| In industrial electronic systems,PHM can predict the time of breakdown,the Remaining Useful Life(URL)of the whole system in advance.Jay Lee,a professor at University of Cincinnati,has presented a set of data driven research route for many years during the study of PHM.The research route is data analysis modeling,data visualization and data platform.In this paper,according to this research route,the degradation state of industrial capacitor is studied,and the visualization system is designed:1.Data analysis modeling.Built on the EIS information obtained from the industry capacitor charging cycle,the hidden variables that change with the degradation of the capacitance are searched.According to these hidden variables,digitized modeling of the nourishing state of the capacitor is arranged.Finally,took into account these digitized state,the model of degradation forecasting of capacitance based on ARMA is established.2.Data visualization system.The capacitance degradation model is visualized and the visualization system is to be integrated into a state management system for the professional equipment of non-technical management personnel.This section focus on the intuitive and interactive interface,designing and completing the visualization system for more equipments.3.Data platform.The server cluster is designed for the operation characteristics of the PHM system.From the idea of redundancy,we design the cluster network based on the Web server and the database server,and integrate off-line large data processing spark platform,for the computation of the large numbers.According to these schemes,the industrial capacitance PHM system,which is suitable for non-technical industrial device managers,provides the assistant decision support and knowledge service for the device managers to replace the excessive wastage equipment in time,avoids the downtime loss caused by accidental interruption of the pipeline,and improves the benefit and work of the enterprise. |
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