The Integration Real-Time fault detection and prognosis framework based on unsupervised data-driven approaches for prognostic and health management of railway door systems

Despite much attention to data-driven approaches for fault detection, the major challenge is the lack of labelled datasets to build the models since maintenance is usually conducted regularly to avoid significant defects. In order to tackle the issue, we aim to develop a novel framework for fault detection and prognosis...