FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385408893> ?p ?o ?g. }

• W4385408893 endingPage "095026" @default.
• W4385408893 startingPage "095026" @default.
• W4385408893 abstract "Abstract Structural health monitoring of grouted sleeves is one of the assembly industry’s huge challenges. In this study, a combined two-level damage detection was introduced. It comprises defect classification (healthy, rebar eccentricity, and grout leakage) and severity evaluation for early-age grouted sleeves using guided waves. Multiple features (MF) from time-, frequency-, and time-frequency domains were extracted and defined according to the diverse defects and ages of grouted sleeves to represent complex damage characteristics. Moreover, the egret swarm algorithm optimization–extreme learning machine (ESAO-ELM) models were proposed to avoid the influence of subjective experience and judgment from experts. ESAO optimized the initial random parameters (input weights and hidden layer bias) of ELM. Then, two MF-ESAO-ELM models were trained for two-level damage detection on the experimental dataset. The performance of the proposed models was comprehensively evaluated using accuracy, recall, precision, and confusion matrix. MF-ESAO-ELM performs better than ELM and PSO-ELM in accuracy. In this strategy, the defect classification model works in the outer layer to distinguish the state and types of defects of grouted sleeves (healthy, eccentric, or leakage). In comparison, the inner layer starts predicting the severity only if the defect type is leakage. MF-ESAO-ELM offers advantages in terms of accuracy, strategy, and calculation time." @default.
• W4385408893 created "2023-08-01" @default.
• W4385408893 creator A5016031945 @default.
• W4385408893 creator A5018929178 @default.
• W4385408893 creator A5052184829 @default.
• W4385408893 creator A5083200116 @default.
• W4385408893 date "2023-08-17" @default.
• W4385408893 modified "2023-09-27" @default.
• W4385408893 title "Combined two-level guided wave structural health monitoring strategy using multifeature integration and machine learning: application to early-age grouted sleeves" @default.
• W4385408893 cites W1482405651 @default.
• W4385408893 cites W2090218979 @default.
• W4385408893 cites W2090991423 @default.
• W4385408893 cites W2111072639 @default.
• W4385408893 cites W2131929809 @default.
• W4385408893 cites W2147926935 @default.
• W4385408893 cites W2155986620 @default.
• W4385408893 cites W2567711369 @default.
• W4385408893 cites W2729668807 @default.
• W4385408893 cites W2803180332 @default.
• W4385408893 cites W2883246601 @default.
• W4385408893 cites W2930308033 @default.
• W4385408893 cites W2936348812 @default.
• W4385408893 cites W2950069040 @default.
• W4385408893 cites W2951258098 @default.
• W4385408893 cites W2981913087 @default.
• W4385408893 cites W2991342253 @default.
• W4385408893 cites W3004330905 @default.
• W4385408893 cites W3005058230 @default.
• W4385408893 cites W3005290228 @default.
• W4385408893 cites W3006407845 @default.
• W4385408893 cites W3013336113 @default.
• W4385408893 cites W3035334196 @default.
• W4385408893 cites W3046395836 @default.
• W4385408893 cites W3083570611 @default.
• W4385408893 cites W3115269447 @default.
• W4385408893 cites W3116250684 @default.
• W4385408893 cites W3119234631 @default.
• W4385408893 cites W3121557814 @default.
• W4385408893 cites W3123412705 @default.
• W4385408893 cites W3130466997 @default.
• W4385408893 cites W3135986616 @default.
• W4385408893 cites W3137720686 @default.
• W4385408893 cites W3159137010 @default.
• W4385408893 cites W3159967244 @default.
• W4385408893 cites W3164086628 @default.
• W4385408893 cites W3171348786 @default.
• W4385408893 cites W3173537526 @default.
• W4385408893 cites W3174276757 @default.
• W4385408893 cites W3180472737 @default.
• W4385408893 cites W3184971861 @default.
• W4385408893 cites W3190533868 @default.
• W4385408893 cites W3211243819 @default.
• W4385408893 cites W3211591752 @default.
• W4385408893 cites W3214818732 @default.
• W4385408893 cites W3217258731 @default.
• W4385408893 cites W4210510343 @default.
• W4385408893 cites W4210739375 @default.
• W4385408893 cites W4214864869 @default.
• W4385408893 cites W4281691125 @default.
• W4385408893 cites W4297348022 @default.
• W4385408893 cites W4306148673 @default.
• W4385408893 cites W4310802659 @default.
• W4385408893 cites W4313252146 @default.
• W4385408893 cites W4318465034 @default.
• W4385408893 cites W4366815280 @default.
• W4385408893 doi "https://doi.org/10.1088/1361-665x/acec22" @default.
• W4385408893 hasPublicationYear "2023" @default.
• W4385408893 type Work @default.
• W4385408893 citedByCount "0" @default.
• W4385408893 crossrefType "journal-article" @default.
• W4385408893 hasAuthorship W4385408893A5016031945 @default.
• W4385408893 hasAuthorship W4385408893A5018929178 @default.
• W4385408893 hasAuthorship W4385408893A5052184829 @default.
• W4385408893 hasAuthorship W4385408893A5083200116 @default.
• W4385408893 hasConcept C11171543 @default.
• W4385408893 hasConcept C11413529 @default.
• W4385408893 hasConcept C119857082 @default.
• W4385408893 hasConcept C127413603 @default.
• W4385408893 hasConcept C138602881 @default.
• W4385408893 hasConcept C139719470 @default.
• W4385408893 hasConcept C153180895 @default.
• W4385408893 hasConcept C154945302 @default.
• W4385408893 hasConcept C15744967 @default.
• W4385408893 hasConcept C162324750 @default.
• W4385408893 hasConcept C2776247918 @default.
• W4385408893 hasConcept C2777042071 @default.
• W4385408893 hasConcept C2778249042 @default.
• W4385408893 hasConcept C2778664469 @default.
• W4385408893 hasConcept C2780150128 @default.
• W4385408893 hasConcept C2781140086 @default.
• W4385408893 hasConcept C41008148 @default.
• W4385408893 hasConcept C50644808 @default.
• W4385408893 hasConcept C66938386 @default.
• W4385408893 hasConceptScore W4385408893C11171543 @default.
• W4385408893 hasConceptScore W4385408893C11413529 @default.
• W4385408893 hasConceptScore W4385408893C119857082 @default.
• W4385408893 hasConceptScore W4385408893C127413603 @default.
• W4385408893 hasConceptScore W4385408893C138602881 @default.

• next