Feature fusion-based fiber-optic distributed acoustic sensing signal identification method Article Swipe
Xiaodong Wang
,
Chang Wang
,
Faxiang Zhang
,
Shaodong Jiang
,
Zhihui Sun
,
Hongyu Zhang
,
Zhenhui Duan
,
Zhaoying Liu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1361-6501/acf781
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1361-6501/acf781
Fiber-optic distributed acoustic sensing (DAS) systems based on phase-sensitive optical time-domain reflection technology have been widely used for perimeter security and oil and gas pipeline safety monitoring. To address the problem of low recognition accuracy of high-sampling-rate long-sequence signal data (length greater than or equal to 1000 points) collected by the DAS system, we propose a CDIL-CBAM-BiLSTM network model based on feature fusion. The model uses a modified circular dilated convolutional neural network to extract detailed temporal structure information from each signal node, and combines it with bidirectional long short-term memory network using feature fusion to dig deeper into the data. Meanwhile, a convolutional block attention module was introduced to improve the model performance. The experimental results based on 5040 training samples and 2160 test samples show that the proposed model can achieve an average recognition accuracy of more than 99 for six real disturbance events under perimeter security scenarios, and the recognition time was less than 2 ms. In addition, our method achieved the highest recognition accuracy compared with other methods used in the experiments and can be extended to other areas, such as pipeline safety monitoring and industrial inspection measurements.
Related Topics
Concepts
Computer science
Feature (linguistics)
Artificial intelligence
Pattern recognition (psychology)
Pipeline (software)
Convolutional neural network
SIGNAL (programming language)
Block (permutation group theory)
Time domain
Real-time computing
Algorithm
Computer vision
Mathematics
Philosophy
Geometry
Linguistics
Programming language
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1361-6501/acf781
- OA Status
- hybrid
- Cited By
- 12
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386516270
All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4386516270Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1361-6501/acf781Digital Object Identifier
- Title
-
Feature fusion-based fiber-optic distributed acoustic sensing signal identification methodWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-09-07Full publication date if available
- Authors
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Xiaodong Wang, Chang Wang, Faxiang Zhang, Shaodong Jiang, Zhihui Sun, Hongyu Zhang, Zhenhui Duan, Zhaoying LiuList of authors in order
- Landing page
-
https://doi.org/10.1088/1361-6501/acf781Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1088/1361-6501/acf781Direct OA link when available
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Computer science, Feature (linguistics), Artificial intelligence, Pattern recognition (psychology), Pipeline (software), Convolutional neural network, SIGNAL (programming language), Block (permutation group theory), Time domain, Real-time computing, Algorithm, Computer vision, Mathematics, Philosophy, Geometry, Linguistics, Programming languageTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
12Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 6, 2024: 6Per-year citation counts (last 5 years)
- References (count)
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35Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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