国内外在役大中型现代桥梁的正交异性钢桥面板面临着严重的疲劳问题，然而针对其运营状态下疲劳裂纹的诊断和监测，特别是裂纹尺寸估计，还没有切实有效的方法。本项目利用声发射技术在裂纹监测中的优势，充分考虑钢桥面板的受力特点、开裂特征、几何特征和运营噪声，研究基于声发射信号改进经验小波分析的钢桥面板疲劳裂纹定量监测方法。以裂纹扩展和闭合两类声发射信号的时频特征提取为出发点，提出基于自适应频带划分技术的改进经验小波变换，进而根据信号的多尺度时频能量分布特征建立具有抗噪性和鲁棒性的分类指标，提高两类声发射信号分离的准确度。在此基础上，提出一种基于裂纹闭合声发射信号的疲劳裂纹尺寸估计新方法，用于正交异性钢桥面板的疲劳裂纹定量监测。本项目采用理论与试验相结合的研究方案，利用先进的声发射信号处理方法解决正交异性钢桥面板疲劳裂纹监测中裂纹尺寸估计的难题，研究成果对在役桥梁结构的安全和使用性能评价具有重要意义。

The orthotropic steel bridge decks of existing medium- and long-span modern bridges all over the world are particularly vulnerable to fatigue. However, there is no satisfactory solution for the in-service diagnosis and monitoring of fatigue cracks, especially the crack size quantification, in orthotropic bridge decks. Taking advantages of the acoustic emission (AE) technique in crack detection, this project investigates the fatigue crack monitoring in orthotropic steel bridge decks based on improved empirical wavelet transform (EWT), according to their loading features, cracking modes, geometrical properties and operational noise. In order to extract the time-frequency features of AE signals, EWT will be improved by developing an adaptive wavelet spectrum segmentation method. Then, an anti-noise robust classification index based on the energy distribution in multiple time-frequency scales will be established to distinguish between the crack propagation-induced AE signals and the crack closure-induced AE signals with a high accuracy. Following the AE wave classification, a novel method to estimate the fatigue crack size is proposed by making use of crack closure-induced AE signals and applied to the crack monitoring of orthotropic steel bridge decks. Aiming at fatigue crack size estimation of orthotropic steel bridge decks, this project develops advanced AE signal processing algorithms based on theoretical analysis and experimental study. The outcomes of this project are of great significance for safety and usability performance evaluation.