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International Standard Serial Number:
ISSN 1001-4551
Sponsor:
Zhejiang University;
Zhejiang Machinery and Electrical Group
Edited by:
Editorial of Journal of Mechanical & Electrical Engineering
Chief Editor:
ZHAO Qun
Vice Chief Editor:
TANG ren-zhong,
LUO Xiang-yang
Tel:
86-571-87041360,87239525
Fax:
86-571-87239571
Add:
No.9 Gaoguannong,Daxue Road,Hangzhou,China
P.C:
310009
E-mail:
meem_contribute@163.com
Abstract: Aiming at the problem of low accuracy of direct identification of working cycle state of hydraulic excavator, an intelligent identification method of working state of hydraulic excavator based on composite signal and support vector machine (SVM) was proposed. Firstly, the working stages of the hydraulic excavator cycle operation were divided, and the beginning or end waveform of each working stage was taken as the segmented mark, and the segmented mark was extracted from the data of the cycle operation. Then, the data of each extracted segmented marks were preprocessed, and the library for support vector machine(LIBSVM)multiclassification method was used to establish the working state recognition model based on the composite signals of main pump pressure and pilot pressure, and the classification credibility threshold was set. Finally, the intelligent calibration system was introduced to correct the direct identification results and complete the identification of the running state of the excavator. The research results show that, comparing with the main pump pressure identification method, the direct identification accuracy of excavator working state is improved from 54% to 78% by using the composite signal identification method, and the final identification accuracy is above 95%;the compound signal recognition method can effectively identify each working stage of hydraulic excavator, and has obvious effect on solving the problem of low accuracy of direct identification of hydraulic excavator operating cycle state.
Key words: excavator; operation cycle; support vector machine(SVM); intelligent check system; main pump pressure identification method; composite signal identification method
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- Chinese Core Periodicals
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- Chinese Sci-tech Core Periodicals
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- SA, INSPEC Indexed
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- CSA: T Indexed
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- UPD:Indexed
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2010 Zhejiang Information Institute of Mechinery Industry
Technical Support：Hangzhou Bory science and technology
