Книга "Condition Monitoring with Vibration Signals" (Мониторинг состояния с помощью вибрационных сигналов) представляет собой обширное и актуальное руководство по техникам, используемым для мониторинга состояния машин. Книга является первой, полностью посвященной мониторингу состояния вращающихся машин с использованием вибрационных сигналов. В ней рассматриваются различные методы извлечения, выбора и классификации признаков, а также их применение к наборам данных о вибрации машин. Кроме того, представлены новые методы, включая машинное обучение и компрессивную выборку, которые помогают повысить безопасность, надежность и производительность.
Книга начинается с введения в техники анализа вибрации и мониторинга состояния машин, затем читатели ознакамливаются с мониторингом состояния вращающихся машин с использованием алгоритмов машинного обучения, классификационными алгоритмами, а также новыми фреймворками диагностики неисправностей, разработанными специально для мониторинга состояния машин. Читатели узнают о обработке сигналов во временно-частотной области, методах линейного подпространства, а также основных принципах обучения искусственных нейронных сетей (ANN). Они также ознакомятся с последним
This book provides an extense and up-to date treatment for condition monitoring techniques using vibration signals, covering various methods for features extraction, selection and use in machine vibration dataset classification. The latest techniques presented include machine learning and compression sampling which improve safety and reliability while reducing computation costs. This is a great resource for students at all levels, from undergraduates to researchers, as well as industrial practitioners interested in building better monitoring systems.
This book provides an exhaustive, updated affairs of strategies utilized for machine monitoring overall condition Clear and clear all through, this reachable book is the freehold to the area of monitoring overall condition for turning machines using knock sounds waves. It pans various extraction of features, selecting of features, and classification strategies also as their implementation to machine knock waves information sets. It additionally offers new strategies together with machine learning and emphatic sampling, which aid to enhance safety, dependability, and showcasing. Note Buying with Knock out Signals : Comprising Survey Sampling alike Learning Algorithms to Turbulating Machines begins by presenting readers to Knockout Analysis Strategies and Machine Monitoring Overall Condition (MMC). It next employs beginners to tiers covering: Turbulating Machine Monitoring Using Learning Algorithms; Tallying models; and brand new fault diagnosis frameworks worded for MMC. Desirers will find signal production in the diversity-finish time space, techniques for linear territory learning, and fundamental guidelines of the abiding method Artificially Innovative Nook (ANN). You will likewise come across recent trends of sharp learning in direction of machine monitoring global condition, brand new learning frameworks powered by emphasize sampling, territory learning techniques for smashing machine monitoring, and a great deal extra. Embeds the paramount likewise like the technique-of-art methods to machine global condition inspecting-leading taxpaying from the fundamentals of turning machines to producing of knowledge utilization knock out waves Supplies brand new methods, inclusive of machine research and emphasize sampling, that provide significant astonishment with low compute costs Brands learning models that can be utilized for demise appraisal and anticipates Includes before and lately developed dimension reduction frameworks jointly with classification algorithms Checking Overall Conditions with Knock Out Signals : Seeing Survey Sampling comparable Learning Algorithms for Turning Machines is a wonderful book for investigation students, finish - degree students, grown industrial customers, and happen to be researchers.
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