{"title":"A multi-sensor information fusion monitoring system for photovoltaic power generation","authors":"Xiao Wang, Bo Zhao, Shengxian Cao, Siyuan Fan","doi":"10.1109/cvidliccea56201.2022.9824758","DOIUrl":null,"url":null,"abstract":"In this paper, a novel multi-sensor information fusion (MSIF) monitoring system of photovoltaic (PV) power station is proposed, which can solve the difficulty in determining the dust accumulation degree of PV power station operation and maintenance personnel to the panels. According to the real-time monitoring data, a relationship model can be established to reflect the effect of dust accumulation on PV panels operating state. Meanwhile, a dust detection and classification method based on convolutional neural network (CNN) is also given to analyze the visible-light images and operation data. Because of identifying rapidly the images of the dust-covered PV panels, the classification result can be used as a guideline for cleaning the dust accumulation of PV panels. Finally, the experimental results show the effectiveness of the proposed monitoring system.","PeriodicalId":23649,"journal":{"name":"Vision","volume":"45 1","pages":"955-959"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/cvidliccea56201.2022.9824758","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a novel multi-sensor information fusion (MSIF) monitoring system of photovoltaic (PV) power station is proposed, which can solve the difficulty in determining the dust accumulation degree of PV power station operation and maintenance personnel to the panels. According to the real-time monitoring data, a relationship model can be established to reflect the effect of dust accumulation on PV panels operating state. Meanwhile, a dust detection and classification method based on convolutional neural network (CNN) is also given to analyze the visible-light images and operation data. Because of identifying rapidly the images of the dust-covered PV panels, the classification result can be used as a guideline for cleaning the dust accumulation of PV panels. Finally, the experimental results show the effectiveness of the proposed monitoring system.