Integrative Modeling Method Based on Empirical Mode Decomposition and Least Square Support Vector Machines about Dynamic Weighing of Loaders

Abstract

Abstract: For dynamic weighing about loaders, to obtain a quick and exact measure result synchronously is a complex problem. Based on an existent dynamic weighing method about loaders, an original integrative modeling method for dynamic weighing is given. In the method, empirical mode decomposition is used to be the signal processing method for local pressure signal contaminated; and the least square support vector machines is used to be learning machine for dynamic pressure compensation varying with different lift crane velocity; also the Bayesian evidence framework for selecting and tuning parameters of least square support vector machines; Finally, after doing some simple linear proportional calculation, the weight of load is obtained. In the end, emulation analysis and test results all indicate that by using the above modeling method, measure precision within 1% can be obtained.

Key words: Bayesian evidence framework, Dynamic weighing, Empirical mode decomposition, Integrative modeling method, Least square support vector machines, Loaders

CLC Number:

TH823

WANG Wei;WEI Hongxing;CHEN Diansheng;WANG Tianmiao. Integrative Modeling Method Based on Empirical Mode Decomposition and Least Square Support Vector Machines about Dynamic Weighing of Loaders[J]. , 2008, 44(2): 87-93.

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Integrative Modeling Method Based on Empirical Mode Decomposition and Least Square Support Vector Machines about Dynamic Weighing of Loaders

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