Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/107153
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electrical and Electronic Engineering | - |
dc.contributor | Mainland Development Office | - |
dc.creator | Wu, H | en_US |
dc.creator | Shang, C | en_US |
dc.creator | Zhu, K | en_US |
dc.creator | Lu, C | en_US |
dc.date.accessioned | 2024-06-13T01:04:14Z | - |
dc.date.available | 2024-06-13T01:04:14Z | - |
dc.identifier.issn | 0733-8724 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/107153 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.rights | The following publication H. Wu, C. Shang, K. Zhu and C. Lu, "Vibration Detection in Distributed Acoustic Sensor With Threshold-Based Technique: A Statistical View and Analysis," in Journal of Lightwave Technology, vol. 39, no. 12, pp. 4082-4093, 15 June 2021 is available at https://doi.org/10.1109/JLT.2020.3036450. | en_US |
dc.subject | Detection probability | en_US |
dc.subject | Distributed acoustic sensor (DAS) | en_US |
dc.subject | False alarm probability | en_US |
dc.subject | False alarm rate | en_US |
dc.subject | Signal-to-noise ratio (SNR) | en_US |
dc.subject | Threshold-based technique | en_US |
dc.subject | Vibration detection | en_US |
dc.title | Vibration detection in distributed acoustic sensor with threshold-based technique : a statistical view and analysis | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 4082 | en_US |
dc.identifier.epage | 4093 | en_US |
dc.identifier.volume | 39 | en_US |
dc.identifier.issue | 12 | en_US |
dc.identifier.doi | 10.1109/JLT.2020.3036450 | en_US |
dcterms.abstract | Detecting vibrations with high probability and low false alarm probability is crucial for prompting distributed acoustic sensors (DASs) to real applications. It is known that detection performance mainly depends on signal-to-noise ratio (SNR) and many efforts have been made to improve it. However, the relationship between SNR and detection performance has not been quantitatively analyzed so far. Threshold-based vibration detection is a simple and commonly used technique, but how to set the decision threshold in DAS is still an open question. In this work, for the first time, we propose a model to quantify the relationship between SNR and detection performance and provide a method for setting the decision threshold. Firstly, we build a model to differentiate vibrations from the background noise based on their short-time average energy. This model reveals that setting decision threshold requires perfect knowledge of noise power, which is a difficult task in DAS since noise power varies frequently with time and position. To solve this problem, secondly, we propose a noise-irrelevant threshold setting method based on autocorrelation-energy. Finally, experimental validation is performed on a DAS system along 47.4km sensing fiber with 5m spatial resolution. Results of autocorrelation-energy-based method show 100% and 98.1% detection probability for two vibrations with 1.12 × 10−7 false alarm probability in a one-hour measurement period. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Journal of lightwave technology, 15 June 2021, v. 39, no. 12, p. 4082-4093 | en_US |
dcterms.isPartOf | Journal of lightwave technology | en_US |
dcterms.issued | 2021-06-15 | - |
dc.identifier.scopus | 2-s2.0-85098773489 | - |
dc.identifier.eissn | 1558-2213 | en_US |
dc.description.validate | 202403 bckw | - |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | EIE-0265 | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Key Research and Development Program of China; National Natural Science Foundation of China (NSFC); The Hong Kong Polytechnic University | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 43301601 | - |
dc.description.oaCategory | Green (AAM) | en_US |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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Wu_Vibration_Detection_Distributed.pdf | Pre-Published version | 500.41 kB | Adobe PDF | View/Open |
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