大型船舶轴系故障非接触式监测方法

Non-contact monitoring method for large scale ship shafting failure

大型船舶轴系故障具有多变性,导致当前故障识别方法无法有效对各种类型的大型船舶轴系故障进行准确识别,为了提高大型船舶轴系故障识别的效果,设计一种新型的大型船舶轴系故障非接触式监测方法。首先采集大型船舶轴系故障识别信号,采用小波对其进行去噪,然后换提取大型船舶轴系故障识别信号特征,最后采用最小二乘支持向量机设计大型船舶轴系故障识别的分类器,并进行了具体的大型船舶轴系故障识别模拟实验。与其他大型船舶轴系故障识别方法相比,本文方法通过小波抑制了大型船舶轴系故障识别信号中的噪声干扰,提高了大型船舶轴系故障识别成功率,加快了大型船舶轴系故障识别的训练时间,建立更高效率的大型船舶轴系故障识别分类器。

The shafting faults of large ships are changeable, which leads to the failure identification methods of shafting faults of large ships can not effectively identify all kinds of shafting faults of large ships. In order to improve the effect of shafting fault identification of large ships, a non-contact monitoring method for shafting faults of large ships is designed. . Firstly, the fault identification signals of large ship shafting are collected and denoised by wavelet pairs. Then, extract the fault identification signal features of large ship shafting. Finally, a classifier for fault identification of large ship shafting is designed by using least squares support vector machine (SVM), and a simulation experiment for fault identification of large ship shafting is carried out. Compared with other large-scale ship shafting fault identification methods, this method suppresses the noise interference in the large-scale ship shafting fault identification signal by wavelet, improves the success rate of large-scale ship shafting fault identification, speeds up the training time of large-scale ship shafting fault identification, and establishes a more efficient large-scale ship shafting fault identification. Classifier is identified.