论文部分内容阅读
探索和尝试以轴心轨迹为依据 ,以全等度、相似度和扩散度三个特征参数为输入的神经网络捕获设备故障信号模型 ,可大大提高故障症兆提取的效率和质量 ,并以大型化工装置透平压缩机组的监测系统为例做了应用说明
To explore and try to capture the fault signal model of equipment based on the axis locus and the neural network with three full parameters of full degree, similarity and degree of diffusion as the input can greatly improve the efficiency and quality of fault symptom extraction, Chemical plant turbine compressor monitoring system as an example to do the application instructions