Modelling the Positional and Orientation Sensitivity of Inductively Coupled Sensors for Industrial IoT Applications

McWilliam, Richard; Purvis, Alan; Khan, Samir

Abstract

As the Internet of Things (IoT) sector continually expands there is a growing abstraction between physical objects and the data associated with them. At the same time, emerging Industrial-IoT applications rely upon diverse and robust hardware sensing interfaces in order to deliver high quality data. In this paper, the fundamental limitations associated with inductive proximity sensing interfaces are considered in terms of positional and orientation sensitivity and a triaxial approach is proposed that enables arbitrary source-sensor positioning. A matrix transformation model based on the field coupling equations is applied to a number of candidate configurations assessed according their relative source-sensor coverage and graphical visualization of coupling quality. Particular attention is paid to the recombination of tri-sensor outputs involving direct-summation, rectifysummation, best-coil and root-mean-square methods. Of these, the rectify-summation method was observed to provide favorable performance, exceeding 70% coverage for practical cases, thus far exceeding that of traditional co-planar arrangements.

Citation

McWilliam, R., Purvis, A., & Khan, S. (2016). Modelling the Positional and Orientation Sensitivity of Inductively Coupled Sensors for Industrial IoT Applications. International journal of simulation: systems, science & technology, 17(35), Article 23.1

• Journal Article Type: Article
• Acceptance Date: Aug 1, 2016
• Publication Date: Oct 1, 2016
• Deposit Date: Oct 26, 2016
• Publicly Available Date: Oct 27, 2016
• Journal: International journal of simulation systems, science & technology
• Print ISSN: 1473-8031
• Electronic ISSN: 1473-804X
• Publisher: United Kingdom Simulation Society
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Issue: 35
• Article Number: 23.1
• Public URL: https://durham-repository.worktribe.com/output/1373524
• Publisher URL: http://ijssst.info/