A novel unsupervised anomaly detection method for rotating machinery based on memory augmented temporal convolutional autoencoder
Wanxiang Li, Zhiwu Shang, Jie Zhang, Maosheng Gao, Shiqi Qian
Topics & Concepts
AutoencoderAnomaly detectionComputer sciencePattern recognition (psychology)Artificial intelligenceFault detection and isolationEncoderDeep learningActuatorOperating systemAnomaly Detection Techniques and ApplicationsMachine Fault Diagnosis TechniquesOccupational Health and Safety Research