大型船舶加筋板结构焊接若出现裂纹,会降低加筋板结构强度,为船舶航行安全带来不可预估的风险,为此研究大型船舶加筋板结构焊接裂纹在线检测方法。使用有限元软件Ansys,依据船舶加筋板结构参数,对加筋板结构焊接裂纹模态进行模拟,获取大型船舶加筋板结构焊接裂纹模态,依据该模态,使用改进连续小波分解方式从加筋板结构焊接裂纹模态中获取裂纹对应的小波系数,通过获取裂纹模态小波系数突变点,依据该突变点得到加筋板结构焊接裂纹深度、长度、宽度等在线检测结果。实验结果表明,该方法可有效获取船舶加筋板结构焊接裂纹模态,并依据该模态在线检测到船舶加筋板结构焊接裂纹的长度、宽度等,应用效果较佳。
If cracks appear in the welding of reinforced plate structures on large ships, it will reduce the strength of the reinforced plate structure and bring unpredictable risks to ship navigation safety. Therefore, an online detection method for welding cracks in reinforced plate structures on large ships is studied. This method uses finite element software Ansys to simulate the welding crack mode of the stiffened plate structure based on the structural parameters of the ship's stiffened plate, and obtains the welding crack mode of the large ship's stiffened plate structure. Based on this mode, an improved continuous wavelet decomposition method is used to obtain the wavelet coefficients corresponding to the cracks from the welding crack mode of the stiffened plate structure. By obtaining the mutation point of the wavelet coefficients of the crack mode, Obtain online detection results for the depth, length, and width of welding cracks in the reinforced plate structure based on this mutation point. The experimental results show that this method can effectively obtain the mode of welding cracks in ship reinforced plate structures, and based on this mode, the length and width of welding cracks in ship reinforced plate structures can be detected online, with better application effects.
2024,46(6): 157-160 收稿日期:2023-06-12
DOI:10.3404/j.issn.1672-7649.2024.06.027
分类号:TP391
作者简介:宋敏霞(1979-),女,博士,讲师,研究方向为过程装备及新材料连接
参考文献:
[1] 杜言, 俞健, 吴卫国, 等. 焊接工艺参数对船舶加筋板结构的声振特性影响研究[J]. 中国舰船研究, 2023, 18(6): 216-225.
DU Yan, YU Jian, WU Wei-guo, et al. Influence of welding residual stress on dynamic and acoustic behavior of typical ship structures[J]. Chinese Journal of Ship Research, 2023, 18(6): 216-225.
[2] 杨启航, 李林安, 李利青, 等. 基于变分模态分解的结构裂纹识别[J]. 应用数学和力学, 2022, 43(12): 1324-1335.
YANG Qi-hang, LI Lin-an, LI Li-qing, et al. Structural crack identification based on the variation mode decomposition[J]. Applied Mathematics and Mechanics, 2022, 43(12): 1324-1335.
[3] 邓江勇, 陈振华, 汤恒, 等. 核级阀门唇焊焊缝熔深的超声检测方法[J]. 应用声学, 2023, 42(6): 1115-1122.
DENG Jiang-yong, CHEN Zhen-hua, TANG Heng, et al. Ultrasonic testing method for weld penetration of nuclear-grade valve lip welds[J]. Journal of Applied Acoustics, 2023, 42(6): 1115-1122.
[4] 周利, 蔡金延, 丁仕风, 等. 基于YOLACT的冰体环向裂纹尺寸识别方法[J]. 中国舰船研究, 2023, 18(6): 150-157.
ZHOU Li, CAI Jin-yan, DING Shi-feng, et al. Method of recognizing ice circumferential crack size based on YOLACT[J]. Chinese Journal of Ship Research, 2023, 18(6): 150-157.
[5] 杨茂, 陆山, 刘小桃, 等. 车削表面及微观结构影响小裂纹形核扩展概率模型[J]. 推进技术, 2023, 44(3): 175-183.
YANG Mao, LU Shan, LIU Xiao-tao, et al. Probabilistic model of small crack nucleation and propagation considering turning surface and microstructure influence[J]. Journal of Propulsion Technology, 2023, 44(3): 175-183.
[6] 骆撷冬, 马栋梁, 张松林, 等. 基于门控循环单元神经网络的箱型梁结构裂纹损伤检测方法[J]. 中国舰船研究, 2022, 17(4): 194-203.
LUO Xie-dong, MA Dong-liang, ZHANG Song-lin, et al. GRU neural network-based method for box girder crack damage detection[J]. Chinese Journal of Ship Research, 2022, 17(4): 194-203.