{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T16:08:07Z","timestamp":1782317287727,"version":"3.54.5"},"reference-count":26,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T00:00:00Z","timestamp":1737676800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program","doi-asserted-by":"publisher","award":["2023YFB3210000"],"award-info":[{"award-number":["2023YFB3210000"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Pressure transmitters are widely used in the process industry for pressure measurement. The sensing line, a core component of the pressure sensor in the pressure transmitter, significantly impacts the accuracy of the pressure transmitter\u2019s output. The reliability of pressure transmitters is critical in the nuclear power industry. Blockage is recognized as a common failure in pressure sensing lines; therefore, a novel detection method based on Trend Features in Time\u2013Frequency domain characteristics (TFTF) is proposed in this paper. The dataset of pressure transmitters comprises both fault and normal data. This method innovatively integrates multi-scale time series decomposition algorithms with time-domain and frequency-domain feature extraction techniques. Initially, this dataset is decomposed into multi-scale time series to mitigate periodic component interference in diagnosis. Subsequently, via the sliding window algorithm, both the time-domain features and frequency-domain features of the trend components are extracted, and finally, the XGBoost algorithm is used to detect faults. The experimental results demonstrate that the proposed TFTF algorithm achieves superior fault detection accuracy for diagnosing sensing line blockage faults compared with traditional machine learning classification algorithms.<\/jats:p>","DOI":"10.3390\/e27020120","type":"journal-article","created":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T08:48:23Z","timestamp":1737708503000},"page":"120","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Novel Machine Learning Technique for Fault Detection of Pressure Sensor"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-9175-4786","authenticated-orcid":false,"given":"Xiufang","family":"Zhou","sequence":"first","affiliation":[{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aidong","family":"Xu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bingjun","family":"Yan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingxu","family":"Gang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110169, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4267-5570","authenticated-orcid":false,"given":"Maowei","family":"Jiang","sequence":"additional","affiliation":[{"name":"Institute of Future Human Habitats, Tsinghua Shenzhen International Graduate School, University Town of Shenzhen, Nanshan District, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruiqi","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yue","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zixuan","family":"Tang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110169, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"367","DOI":"10.1016\/j.pnucene.2009.08.001","article-title":"Using the noise analysis technique to detect response time problems in the sensing lines of nuclear plant pressure transmitters","volume":"52","author":"Hashemian","year":"2010","journal-title":"Prog. 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