为准确检测船用耐腐蚀材料内部是否存在内部缺陷，提出基于激光超声技术的船用耐腐蚀材料内部缺陷检测方法。使用基于激光超声的材料内部信息采集方法，将激光超声波照射在船用耐腐蚀材料表面，获取材料内部反射的激光超声回波信息；采用基于经验模式分解的激光超声波特征提取方法，提取回波信息中的一次回波特征、二次回波特征；将所提特征输入基于改进支持向量机的内部缺陷检测模型，此模型使用遗传算法，获取可保证缺陷检测结果均方误差最小的惩罚因子后，将该惩罚因子导入支持向量机中，通过该支持向量机分类检测船用耐腐蚀材料内部缺陷。实验结果显示，本文方法对铝制船用耐腐蚀材料内部缺陷检测结果准确，具备显著的内部缺陷检测效力。
In order to accurately detect whether there are internal defects in Marine corrosion resistant materials, a method of detecting internal defects in marine corrosion resistant materials based on laser ultrasound technology was proposed. Using the method of material internal information collection based on laser ultrasound, the laser ultrasonic wave is irradiated on the surface of marine corrosion resistant material, and the laser ultrasonic echo information reflected inside the material is obtained. The laser ultrasonic feature extraction method based on empirical mode decomposition was used to extract the primary and secondary echo features of the echo information. The proposed features were input into the internal defect detection model based on improved support vector machine. The model used genetic algorithm to obtain a penalty factor that could ensure the minimum mean square error of defect detection results. The penalty factor was imported into the support vector machine, and the internal defects of marine corrosion resistant materials were detected by the support vector machine classification. The experimental results show that the proposed method is accurate and effective in detecting internal defects of aluminum marine corrosion resistant materials.
2022,44(21): 51-54 收稿日期：2022-09-07
DOI：10.3404/j.issn.1672-7649.2022.21.011
分类号：TP181
基金项目：江苏省高等学校基础科学（自然科学）研究面上项目（21KJB580010）
作者简介：刘昭亮(1990-),男,硕士,讲师,研究方向为轮机工程技术及船舶柴油机
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