Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health Monitoring Article Swipe
Nur Dalilla Nordin
,
Fairuz Abdullah
,
Mohd Saiful Dzulkefly Zan
,
Ahmad Ashrif A. Bakar
,
A.I. Krivosheev
,
F. L. Barkov
,
Yuri A. Konstantinov
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/s22072677
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.3390/s22072677
In this paper, we studied the possibility of increasing the Brillouin frequency shift (BFS) detection accuracy in distributed fibre-optic sensors by the separate and joint use of different algorithms for finding the spectral maximum: Lorentzian curve fitting (LCF, including the Levenberg–Marquardt (LM) method), the backward correlation technique (BWC) and a machine learning algorithm, the generalized linear model (GLM). The study was carried out on real spectra subjected to the subsequent addition of extreme digital noise. The precision and accuracy of the LM and BWC methods were studied by varying the signal-to-noise ratios (SNRs) and by incorporating the GLM method into the processing steps. It was found that the use of methods in sequence gives a gain in the accuracy of determining the sensor temperature from tenths to several degrees Celsius (or MHz in BFS scale), which is manifested for signal-to-noise ratios within 0 to 20 dB. We have found out that the double processing (BWC + GLM) is more effective for positive SNR values (in dB): it gives a gain in BFS measurement precision near 0.4 °C (428 kHz or 9.3 με); for BWC + GLM, the difference of precisions between single and double processing for SNRs below 2.6 dB is about 1.5 °C (1.6 MHz or 35 με). In this case, double processing is more effective for all SNRs. The described technique’s potential application in structural health monitoring (SHM) of concrete objects and different areas in metrology and sensing were also discussed.
Related Topics
Concepts
Noise (video)
Structural health monitoring
Accuracy and precision
Signal processing
SIGNAL (programming language)
Signal-to-noise ratio (imaging)
Algorithm
Computer science
Spectral line
Acoustics
Optics
Materials science
Mathematics
Physics
Digital signal processing
Statistics
Artificial intelligence
Programming language
Computer hardware
Composite material
Image (mathematics)
Astronomy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s22072677
- https://www.mdpi.com/1424-8220/22/7/2677/pdf?version=1648698555
- OA Status
- gold
- Cited By
- 21
- References
- 55
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4220735568
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4220735568Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s22072677Digital Object Identifier
- Title
-
Improving Prediction Accuracy and Extraction Precision of Frequency Shift from Low-SNR Brillouin Gain Spectra in Distributed Structural Health MonitoringWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-03-31Full publication date if available
- Authors
-
Nur Dalilla Nordin, Fairuz Abdullah, Mohd Saiful Dzulkefly Zan, Ahmad Ashrif A. Bakar, A.I. Krivosheev, F. L. Barkov, Yuri A. KonstantinovList of authors in order
- Landing page
-
https://doi.org/10.3390/s22072677Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/22/7/2677/pdf?version=1648698555Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/1424-8220/22/7/2677/pdf?version=1648698555Direct OA link when available
- Concepts
-
Noise (video), Structural health monitoring, Accuracy and precision, Signal processing, SIGNAL (programming language), Signal-to-noise ratio (imaging), Algorithm, Computer science, Spectral line, Acoustics, Optics, Materials science, Mathematics, Physics, Digital signal processing, Statistics, Artificial intelligence, Programming language, Computer hardware, Composite material, Image (mathematics), AstronomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
21Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 5, 2023: 14, 2022: 2Per-year citation counts (last 5 years)
- References (count)
-
55Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.possibility | 6 |
| abstract_inverted_index.temperature | 123 |
| abstract_inverted_index.incorporating | 95 |
| abstract_inverted_index.technique’s | 222 |
| abstract_inverted_index.signal-to-noise | 90, 139 |
| abstract_inverted_index.Levenberg–Marquardt | 40 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 94 |
| corresponding_author_ids | https://openalex.org/A5003531684 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I4210119369 |
| citation_normalized_percentile.value | 0.86831012 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |