构建起重机载荷谱v-SVRM预测模型的改进方法  被引量:7

Improved modeling method for prediction model of crane load spectrum based on support vector regression machine

在线阅读下载全文

作  者:陆凤仪[1] 王爽[1] 徐格宁[1] 戚其松[1] 

机构地区:[1]太原科技大学机械工程学院,山西太原030024

出  处:《工程设计学报》2015年第5期412-419,共8页Chinese Journal of Engineering Design

基  金:"十二五"国家科技支撑计划资助项目(2011BAK06B05-05);山西省研究生创新项目(201214502)

摘  要:载荷谱预测精度和鲁棒性直接影响起重机械的疲劳可靠性计算以及安全寿命评估.因此,绘制模拟实际工作状态的载荷谱是解决起重机械疲劳断裂问题的重要环节.然而传统的回归模拟算法对其预测精度较低.支持向量回归机(SVRM)同其他数据分析算法相比,具有出色的小样本和非线性特性,预测精度高、稳健性好,可较好地解决欠学习、过学习以及局部最小值等传统回归算法的难题.因此,选用支持向量回归机预测起重机载荷谱,提高了模型的预测精度和鲁棒性.在此基础上,从核函数的构造和决策函数的建立两方面的改进,建立了改进的vSVRM预测模型.工程实例分析结果表明:从BP神经网络模型、v-SVRM模型到改进的v-SVRM模型,Er和RMSRE逐渐减小,R2逐渐增大,验证了所提出的改进方法具有良好的实用性、鲁棒性以及较高的预测精度,为起重机载荷谱的获取与预测提供了新方法.The load spectrum simulation of actual working status is the key factor to solve the problem of crane endurance failure.The precision and robustness of load spectrum predicting have great significance for reliability analysis of crane fatigue fracture and evaluation of its safety life.However,the predicting performance of classic linear regression model is weaker.Compared with other data analysis algorithms,support vector regression machine(SVRM)has excellent performance for small sample and nonlinear properties,including higher prediction accuracy and nice robustness.It can also overcome the difficulty of the curse of dimensionality,local minima and over-fitting and under-fitting for traditional pattern recognition methods.So,accuracy prediction precision and reliability can be obtained by using SVRM.Furthermore,an improved vSVRM prediction model was established with constructing new kernel function and decision function.The results of engineering application showed that the values of Erand of RMSREall the three models(the BP neural network model and the SVRM model and the modified model of v-SVRM)gradually decreased while the fitting degrees R2 gradually increased.It proves that the modified method has higher prediction precision and nicer robustness and it also provides a new way for obtaining and predicting crane load spectrum.

关 键 词:v-支持向量回归机 核函数 决策函数 载荷谱 

分 类 号:TH213[机械工程—机械制造及自动化]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象