A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling Bearings
Condition monitoring techniques have been successfully applied to detect damaged bearings. However, the signal acquisition and the subsequent processing are typically outsourced to expensive data acquisition boards and complex software, resulting in expensive solutions. As a side effect, the integra...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/16/5645 |
| _version_ | 1827709759366627328 |
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| author | Erica Raviola Franco Fiori |
| author_facet | Erica Raviola Franco Fiori |
| author_sort | Erica Raviola |
| collection | DOAJ |
| description | Condition monitoring techniques have been successfully applied to detect damaged bearings. However, the signal acquisition and the subsequent processing are typically outsourced to expensive data acquisition boards and complex software, resulting in expensive solutions. As a side effect, the integration of condition monitoring systems in wireless sensor networks can be tough to achieve. Aiming to overcome such issues, a low-cost and small-size electronic module to be placed in the proximity of the bearing to be monitored was developed. The acoustic signal delivered by the bearing is acquired, and the corresponding frequency spectrum is evaluated on-board. Based on that, the developed module automatically detects the presence of defects and notifies the remote controller via a wireless connection only when a fault is detected, thus avoiding the use of data cables whilst minimizing the amount of transferred data. Experimental tests carried out on the proposed system assessed the accuracy of the evaluated frequency spectrum, resulting in an amplitude error within <inline-formula><math display="inline"><semantics><mrow><mo>±</mo><mn>0.6</mn><mo>%</mo></mrow></semantics></math></inline-formula>, as well as the fault detection capability in the presence of environmental acoustic noise. |
| first_indexed | 2024-03-10T17:26:27Z |
| format | Article |
| id | doaj.art-7f3b7ba0aa7a43b2a666f7fcded919c5 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T17:26:27Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-7f3b7ba0aa7a43b2a666f7fcded919c52023-11-20T10:09:28ZengMDPI AGApplied Sciences2076-34172020-08-011016564510.3390/app10165645A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling BearingsErica Raviola0Franco Fiori1Department of Electronics and Telecommunications (DET), Politecnico di Torino, 10129 Turin, ItalyDepartment of Electronics and Telecommunications (DET), Politecnico di Torino, 10129 Turin, ItalyCondition monitoring techniques have been successfully applied to detect damaged bearings. However, the signal acquisition and the subsequent processing are typically outsourced to expensive data acquisition boards and complex software, resulting in expensive solutions. As a side effect, the integration of condition monitoring systems in wireless sensor networks can be tough to achieve. Aiming to overcome such issues, a low-cost and small-size electronic module to be placed in the proximity of the bearing to be monitored was developed. The acoustic signal delivered by the bearing is acquired, and the corresponding frequency spectrum is evaluated on-board. Based on that, the developed module automatically detects the presence of defects and notifies the remote controller via a wireless connection only when a fault is detected, thus avoiding the use of data cables whilst minimizing the amount of transferred data. Experimental tests carried out on the proposed system assessed the accuracy of the evaluated frequency spectrum, resulting in an amplitude error within <inline-formula><math display="inline"><semantics><mrow><mo>±</mo><mn>0.6</mn><mo>%</mo></mrow></semantics></math></inline-formula>, as well as the fault detection capability in the presence of environmental acoustic noise.https://www.mdpi.com/2076-3417/10/16/5645rolling bearingscondition monitoringreliabilityfault detectionwireless nodeacoustic emissions |
| spellingShingle | Erica Raviola Franco Fiori A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling Bearings Applied Sciences rolling bearings condition monitoring reliability fault detection wireless node acoustic emissions |
| title | A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling Bearings |
| title_full | A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling Bearings |
| title_fullStr | A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling Bearings |
| title_full_unstemmed | A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling Bearings |
| title_short | A Low-Cost, Small-Size, and Bluetooth-Connected Module to Detect Faults in Rolling Bearings |
| title_sort | low cost small size and bluetooth connected module to detect faults in rolling bearings |
| topic | rolling bearings condition monitoring reliability fault detection wireless node acoustic emissions |
| url | https://www.mdpi.com/2076-3417/10/16/5645 |
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