Design of Motor Intelligent Monitoring and Fault Diagnosis System Based on LoRa
| Autor: | Gang Zhang, Cheng L. Lu, Jie Fang, Bin Wang, Jun H. Cheng |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry Real-time computing Topology (electrical circuits) Condensed Matter Physics Fault (power engineering) Electronic Optical and Magnetic Materials Transmission (telecommunications) Data redundancy Control theory Wireless Electrical and Electronic Engineering business Wireless sensor network Data transmission |
| Zdroj: | IEEE Transactions on Applied Superconductivity. 31:1-4 |
| ISSN: | 2378-7074 1051-8223 |
| DOI: | 10.1109/tasc.2021.3091094 |
| Popis: | Aiming at the characteristics of low intelligence of the current motor cluster and superconducting electrical equipment monitoring system, high construction and maintenance costs of wired transmission methods. The wireless sensor network constructed by LoRa technology is applied to the motor operating state monitoring system, while the data transmission efficiency of the system is improved by optimizing the topology of the wireless sensor network (WSN) and processing the transmission data redundancy. The system uses STM32F407ZET6 as the main controller, builds an offline operating state library, and uses HMM model for training to achieve real-time acquisition and fault diagnosis of the status information of the cluster system motor's voltage, current, speed, and position. Practical application shows that the system is running well and can realize the acquisition of the motor's running status and fault diagnosis. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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