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  • Open Access

    ARTICLE

    Research on Asymmetric Fault Location of Wind Farm Collection System Based on Compressed Sensing

    Huanan Yu1, Gang Han1,*, Hansong Luo2, He Wang1

    Energy Engineering, Vol.120, No.9, pp. 2029-2057, 2023, DOI:10.32604/ee.2023.028365

    Abstract Aiming at the problem that most of the cables in the power collection system of offshore wind farms are buried deep in the seabed, which makes it difficult to detect faults, this paper proposes a two-step fault location method based on compressed sensing and ranging equation. The first step is to determine the fault zone through compressed sensing, and improve the data measurement, dictionary design and algorithm reconstruction: Firstly, the phase-locked loop trigonometric function method is used to suppress the spike phenomenon when extracting the fault voltage, so that the extracted voltage value will not have a large error due… More >

  • Open Access

    ARTICLE

    A New Multi Chaos-Based Compression Sensing Image Encryption

    Fadia Ali Khan1, Jameel Ahmed1, Suliman A. Alsuhibany2,*

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 437-453, 2023, DOI:10.32604/cmc.2023.032236

    Abstract The advancements in technology have substantially grown the size of image data. Traditional image encryption algorithms have limited capabilities to deal with the emerging challenges in big data, including compression and noise toleration. An image encryption method that is based on chaotic maps and orthogonal matrix is proposed in this study. The proposed scheme is built on the intriguing characteristics of an orthogonal matrix. Gram Schmidt disperses the values of pixels in a plaintext image by generating a random orthogonal matrix using logistic chaotic map. Following the diffusion process, a block-wise random permutation of the data is performed using multi-chaos.… More >

  • Open Access

    ARTICLE

    Three-Stages Hyperspectral Image Compression Sensing with Band Selection

    Jingbo Zhang, Yanjun Zhang, Xingjuan Cai*, Liping Xie*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 293-316, 2023, DOI:10.32604/cmes.2022.020426

    Abstract Compressed sensing (CS), as an efficient data transmission method, has achieved great success in the field of data transmission such as image, video and text. It can robustly recover signals from fewer Measurements, effectively alleviating the bandwidth pressure during data transmission. However, CS has many shortcomings in the transmission of hyperspectral image (HSI) data. This work aims to consider the application of CS in the transmission of hyperspectral image (HSI) data, and provides a feasible research scheme for CS of HSI data. HSI has rich spectral information and spatial information in bands, which can reflect the physical properties of the… More >

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