Centrifugal pumps are an integral part of many industrial processes and are used extensively in water supply, sewage, heating and cooling systems. While there are several review papers on machine learning-based fault diagnosis on induction motors, its application to centrifugal pumps has received relatively little attention. This work attempts to summarize and review recent research and development in machine learning-based pump condition monitoring and fault diagnosis. The paper starts with a brief explanation of pump operation including common pump faults and the main principles of the motor current signature analysis (MCSA) method. This is followed by a detailed explanation of various machine learning-based methods including the types of detected faults, experimental details and reported accuracies. The performances of different approaches are then presented systematically in a unified table. Finally, the authors discuss practical aspects and challenges related to data collection, storage and real-world implementation.
Fencing is a fast-paced sport played with swords which are Épée, Foil, and Sabre. However, such fast-pace can cause referees to make wrong decisions. Review of slow-motion camera footage in tournaments helps referees' decision-making, but it interrupts the match and may not be available for every organisation. Motivated by the need for better decision-making, analysis and availability, we introduce the first fully-automated deep learning classification and detection system for fencing body moves at the moment a touch is made. This is an important step towards creating a fencing analysis system, with player profiling and decision tools that will benefit the fencing community. The proposed architecture combines You Only Look Once version three (YOLOv3) with a ResNet-34 classifier, trained on ImageNet settings, to obtain 83.0% test accuracy on the fencing moves. These results are exciting development in the sport, providing immediate feedback and analysis along with accessibility, hence making it a valuable tool for trainers and fencing match referees.
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