轧机液压AGC系统是轧机板厚控制的核心系统，它在运行过程中不仅产生大量的过程控制数据，而且还采集了海量的状态监测数据，这些数据长期受限于存储空间和数据传输等因素一直难以有效利用。工业互联网的诞生为挖掘这些大数据提供了新平台，为轧机液压AGC系统预测性维护提供了新途径。本项目将工业互联网平台与液压AGC系统相结合，构建液压AGC系统的CPS系统架构，在工业云平台上设计大数据云存储和数据管理布局模式，开发大数据管理算法和通用分析算法与轧机液压AGC系统物理机理相融合的专用分析算法，构建轧机液压AGC系统数字孪生体实现大数据可视化分析，并创建轧机液压AGC系统的预测性维护的测试床试验平台对理论进行验证。本研究成果不仅可以为挖掘轧机液压AGC系统的大数据提供关键技术，为设备预测性维护奠定理论基础，而且还可以为我国“互联网+液压”提供范例。此外，该项目对推动我国钢铁业转型升级和智能制造具有重要作用。

Hydraulic automatic gauge control (AGC) system is a core control system to guarantee the accuracy of the plate thickness of rolling mill. It not only produces a lot of process control data in the operation process, but also collects a huge amount of condition monitoring data. For a long time, these data are restricted by storage space, data transmission and other factors, so they haven't been used effectively. The birth of industrial Internet provides a new platform for mining these big data and provides a new way for the predictive maintenance of the hydraulic AGC system of rolling mill. This project combines the industrial Internet platform with the hydraulic AGC system. Build the CPS system architecture of hydraulic AGC system. Design big data cloud storage and data layout patterns on cloud platform. Develop big data management algorithm, general analysis algorithm and a special analysis algorithm which is combined with the physical mechanism of the hydraulic AGC system of rolling mill. Develop a digital twin virtual simulation system for visualization of big data analytics, and create a test bed experimental platform for the predictive maintenance of mill hydraulic AGC systems to validate the theory. The results of this research can not only for mining the rolling mill hydraulic AGC system of big data to provide key technology and lay a theoretical foundation for predictive maintenance, but also provide an example for " Internet+hydraulic" in our country. In addition, the research project will plays an important role in the transformation and upgrading of China's steel industry and intelligent manufacturing.