Algorithms for Fault Detection and Diagnosis

• Muut tekijät: Ferracuti, Francesco (Toimittaja), Freddi, Alessandro (Toimittaja), Monteriù, Andrea (Toimittaja)
• Aineistotyyppi: Elektroninen Kirjan osa
• Kieli: englanti
• Julkaistu: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
• Aiheet: History of engineering & technology; structural health monitoring; digital image processing; damage; gray level co-occurrence matrix; self-organization map; rolling bearings; fault diagnosis; multiscale entropy; amplitude-aware permutation entropy; random forest; reusable launch vehicle; thruster valve failure; thruster fault detection; Kalman filter; machine vision; machine diagnostics; instantaneous angular speed; SURVISHNO 2019 challenge; video tachometer; motion tracking; edge detection; parametric template modeling; adaptive template matching; genetic algorithm; misalignment; fault prediction; combined prediction; multivariate grey model; quantum genetic algorithm; least squares support vector machine; lithium-ion battery; battery faults; battery safety; battery management system; fault diagnostic algorithms
• Linkit: DOAB: download the publication; DOAB: description of the publication

Due to the increasing demand for security and reliability in manufacturing and mechatronic systems, early detection and diagnosis of faults are key points to reduce economic losses caused by unscheduled maintenance and downtimes, to increase safety, to prevent the endangerment of human beings involv...