A review of self‐validating sensor technology

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.

Strain gauges debonding fault detection for structural health monitoring

“…A similar concept to sensor fault detection is sensor validation. Three main approaches to sensor fault detection and validation are known: (a) The first relies on the redundancy of information among different sensors, using physical redundancy or analytical redundancy based on knowledge or process models; (b) the second approach uses the information of the sensor output to detect changes in its characteristic behavior; and (c) the third approach uses sensors, known as self‐validating sensors—these sensors detect and correct their own faults, providing in real time the corrected readings and extra information about the measurement reliability …”

Double bridge circuit for self‐validated structural health monitoring strain measurements

“…These sensors detect and correct their own faults, providing in real time the corrected readings and extra information about the measurement reliability. ()…”

“…These sensors detect and correct their own faults, providing in real time the corrected readings and extra information about the measurement reliability. [11][12][13][14] A self-diagnosis strain sensor, operating in a continuous online SHM scenario, is considered in this study. Figure 1 shows the proposed self-diagnosis strain sensor architecture.…”

Sensor Devices with High Metrological Reliability

“…A self-validating Coriolis flow meter developed on the basis of the above sources of additional information provides the self-diagnostics and diagnostics of corresponding actuators, the result of measurements being accompanied by a value of uncertainty (Henry et al, 2000). In (Feng et al, 2007), sources of information intended for diagnostics of sensor device faults are classified in the following way:  hardware redundancy (e.g., combination of a thermocouple and resistance thermometer);  analytical redundancy taking into account a known relationships between the signals of several sensors or the signals of sensors and parameters of a technological process model;  information redundancy of a sequence of sensor device signals which is revealed with the help of mathematical methods.…”

“…Development of sensor devices with a structure that enables, to some extent, to control their metrological serviceability within the process of operation has been started in Russia since 1980s (Druzhinin & Kochugurov, 1988;Sapozhnikova, 1991;Sapozhnikova et al, 1988;Tarbeyev et al, 2007). Later on, such activity was also expanded in the UK and USA as well as in Germany, China and other countries (Barberree, 2003;Hans & Ricken, 2007;Henry & Clarke, 1993;Henry et al, 2000;Feng et al, 2007Feng et al, , 2009Reed, 2003;Werthschutzky & Muller, 2007;Werthschutzky & Werner, 2009). In general, the above works are of an heuristic character.…”