Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis
he use of acoustic emission (AE) signal in machinery condition has considerable interest due to AE signal characteristics that can refer to machine condition. However, selecting correct AE parameters playing a pivotal role in machinery condition monitoring. This study proposed a methodology of selec...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Published: |
Asian Research Publishing Network
2016
|
| Subjects: |
| _version_ | 1796960450850586624 |
|---|---|
| author | Al-Obaidi, S.M.A. Salman Leong, M. Raja Hamzah, R.I. Abdelrhman, A.M. Danaee, M. |
| author_facet | Al-Obaidi, S.M.A. Salman Leong, M. Raja Hamzah, R.I. Abdelrhman, A.M. Danaee, M. |
| author_sort | Al-Obaidi, S.M.A. |
| collection | UM |
| description | he use of acoustic emission (AE) signal in machinery condition has considerable interest due to AE signal characteristics that can refer to machine condition. However, selecting correct AE parameters playing a pivotal role in machinery condition monitoring. This study proposed a methodology of selecting the best parameters of AE based on multivariate analysis of variance (MANOVA) method. The study aiming at monitoring or modeling enhancement by quantitatively measuring the divergence of AE parameters acquired from 72 operational conditions of industrial reciprocating compressor. In this case, nine out of thirteen AE parameters are selected as the most sensitive parameter to the compressor operational conditions according to MANOVA eta squared (η2). Eventually, the authors believe that using this method can enhance the monitoring or modelling using AE parameter in the field of machinery condition monitoring. |
| first_indexed | 2024-03-06T05:44:48Z |
| format | Article |
| id | um.eprints-18220 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:44:48Z |
| publishDate | 2016 |
| publisher | Asian Research Publishing Network |
| record_format | dspace |
| spelling | um.eprints-182202017-11-10T05:40:16Z http://eprints.um.edu.my/18220/ Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis Al-Obaidi, S.M.A. Salman Leong, M. Raja Hamzah, R.I. Abdelrhman, A.M. Danaee, M. TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery he use of acoustic emission (AE) signal in machinery condition has considerable interest due to AE signal characteristics that can refer to machine condition. However, selecting correct AE parameters playing a pivotal role in machinery condition monitoring. This study proposed a methodology of selecting the best parameters of AE based on multivariate analysis of variance (MANOVA) method. The study aiming at monitoring or modeling enhancement by quantitatively measuring the divergence of AE parameters acquired from 72 operational conditions of industrial reciprocating compressor. In this case, nine out of thirteen AE parameters are selected as the most sensitive parameter to the compressor operational conditions according to MANOVA eta squared (η2). Eventually, the authors believe that using this method can enhance the monitoring or modelling using AE parameter in the field of machinery condition monitoring. Asian Research Publishing Network 2016 Article PeerReviewed Al-Obaidi, S.M.A. and Salman Leong, M. and Raja Hamzah, R.I. and Abdelrhman, A.M. and Danaee, M. (2016) Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis. ARPN Journal of Engineering and Applied Sciences, 11 (12). pp. 7507-7514. ISSN 1819-6608, http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0616_4467.pdf |
| spellingShingle | TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery Al-Obaidi, S.M.A. Salman Leong, M. Raja Hamzah, R.I. Abdelrhman, A.M. Danaee, M. Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis |
| title | Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis |
| title_full | Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis |
| title_fullStr | Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis |
| title_full_unstemmed | Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis |
| title_short | Acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis |
| title_sort | acoustic emission parameters evaluation in machinery condition monitoring by using the concept of multivariate analysis |
| topic | TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery |
| work_keys_str_mv | AT alobaidisma acousticemissionparametersevaluationinmachineryconditionmonitoringbyusingtheconceptofmultivariateanalysis AT salmanleongm acousticemissionparametersevaluationinmachineryconditionmonitoringbyusingtheconceptofmultivariateanalysis AT rajahamzahri acousticemissionparametersevaluationinmachineryconditionmonitoringbyusingtheconceptofmultivariateanalysis AT abdelrhmanam acousticemissionparametersevaluationinmachineryconditionmonitoringbyusingtheconceptofmultivariateanalysis AT danaeem acousticemissionparametersevaluationinmachineryconditionmonitoringbyusingtheconceptofmultivariateanalysis |