Data on Kurtosis Detailed by Researchers at Yanshan University (Feature Extraction and Diagnosis of Periodic Transient Impact Faults Based On a Fast Average Kurtogram-ghostnet Method).

Researchers at Yanshan University in Qinhuangdao, China have developed an improved fault diagnosis algorithm for extracting features and diagnosing periodic transient impact faults. The algorithm combines a modified fast kurtogram method with the lightweight convolutional neural network GhostNet. By converting vibration signals into two-dimensional kurtosis graphs, the algorithm achieves accurate fault diagnosis and classification with improved computational efficiency and resource utilization. The research was supported by the National Natural Science Foundation of China and the Province Natural Science Foundation of Hebei. [Extracted from the article]