In detecting apparent defects in prefabricated steel structures,the detection of small defects affected by environmental and subjective factors has a relatively poor performance.Therefore,using the BP algorithm,a new method for detecting apparent defects in prefabricated building steel structures is designed.An industrial camera is installed on the inspection vehicle to capture images of prefabricated building steel structures,and preprocess the images through line-ar grayscale stretching,nonlinear filtering and other methods.The image grayscale co-occurrence matrix is employed to determine the texture feature parameters.Based on the BP algorithm,a surface defect detection model consisting of several 3-layer neural subnetworks is constructed,and accurate detection of surface defects in prefabricated steel structures in complex environments is achieved through adaptive adjustment and training.The experimental results show that the val-ue of the comprehensive index F1 of the output detection results of the proposed method is above 0.9,which meets quality requirements for apparent disease detection and optimizes detection quality.
关键词
BP算法/装配式建筑/钢结构/表观病害/梯度下降法
Key words
BP algorithm/fabricated building/steel structure/apparent defect/gradient de-scent method
维普
万方数据