intelligent partial discharge diagnosis for condition monitoring

Provides an extensive, up-to-date treatment of techniques used for machine condition monitoring Clear and concise throughout, this accessible book is the first to be wholly devoted to the field of condition monitoring for rotating machines using vibration signals. It covers various feature extraction, feature selection, and classification methods as well as their applications to machine vibration datasets. It also presents new methods including machine learning and compressive sampling, which help to improve safety, reliability, and performance. Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines starts by introducing readers to Vibration Analysis Techniques and Machine Condition Monitoring (MCM). It then offers readers sections covering: Rotating Machine Condition Monitoring using Learning Algorithms; Classification Algorithms; and New Fault Diagnosis Frameworks designed for MCM. Readers will learn signal processing in the time-frequency domain, methods for linear subspace learning, and the basic principles of the learning method Artificial Neural Network (ANN). They will also discover recent trends of deep learning in the field of machine condition monitoring, new feature learning frameworks based on compressive sampling, subspace learning techniques for machine condition monitoring, and much more. Covers the fundamental as well as the state-of-the-art approaches to machine condition monitoring—guiding readers from the basics of rotating machines to the generation of knowledge using vibration signals Provides new methods, including machine learning and compressive sampling, which offer significant improvements in accuracy with reduced computational costs Features learning algorithms that can be used for fault diagnosis and prognosis Includes previously and recently developed dimensionality reduction techniques and classification algorithms Condition Monitoring with Vibration Signals: Compressive Sampling and Learning Algorithms for Rotating Machines is an excellent book for research students, postgraduate students, industrial practitioners, and researchers.



Что искали на сайте
кружка printio пионы | dsquared2 пляжные брюки и шорты | cs 12 24 in s hook s hook not include pot | 110cm wide wedding dress lace embroidery diy women clothes materials clothing fabric accessories ivory white church happy hour | printio soviet tank | faux pearl espadrille flatform sliders | linux® administrator street smarts | best deal quartz watch women fashion tower pattern diamond dial watches men faux leather watch women s dress clock montre relo | 14pcs set stainless steel dumplings wrappers cutter maker tools cake moulds mousse ring round stainless steel cookie molds set | брюки fiorella rubino fiorella rubino fi013ewbeeg7 | cute resin bride and bridegroom toy doll | резиновые сапоги playtoday playtoday mp002xg006pn | autumn summer new women shirt dress long sleeved female dresses slim fashion party office lady sundress plus size casual rob | 350a 500a gas welding gun shunt connecting rod insulation cover bent pipe nozzle gas welding gun accessories welder gun parts | creative fun cheese snacks pu pocketbook coin bag girls purse small canvas purse cat coin purse | len deighton spy line | лампа энергосберегающая tdm sq0323 0054 | motorcycle atv riding scooter driving flying protective frame clear lens portable vintage helmet goggles glasses for 2009 buell xb12r | skeleton skull head silicone chocolate muffin cupcake candy ice cube mold halloween | issey miyake l eau d issey pour homme summer edition eau de toilette | macarons ceiling lamps rose colors metal lamp body acrylic lamp shade colorful post modern ceiling light led lighting fixture | батарейка perfeo алкалиновая pf lr6 4sh | кеды y | deadly animals | the shining |