LS-SVM method for dynamic weighing velocity compensation about loaders
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摘要: 能否合理补偿动臂举升速度对所测油压信号的影响是制约装载机载重动态测量精度的关键问题.在给出载重测量的实现方法后，建立了实现载重测量速度补偿和载重量计算的框架模型，然后详细阐述了贝叶斯证据框架下最小二乘支持向量机(LSSVM，Least Square Support Vector Machines)参数的推断优化过程，以及基于贝叶斯证据框架下的LSSVM速度补偿方法.试验结果表明，采用该方法进行速度补偿后的载重测量误差均能控制到1%以下，验证了其有效性.Abstract: Whether or not to compensate the oil pressure because of lift crane velocity reasonably, i.e., the velocity compensation was thought to be the key to obtain accurate dynamic weighing about loaders. After the method of dynamic weighing was given, the parameter inferring course of least square support vector machines (LS-SVM) within Bayesian evidence framework was introduced. Then the frame model of velocity compensation based on LS-SVM was given, and the means of velocity compensation and the course of weight computing were introduced in detail. Test results indicate that using LS-SVM within Bayesian evidence framework for solving velocity compensation, a relative measuring error within 1% can be obtained, which verifies that the validity of the method.
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