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.

中文翻译：

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基于LoRa的电机智能监测与故障诊断系统设计


针对当前电机集群及超导电气设备监控系统智能化程度低、有线传输方式建设及维护成本高等特点。将LoRa技术构建的无线传感器网络应用于电机运行状态监测系统，同时通过优化无线传感器网络（WSN）的拓扑结构和处理传输数据冗余，提高系统的数据传输效率。系统采用STM32F407ZET6作为主控制器，构建离线运行状态库，并采用HMM模型进行训练，实现集群系统电机电压、电流、转速、位置等状态信息的实时采集和故障诊断。实际应用表明，系统运行良好，能够实现电机运行状态的采集和故障诊断。