综合BIM结合表面图像分析的钢结构无损检测方法

采用质量脆弱性评价方法检测地震区绿色施工建筑钢结构时,易受噪声的干扰,且检测深度较浅,未能全面检测钢结构的损坏情况。提出综合BIM结合表面图像分析的钢结构无损检测方法,使用小波分解方法对建筑钢结构的检测图像进行去噪处理,通过膨胀与腐蚀处理增强检测图像的清晰度,采用红外图像技术,依据缺陷边缘处检测图像恢复的变化率,通过旋转跟踪法依次提取缺陷边缘,构建基于BIM的地震区绿色施工建筑钢结构检测模型,全面掌控地震区绿色建筑钢结构的材料、无损检测以及管理等过程,管控建筑钢结构全寿命周期,完成建筑钢结构的无损检测。实验结果表明,所提方法有效检测率为100%,检测深度高达1 499 mm,且检测结果的相对误差仅有0.000 7%。

Nondestructive Testing Method for Steel Structures Based on Building Information Modeling and Surface Image Analysis

Using the method of quality vulnerability assessment to detect the steel structure of green construction buildings in the earthquake area easily leads to noise disturbance. Moreover, the detection depth is shallow; therefore, the damage of the steel structure cannot be detected comprehensively. Herein, a nondestructive detection method for steel structure based on building information modeling (BIM) and surface image analysis is proposed. The wavelet decomposition method is used to denoise the detection image of the steel structure. Further, the expansion and corrosion processings are used to enhance the clarity of the detection image. According to the change rate of image restoration at defect edges, the infrared image technology, and rotation tracking method are adopted to extract the defect edge. The detection model of green construction steel structure based on BIM in seismic area was constructed to comprehensively control the material, nondestructive testing, and management of green construction steel structure in the seismic area. Additionally, the whole life cycle of steel structure is controlled, and the nondestructive testing of steel structure is completed. The experimental results show that the effective detection rate of the proposed method, detection depth, and relative error of the detection results are 100%, 1 499 mm, and 0.000 7%, respectively.