摘要
针对无轨胶轮车全液压制动系统长期工作在煤矿井下恶劣的环境中而易于发生故障的问题,提出了基于支持向量机的故障诊断方法。应用支持向量机回归估计算法建立全液压制动系统的故障预测辨识模型,将支持向量机模式分类算法应用于故障分离,并在Matlab环境下分别进行了故障检测与故障分离试验。试验结果表明,将支持向量机方法应用于无轨胶轮车全液压制动系统故障诊断中是完全可行的,可以有效提高故障检测效率和诊断准确率。
To solve problem that full hydraulic braking system of trackless tyred vehicle was prone to failure in harsh environment of coal mine,a fault diagnosis method based on support vector machine was proposed.The support vector machine regression estimate algorithm was applied to establish fault prediction model of the full hydraulic braking system,while pattern classification algorithm was used to isolate fault,and fault diagnosis tests and isolation experiments were carried out in Matlab environment.The experiment results show that it is entirely feasible to use fault diagnosis method based on support vector machine to diagnose fault of full hydraulic braking system of trackless tyred vehicle,which can improve fault detection efficiency and diagnostic accuracy.
出处
《工矿自动化》
北大核心
2016年第10期30-34,共5页
Journal Of Mine Automation
基金
国家自然科学基金项目(51375282)
山东省科技发展计划课题(2014GGX103043)
山东省科技重大专项项目(2015ZDXX0601C01)
山东省研究生教育创新计划项目(SDYY14084)
关键词
无轨胶轮车
全液压制动系统
支持向量机
故障诊断
trackless tyred vehicle
full hydraulic braking system
support vector machine
fault diagnosis
