An Early Fault Detection Method of Rotating Machines Based on Unsupervised Sequence Segmentation Convolutional Neural Network

Early fault detection (EFD) is vital for mechanical systems to reduce downtime and increase stability. The main challenge of EFD for rotating machines is to extract discriminative features from noisy signals to identify early faults. However, the lack of labels for the whole lifecycle data hinders the application of some powerful supervised deep learning methods in EFD. Besides, many EFD methods have to set a criterion manually, such as a …