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An optimization algorithm for locomotive secondary spring load adjustment based on artificial immune

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Abstract

In order to control the locomotive wheel (axle) load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the performance of the optimization algorithm for locomotive secondary spring load adjustment, especially to solve the lack of control on the output shim quantity. The algorithm was designed into a two-level optimization structure according to the preferences of the problem, and the priori knowledge of the problem was used as the immune dominance. Experiments on various types of locomotives show that owing to the novel algorithm, the shim quantity is cut down by 30%–60% and the calculation time is about 90% less while the secondary spring load distribution is controlled on the same level as before. The application of this optimization algorithm can significantly improve the availability and efficiency of the secondary spring adjustment process.

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Authors and Affiliations

  1. School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China

    Di-fu Pan  (潘迪夫), Meng-ge Wang  (王梦格), Ya-nan Zhu  (朱亚男) & Kun Han  (韩锟)

Authors
  1. Di-fu Pan  (潘迪夫)
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  2. Meng-ge Wang  (王梦格)
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  3. Ya-nan Zhu  (朱亚男)
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  4. Kun Han  (韩锟)
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Corresponding author

Correspondence to Di-fu Pan  (潘迪夫).

Additional information

Foundation item: Project(51305467) supported by the National Natural Science Foundation of China; Project(12JJ4050) supported by the Natural Science Foundation of Hunan Province, China

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Pan, Df., Wang, Mg., Zhu, Yn. et al. An optimization algorithm for locomotive secondary spring load adjustment based on artificial immune. J. Cent. South Univ. 20, 3497–3503 (2013). https://doi.org/10.1007/s11771-013-1874-3

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  • DOI: https://doi.org/10.1007/s11771-013-1874-3

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