液压精冲机工况能耗智能云端监测平台研究

Research on intelligent cloud working condition and energy consumption monitoring platform for hydraulic fine blanking machine

精冲机液压系统元部件数量众多,能量损耗特性复杂,一直缺少低成本高性能的监测方法。为解决该问题,提出了一种基于三相电信号的精冲机液压系统工作状态和能耗智能云端监测平台,将液压系统功能元部件绑定为功能单元,建立了总消耗的功率信号与液压系统工作阶段预测和功能单元能耗之间的深度学习模型,实现了精冲机工况和功能单元能耗的智能识别与预测。以KHF500型液压精冲机为研究对象,基于一维卷积神经网络模型搭建了精冲机智能云端监测平台。结果表明,该平台能高精度识别精冲机的工况类别和预测各功能单元的实时能耗。

The hydraulic system of fine blanking machine has a large number of components and complex energy consumption characteristics,and the low-cost and efficient monitoring methods are always lack.To solve this problem,an intelligent cloud monitoring platform for working condition and energy consumption of the hydraulic fine blanking machine system based on the three term electrical signal was proposed.The functional components of the hydraulic system were bound as the function unit,the deep learning model between the power signal of total consumption and the hydraulic system working stage prediction and the function unit energy consumption was established,and the intelligent identification and prediction of fine blanking machine working condition and energy consumption of function units were realized.Taking the KHF500 hydraulic fine blanking machine as the research object,an intelligent cloud monitoring platform for fine blanking machine was built based on the one-dimensional folding neural network model.The results show that the platform can accurately identify the type of working condition of fine blanking machine and predict the real-time energy consumption of each function unit.