2018
DOI: 10.3390/s18124456
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Cable Interlayer Slip Damage Identification Based on the Derivatives of Eigenparameters

Abstract: Cables are the main load-bearing structural components of long-span bridges, such as suspension bridges and cable-stayed bridges. When relative slip occurs among the wires in a cable, the local bending stiffness of the cable will significantly decrease, and the cable enters a local interlayer slip damage state. The decrease in the local bending stiffness caused by the local interlayer slip damage to the cable is symmetric or approximately symmetric for multiple elements at both the fixed end and the external l… Show more

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Cited by 1 publication
(2 citation statements)
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“…Moreover, all the considered classes of mosquitoes could be detected through the various models with a high accuracy (97–98.9%) and specificity (98.4–99.4%), as indicated in Table 2 . These results are comparable to those of the existing classifiers and network models 9 , 21 , 24 . Notably, the well-trained model shows the sensitivity (92.4%), the specificity (99.40%), the precision (95.56%) and the accuracy (98.9%) to detect the species and gender of mosquito vectors.…”
Section: Discussionsupporting
confidence: 83%
See 1 more Smart Citation
“…Moreover, all the considered classes of mosquitoes could be detected through the various models with a high accuracy (97–98.9%) and specificity (98.4–99.4%), as indicated in Table 2 . These results are comparable to those of the existing classifiers and network models 9 , 21 , 24 . Notably, the well-trained model shows the sensitivity (92.4%), the specificity (99.40%), the precision (95.56%) and the accuracy (98.9%) to detect the species and gender of mosquito vectors.…”
Section: Discussionsupporting
confidence: 83%
“…This detection and recognition model based on regression can instantly learn the global information of the images for end-to-end training, thereby considerably enhancing the speed of target detection. The YOLO algorithm has been noted to exhibit a high performance in terms of the accuracy and computational speed 21 , 27 , 28 . Additionally, enhanced versions of the network algorithm have been noted to operate faster than other detection frameworks.…”
Section: Introductionmentioning
confidence: 99%