公开(公告)号：US12068717B2

公开(公告)日：2024-08-20

申请号：US17093244

申请日：2020-11-09

Applicant: BEIJING INSTITUTE OF TECHNOLOGY

Inventor： Fang Deng ,  Zelang Liang ,  Ning Ding ,  Xinyu Fan ,  Xin Gao ,  Yeyun Cai ,  Jie Chen

IPC: H02S50/10 ,  G06F18/21 ,  G06F18/2135 ,  G06F18/214 ,  G06F18/241 ,  G06F18/25 ,  G06N3/04 ,  G06N3/084 ,  G06T7/00 ,  G06V10/764 ,  G06V10/774 ,  G06V10/776 ,  G06V10/80 ,  G06V10/82

CPC classification number: H02S50/10 ,  G06F18/2135 ,  G06F18/214 ,  G06F18/217 ,  G06F18/241 ,  G06F18/25 ,  G06N3/04 ,  G06N3/084 ,  G06T7/0002 ,  G06V10/764 ,  G06V10/774 ,  G06V10/776 ,  G06V10/809 ,  G06V10/82 ,  G06T2207/10024 ,  G06T2207/10048 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: A photovoltaic array fault diagnosis method based on composite information is provided. The method includes: collecting and preprocessing composite information data of photovoltaic array working state, including image data and text data; using the image data of photovoltaic array working state to train a pre-established fault classification model of deep convolutional neural network, to thereby obtain an image fault classification model; using the text data of photovoltaic array working state to train a pre-established fault classification model based on a support vector machine, to thereby obtain a text fault classification model; fusing the image fault classification model and the text fault classification model by logistic regression algorithm to obtain a fusion model, and training the fusion model using the composite information data of photovoltaic array working state to thereby obtain the photovoltaic array fault diagnosis model.