Super-resolution Reconstruction of Night-light Images Based on Improved SRCNN

Wu, Tao; Song, Xinning; Gan, Tian; Zeng, Bowen; Chen, Jiaqi

doi:10.1109/ctisc54888.2022.9849813

Cited by 3 publications

(1 citation statement)

References 10 publications

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“…Since the goal of the CNN here is to generate high-frequency signals rather than classification, it is necessary to design a neural network that can capture the timing relationships of the data and satisfy the properties of the super-resolution metrology problem. Therefore, in this paper, based on the super-resolution convolutional neural network (SRCNN) proposed in the research of image super-resolution [22], its network structure and parameters are improved to meet the requirements above. Additionally, the computational inefficiency of the traditional CNN outputting one-dimensional sequential data is solved by adopting a fully convolutional design and parallel processing method.…”

Section: Super Resolution Measurementmentioning

confidence: 99%

An Intelligent Location Method for Power System Oscillation Sources Based on a Digital Twin

Yang,

Wang,

Gao

et al. 2023

Electronics

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Aiming at the difficult problem of broadband oscillation localization in power systems, the intelligent localization method of an oscillation source based on a digital twin is proposed, and the oscillation source localization system is thus constructed. Firstly, a digital twin-based oscillation source localization method and its system architecture are proposed. Furthermore, an intelligent positioning method of the oscillation source, based on data-driven and mechanism fusion, is proposed. It includes three steps: oscillation signal preprocessing, oscillation modal analysis and oscillation source localization. For the oscillation signal preprocessing, the generative adversarial imputation network is used to repair the missing samples, and the super-resolution technique is used to realize the super-resolution measurement of broadband oscillation. In the oscillation modal analysis, the spectrum of the oscillation signal is extracted using the fast Fourier transform. To accurately locate the oscillation source, branch potential energy is used as the input to the data-driven model, such as LSTM and CNN. Finally, an oscillation source localization system is developed based on the digital twin workshop CloudPSS-XStudio, which can locate the oscillation source quickly and accurately.

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Section: Super Resolution Measurementmentioning

confidence: 99%

An Intelligent Location Method for Power System Oscillation Sources Based on a Digital Twin

Yang,

Wang,

Gao

et al. 2023

Electronics

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Design and Evaluation of a Vehicle Detection System in Low Light Conditions

Bidare,

Siri,

Param

et al. 2023

2023 10th International Conference on Signal Processing and Integrated Networks (SPIN)

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Intelligent Location Method and System for Power System Oscillation Sources Based on Digital Twin

Yang¹,

Wang²,

Gao³

et al. 2023

Preprint

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Aiming at the difficult problem of broadband oscillation localization in power systems, the intel-ligent localization method of oscillation source based on the digital twin is proposed and the os-cillation source localization system based on the digital twin is constructed. Firstly, a digital twin-based oscillation source localization method and system architecture are proposed. Fur-thermore, an intelligent positioning method of oscillation source based on data-driven and mechanism fusion is proposed. It includes three steps: oscillation signal preprocessing, oscillation modal analysis and oscillation source localization. For the oscillation signal preprocessing, the generative adversarial imputation network is used to repair the missing samples, and the su-per-resolution technique is used to realize the super-resolution measurement of broadband os-cillation. In the oscillation modal analysis, the spectrum of the oscillation signal is extracted using the fast Fourier transform. To accurately locate the oscillation source, the branch potential energy is used as input to the data-driven model, such as LSTM and CNN. Finally, an oscillation source localization system is developed based on the digital twin workshop CloudPSS-XStudio, which can locate the oscillation source quickly and accurately.

show abstract

Super-resolution Reconstruction of Night-light Images Based on Improved SRCNN

Cited by 3 publications

References 10 publications

An Intelligent Location Method for Power System Oscillation Sources Based on a Digital Twin

An Intelligent Location Method for Power System Oscillation Sources Based on a Digital Twin

Design and Evaluation of a Vehicle Detection System in Low Light Conditions

Intelligent Location Method and System for Power System Oscillation Sources Based on Digital Twin

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