Multi-component fault diagnosis of Self Aligning Troughing Roller (SATR) in belt conveyor system using decision tree: A statistical approach
Self-Aligning Troughing Roller (SATR) is one of the critical components in belt conveyor; it is a very critical component in riding the belt conveyor in fault free condition. SATR arrangement has a long roll to support the given belt and handle maximum load per cross-section. SATR has machine elemen...
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| Format: | Article |
| Language: | English |
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University of Belgrade - Faculty of Mechanical Engineering, Belgrade
2020-01-01
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| Series: | FME Transactions |
| Subjects: | |
| Online Access: | https://scindeks-clanci.ceon.rs/data/pdf/1451-2092/2020/1451-20922002364R.pdf |
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| author | Ravikumar S. Kanagasabapathy H. Muralidharan V. |
| author_facet | Ravikumar S. Kanagasabapathy H. Muralidharan V. |
| author_sort | Ravikumar S. |
| collection | DOAJ |
| description | Self-Aligning Troughing Roller (SATR) is one of the critical components in belt conveyor; it is a very critical component in riding the belt conveyor in fault free condition. SATR arrangement has a long roll to support the given belt and handle maximum load per cross-section. SATR has machine elements like ball bearing, central shaft and the external shell. In belt conveyor system certain faults such as bearing fault (BF), central shaft fault (SF), combined bearing flaw and central shaft fault (BF& SF) occur frequently. Fault diagnosis in SATR essentially forms a classification problem. A prototype setup has been designed and fabricated; Different faults such as bearing fault (BF), central shaft fault (SF), combined bearing flaw and central shaft fault (BF& SF) are introduced one at a time and the corresponding vibration signals have been acquired from the setup . Followed by this step a set if statistical parameters were computed which forms the feature set and classified using Artificial Neural Network (ANN) algorithms and decision tree algorithms. At the outset, decision tree algorithm shows superior performance in terms of classification accuracy. The whole effort is to bring out the best number of features for maximum efficiency. A tenfold cross validation was performed to validate the results. |
| first_indexed | 2024-04-12T00:58:26Z |
| format | Article |
| id | doaj.art-ee640f8ab1734010b390c08c2d283da2 |
| institution | Directory Open Access Journal |
| issn | 1451-2092 2406-128X |
| language | English |
| last_indexed | 2024-04-12T00:58:26Z |
| publishDate | 2020-01-01 |
| publisher | University of Belgrade - Faculty of Mechanical Engineering, Belgrade |
| record_format | Article |
| series | FME Transactions |
| spelling | doaj.art-ee640f8ab1734010b390c08c2d283da22022-12-22T03:54:33ZengUniversity of Belgrade - Faculty of Mechanical Engineering, BelgradeFME Transactions1451-20922406-128X2020-01-014823643711451-20922002364RMulti-component fault diagnosis of Self Aligning Troughing Roller (SATR) in belt conveyor system using decision tree: A statistical approachRavikumar S.0Kanagasabapathy H.1Muralidharan V.2Faculty of Mechanical Engineering, B.S. Abdur Rahman Crescent Institute of Science & Technology, Chennai, Tamilnadu, IndiaP.S.R. Engineering College, Faculty of Mechanical Engineering, Sivakasi, Tamilnadu, IndiaFaculty of Mechanical Engineering, B.S. Abdur Rahman Crescent Institute of Science & Technology, Chennai, Tamilnadu, IndiaSelf-Aligning Troughing Roller (SATR) is one of the critical components in belt conveyor; it is a very critical component in riding the belt conveyor in fault free condition. SATR arrangement has a long roll to support the given belt and handle maximum load per cross-section. SATR has machine elements like ball bearing, central shaft and the external shell. In belt conveyor system certain faults such as bearing fault (BF), central shaft fault (SF), combined bearing flaw and central shaft fault (BF& SF) occur frequently. Fault diagnosis in SATR essentially forms a classification problem. A prototype setup has been designed and fabricated; Different faults such as bearing fault (BF), central shaft fault (SF), combined bearing flaw and central shaft fault (BF& SF) are introduced one at a time and the corresponding vibration signals have been acquired from the setup . Followed by this step a set if statistical parameters were computed which forms the feature set and classified using Artificial Neural Network (ANN) algorithms and decision tree algorithms. At the outset, decision tree algorithm shows superior performance in terms of classification accuracy. The whole effort is to bring out the best number of features for maximum efficiency. A tenfold cross validation was performed to validate the results.https://scindeks-clanci.ceon.rs/data/pdf/1451-2092/2020/1451-20922002364R.pdfself aligning troughing roller (satr)belt conveyor system (bcs)decision treestatistical featuresconfusion matrix |
| spellingShingle | Ravikumar S. Kanagasabapathy H. Muralidharan V. Multi-component fault diagnosis of Self Aligning Troughing Roller (SATR) in belt conveyor system using decision tree: A statistical approach FME Transactions self aligning troughing roller (satr) belt conveyor system (bcs) decision tree statistical features confusion matrix |
| title | Multi-component fault diagnosis of Self Aligning Troughing Roller (SATR) in belt conveyor system using decision tree: A statistical approach |
| title_full | Multi-component fault diagnosis of Self Aligning Troughing Roller (SATR) in belt conveyor system using decision tree: A statistical approach |
| title_fullStr | Multi-component fault diagnosis of Self Aligning Troughing Roller (SATR) in belt conveyor system using decision tree: A statistical approach |
| title_full_unstemmed | Multi-component fault diagnosis of Self Aligning Troughing Roller (SATR) in belt conveyor system using decision tree: A statistical approach |
| title_short | Multi-component fault diagnosis of Self Aligning Troughing Roller (SATR) in belt conveyor system using decision tree: A statistical approach |
| title_sort | multi component fault diagnosis of self aligning troughing roller satr in belt conveyor system using decision tree a statistical approach |
| topic | self aligning troughing roller (satr) belt conveyor system (bcs) decision tree statistical features confusion matrix |
| url | https://scindeks-clanci.ceon.rs/data/pdf/1451-2092/2020/1451-20922002364R.pdf |
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