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Zhao Shunan,He Lin,Wu Xin,Xu Guowen,Xie Junlong,Cai Shanshan 대한설비공학회 2023 International Journal of Air-Conditioning and Refr Vol.31 No.1
Evaluating the thermal environment and thermal comfort in an air-conditioned room is an essential for estimating the performance of air-conditioning systems. However, multiple component structures and control-related parameters often lead to a long test cycle and large number of tests, significantly affecting the testing efficiency and speed. To address these problems, in this study, a data-mining method was proposed to predict and evaluate the thermal environment of an air-conditioned room. Owing to the limited amount of experimental data, the sample data were expanded by the simulation data of a collaborative platform between the air-conditioning system and air-conditioned room. Data-mining models, including the support vector regression (SVR), backpropagation (BP), and multiple linear regression (MLR) models, were developed and achieved good accuracy in evaluating the thermal environment by considering air-conditioning systems with various structures and control parameters. In the multiple-input single-output evaluation method, the prediction accuracy of the SVR model was higher than those of the BP and MLR models with respect to the vertical air temperature difference, temperature uniformity, temperature drop rate, and draft rate, while the result was the opposite in terms of the predicted mean vote indices. In the multiple-input multiple-output evaluation method, there was a decline in prediction accuracy and an increase in efficiency prediction compared with multiple-input single-output evaluation.
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Ni, Zhiyu,Wu, Zhigang,Wu, Shunan The Korean Society for Aeronautical and Space Scie 2016 International Journal of Aeronautical and Space Sc Vol.17 No.2
In existing identification methods for on-orbit spacecraft, such as eigensystem realization algorithm (ERA) and subspace method identification (SMI), singular value decomposition (SVD) is used frequently to estimate the modal parameters. However, these identification methods are often used to process the linear time-invariant system, and there is a lower computation efficiency using the SVD when the system order of spacecraft is high. In this study, to improve the computational efficiency in identifying time-varying modal parameters of large spacecraft, a faster recursive algorithm called fast approximated power iteration (FAPI) is employed. This approach avoids the SVD and can be provided as an alternative spacecraft identification method, and the latest modal parameters obtained can be applied for updating the controller parameters timely (e.g. the self-adaptive control problem). In numerical simulations, two large flexible spacecraft models, the Engineering Test Satellite-VIII (ETS-VIII) and Soil Moisture Active/Passive (SMAP) satellite, are established. The identification results show that this recursive algorithm can obtain the time-varying modal parameters, and the computation time is reduced significantly.
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Zhiyu Ni,Zhigang Wu,Shunan Wu 한국항공우주학회 2016 International Journal of Aeronautical and Space Sc Vol.17 No.2
In existing identification methods for on-orbit spacecraft, such as eigensystem realization algorithm (ERA) and subspace method identification (SMI), singular value decomposition (SVD) is used frequently to estimate the modal parameters. However, these identification methods are often used to process the linear time-invariant system, and there is a lower computation efficiency using the SVD when the system order of spacecraft is high. In this study, to improve the computational efficiency in identifying time-varying modal parameters of large spacecraft, a faster recursive algorithm called fast approximated power iteration (FAPI) is employed. This approach avoids the SVD and can be provided as an alternative spacecraft identification method, and the latest modal parameters obtained can be applied for updating the controller parameters timely (e.g. the self-adaptive control problem). In numerical simulations, two large flexible spacecraft models, the Engineering Test Satellite-VIII (ETS-VIII) and Soil Moisture Active/Passive (SMAP) satellite, are established. The identification results show that this recursive algorithm can obtain the time-varying modal parameters, and the computation time is reduced significantly.
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