Feature Extraction of Lubricating Oil Debris Signal Based on Segmentation Entropy with an Adaptive Threshold
Ferromagnetic debris in lubricating oil, serving as an important communication carrier, can effectively reflect the wear condition of mechanical equipment and predict the remaining useful life. In practice application, the detection signals collected by using inductive sensors contain not only debri...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/5/1380 |
| _version_ | 1797263854213791744 |
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| author | Baojun Yang Wei Liu Sheng Lu Jiufei Luo |
| author_facet | Baojun Yang Wei Liu Sheng Lu Jiufei Luo |
| author_sort | Baojun Yang |
| collection | DOAJ |
| description | Ferromagnetic debris in lubricating oil, serving as an important communication carrier, can effectively reflect the wear condition of mechanical equipment and predict the remaining useful life. In practice application, the detection signals collected by using inductive sensors contain not only debris signals but also noise terms, and weak debris features are prone to be distorted, which makes it a severe challenge to debris signature identification and quantitative estimation. In this paper, a debris signature extraction method established on segmentation entropy with an adaptive threshold was proposed, based on which five identification indicators were investigated to improve detection accuracy. The results of the simulations and oil experiment show that the proposed algorithm can effectively identify wear particles and preserve debris signatures. |
| first_indexed | 2024-04-25T00:19:37Z |
| format | Article |
| id | doaj.art-04d53b34a0e94139820b59260a91aef7 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-25T00:19:37Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-04d53b34a0e94139820b59260a91aef72024-03-12T16:54:34ZengMDPI AGSensors1424-82202024-02-01245138010.3390/s24051380Feature Extraction of Lubricating Oil Debris Signal Based on Segmentation Entropy with an Adaptive ThresholdBaojun Yang0Wei Liu1Sheng Lu2Jiufei Luo3College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, ChinaCollege of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, ChinaSchool of Advanced Manufacturing Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, ChinaCollege of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, ChinaFerromagnetic debris in lubricating oil, serving as an important communication carrier, can effectively reflect the wear condition of mechanical equipment and predict the remaining useful life. In practice application, the detection signals collected by using inductive sensors contain not only debris signals but also noise terms, and weak debris features are prone to be distorted, which makes it a severe challenge to debris signature identification and quantitative estimation. In this paper, a debris signature extraction method established on segmentation entropy with an adaptive threshold was proposed, based on which five identification indicators were investigated to improve detection accuracy. The results of the simulations and oil experiment show that the proposed algorithm can effectively identify wear particles and preserve debris signatures.https://www.mdpi.com/1424-8220/24/5/1380inductive sensorssegmentation entropyadaptive thresholdnoise suppression |
| spellingShingle | Baojun Yang Wei Liu Sheng Lu Jiufei Luo Feature Extraction of Lubricating Oil Debris Signal Based on Segmentation Entropy with an Adaptive Threshold Sensors inductive sensors segmentation entropy adaptive threshold noise suppression |
| title | Feature Extraction of Lubricating Oil Debris Signal Based on Segmentation Entropy with an Adaptive Threshold |
| title_full | Feature Extraction of Lubricating Oil Debris Signal Based on Segmentation Entropy with an Adaptive Threshold |
| title_fullStr | Feature Extraction of Lubricating Oil Debris Signal Based on Segmentation Entropy with an Adaptive Threshold |
| title_full_unstemmed | Feature Extraction of Lubricating Oil Debris Signal Based on Segmentation Entropy with an Adaptive Threshold |
| title_short | Feature Extraction of Lubricating Oil Debris Signal Based on Segmentation Entropy with an Adaptive Threshold |
| title_sort | feature extraction of lubricating oil debris signal based on segmentation entropy with an adaptive threshold |
| topic | inductive sensors segmentation entropy adaptive threshold noise suppression |
| url | https://www.mdpi.com/1424-8220/24/5/1380 |
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