Wood failure percentage (WFP) is one of most important indices to evaluate the shear properties for wood-based composite bonded by adhesive, especially for cross-laminated timber. A new WFP measurement method for wood-bamboo composite bonded by phenolic resin (PF) and methylene diphenyl diisocyanate (MDI) separately under shear stress was proposed by combing image processing and deep learning (DL): its accuracy was corrected by the entropy weight method. The results show that the WFP measured by the DL method is in good agreement with the experimental value, however, the experimental conditions still exert a significant influence on the accuracy of measurement attained using the DL method, in which the inherent color of the adhesive and the change in the substrate of the specimens are the main factors affecting measurement accuracy. The relative error between the DL method and the experimental value can be reduced to no more than 14.29% after correction by the entropy weight method.

木材破坏率 (WFP) 是评估粘合剂粘合的木基复合材料剪切性能的最重要指标之一，尤其是对于交叉层压木材。结合图像处理和深度学习（DL）提出了一种新的酚醛树脂（PF）和亚甲基二苯基二异氰酸酯（MDI）分别粘合的木竹复合材料在剪切应力下的WFP测量方法：其精度通过熵权法校正. 结果表明，DL 法测得的 WFP 与实验值吻合较好，但实验条件对 DL 法测得的精度仍有显着影响，其中粘合剂的固有颜色和试样基材的变化是影响测量精度的主要因素。