Use of Self-Calibration Data for Multifunctional MEMS Sensor Prognostics

Khan, Hamid; Tahir, I.; Richardson, A.

doi:10.1109/jmems.2016.2564499

Cited by 3 publications

(1 citation statement)

References 28 publications

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“…For BIST, cross-sensitivity can be exploited as a substitute for redundancy. Extensive research has been carried out in the field of multi-functional sensors (MFS) at Lancaster University by Richardson et al, an example of which is provided in Figure 22 [ 93 , 94 , 95 ].…”

Section: Bist Methods Building On Multi-functional Sensorsmentioning

confidence: 99%

Built-In Self-Test (BIST) Methods for MEMS: A Review

2020

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A novel taxonomy of built-in self-test (BIST) methods is presented for the testing of micro-electro-mechanical systems (MEMS). With MEMS testing representing 50% of the total costs of the end product, BIST solutions that are cost-effective, non-intrusive and able to operate non-intrusively during system operation are being actively sought after. After an extensive review of the various testing methods, a classification table is provided that benchmarks such methods according to four performance metrics: ease of implementation, usefulness, test duration and power consumption. The performance table provides also the domain of application of the method that includes field test, power-on test or assembly phase test. Although BIST methods are application dependent, the use of the inherent multi-modal sensing capability of most sensors offers interesting prospects for effective BIST, as well as built-in self-repair (BISR).

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Section: Bist Methods Building On Multi-functional Sensorsmentioning

confidence: 99%

Built-In Self-Test (BIST) Methods for MEMS: A Review

2020

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Estimation of IMU orientation using Nesterov’s accelerated gradient improved by fuzzy control rule

Tang

Fan

et al. 2021

Sensors and Actuators A: Physical

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Self-Monitoring, Self-Healing Biomorphic Sensor Technology

Richardson

Cheneler

2019

2019 IEEE 25th International Symposium on on-Line Testing and Robust System Design (IOLTS)

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The deployment of autonomous sensors within electronic systems for both existing and emerging markets requires an increase in the reliability, security and dependability of the associated data generated. The availability of intelligent sensors that can self-adapt and ultimately self-heal would be a key step towards this objective. This paper presents ideas associated with the utilisation of sensor self-test principles and software algorithms able to generate sensor prognostics and drive adaptation, compensation and self-healing functions. Major initiatives supported both within Europe and further afield to migrate processing power to the "Edge", deploy 5G technologies and integrate Artificial Intelligence across the system hierarchy provide technological platforms to deliver many of these concepts. An example associated with simple printed electrodes targeting corrosion detection and potentially the detection of hydrogen is presented in the context of a step towards full biomorphic capability.

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Use of Self-Calibration Data for Multifunctional MEMS Sensor Prognostics

Cited by 3 publications

References 28 publications

Built-In Self-Test (BIST) Methods for MEMS: A Review

Built-In Self-Test (BIST) Methods for MEMS: A Review

Estimation of IMU orientation using Nesterov’s accelerated gradient improved by fuzzy control rule

Self-Monitoring, Self-Healing Biomorphic Sensor Technology

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