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Sensor network optimization of gearbox based on dependence matrix and improved discrete shuffled frog leaping algorithm

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Abstract

This paper reports a new improved discrete shuffled frog leaping algorithm (ID-SFLA) and its application in multi-type sensor network optimization for the condition monitoring of a gearbox. A mathematical model is established to illustrate the sensor network optimization based on fault-sensor dependence matrix. The crossover and mutation operators of genetic algorithm (GA) are introduced into the update strategy of shuffled frog leaping algorithm (SFLA) and a new ID-SFLA is systematically developed. Numerical simulation results show that the ID-SFLA has an excellent global search ability and outstanding convergence performance. The ID-SFLA is applied to the sensor’s optimal selection for a gearbox. In comparison with GA and discrete shuffled frog leaping algorithm (D-SFLA), the proposed ID-SFLA not only poses an effective solving method with swarm intelligent algorithm, but also provides a new quick algorithm and thought for the solution of related integer NP-hard problem.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under Grant 51075070 and 51175001, in part by the Jiangsu Province Research Innovation Program for College Graduates, China under Grant CXZZ_0139, in part by the Anhui Province Foundation for Youth Scholars of Educational Commission, China under Grant 2012SQRL085 and Anhui Province Natural Science Foundation of China under Grant 1308085ME78, and in part by the Macao Science and Technology Development Fund under Grant 052/2014/A1.

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Correspondence to Minping Jia.

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Zhao, Z., Xu, Q. & Jia, M. Sensor network optimization of gearbox based on dependence matrix and improved discrete shuffled frog leaping algorithm. Nat Comput 15, 653–664 (2016). https://doi.org/10.1007/s11047-015-9515-4

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