Design And Development Of Predictive Maintenance System For Marine Hydraulic Equipment Based On Digital Twin

With the in-depth advancement of manufacturing strategies such as "Made in China2025","Industry 4.0","Industrial Internet",and the rapid development of industrial information technology,equipment maintenance are evolving toward intelligence and digitization.As a connecting bridge between the physical world and the digital world,digital twin technology provides technical means for equipment maintenance.This paper will focus on the marine hydraulic equipment,technologies such as Web3 D modeling,prognostics health management,and software system development are used to design and develop predictive maintenance system.The main research contents are as follows:First of all,the technical characteristics of digital twin is considered to analyze the five-layer structure of the physical layer,data layer,model layer,function layer,and application layer,and then the overall architecture of the predictive maintenance system is designed for marine hydraulic equipment.Secondly,by analyzing the technical requirements of the system,the front-end and back-end software architecture of the predictive maintenance system and the database relationship model is designed based on B/S structure.In the meanwhile,based on the Three.js technology,the digital twin model of the hydraulic equipment is designed to implement the digital mapping of physical entities.Thirdly,based on the deployed sensors,the Raspberry Pi is used to collect and transmit the monitoring data,and then perform preprocessing operations such as outlier elimination and noise reduction on the collected data;signal analyzing from multiple dimensions such as time domain and frequency domain to diagnose the health status of hydraulic equipment by using artifical intelligence algorithms.Finally,the predictive maintenance system is developed by configuring the development environment,constructing the front-end and back-end engineering structures,integrating digital twin models and data processing algorithms,and then performing functional,compatibility and performance tests on the system to verify the reliability and availability.The research results show that the system can implement the monitoring,diagnosis and predictive maintenance of the marine hydraulic equipment.