基于模态柔度差曲率的云杉锯材梁缺陷检测

在机械和环境荷载作用下,木质构件和结构的局部缺陷如节疤、腐朽和裂缝等会导致使用寿命的缩减.在木结构工程领域,如果能够尽早对结构和构件的最薄弱位置进行检出和评估,可避免因突然破坏而导致的灾难性事故.在本研究中,通过振动测试获取前两阶模态振型,并利用锯材梁损伤前后的模态柔度矩阵差值曲率提出损伤识别指标.为了验证提案损伤指标的有效性,通过人工切除截面质量来模拟不同损伤程度、不同损伤位置和双数个损伤的情景,试验结果表明损伤指标对不同程度、不同位置和双数个损伤均能准确定位,并可对损伤轻重程度进行定性评价.

Damage Detection of Picea asperata Sawn Timber Beams Using the Modal Flexibility Curvature

The local damages such as knots,decay,and cracks can be translated into a reduction of service life due to mechanical and environmental loadings.In wood construction,it is very important to evaluate the weakest location and detect damage at the earliest possible stage to avoid the future catastrophic failure.In this study,the modal testing was operated on wood beams to generate the first two mode shapes.A novel statistical algorithm was proposed to extract the damage indicator by computing the modal flexibility curvature before and after damage in timbers.The different damage severities,damage locations,and damage counts were simulated by removing mass from intact beams to verify the algorithm.The results showed that the proposed statistical algorithm was effective and suitable to the designed damage scenarios.It was reliable to detect and locate local damages under different severities,locations,and counts.The peak values of the damage indicators computed from the first two mode shapes were sensitive to different damage severities and locations.They were also reliable to detect the multiple damages.