【作者】 肖成勇； 冯志鹏； 李学军； 石博强；

【Author】 Xiao Chengyong~1 Feng Zhipeng~1 Li Xuejun~2 Shi Boqiang~1 (1 Civil and Environmental Engineering School,University of Science and Technology Beijing,Beijing 100083; 2 Hunan Province Key Laboratory of Machinery Health Maintenance,Hunan University,of Science and Techndogy,Xiangtan 411201,Hunan Province)

【机构】 北京科技大学土木与环境工程学院； 湖南科技大学机械设备健康维护省重点实验室；

【摘要】 结合小波理论优良的时频局部化特性、支持向量机在小样本情况下出色的学习性能和良好的推广特性以及遗传算法有全局优化能力的优势,建立了WT-AGA-SVM混合智能预测模型。对某电铲供电机组运行状态的预测结果验证了模型的有效性和优越性。更多还原

【Abstract】 A hybrid prediction model based on wavelet theory and genetic-support vector machine is proposed.It makes full use of the fine time-frequency resolution of wavelets,the excellent leaming and generalization ability of support vector machines in situation of small sample,and the global optimization performance of genetic algorithm.The model is applied to the running condition prediction of the electric drive system of a shovel,and its effectiveness and advantage is validated.更多还原