… methods for rotating machinery fault diagnosis, as shown in Figure 2. First, the vibration data
is … method can improve the fault recognition rate and overcome the problem of difficult time …

… The SA algorithm is conducted to search for the optimal segmentation time t of the whole
lifecycle data in this article. The pseudocode of USSCNN is shown in Algorithm 1. …

… fault-related information and improve the accuracy of defect diagnosis, this paper presents a
segmented … It consists of several modules including data acquisition, image segment, region …

… In order to reveal the effectiveness of the proposed rotating machinery fault diagnosis … ,
(2) the evaluation of the data fusion method and (3) the performance of the proposed classifier. …

… on CNN-based fault diagnosis approaches in rotating machinery. Firstly, data preprocessing
… CNN was employed for fault diagnosis of planetary gearbox, data segmentation as a way of …

… image data and then classifying images. The thermal image-based rotating machinery fault
diagnosis method used in … Wang, “Segmented infrared image analysis for rotating machinery …

… short data segments. In other words, if we applied the pattern recognition methods for rotating
machinery fault diagnosis, the predicted health state labels of these short data segments …

… signals in the field of fault diagnosis, original data segmentation, typical feature … data
segmentation is selected as input to the deep neural network. In fault diagnosis of rotary equipment, …

… [106] proposed a one-dimensional CNN-GRU composite model to learn the vibration signals
reconstructed by data segmentation, which tried to overcome the important information loss …

… , a common fault diagnosis system often consists of two key steps: data … segmented infrared
image analysis for rotating machinery fault diagnosis, which applies an image segmentation …