The electrical connector disconnection is a common problem in automotive systems. It can be caused by bad design, manufacturing issues, ageing in harsh environment, or low product quality. An imminent disconnection during driving may result in severe safety issues. A loose connection manifests itself as intermittent faults of various vehicle components, which is hard to diagnose and likely leads to unnecessary component replacement or dealership revisit. In order to predict the connector disconnection, a low-cost canary-based approach is proposed in this paper. A shortened male terminal is employed to foretell the loose factory terminals in the same connector housing. The dimension and placement of the shortened terminal are theoretically and experimentally investigated to achieve optimal performance. The proposed solution is tested and compared to other common diagnostic and prognostic approaches, including inductance–, capacitance–, resistance–based approaches, time domain reflectometry, and frequency domain transmissometry, using a connector bench test setup. The placement variation test and the accelerated vibration test are performed to simulate the long-term real driving scenario as well. It’s shown that the proposed solution is capable of
predicting connector disconnection robustly before the vehicle functionality is affected.
How to Cite
connector disconnection, prognosis, canary
Chung, Y. C., Furse, C., & Pruitt, J. (2005). Application of Phase Detection Frequency Domain Reflectormetry for Locating Faults in an F-18 Flight Control Harness. IEEE Transctions on Electromagnetic Compatibility, vol. 47, pp. 327-334. doi: 10.1109/TEMC.2005.847403
Furse, C., Chung, Y. C., Dangol, R., Neilson, M., Mabey, G., & Woodward, R. (2003). Frequency-Domain Reflectometery for on-Board Testing of Aging
Aircraft Wiring. IEEE Transaction on Electromagnetic Compatibility, vol. 45, pp. 306-315. doi: 10.1109/TEMC.2003.811305
Furse, C., Chung, Y. C., Lo, C., & Pendalaya, P. (2006). A critical comparison of reflectometry methods for location of wiring faults. Smart Structures and Systems, vol. 2, pp. 25-46.
Furse, C., Smith, P., & Safavi, M. (2005). Feasibility of Spread Spectrum Sensors for Location of Arcs on Live Wires. IEEE Sensors Journal, vol. 5, pp.1445-
1450. doi: 10.1109/JSEN.2005.858900
Okada, T., Nishina, S., Ataka, T., Hashimoto, M., Irisawa, A., & Imamura, M. (2015). Development of Terahertz Pulse Time-Domain Reflectometry System for Transmission Line Failure Analysis. 40th International Conference on Infrared, Millimeter, and Terahertz waves (IRMMW-THz) . Hong Kong.
Serway, Raymond A. & Jewett, John W. Physics for Scientists and Engineerings, Brooks/Cole Cengage Learning, Boston, USA, 2014.
Shi, Q., & Kanoun, O. (2014). A New Algorithm for Wire Fault Location Using Time-Domain Reflectometry. IEEE Sensors Journal, vol. 14, pp. 1171-1178. doi:10.1109/JSEN.2013.2294193
Smail, M. K., Hacib, T., Pichon, L., & Loete, F. (2011). Detection and Location of Defects in Wiring Networks Using Time-Domain Reflectometry and
Neural Networks. IEEE Transactions on Magnetics, vol. 47, pp. 1502-1505, doi: 10.1109/ TMAG. 2010.2089503
Smail, M. K., Pichon, L., Olivas, M., Auzanneau, F., & Lambert, M. (2010). Detection of Defects in Wiring Networks Using Time Domain Reflectometry. IEEE Transactions on Magnetics, vol. 46, pp. 2998-3001. doi: 10.1109/TMAG.2010.2043720
Smith, P., Furse, C., & Gunther, J. (2005). Analysis of spread spectrum time domain reflectometry for wire fault location. IEEE Sensors Journal, vol. 5, pp.1469-1478. doi: 10.1109/JSEN.2005.858964
Tsai, P., Lo, C., Chung, Y. C., & Furse, C. (2005). Mixed-Signal Reflectometer for Location of Faults on Aging Wiring. IEEE Sensors Journal, vol. 5, pp.
1479-1482. doi: 10.1109/JSEN.2005.858894
Vichare, N., & Pecht, M. (2006). Prognostics and Health Management of Electronics. IEEE Transactions on Components and Packaging Technologies, vol. 29, pp. 222-229. doi: 10.1109/TCAPT.2006.870387
Will, B., & Rolfes, I. (2013). Comparative Study of Moisture Measurements by Time Domain Transmissometry. IEEE Sensors, pp. 1-4. doi: 10.1109/ICSENS. 2013.6688529
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