Detecting Punctual Damage to Gears through the Continuous Morlet Wavelet Transform
In predictive maintenance, vibration signal analyses are frequently used to diagnose reducer failures because these analyses contain information about the conditions of the mechanical components. Reducer vibration signals are very noisy and the signal-to-noise ratio is so low that extracting informa...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2020/8879565 |
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| _version_ | 1850216129633452032 |
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| author | Andre Luis Vinagre Pereira Aparecido Carlos Gonçalves Rubens Ribeiro Fábio Roberto Chavarette Roberto Outa |
| author_facet | Andre Luis Vinagre Pereira Aparecido Carlos Gonçalves Rubens Ribeiro Fábio Roberto Chavarette Roberto Outa |
| author_sort | Andre Luis Vinagre Pereira |
| collection | DOAJ |
| description | In predictive maintenance, vibration signal analyses are frequently used to diagnose reducer failures because these analyses contain information about the conditions of the mechanical components. Reducer vibration signals are very noisy and the signal-to-noise ratio is so low that extracting information from the signal components is complex, especially in practical situations. Therefore, signal processing techniques are used to solve this problem and facilitate the retrieval of information. In this work, the adopted technique included noise-canceling technique, synchronous temporal mean (TSA), and continuous Morlet wavelet transform (CWT), designed to extract resources and diagnose local gear damage. These techniques are used in measured signals in an experimental workbench consisting of the gear pair coupled to a motor and a generator. The experiment was monitored according to the conditions of a gear pair throughout its useful life. The continuous wavelet transforms accurately identified faults in the gear teeth, and it was possible to detect in which tooth the fault was occurring. |
| format | Article |
| id | doaj-art-3e2973ce2ed7497e920a1de329d67545 |
| institution | OA Journals |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-3e2973ce2ed7497e920a1de329d675452025-08-20T02:08:24ZengWileyShock and Vibration1070-96221875-92032020-01-01202010.1155/2020/88795658879565Detecting Punctual Damage to Gears through the Continuous Morlet Wavelet TransformAndre Luis Vinagre Pereira0Aparecido Carlos Gonçalves1Rubens Ribeiro2Fábio Roberto Chavarette3Roberto Outa4PPG in Mechanical Engineering, DEM, FEIS/UNESP, Ilha Solteira, BrazilDepartment of Mechanical Engineering, DEM, FEIS/UNESP, Ilha Solteira, BrazilPPG in Mechanical Engineering, DEM, FEIS/UNESP, Ilha Solteira, BrazilDepartment of Mathematics, MAT, FEIS/UNESP, Ilha Solteira, BrazilDepartment of Biofuels, Araçatuba Technology College, FATEC, Sorocaba, BrazilIn predictive maintenance, vibration signal analyses are frequently used to diagnose reducer failures because these analyses contain information about the conditions of the mechanical components. Reducer vibration signals are very noisy and the signal-to-noise ratio is so low that extracting information from the signal components is complex, especially in practical situations. Therefore, signal processing techniques are used to solve this problem and facilitate the retrieval of information. In this work, the adopted technique included noise-canceling technique, synchronous temporal mean (TSA), and continuous Morlet wavelet transform (CWT), designed to extract resources and diagnose local gear damage. These techniques are used in measured signals in an experimental workbench consisting of the gear pair coupled to a motor and a generator. The experiment was monitored according to the conditions of a gear pair throughout its useful life. The continuous wavelet transforms accurately identified faults in the gear teeth, and it was possible to detect in which tooth the fault was occurring.http://dx.doi.org/10.1155/2020/8879565 |
| spellingShingle | Andre Luis Vinagre Pereira Aparecido Carlos Gonçalves Rubens Ribeiro Fábio Roberto Chavarette Roberto Outa Detecting Punctual Damage to Gears through the Continuous Morlet Wavelet Transform Shock and Vibration |
| title | Detecting Punctual Damage to Gears through the Continuous Morlet Wavelet Transform |
| title_full | Detecting Punctual Damage to Gears through the Continuous Morlet Wavelet Transform |
| title_fullStr | Detecting Punctual Damage to Gears through the Continuous Morlet Wavelet Transform |
| title_full_unstemmed | Detecting Punctual Damage to Gears through the Continuous Morlet Wavelet Transform |
| title_short | Detecting Punctual Damage to Gears through the Continuous Morlet Wavelet Transform |
| title_sort | detecting punctual damage to gears through the continuous morlet wavelet transform |
| url | http://dx.doi.org/10.1155/2020/8879565 |
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