Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment
To reduce the difficulty of acquiring and transmitting data in mining hoist fault diagnosis systems and to mitigate the low efficiency and unreasonable reasoning process problems, a fault diagnosis method for mine hoisting equipment based on the Internet of Things (IoT) is proposed in this study. Th...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-06-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/6/1920 |
| _version_ | 1817996716298731520 |
|---|---|
| author | Juanli Li Jiacheng Xie Zhaojian Yang Junjie Li |
| author_facet | Juanli Li Jiacheng Xie Zhaojian Yang Junjie Li |
| author_sort | Juanli Li |
| collection | DOAJ |
| description | To reduce the difficulty of acquiring and transmitting data in mining hoist fault diagnosis systems and to mitigate the low efficiency and unreasonable reasoning process problems, a fault diagnosis method for mine hoisting equipment based on the Internet of Things (IoT) is proposed in this study. The IoT requires three basic architectural layers: a perception layer, network layer, and application layer. In the perception layer, we designed a collaborative acquisition system based on the ZigBee short distance wireless communication technology for key components of the mine hoisting equipment. Real-time data acquisition was achieved, and a network layer was created by using long-distance wireless General Packet Radio Service (GPRS) transmission. The transmission and reception platforms for remote data transmission were able to transmit data in real time. A fault diagnosis reasoning method is proposed based on the improved Dezert-Smarandache Theory (DSmT) evidence theory, and fault diagnosis reasoning is performed. Based on interactive technology, a humanized and visualized fault diagnosis platform is created in the application layer. The method is then verified. A fault diagnosis test of the mine hoisting mechanism shows that the proposed diagnosis method obtains complete diagnostic data, and the diagnosis results have high accuracy and reliability. |
| first_indexed | 2024-04-14T02:26:20Z |
| format | Article |
| id | doaj.art-383e336ea0c6428796f52bdf3a92880b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-14T02:26:20Z |
| publishDate | 2018-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-383e336ea0c6428796f52bdf3a92880b2022-12-22T02:17:52ZengMDPI AGSensors1424-82202018-06-01186192010.3390/s18061920s18061920Fault Diagnosis Method for a Mine Hoist in the Internet of Things EnvironmentJuanli Li0Jiacheng Xie1Zhaojian Yang2Junjie Li3Shanxi Key Laboratory of Fully Mechanized Coal Mining Equipment, College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024, ChinaShanxi Key Laboratory of Fully Mechanized Coal Mining Equipment, College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024, ChinaShanxi Key Laboratory of Fully Mechanized Coal Mining Equipment, College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024, ChinaShanxi Key Laboratory of Fully Mechanized Coal Mining Equipment, College of Mechanical Engineering, Taiyuan University of Technology, Taiyuan 030024, ChinaTo reduce the difficulty of acquiring and transmitting data in mining hoist fault diagnosis systems and to mitigate the low efficiency and unreasonable reasoning process problems, a fault diagnosis method for mine hoisting equipment based on the Internet of Things (IoT) is proposed in this study. The IoT requires three basic architectural layers: a perception layer, network layer, and application layer. In the perception layer, we designed a collaborative acquisition system based on the ZigBee short distance wireless communication technology for key components of the mine hoisting equipment. Real-time data acquisition was achieved, and a network layer was created by using long-distance wireless General Packet Radio Service (GPRS) transmission. The transmission and reception platforms for remote data transmission were able to transmit data in real time. A fault diagnosis reasoning method is proposed based on the improved Dezert-Smarandache Theory (DSmT) evidence theory, and fault diagnosis reasoning is performed. Based on interactive technology, a humanized and visualized fault diagnosis platform is created in the application layer. The method is then verified. A fault diagnosis test of the mine hoisting mechanism shows that the proposed diagnosis method obtains complete diagnostic data, and the diagnosis results have high accuracy and reliability.http://www.mdpi.com/1424-8220/18/6/1920Internet of Things (IoT)mine hoistfault diagnosisZigBeeDezert-Smarandache Theory (DSmT) |
| spellingShingle | Juanli Li Jiacheng Xie Zhaojian Yang Junjie Li Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment Sensors Internet of Things (IoT) mine hoist fault diagnosis ZigBee Dezert-Smarandache Theory (DSmT) |
| title | Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment |
| title_full | Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment |
| title_fullStr | Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment |
| title_full_unstemmed | Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment |
| title_short | Fault Diagnosis Method for a Mine Hoist in the Internet of Things Environment |
| title_sort | fault diagnosis method for a mine hoist in the internet of things environment |
| topic | Internet of Things (IoT) mine hoist fault diagnosis ZigBee Dezert-Smarandache Theory (DSmT) |
| url | http://www.mdpi.com/1424-8220/18/6/1920 |
| work_keys_str_mv | AT juanlili faultdiagnosismethodforaminehoistintheinternetofthingsenvironment AT jiachengxie faultdiagnosismethodforaminehoistintheinternetofthingsenvironment AT zhaojianyang faultdiagnosismethodforaminehoistintheinternetofthingsenvironment AT junjieli faultdiagnosismethodforaminehoistintheinternetofthingsenvironment |