FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3196060986> ?p ?o ?g. }

• W3196060986 abstract "Gear flank changes caused by wear do not only affect the dynamic behavior of gear systems, but they can also compromise the load-carrying capacity of gear teeth up to critical failure. To help avoid unintended consequences like downtime or safety risks, a condition monitoring system needs to be able to estimate the current wear during operation based on available sensor measurements. While many condition monitoring approaches in research rely on vibrational analysis with manual feature engineering, gearboxes running at slow speed do not reveal much excitation information for this purpose. We therefore introduce an approach for slow-speed gear wear monitoring that is based on the dynamic gear transmission error and that contains an automated feature selection process. For this purpose, we extract a large set of features from the preprocessed transmission error samples. Applying combined filter and embedded feature selection methods enables us to automatically identify and remove features with low relevance. The selection process consists of filtering features with no statistical dependence on the target wear value, removing redundant features with a correlation analysis and a recursive feature elimination process with cross-validation based on a random forest regressor. The remaining relevant set of features is the basis for model training and subsequent wear estimation. For this, the present research employed two independent ensemble models, random forest regression and gradient boosted regression trees. To train and test the proposed approach, we conducted slow-speed gear experiments with developing gear wear on a single-stage spur gear test rig setup. The results of both models show good gear wear estimation performance compared to the actual wear mass loss, even for small quantities. Hence, the proposed transmission error-based approach with automated feature selection is able to quantify the degree of slow-speed wear and offers a possible way for condition monitoring and fault diagnosis." @default.
• W3196060986 created "2021-08-30" @default.
• W3196060986 creator A5006394640 @default.
• W3196060986 creator A5010189748 @default.
• W3196060986 creator A5053607357 @default.
• W3196060986 creator A5080464781 @default.
• W3196060986 creator A5089581769 @default.
• W3196060986 date "2021-08-17" @default.
• W3196060986 modified "2023-10-14" @default.
• W3196060986 title "Condition Monitoring of Slow-speed Gear Wear using a Transmission Error-based Approach with Automated Feature Selection" @default.
• W3196060986 cites W1503398984 @default.
• W3196060986 cites W1596515083 @default.
• W3196060986 cites W1678356000 @default.
• W3196060986 cites W1889820893 @default.
• W3196060986 cites W1970066309 @default.
• W3196060986 cites W1989770855 @default.
• W3196060986 cites W1991723619 @default.
• W3196060986 cites W1994010057 @default.
• W3196060986 cites W2009082127 @default.
• W3196060986 cites W2024860047 @default.
• W3196060986 cites W2042193040 @default.
• W3196060986 cites W2042837584 @default.
• W3196060986 cites W2049003912 @default.
• W3196060986 cites W2060304859 @default.
• W3196060986 cites W2064946764 @default.
• W3196060986 cites W2074724805 @default.
• W3196060986 cites W2083102256 @default.
• W3196060986 cites W2091809240 @default.
• W3196060986 cites W2101234009 @default.
• W3196060986 cites W2106525823 @default.
• W3196060986 cites W2124833832 @default.
• W3196060986 cites W2129018774 @default.
• W3196060986 cites W2143426320 @default.
• W3196060986 cites W2273449731 @default.
• W3196060986 cites W2276621400 @default.
• W3196060986 cites W2317595875 @default.
• W3196060986 cites W2396076036 @default.
• W3196060986 cites W2404692435 @default.
• W3196060986 cites W2545001194 @default.
• W3196060986 cites W2580840020 @default.
• W3196060986 cites W2621019941 @default.
• W3196060986 cites W2755311268 @default.
• W3196060986 cites W2776998341 @default.
• W3196060986 cites W2802314367 @default.
• W3196060986 cites W2897895022 @default.
• W3196060986 cites W2909918698 @default.
• W3196060986 cites W2911964244 @default.
• W3196060986 cites W2963905884 @default.
• W3196060986 cites W2991190331 @default.
• W3196060986 cites W3037481734 @default.
• W3196060986 cites W3154274841 @default.
• W3196060986 cites W625540141 @default.
• W3196060986 doi "https://doi.org/10.36001/ijphm.2021.v12i2.3026" @default.
• W3196060986 hasPublicationYear "2021" @default.
• W3196060986 type Work @default.
• W3196060986 sameAs 3196060986 @default.
• W3196060986 citedByCount "7" @default.
• W3196060986 countsByYear W31960609862022 @default.
• W3196060986 countsByYear W31960609862023 @default.
• W3196060986 crossrefType "journal-article" @default.
• W3196060986 hasAuthorship W3196060986A5006394640 @default.
• W3196060986 hasAuthorship W3196060986A5010189748 @default.
• W3196060986 hasAuthorship W3196060986A5053607357 @default.
• W3196060986 hasAuthorship W3196060986A5080464781 @default.
• W3196060986 hasAuthorship W3196060986A5089581769 @default.
• W3196060986 hasBestOaLocation W31960609861 @default.
• W3196060986 hasConcept C106131492 @default.
• W3196060986 hasConcept C111919701 @default.
• W3196060986 hasConcept C119599485 @default.
• W3196060986 hasConcept C124101348 @default.
• W3196060986 hasConcept C127413603 @default.
• W3196060986 hasConcept C138885662 @default.
• W3196060986 hasConcept C148483581 @default.
• W3196060986 hasConcept C153180895 @default.
• W3196060986 hasConcept C154945302 @default.
• W3196060986 hasConcept C169258074 @default.
• W3196060986 hasConcept C180591934 @default.
• W3196060986 hasConcept C200601418 @default.
• W3196060986 hasConcept C2775846686 @default.
• W3196060986 hasConcept C2776401178 @default.
• W3196060986 hasConcept C31972630 @default.
• W3196060986 hasConcept C41008148 @default.
• W3196060986 hasConcept C41895202 @default.
• W3196060986 hasConcept C761482 @default.
• W3196060986 hasConcept C76155785 @default.
• W3196060986 hasConcept C98045186 @default.
• W3196060986 hasConceptScore W3196060986C106131492 @default.
• W3196060986 hasConceptScore W3196060986C111919701 @default.
• W3196060986 hasConceptScore W3196060986C119599485 @default.
• W3196060986 hasConceptScore W3196060986C124101348 @default.
• W3196060986 hasConceptScore W3196060986C127413603 @default.
• W3196060986 hasConceptScore W3196060986C138885662 @default.
• W3196060986 hasConceptScore W3196060986C148483581 @default.
• W3196060986 hasConceptScore W3196060986C153180895 @default.
• W3196060986 hasConceptScore W3196060986C154945302 @default.
• W3196060986 hasConceptScore W3196060986C169258074 @default.
• W3196060986 hasConceptScore W3196060986C180591934 @default.
• W3196060986 hasConceptScore W3196060986C200601418 @default.
• W3196060986 hasConceptScore W3196060986C2775846686 @default.
• W3196060986 hasConceptScore W3196060986C2776401178 @default.

• next