Research On Health Management Technology In Equipment System

In recent years,along with the upgrading of equipment automation and equipment reliability and maintainability indicators.It was time consuming and laborious to use the method of regular maintenance of equipment,especially for equipment that was placed in the wild and was left unattended for a long period of time.Therefore,health management technology has begun to be applied to some complex equipment systems,thereby changing the waste of resources and manpower in the traditional way,so establishing a new model of " Condition Based Maintenance ".Because the health management thoughts started late in the application of equipment systems,the research on related theories and technologies has broad prospects.The core of health management technology includes data monitoring,health diagnosis and prediction.The photovoltaic industry is an important part of the nation's new energy strategy.This paper focuses on the health management of photovoltaic power generation equipment systems and conducts the following research work:(1)With OSA-CBM as a reference,the workflow,functional modules,and key technologies of the health management system were systematically analyzed and studied.(2)For the actual photovoltaic equipment system,a health state prediction model based on LS-SVM time series was constructed,and a model hyperparameter optimization method suitable for photovoltaic equipment was proposed.And through the combination of normal,slight anomalies,severe abnormalities and other state characteristics of the experimental verification.Realize the health diagnosis and prediction of PV equipment systems.(3)In this paper,an intelligent algorithm model based on BP neural network is proposed.Through the forward propagation process of BP neural network model and the back propagation process of error,the optimal network structure and hyperparameter are searched.The BP neural network model was used to diagnose and predict the future status of the photovoltaic equipment system,and the reliability was verified through experiments.(4)According to the actual health management needs of the actual photovoltaic equipment system,a health management system for photovoltaic equipment was developed based on the Qt5.9 development platform and the My SQL database.It has been completed remote data monitoring,data storage and query,health diagnosis,health prediction,remote control and user interface and other functions.This paper systematically analyzes the health management technology and its framework in the equipment system,and focuses on the more advanced health prediction technology to do in-depth research.The effectiveness and feasibility of the proposed method are verified by experiments.