Abstract:Aiming at the large error of the detection result of the DC ground fault detection system, the design of a fault diagnosis system for electromechanical special equipment based on MapReduce parallel processing is proposed. According to the overall architecture of the system, the hardware structure is divided into fault detection display unit and data processing and transmission unit. To rectify the current, use a diode rectifier to design a current-fault detection indicator circuit. The multi-layer differential circuit is used to obtain the pulse signal, and the fault detector at the low-level voltage position is used as the detection point to design the current mutation detection module. Use the DH08 model switch state detection module, with 8-way AC input, thereby detecting power failure of the device. Optional 6AU1410-0AB00-0AA0 Siemens alarm module can be used for alarm processing of the fault point. Design the MapReduce execution process, analyze the training process of the four MapReduce jobs, and calculate the frequency value of the data attribute feature words in each fault class, thus completing the fault diagnosis. Taking bearing failure as an example, an experimental verification analysis is conducted. The experimental results show that the difference between the system and the actual waveform is small, and the waveform change of phase a, phase B and phase C current short circuit fault diagnosis is basically consistent with the actual curve, and fluctuates around 0A, indicating that the method has accurate detection results and can provide equipment support for the wide application of electromechanical special equipment.