Computer Engineering Department, Firat University, 23119 Elazig, Turkey.
ISA Trans. 2014 Mar;53(2):220-9. doi: 10.1016/j.isatra.2013.11.004. Epub 2013 Dec 2.
Although reconstructed phase space is one of the most powerful methods for analyzing a time series, it can fail in fault diagnosis of an induction motor when the appropriate pre-processing is not performed. Therefore, boundary analysis based a new feature extraction method in phase space is proposed for diagnosis of induction motor faults. The proposed approach requires the measurement of one phase current signal to construct the phase space representation. Each phase space is converted into an image, and the boundary of each image is extracted by a boundary detection algorithm. A fuzzy decision tree has been designed to detect broken rotor bars and broken connector faults. The results indicate that the proposed approach has a higher recognition rate than other methods on the same dataset.
尽管重构相空间是分析时间序列最强大的方法之一，但如果没有进行适当的预处理，它可能会在感应电动机的故障诊断中失效。因此，提出了一种基于相空间中边界分析的新特征提取方法，用于诊断感应电动机故障。该方法仅需要测量一相电流信号来构建相空间表示。将每个相空间转换为图像，并通过边界检测算法提取每个图像的边界。设计了一个模糊决策树来检测断条和断接器故障。结果表明，在相同的数据集上，该方法的识别率高于其他方法。
