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Keywords = Inverse Heat Transfer Problem (IHTP)

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11 pages, 4156 KB  
Article
Prediction Method for Excess Surface Temperature Peak Time Inclusion Defect Depth Based on Conjugate Gradient Algorithm
by Yajing Yue, Weixiang Du, Jianping Yu and Baocun Ren
Processes 2024, 12(10), 2061; https://doi.org/10.3390/pr12102061 - 24 Sep 2024
Cited by 1 | Viewed by 930
Abstract
This study addresses the challenge of accurately calculating the depth of inclusion defects in Glass Fiber-Reinforced Plastic (GFRP), which is commonly used in onshore wind turbine blades. To overcome this issue, we proposed a novel Excess Surface Temperature Peak Time (ESPT) estimation method [...] Read more.
This study addresses the challenge of accurately calculating the depth of inclusion defects in Glass Fiber-Reinforced Plastic (GFRP), which is commonly used in onshore wind turbine blades. To overcome this issue, we proposed a novel Excess Surface Temperature Peak Time (ESPT) estimation method that combines a conjugate gradient algorithm with a conventional analytical approach. This research employed the Inverse Heat Transfer Problem (IHTP) solution method to estimate the boundary conditions of an experimental sample subjected to pulse excitation. By drawing analogies with traditional depth detection methods, we analyzed specific physical models and determined the calculated thickness of the sample. The Excess Surface Temperature Peak Time characteristics were then used to estimate the defect depth, and the resulting estimates and relative errors were evaluated. Our results demonstrated that the proposed method achieved a relative error of less than 15% when calculating defect depth, confirming its effectiveness. This approach provides new insights and possibilities for improving defect depth estimation in GFRP materials, offering valuable contributions to the assessment and maintenance of wind turbine blade safety. Full article
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