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Articles by Gong Li
Total Records ( 4 ) for Gong Li
  Gong Li and Jing Shi
  Wind speed forecasting is critical for wind energy conversion systems since it greatly influences the issues such as the scheduling of a power system, and the dynamic control of the wind turbine. In this paper, we present a comprehensive comparison study on the application of different artificial neural networks in 1-h-ahead wind speed forecasting. Three types of typical neural networks, namely, adaptive linear element, back propagation, and radial basis function, are investigated. The wind data used are the hourly mean wind speed collected at two observation sites in North Dakota. The performance is evaluated based on three metrics, namely, mean absolute error, root mean square error, and mean absolute percentage error. The results show that even for the same wind dataset, no single neural network model outperforms others universally in terms of all evaluation metrics. Moreover, the selection of the type of neural networks for best performance is also dependent upon the data sources. Among the optimal models obtained, the relative difference in terms of one particular evaluation metric can be as much as 20%. This indicates the need of generating a single robust and reliable forecast by applying a post-processing method.
  Gong Li and YAN Songhong
  The railway operating tunnel security evaluation is the chief problem in the tunnel operation and management. There are many factors affect the railway tunnel security. And there are great harms in the safety incidents. So the heart of ensuring operational safety is to establish effective security risk evaluation model in the security monitoring. The fuzzy mathematical method was used in this study to estimate the railway operating tunnel security evaluation index and construct the evaluation index system. On the basis of the main factors that affect the railway operating tunnel security, this study classified the main parameters according to the corresponding indexes. Furthermore, it proposed the railway operating tunnel security evaluation model and method which combined the qualitative and quantitative analysis together. The study considered the security evaluation indexes weight by the expert evolution method. Then it gave the security level standard for the evaluation result. Compared with the existing railway security evaluation method, this fuzzy comprehensive evaluation model can better reflect the actual situation to the railway tunnel. And the model has high reliability and accuracy.
  Gong Li and Yan Song-Hong
  To ensure the safety in the high-speed railway tunnel whole process, from planning, design, construction, operating to abandon, this study constructed the railway tunnel security evaluation system and method. The existing evaluation systems simply evaluate one certain phase of the railway tunnel life, without the whole process of the railway tunnel security. This paper considered the railway tunnel full life cycle security. It evaluated the security from the planning phase, design phase, construction phase, operating phase to abandon phase. The aim is to ensuring the whole process security, which are the designing security, construction security and operating security. This study adopted the Fuzzy Evaluation Method to establish the Railway Full Life Cycle Security system. The evaluation system has 31-layer factors, 192-layer factors, 683-layer factors. Applying the mathematical modelon the practical engineering, the results matched with the actual situation. The research provides a theoretical basis on the railway tunnel whole process safety.
  Jing Shi , Xiangjun Xu , Jialai Wang and Gong Li
  In this paper, a new approach for efficient damage detection in engineering structures is introduced. The key concept is to use the mature computer vision technology to capture the static deformation profile of a structure, and then employ profile analysis methods to detect the locations of the damages. By combining with wireless communication techniques, the proposed approach can provide an effective and economical solution for remote monitoring of structure health. Moreover, a preliminary experiment is conducted to verify the proposed concept. A commercial computer vision camera is used to capture the static deformation profiles of cracked cantilever beams under loading. The profiles are then processed to reveal the existence and location of the irregularities on the deformation profiles by applying fractal dimension, wavelet transform and roughness methods, respectively. The proposed concept is validated on both one-crack and two-crack cantilever beam-type specimens. It is also shown that all three methods can produce satisfactory results based on the profiles provided by the vision camera. In addition, the profile quality is the determining factor for the noise level in resultant detection signal.
 
 
 
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