基于改進(jìn)FasterR-CNN的機(jī)場(chǎng)跑道道面裂縫檢測(cè)方法

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中圖分類(lèi)號(hào)：TP391.92;U418.6 文獻(xiàn)標(biāo)志碼：A文章編號(hào)：1001-5922（2025）05-0159-04

Abstract：Civil aviation plays a vital rolein China's transportationsystem.With theextension of theservice life of airports，the problem of pavement damage is becoming more and more serious，which poses a major threat to the safetyof aircraft taxing，take-offand landing.Inorder to reduce theriskofaircraft inthe processof take-off and landing，an improved detection method based on Faster R-CNN was proposed.The detection method comprehensivelyused deep learningand objectdetection technologiessuch as GC-ASFF module，CIoU index，improved loss functionand transfer learning to achieve accurate detectionof pavement cracks，so as to evaluate thecurent pavement safety status by using the identified characteristic parameters of pavement cracks.The experimental results showedthat the improved model had high recognition accuracyand excelent comprehensive performance，and can accurately identify and detect runway pavement damage，which has high reliability.

Key Words：crack detection；faster R-CNN；ASFF ；merging ratio；loss function

機(jī)場(chǎng)跑道是飛機(jī)起降的主要區(qū)域，在荷載和環(huán)境因素的相互作用下，機(jī)場(chǎng)道面很容易出現(xiàn)各種病害，裂縫病害則是大多數(shù)問(wèn)題的早期表現(xiàn)之一，若不及時(shí)進(jìn)行處理，則會(huì)造成巨大的安全隱患[1]。（剩余7028字）