基于GA-SVDD的轴承性能退化评估

Evaluation of Bearing Performance Degradation Based on GA-SVDD

为解决因机械设备轴承损伤导致机械故障而无法正常工作的问题,提出了一种基于GA-SVDD的轴承性能退化定量评估方法。该方法采用遗传算法优化选择特征参量,并建立SVDD超球体模型,运用SVDD距离评估轴承的性能退化程度。实验分析表明：该方法能够有效地对轴承性能退化过程的细节进行描述,实现对待测样本退化程度的定量评估。

In order to solve the problem of mechanical failure caused from the damage of bearing, the paper proposes a quantitative evaluation method of bearing performance degradation based on GA-SVDD. The method uses genetic algorithm to select feature parameters and build SVDD model. The SVDD distance can be used to evaluate the bearing performance degradation degree. The test analysis show that the method can show the details of bearing performance degradation and realize the quantitative evaluation of performance degradation degree of the bearing samples.