支持向量机故障诊断技术在焦炉冷鼓系统中的应用  

Fault Diagnosis for Coke Oven Blowing Cooler System Based on Support Vector Machine

作　　者：程曾婉 张世峰[1] 张祝威 陈威[1] 

机构地区：[1]安徽工业大学电气与信息工程学院,安徽马鞍山243032

出　　处：《宜宾学院学报》2017年第6期6-9,共4页Journal of Yibin University

基　　金：安徽省教育厅自然科学研究项目(KJ2008B104)

摘　　要：为了解决焦炉冷鼓系统出现故障不能及时发现的问题,提出将基于结构风险极小化原则的支持向量机应用于系统的故障诊断技术中.利用支持向量机建立系统模型得到期望输出,将其与系统实际输出相比较,利用残差值的大小判断系统是否发生故障.仿真结果表明,该方法可以及时发现故障,提高系统安全运行系数.In order to solve the problem that the failure of coke oven blowing cooler system cannot be found timely, the fault diagnosis technology based on structural risk minimization principle of support vector machine was applied to the system. Using the support vector machine to establish the system model to get the expected output, compared with the actual output of the system, the residual value of the size of the system was used to determine the failure. The simulation results show that the method can detect the faults in time and provide guarantee for safe operation of the system.

关 键 词：焦炉冷鼓系统 支持向量机 故障诊断 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]