基于支持向量机的航标故障识别

On the AtoN Fault Identification based on Support Vector Machines

航标的健康运行不仅与船舶运输效率和航行安全有关,而且还是评估航标维护质量的重要指标,是船舶航行的重要参考依据,也是衡量一个国家航运业发展水平的重要标准。因此,及早发现航标失常并及时采取相应的修复措施,符合航运及航标管理机构的实际需求。对于航标设备故障识别问题,实质上可归结为分类问题。文中详细介绍了支持向量机(SVM)用于分类的方法,最终采用支持向量机(SVM)的分类方法,通过MATLAB建立分类模型,实现对航标设备故障的识别。

The sound operation of aids to navigation (AtoN) not only bears on ship transportation efficiency and ship safety, but also acts as an important indicator for evaluating the AtoN maintenance. It is the major source of reference for the navigation of ships as well as an important standard to measure the development level of a country's shipping industry. Therefore, the early identification of AtoN failures and the timely adoption of appropriate maintenance measures conform with the actual needs of the shipping industry and the AtoN authority. The problem of fault identification can essentially be attributed to the problem in classification. The article introduces in detail the method of support vector machines (SVM) for the classification. Finally, a classification method based on support vector machines (SVM) is applied in establishing a classification model through MATLAB aiming at realizing the identification of AtoN fault.