A soft-sensing model on hydraulic excavator's backhoe vibratory excavating resistance based on fuzzy support vector machine

被引:2
|
作者
Huang Zhi-xiong [1 ]
He Qing-hua [1 ]
机构
[1] Cent S Univ, Coll Mech & Elect Engn, Changsha 410083, Peoples R China
基金
国家高技术研究发展计划(863计划);
关键词
fuzzy support vector machine; hydraulic excavator; backhoe vibration; excavating resistance; soft-sensing technique; TILLAGE TOOL; DISTURBANCE; FORCE;
D O I
10.1007/s11771-014-2128-8
中图分类号
TF [冶金工业];
学科分类号
0806 ;
摘要
In order to measure the backhoe vibratory excavating resistance of a hydraulic excavator fast and precisely, the influences of vibratory excavating depth, angle, vibratory frequency, amplitude, bucket inserting velocity and soil type on the vibratory excavating resistance were analyzed. Simulation analysis was carried out to establish the bucket inserting velocity, amplitude and vibratory frequency considered as secondary variables and excavating resistance as primary variable. A fuzzy membership function was introduced to improve the anti-noise capacity of support vector machine, which is a soft-sensing model on the hydraulic excavator's backhoe vibratory excavating resistance based on fuzzy support vector machine. The simulation result reveals that its maximum relative training and testing error are nearly 0.68% and -0.47%, respectively. It is concluded that the model has quite high modeling precision and generalization capacity, and it can measure the vibratory excavating resistance accurately, reliably and fast in an indirect way.
引用
收藏
页码:1827 / 1832
页数:6
相关论文
共 50 条
  • [1] A soft-sensing model on hydraulic excavator’s backhoe vibratory excavating resistance based on fuzzy support vector machine
    Zhi-xiong Huang
    Qing-hua He
    Journal of Central South University, 2014, 21 : 1827 - 1832
  • [2] A soft-sensing model on hydraulic excavator's backhoe vibratory excavating resistance based on fuzzy support vector machine
    黄志雄
    何清华
    Journal of Central South University, 2014, (05) : 1827 - 1832
  • [3] A soft-sensing model for feedwater flow rate using fuzzy support vector regression
    Na, Man Gyun
    Yang, Heon Young
    Lim, Dong Hyuk
    NUCLEAR ENGINEERING AND TECHNOLOGY, 2008, 40 (01) : 69 - 76
  • [4] Study on Soft-sensing Model for Condenser Vacuum Based-on Support Vector Regression
    Wang, Lei
    Zhang, Rui-qing
    2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 2, 2010, : 497 - 499
  • [5] Study on soft-sensing model of carbon content in fly ash based on support vector regression
    Bian, He-Ying
    Li, Zeng-Quan
    Fang, Yan-Jun
    Information Technology Journal, 2013, 12 (15) : 3122 - 3127
  • [6] SOFT SENSING MODEL BASED ON SUPPORT VECTOR MACHINE AND ITS APPLICATION
    Yan WeiwuShao HuiheWang XiaofanDepartment of Automation
    Chinese Journal of Mechanical Engineering, 2004, (01) : 55 - 58
  • [7] Soft sensing model based on support vector machine and its application
    Yan, Weiwu
    Shao, Huihe
    Wang, Xiaofan
    Chinese Journal of Mechanical Engineering (English Edition), 2004, 17 (01): : 55 - 58
  • [8] Soft sensing modeling based on support vector machine and Bayesian model selection
    Yan, WW
    Shao, HH
    Wang, XF
    COMPUTERS & CHEMICAL ENGINEERING, 2004, 28 (08) : 1489 - 1498
  • [9] Soft-Sensing in Batch Annealing Based on Finite Differential Method and Support Vector Regression
    Kacur, Jan
    Durdan, Milan
    Laciak, Marek
    Flegner, Patrik
    ADVANCES IN SCIENCE AND TECHNOLOGY-RESEARCH JOURNAL, 2019, 13 (04) : 70 - 86
  • [10] Soft-sensing model of Temperature for Aluminum Reduction Cell on Improved Twin Support Vector Regression
    Li, Tao
    MATERIALS SCIENCE, ENERGY TECHNOLOGY AND POWER ENGINEERING II (MEP2018), 2018, 1971