基于最小二乘支持向量机的混合动力地下铲运机电机输出转矩预测

Output torque prediction of hybrid underground LHD motor based on least square support vector machine

  • 摘要: 针对电机转矩传感器体积较大,在当前的大部分工程机械和汽车中无法安装,造成无法直接实时采集电机的输出转矩的问题。在分析电气系统组成的基础上,提出了基于最小二乘支持向量机(LS-SVM)算法的电机输出转矩预测模型。模型以混合动力地下铲运机分别在地下试验巷道和眼前山地下矿山巷道工作时采集的载荷谱作为训练和测试样本,以混合动力地下铲运机电机的实际转速、电机直流端电流、电机直流端电压、电机控制器温度和电机绕组温度作为训练模型的输入,以电机的输出转矩作为输出,从而使基于最小二乘支持向量机的模型能够更加全面的体现影响电机输出转矩的影响因素。研究结果表明该模型具有良好的预测精度和适用能力。

     

    Abstract: In order to realize the real-time prediction of motor torque, an output torque prediction model is proposed based on Least Square Support Vector Machine (LS-SVM).Based on the analysis of the composition of an electrical system, the load spectra obtained from underground power test and underground mine roadway are taken as training and test samples, the authors make the use of the hybrid scraper motor actual speed, the DC terminal current of motor, the DC terminal voltage of motor, the motor controller temperature and the motor winding temperature as the input, the output torque of the motor is used as the output, thus, the model based on least square support vector machines (LS-SVM) can reflect the influence factors of motor output torque more comprehensively.Experiment results show that the proposed model has a good prediction accuracy and suitable ability.

     

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