【摘要】 当前，无损检测技术已经逐渐成为人造板检测的主要手段，超声波无损检测技术凭借着较高检测准确性和高效性成为人造板无损检测技术中应用最广泛的使用方法之一，无损检测技术通过非破坏性方式，能有效检测人造板物理力学性能、表面以及内部缺陷，为人造板质量与安全检测提供了科学依据。根据不同检测原理(脉冲反射法、脉冲透射法、衍射时差法、共振法)、不同探头数量(单个探头、双探头、多个探头)、不同波形(Lamb法、横波法、纵波法、表面波法)以及不同耦合方式(直接接触法、液浸法、电磁耦合法、干耦合法、空气耦合法)对超声波检测方法进行概括分类。从物理力学性能检测与缺陷检测深入分析了国内外超声波在人造板无损检测领域的研究现状、存在的问题以及探究影响超声波检测效果的原因和不同人造板在检测方法、内容上的差异。提出今后应着重关注4个方面研究重点：非接触式技术推动检测智能化与自动化；深度学习算法提升力学性能评估效率；高分辨率成像实现缺陷可视化；化学材料引入对性能检测的影响。更多还原

【Abstract】 At present, non-destructive testing technology has gradually become the main means of wood-based panel testing, ultrasonic non-destructive testing technology has become one of the most widely used methods in non-destructive testing of engineered wood panels due to its high testing accuracy and efficiency, non-destructive testing technology can effectively detect the physical and mechanical properties, surface, and internal defects of wood-based panels in a non-destructive manner, providing a scientific basis for the quality and safety testing of wood-based panels.Based on different detection principles(pulse reflection method, pulse transmission method, diffraction time-of-flight method, resonance method),different probe configurations(single probe, dual probes, multiple probes),different waveforms(Lamb method, shear wave method, compressional wave method, surface wave method),and different coupling methods(direct contact method, liquid immersion method, electromagnetic coupling method, dry coupling method, air coupling method),ultrasonic testing methods can be broadly classified.This study conducts an in-depth analysis of the current state of research, existing issues, and factors influencing the effectiveness of ultrasonic testing in the field of non-destructive testing of engineered wood panels, both domestically and internationally.It also explores the differences in testing methods and content across various types of engineered wood panels.Four key areas of research should be focused on in the future: non-contact technology to promote intelligent and automated testing; deep learning algorithms to improve the efficiency of mechanical property assessment; high-resolution imaging to enable defect visualization; and the impact of chemical materials on performance testing.更多还原