A review of self‐validating sensor technology

Author:

Feng Zhigang,Wang Qi,Shida Katsunori

Abstract

PurposeTo provide an overview of self‐validating sensor technology for researchers and engineers which can help them understand the concept and recent developments of this research area.Design/methodology/approachThe concept of self‐validating (SEVA) sensors, including definition, output parameters and requirement of SEVA sensors are introduced. The differences between SEVA sensors and traditional sensors are given from which we can see many advantages of SEVA sensors. The principium of SEVA sensors is presented by the functional architecture. The research development of SEVA sensors is introduced in two aspects: research development of sensor fault diagnosis and signal reconstruction and research development of SEVA sensor hardware.FindingsSummarizes the methods for sensor fault diagnosis and signal reconstruction in the research of SEVA sensors, and the development steps of SEVA sensor hardware. Indicates the shortages and problems of current research and gives our research and ideas to solve these problems.Originality/valueThis paper provides a detailed description and research information of self‐validating sensor technology for those who want to know and research on this area.

Publisher

Emerald

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering

Reference40 articles.

1. Abdelrahman, M. and Kandasamy, F.J. (2000), “Methodology for the fusion of redundant sensors”, Proceedings of the American Control Conference, No. 4, pp. 2922‐6.

2. Atia, M., Bowles, J., Clarke, D.W. and Henry, M.P. (1995), “Self‐validating temperature sensor implemented in FPGAs”, Lecture Notes in Computer Science, No. 957, p. 321.

3. Barberree, D. (2002), “The next generation of thermocouples for the turbine engine industry”, Proceedings of the International Instrumentation Symposium, No. 48, pp. 419‐29.

4. Barberree, D. (2003), “Dynamically self‐validating contact temperature sensors”, AIP Conference Proceedings, No. 684, pp. 1097‐102.

5. BS‐7986 (2001), “Specification for data quality for industrial measurement and control systems”, BS‐7986, 2001.

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