Fault Diagnosis of Mechanized Bridge’s Electrical System Based on I2C-bus and Virtual Instrument Technology

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Abstract:

The electrical system fault testing and diagnosis system based on I2C-bus and embedded equipment is proposed. This system is accomplished with the integration of PXI-based computer, field fault testing platform, dedicated interface adapter unit and accessories with software program of virtual instrument and database management and fault guidance system. It can obtain various state parameters of the heavy mechanized bridge by interface adapter unit and corresponding sensors. The dedicated interface adapter unit, that is the core of the hardware platform is composed of chassis, embedded microcomputer controller, I2C-bus data acquisition modules, VPC connection package and military aviation sockets. Because of its flexibility and modular design, it can support different data conversion, for example, analog, digital, and serial, while functioning as an intelligent conversion bridge between field fault testing platform or PXI computer and electrical system of heavy mechanized bridge electrical system. The fault diagnosis software is of hierarchical modular structure with integration of system management control, fault detection and circuit hardware driver modules together with fault repair and diagnosis database. Therefore it provides functions of human-machine interaction, equipment fault detection, fault diagnosis and analysis, as well as repair and maintenance guidance The fault testing and diagnosis system in this work is also featured with handy structure, lightweight, low consumption, large storage capacity, excellent expandability and intelligent inference capability. The system can be used in the online fault testing and diagnosis of similar engineering equipments. So it has important engineering and military application value to the rapid fault testing and fault diagnosis of engineering equipments.

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444-449

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July 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] L.B. Jack, A.K. Nandi. Fault Detection Using Support Vector Machines and Artificial Neural Networdks Augmented by Gentic Algorithms. Mechanical Systems and Signal Processing, Volume 16, Issues 2-3, March 2002, 373-390.

DOI: 10.1006/mssp.2001.1454

Google Scholar

[2] L Gonzálezf1, I Anderson, D Deane, C Summers, D Buxton. Detection of Immune System Cells in Paraffin Wax-embedded Ovine Tissues. Journal of Comparative Pathology, Volume 125, Issue 1, July 2001, 41-47.

DOI: 10.1053/jcpa.2001.0475

Google Scholar

[3] Paul Kocher, Ruby Lee, Gary McGraw, Anand Raghunathan. Security as a new dimension in embedded system design. Proceedings of the 41st annual Design Automation Conference, ACM New York, NY, USA @(2004).

DOI: 10.1145/996566.996771

Google Scholar

[4] Rolf Isermann. Model-based fault-detection and diagnosis – status and applications, Annual Reviews in Control, Volume 29, Issue 1, 2005, 71-85.

DOI: 10.1016/j.arcontrol.2004.12.002

Google Scholar

[5] Rolf Isermann. Supervision, fault-detection and fault-diagnosis methods — An introduction, Control Engineering Practice, Volume 5, Issue 5, May 1997, 639-652.

DOI: 10.1016/s0967-0661(97)00046-4

Google Scholar

[6] Samuel R. Madden, Michael J. Franklin, Joseph M. Hellerstein, Wei Hong. an acquisitional query processing system for sensor networks. ACM Transactions on Database Systems, Volume 30 Issue 1, 1324-1339,March (2005).

DOI: 10.1145/1061318.1061322

Google Scholar