 (05)
  • [6] Real-time Road Anomaly Detection, Using an on-board Data Logger
    Hameed, Hadia
    Mazhar, Suleman
    Hassan, Naufil
    2018 IEEE 87TH VEHICULAR TECHNOLOGY CONFERENCE (VTC SPRING), 2018,
  • [7] On-board real-time tracking of pedestrians on a UAV
    De Smedt, Floris
    Hulens, Dries
    Goedeme, Toon
    2015 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW), 2015,
  • [8] An innovative on-board processor for the real-time GPR monitoring of railway substructure conditions
    Caorsi, S.
    Cevini, G.
    Burro, F.
    Sciotti, A.
    Sorge, S.
    2007 4TH INTERNATIONAL WORKSHOP ON ADVANCED GROUND PENETRATING RADAR, 2007, : 264 - +
  • [9] ShuffleDet: Real-Time Vehicle Detection Network in On-Board Embedded UAV Imagery
    Azimi, Seyed Majid
    COMPUTER VISION - ECCV 2018 WORKSHOPS, PT II, 2019, 11130 : 88 - 99
  • [10] Real-Time On-Board Deep Learning Fault Detection for Autonomous UAV Inspections
    Ayoub, Naeem
    Schneider-Kamp, Peter
    ELECTRONICS, 2021, 10 (09)