Abstract
A major equipment is generally an extraordinarily large and complex machine containing lots of parameters, understanding and assessment the performance of a major equipment is a great challenge as each of these parameters has uncertainty. In this work, a metamodel-based global sensitivity analysis (MBGSA) method is proposed for understanding the influence of the parameters on the different outputs. The MBGSA consists of global sensitivity analysis (GSA) method to identify the impact of each parameters on each of the outputs, moderate-fidelity computational models to mimic the physical model, and metamodeling technique that constructs the mapping between input and output with a limited sampling data. An example on applying the MBGSA in the dynamics analysis of a tunnel boring machine’s driving system is presented, where hierarchical dynamics model, radial basis function (RBF) metamodel and Sobol’s GSA are bonded together to achieve the aim. The results indicate that the proposed MBGSA is available and efficient for the analysis of TBM and thus can be of great help for other large and complex major equipments at the early stage of design.
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Ding, X., Sun, W., Wang, L., Huo, J., Sun, Q., Song, X. (2015). Sensitivity Analysis of Major Equipment Based on Radial Basis Function Metamodel. In: Liu, H., Kubota, N., Zhu, X., Dillmann, R. (eds) Intelligent Robotics and Applications. Lecture Notes in Computer Science(), vol 9246. Springer, Cham. https://doi.org/10.1007/978-3-319-22873-0_42
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DOI: https://doi.org/10.1007/978-3-319-22873-0_42
Publisher Name: Springer, Cham
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