论提高装备故障预测准确度的方法途径——先进智能预测算法研究  

On the Method of Raising Accurate Degree of Equipment Fault Prediction:Study of the Advanced Intelligence Prediction Algorithm

作　　者：赵玉龙[1] 王昌荣 蒋有才[1] 

机构地区：[1]军械工程学院 [2]北京66176部队

出　　处：《价值工程》2016年第32期159-161,共3页Value Engineering

摘　　要：提高故障预测准确度的方法有很多,研究先进的智能预测算法就是其中的一种。大量的先进预测算法都得到了广泛的应用,如专家系统、神经网络、支持向量机等。每种智能预测算法都有各自的优点和不足,首先介绍了常见的智能预测算法及其应用;然后重点介绍了支持向量机,主要包括其基本原理和主要问题;最后对支持向量机算法的改进方向进行了探讨。支持向量机作为智能预测算法的一种,对于提高故障预测准确度有很好的应用前景。There are many methods to improve the accurate degree of fault prediction, and the advanced intelligent prediction algorithm is one of them. A large number of advanced prediction algorithms have been widely used, such as expert systems, neural networks, support vector machines and so on. Each kind of intelligent prediction algorithm has its own advantages and disadvantages. The common intelligent prediction algorithm and its application are introduced in this paper. Then the support vector machine is introduced, mainly including its basic principles and main problems. Finally, the improvement direction of the support vector machine algorithm is discussed. As a kind of intelligent prediction algorithm, support vector machine has a good application prospect for improving the accuracy of fault prediction.

关 键 词：故障预测 准确度 智能预测算法 支持向量机 

分 类 号：TP206.3[自动化与计算机技术—检测技术与自动化装置]