A remote sensing intelligent extraction method for large-scale photovoltaic power generation facilities

A technology for photovoltaic power generation and extraction methods, which is applied in neural learning methods, instruments, biological neural network models, etc., to achieve rapid automatic extraction and improve extraction efficiency and accuracy.

Active Publication Date: 2022-04-15
自然资源部国土卫星遥感应用中心
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to provide a remote sensing intelligent extraction method for large-scale photovoltaic power generation facilities, thereby solving the aforementioned problems in the prior art

Method used

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  • A remote sensing intelligent extraction method for large-scale photovoltaic power generation facilities
  • A remote sensing intelligent extraction method for large-scale photovoltaic power generation facilities
  • A remote sensing intelligent extraction method for large-scale photovoltaic power generation facilities

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Embodiment 1

[0046] This embodiment provides a remote sensing intelligent extraction method for large-scale photovoltaic power generation facilities, such as figure 1 shown, including the following steps:

[0047] S1. Using pytorch as the development framework, construct the extraction network PVSNet based on the semantic segmentation model D-LinkNet. PVSNet is designed to receive 3×512×512 image samples as input, and the encoder (Encoder) is based on the pre-trained ResNet34 network, using five The downsampling layer extracts deep image features. The middle expansion layer (Dilate-block) uses 4 layers of parallel cascaded hole convolution to expand the acceptance range, integrate multi-scale features, and preserve spatial information. The decoder (Decoder) uses a four-layer transposed convolution unit to upsample the feature map, and uses skip connections to introduce the underlying spatial position information to restore the details in the original image. Finally, Softmax is used to ob...

Embodiment 2

[0067]In this embodiment, taking high-resolution image data in some areas of Shanxi Province as an example, a specific implementation process of a remote sensing intelligent extraction method for photovoltaic power generation facilities is given, including the following steps:

[0068] Step 1. Use pytorch as the development framework, and build the extraction network PVSNet based on the semantic segmentation model D-LinkNet. In this program, PVSNet is designed to receive 3×512×512 image samples as input, and the encoder (Encoder) is based on the pre-trained ResNet34 network. Five down-sampling layers are used to extract deep image features; the middle expansion layer (Dilate-block) uses 4 layers of parallel cascaded hole convolution to expand the acceptance range, integrate multi-scale features, and preserve spatial information; Decoder (Decoder) The four-layer transposed convolution unit is used to upsample the feature map, and the skip connection is used to introduce the unde...

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Abstract

The invention discloses a remote sensing intelligent extraction method for large-scale photovoltaic power generation facilities, which relates to the technical field of remote sensing image recognition; A large number of image samples of photovoltaic power generation facilities, including positive samples and negative samples, can be used to train the constructed automatic extraction network model to learn the deep image features of photovoltaic power generation facilities. After repeated iterative tests, the optimal training model can be obtained to realize remote sensing image data Rapid and automatic extraction of large-scale photovoltaic power generation facilities, thereby improving the extraction efficiency and accuracy of photovoltaic facilities, and providing guarantee for subsequent application requirements.

Description

technical field [0001] The invention relates to the technical field of remote sensing image data extraction, in particular to a remote sensing intelligent extraction method for large-scale photovoltaic power generation facilities. Background technique [0002] At present, solar photovoltaic power generation technology, as one of the emerging renewable clean energy sources, has great potential for development. In recent years, the construction of photovoltaic power plants in my country has developed rapidly, and timely acquisition of the construction scope and changes of photovoltaic power plants is of great significance to government information management, social and economic benefits, and rational use of resources. At present, the time series of high-resolution remote sensing data is updated quickly and covers a wide range. Using high-resolution remote sensing data segmentation to quickly extract the spatial distribution and development of photovoltaic power generation fac...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/10G06V10/764G06V10/26G06V10/44G06V10/82G06N3/04G06N3/08
CPCG06N3/084G06N3/045G06F18/2415
Inventor 王光辉王咏昕郑利娟张涛王更张伟王界彭瑶瑶
Owner 自然资源部国土卫星遥感应用中心
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