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Framework for Validation of Permanently Installed MEMS-Based Acquisition Devices Using Soft Sensor Models

1
School of Mechanical and Chemical Engineering, The University of Western Australia, Perth, WA 6009, Australia
2
Department of Mathematics and Statistics, The University of Western Australia, Perth, WA 6009, Australia
3
Oceans Graduate School, The University of Western Australia, Perth, WA 6009, Australia
4
Department of Defence, Defence Science and Technology Group, Rockingham 6958, Australia
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
CivilEng 2020, 1(2), 93-105; https://doi.org/10.3390/civileng1020007
Received: 13 June 2020 / Revised: 17 July 2020 / Accepted: 24 July 2020 / Published: 28 July 2020
(This article belongs to the Special Issue Addressing Risk in Engineering Asset Management)
Asset integrity and predictive maintenance models require field data for an accurate assessment of an asset’s condition. Historically these data collected periodically in the field by technicians using portable units. The significant investment in inexpensive microelectromechanical (MEMS) sensors mounted on untethered (energy-harvesting or battery-powered) microprocessors communicating wirelessly to the cloud is expected to change the way we collect asset health data. Permanently installed MEMS-based sensing units will enable near-real time data collection and reduce the safety exposure of technicians by eliminating the need to manually collect field data. With hundreds of MEMS-based sensing units expected to be installed at a single site it is vital to assure the data they produce and maintain them cost effectively. An asset management framework for validation of MEMS-based sensing units for condition monitoring and structural integrity (CM&SI) applications is proposed. An integral part of this framework is the proposed use of soft sensor models to replace technician inspections in the field. Soft sensor models are used in the process industry to stabilize product quality and process operations but there are few examples in asset management applications. The contributions of this paper are twofold. Firstly, we use an interdisciplinary approach drawing on electronics, process control, statistics, machine learning, and asset management fields to describe the emerging field of permanently installed MEMS-based sensing units for CM&SI. Secondly, we development a framework for assuring validation of the data these sensing units generate. View Full-Text
Keywords: soft sensor; virtual sensor; calibration; validation; structural health; condition monitoring; asset management; MEMS soft sensor; virtual sensor; calibration; validation; structural health; condition monitoring; asset management; MEMS
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Bartels, A.; Cripps, E.; Keating, A.; Milne, I.; Travaglione, B.; Hodkiewicz, M. Framework for Validation of Permanently Installed MEMS-Based Acquisition Devices Using Soft Sensor Models. CivilEng 2020, 1, 93-105.

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