Fault detection of a spur gear using vibration signal with multivariable statistical parameters
This paper presents a condition monitoring technique of a spur gear fault detection using vibration signal analysis based on time domain. Vibration signals were acquired from gearboxes and used to simulate various faults on spur gear tooth. In this study, vibration signals were applied to monitor...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Prince of Songkla University
2014-10-01
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| Series: | Songklanakarin Journal of Science and Technology (SJST) |
| Subjects: | |
| Online Access: | http://rdo.psu.ac.th/sjstweb/journal/36-5/36-5-11.pdf |
| _version_ | 1828298695087489024 |
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| author | Songpon Klinchaeam Nopdanai Ajavakom Withaya Yongchareon |
| author_facet | Songpon Klinchaeam Nopdanai Ajavakom Withaya Yongchareon |
| author_sort | Songpon Klinchaeam |
| collection | DOAJ |
| description | This paper presents a condition monitoring technique of a spur gear fault detection using vibration signal analysis
based on time domain. Vibration signals were acquired from gearboxes and used to simulate various faults on spur gear
tooth. In this study, vibration signals were applied to monitor a normal and various fault conditions of a spur gear such as
normal, scuffing defect, crack defect and broken tooth. The statistical parameters of vibration signal were used to compare
and evaluate the value of fault condition. This technique can be applied to set alarm limit of the signal condition based on
statistical parameter such as variance, kurtosis, rms and crest factor. These parameters can be used to set as a boundary
decision of signal condition. From the results, the vibration signal analysis with single statistical parameter is unclear to
predict fault of the spur gears. The using at least two statistical parameters can be clearly used to separate in every case of
fault detection. The boundary decision of statistical parameter with the 99.7% certainty ( 3 ) from 300 referenced dataset
and detected the testing condition with 99.7% ( 3 ) accuracy and had an error of less than 0.3 % using 50 testing dataset. |
| first_indexed | 2024-04-13T12:45:12Z |
| format | Article |
| id | doaj.art-07967c5b21d84d19bdb2b22665986892 |
| institution | Directory Open Access Journal |
| issn | 0125-3395 |
| language | English |
| last_indexed | 2024-04-13T12:45:12Z |
| publishDate | 2014-10-01 |
| publisher | Prince of Songkla University |
| record_format | Article |
| series | Songklanakarin Journal of Science and Technology (SJST) |
| spelling | doaj.art-07967c5b21d84d19bdb2b226659868922022-12-22T02:46:23ZengPrince of Songkla UniversitySongklanakarin Journal of Science and Technology (SJST)0125-33952014-10-01365563568Fault detection of a spur gear using vibration signal with multivariable statistical parametersSongpon Klinchaeam0Nopdanai Ajavakom1Withaya Yongchareon2Department of Mechanical Engineering, Faculty of Engineering, Chulalongkorn University, Pathum Wan, Bangkok, 10330 Thailand.Department of Mechanical Engineering, Faculty of Engineering, Chulalongkorn University, Pathum Wan, Bangkok, 10330 Thailand.Department of Mechanical Engineering, Faculty of Engineering, Chulalongkorn University, Pathum Wan, Bangkok, 10330 Thailand.This paper presents a condition monitoring technique of a spur gear fault detection using vibration signal analysis based on time domain. Vibration signals were acquired from gearboxes and used to simulate various faults on spur gear tooth. In this study, vibration signals were applied to monitor a normal and various fault conditions of a spur gear such as normal, scuffing defect, crack defect and broken tooth. The statistical parameters of vibration signal were used to compare and evaluate the value of fault condition. This technique can be applied to set alarm limit of the signal condition based on statistical parameter such as variance, kurtosis, rms and crest factor. These parameters can be used to set as a boundary decision of signal condition. From the results, the vibration signal analysis with single statistical parameter is unclear to predict fault of the spur gears. The using at least two statistical parameters can be clearly used to separate in every case of fault detection. The boundary decision of statistical parameter with the 99.7% certainty ( 3 ) from 300 referenced dataset and detected the testing condition with 99.7% ( 3 ) accuracy and had an error of less than 0.3 % using 50 testing dataset.http://rdo.psu.ac.th/sjstweb/journal/36-5/36-5-11.pdfcondition monitoringvibration signalsspur gear faulttime domainmultivariable statistical parameter |
| spellingShingle | Songpon Klinchaeam Nopdanai Ajavakom Withaya Yongchareon Fault detection of a spur gear using vibration signal with multivariable statistical parameters Songklanakarin Journal of Science and Technology (SJST) condition monitoring vibration signals spur gear fault time domain multivariable statistical parameter |
| title | Fault detection of a spur gear using vibration signal with multivariable statistical parameters |
| title_full | Fault detection of a spur gear using vibration signal with multivariable statistical parameters |
| title_fullStr | Fault detection of a spur gear using vibration signal with multivariable statistical parameters |
| title_full_unstemmed | Fault detection of a spur gear using vibration signal with multivariable statistical parameters |
| title_short | Fault detection of a spur gear using vibration signal with multivariable statistical parameters |
| title_sort | fault detection of a spur gear using vibration signal with multivariable statistical parameters |
| topic | condition monitoring vibration signals spur gear fault time domain multivariable statistical parameter |
| url | http://rdo.psu.ac.th/sjstweb/journal/36-5/36-5-11.pdf |
| work_keys_str_mv | AT songponklinchaeam faultdetectionofaspurgearusingvibrationsignalwithmultivariablestatisticalparameters AT nopdanaiajavakom faultdetectionofaspurgearusingvibrationsignalwithmultivariablestatisticalparameters AT withayayongchareon faultdetectionofaspurgearusingvibrationsignalwithmultivariablestatisticalparameters |