This work evaluates the performance of compression algorithms based on Discrete Cosine Transform when used to encode sounding rockets' vibration signals. Different compression methods that use the three-step strategy (transform, quantization, and entropy encoder) are presented. The performances are evaluated using the relationship between the compression rate and distortion, the latter being measured using the Peak Signal-to-Noise Ratio (PSNR) and the difference observed in the Power Spectral Density (PSD). The focus of the work is on vibration signals from rocket launches conducted by the Institute of Aeronautics and Space of the Brazilian Air Force. The obtained results present a great variation for the vibration data in the test set. Compressors operating with PSNR close to 50 dB can achieve very high compression rates (over 100) for low power signals. However, if the vibration signal strength increases significantly, the compression rate can be much lower. For the worst case in the test set (signal with the highest power), the work shows that the best proposed method needs a rate of 9.8 to achieve a PSNR of 48.2 dB. When compared to the performance of recently published DCT-based compression algorithms, the proposed technique shows significant improvements. Given a PSNR around 50 dB, for signal with moderate power, improvements above 100% are observed in compression rate.
Ao meu orientador Prof. Dr. Walmir Freitas e ao Dr. Diogo Salles, minha gratidão pela amizade, profissionalismo e dedicação. Foram cruciais no incentivo e motivação para realização de trabalho.Agradeço também ao Prof. Dr. Luiz Carlos Pereira da Silva, sua dedicação ao ensino e à pesquisa despertou meu interesse pela área de sistemas de energia elétrica.Agradeço também a Profa. Dr. Fernanda Trindade e ao Tiago R. Ricciardi, toda a colaboração e auxílio foram de grande valor.Aos meus pais, cujo amor sempre me impulsionou a realizar meus sonhos. xiv xv
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