摘要
针对直流接地故障检测系统检测结果误差大的问题,提出了基于MapReduce并行处理的机电特种设备故障诊断系统设计;根据系统总体架构,将硬件结构分为故障检测显示单元和数据处理及传输单元;整流电流,使用二极管整流装置设计集流故障检测指示电路;采用多层差分电路获取脉冲信号,以低电平电压位置的故障检测器作为检测点,设计电流突变检测模块;使用DH08型号开关状态检测模块,具有8路交流输入,由此检测设备断电故障;选配6AU1410-0AB00-0AA0型西门子报警模块,对故障点进行报警处理;设计MapReduce执行流程,分析4个MapReduce作业训练过程,计算数据属性特征词在每个故障类中的频率值,由此完成故障诊断;以轴承故障为例,进行实验验证分析;由实验测试结果可知,该系统与实际波形差别较小,其对A相、B相C相电流短路故障诊断的时间点波形变化与实际曲线基本一致,在0A附近波动,说明该方法具有精准检测结果,能够为机电特种设备广泛应用提供设备支持。
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.
作者
王林
姜萌
Wang Lin;Jiang Meng(College of Automation and Information Engineering,Xi'an University of Technology,Xi'an 710048,China)
出处
《计算机测量与控制》
2021年第2期5-9,共5页
Computer Measurement &Control
基金
陕西省科学技术厅重点研发计划(2017ZDCXL-GY-05-03)。
