Determining the Convergence of Synchronous Measurements for Embedded Industrial Applications
Article
Article Title | Determining the Convergence of Synchronous Measurements for Embedded Industrial Applications |
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ERA Journal ID | 3598 |
Article Category | Article |
Authors | Leis, John (Author) and Buttsworth, David (Author) |
Journal Title | IEEE Transactions on Industrial Electronics |
Journal Citation | 64 (9), pp. 7392-7398 |
Number of Pages | 7 |
Year | 2017 |
Place of Publication | United States |
ISSN | 0278-0046 |
1557-9948 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TIE.2016.2638798 |
Web Address (URL) | https://ieeexplore.ieee.org/document/7781605 |
Abstract | One technique which may be employed in certain types of sensing application is the phase-sensitive or lock-in method. Since this method essentially trades off longer measurement time for a greater accuracy, it is sometimes necessary to capture samples over a long time period to ensure sufficient stability in the calculated parameter estimate. This may adversely affect safety-critical systems, and some method of determining the relative stability of the measured parameter is needed to permit this useful approach to be more widely employed. In this paper, we propose and evaluate a novel entropy-based method for ascertaining stability. The contributions of this paper are to first highlight the need for a convergence measure which is reliable, automatic, and easily computed; second, we propose one such measure, and place it on a theoretical footing; finally, we give results both with simulated Gaussian noise having a typical sensor power spectrum, as well as experimental results using the type of optical sensor which would benefit from the proposed method. It is demonstrated that this approach produces a reliable asymptotic figure for convergence, both under simulated noise conditions as well as with real measurements in the field. |
Keywords | signal to noise ratio, entropy, detection algorithms, filtering algorithms, adaptive signal detection |
ANZSRC Field of Research 2020 | 400907. Industrial electronics |
400607. Signal processing | |
400801. Circuits and systems | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | School of Mechanical and Electrical Engineering |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q3qq1/determining-the-convergence-of-synchronous-measurements-for-embedded-industrial-applications
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