Research On Intelligent Equipment Management System Based On Sensor Network

In May 2015,?Made in China 2025?was officially released.In this strategic planning,"promoting the in-depth integration of informatization and industrialization" is regarded as one of the nine strategic tasks and priorities.It is proposed to accelerate the integration of new-generation information technology and manufacturing technology.Intelligent manufacturing is the main direction of integration of two-dimensional depth.Promoting intelligent manufacturing processes.Pilot construction of smart factory/digital workshop in the focus areas.This paper combines the actual production and equipment status of Zhong Tian Advanced Materials(ZTAM)co.,LTD.From an intelligent point of view,the EtherCAT fieldbus is used to construct the sensor network.collect the data in the production process.and connect the equipment in the factory with the server through the Modbus-TCP protocol.The intelligent equipment operation management system is studied by analyzing and applying the support vector machine method.This thesis mainly has the following three contributions:1?Introduce the sensor network construction based on EtherCAT fieldbus,classify and organize the existing equipment signals.The problems to be solved in sensor network construction are analyzed.And then explain how to optimize the existing equipment I/O and import it into the EtherCAT network.The establishment of sensor network is realized.2?Using the Modbus-TCP communication method.The PLC memory and external data address were mapped to the corresponding modbus-tcp address.and finally transmitted to the corresponding server through the TCP/IP protocol.This paper describes how to map the internal PLC address to the corresponding Modbus-TCP address and perform the corresponding program encapsulation.After completing data collection on the gateway side,the gateway is used as a node to transmit data to the server through the industrial Internet of Things.3?As an important part of intelligent equipment management system,Equipment performance status evaluation is an important content.Support vector machines(SVM)are used to predict and evaluate the equipment operation status,logic regression,support vector machine.Through the rotor vibration test,the equipment state trend is predicted.4?Introduce the support vector machine method according to time series,from time series framework to SVR prediction,and finally form SVM spare parts management model.The data of graphite spare parts inventory management of ZTAM co.,LTD was analyzed.The normalization algorithm is adopted,The final forecast is for graphite demand in 2017.According to the actual needs of 2017,the final conclusion is drawn.