Lightweight Self-Detection and Self-Calibration Strategy for MEMS Gas Sensor Arrays

With the development of Internet of Things (IoT) and edge computing technology, gas sensor arrays based on Micro-Electro-Mechanical System (MEMS) fabrication technique have broad application prospects in intelligent integrated systems, portable devices, and other fields. In such complex scenarios, t...

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Veröffentlicht in:Sensors (Basel, Switzerland) Jg. 22; H. 12; S. 4315
Hauptverfasser: Liu, Bing, Zhou, Yanzhen, Fu, Hongshuo, Fu, Ping, Feng, Lei
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.06.2022
MDPI
Schlagworte:
Accuracy
Advanced manufacturing technologies
Algorithms
Arrays
Calibration
drift compensation
Failure
fault detection
Fault diagnosis
fault isolation and recovery
gas sensor arrays
Gases
intelligent gas sensing system
Internet of Things (IoT)
Metal oxides
Methods
Microelectromechanical systems
Real time
Sensors
Signal processing
China
ISSN:1424-8220, 1424-8220
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Zusammenfassung:With the development of Internet of Things (IoT) and edge computing technology, gas sensor arrays based on Micro-Electro-Mechanical System (MEMS) fabrication technique have broad application prospects in intelligent integrated systems, portable devices, and other fields. In such complex scenarios, the normal operation of a gas sensing system depends heavily on the accuracy of the sensor output. Therefore, a lightweight Self-Detection and Self-Calibration strategy for MEMS gas sensor arrays is proposed in this paper to monitor the working status of sensor arrays and correct the abnormal data in real time. Evaluations on real-world datasets indicate that the strategy has high performance of fault detection, isolation, and data recovery. Furthermore, our method has low computation complexity and low storage resource occupation. The board-level verification on CC1350 shows that the average calculation time and running power consumption of the algorithm are 0.28 ms and 9.884 mW. The proposed strategy can be deployed on most resource-limited IoT devices to improve the reliability of gas sensing systems.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s22124315