关于混凝土桥梁检测与加固技术的有效措施探讨

混凝土桥梁检测工作可以有助于相关人员掌握混凝土桥梁的损伤情况,进而确保桥梁的安全性以及稳固性。本篇文章将针对混凝土桥梁检测工作的重要作用进行阐述,对其检测工作的具体内容以及技术进行分析,对混凝土桥梁表层加固技术、上部结构加固技术、下部结构加固技术以及其他加固技术进行探讨,为日后桥梁行业的可持续发展打下坚实的基础。

预应力混凝土桥梁检测与加固技术研究

在最近几年,我国对于基础性的建设更加重视,因为这与保持社会安定有着一些联系,这也是国家比较关注的。道路桥梁工程作为最具代表性的基础工作之一,有关部门应当对其格外重视,尤其是预应力混凝土桥梁检测与加固技术,这些内容可以有效保证桥梁工程的质量,减少安全事故发生的概率。

混凝土桥梁检测与加固技术的有效措施

随着我国社会经济的飞速发展,混凝土桥梁对于我国的重要性也变得越来越突出,混凝土桥梁的质量不仅直接关系到我国交通运输行业的发展,同时对于我国民众的日常出行安全也有着直接影响.因此,我国必须要定期对混凝土桥梁进行检测工作,找出其中存在的缺陷并采用加固技术将之解决,借此有效保障混凝土桥梁的总体质量,延长其使用寿命,促进我国社会经济的可持续发展.

基于PCNN和遗传算法相结合的新型混凝土桥梁裂缝检测方法

针对混凝土桥梁裂缝对比度低、裂缝图像噪声干扰强等难题,提出了基于脉冲耦合神经网络(PCNN)和遗传算法相结合的混凝土桥梁裂缝检测新算法(GA-PCNN)。该算法首先利用遗传算法优化裂缝PCNN模型参数;然后通过改进的最小对数误差适应度函数区分裂缝与背景,当适应度值大小几乎无变化时,停止分割图像;最后通过连通域去噪算法滤除残余噪声,实现裂缝的自动检测。比较GA-PCNN、PCNN和基于熵及动态阈值算法对裂缝图像的分割效果,并绘制PR和ROC曲线评价分割质量,经计算GA-PCNN算法的PR和ROC曲线下面积为90.6%和91.6%,分别高于PCNN算法10.1%和6.8%、基于熵和动态阈值6.5%和6.7%。实验结果表明,GA-PCNN新算法分割效果好且去噪能力强,该算法能准确地提取混凝土桥梁裂缝特征。

Crack detection of reinforced concrete bridge using video image

With the digital image technology,a crack detection method of reinforced concrete bridge was studied for the performance assessment.The effects including the image gray level,pixel rate,noise filter,and edge detection were analyzed considering cracks qualities.A computer program was developed by visual C++6.0 programming language to detect the cracks,which was tested by 15cases of bridge video images.The results indicate that the relative error is within 6%for cracks larger than 0.3 mm cracks and it is less than 10%for crack width between 0.2 mm and 0.3 mm.In addition,for the crack below 0.1 mm,the relative error is more than30%because the bridge is in safe stage and it is very difficult to detect the actual width of crack.

桥梁结构检测中光纤传感技术应用

以光纤传感技术为研究背景,对该技术在桥梁结构检测中的要点进行探讨。实践可知,光纤传感技术具备可视性、操作性以及便捷性等特点,在桥梁结构检测时,可以全面地对桥梁结构存在的病害问题进行分析,能够为工作人员在后期施工的阶段中提供良好的技术参考。

Dynamic Detection of Reinforced Concrete Bridge Damage by Finite Element Model Updating

The present work consists of dynamic detection of damages in reinforced concrete bridges by using a MMUM （mathematical model updating method） from incomplete test data. A well suited finite element model of a repaired bridge is carried out. The diagnosis enables us to locate and detect the damage in a reinforced concrete bridge. Thus, developments of analytical predictions have been checked by modal testing techniques. Besides, the FTCS （finite time centered space） scheme is developed to solve the set of equations which can easily handle finite element matrices of a bridge model. It is shown in this study that the method is applied to detect damages as well as existing cracks in real time of a repaired bridge. To check the efficiency of the method, the repaired bridge of OuedOumazer in Algeria has been selected. It is proven that identification methods have been able to detect the exact location of damage areas to be corrected avoiding the inaccuracy from the finite element model for the mass, stiffness and loading.