基于改进曲率法和数据融合的结构损伤识别研究
[Abstract]:The service period of buildings is often for several decades, even more than a hundred years of large-scale complex engineering structures, such as super high-rise buildings, large water conservancy projects, super-large space structure and so on. Their safety provides a strong guarantee for the national economy and the social environment. However, external and structural internal factors often lead to the accumulation of structural damage and the attenuation of resistance. Therefore, it is very possible to cause catastrophic accidents in extreme circumstances, resulting in casualties and property losses. The internal damage of the building structure is generally invisible. In order to understand the health of the structure and ensure the normal use of the structure, it is necessary to identify the damage of the structure, determine the location of the damage, and even the degree of damage. Only then can provide the scientific basis for the safe use of the structure in the later stage. In this paper, the widely used simply supported beam structure and story shear frame structure are taken as the research objects. Based on the improved curvature method and the data fusion method to study the damage of the structure, a more accurate method to identify the damage of the structure is proposed. The main research contents are as follows: (1) an improved curvature method is proposed to solve the defect that the existing curvature method can not identify the damage of the front and tail elements of the structure. The results of structural damage identification show that the improved curvature method can accurately identify the damage of the first and the tail elements of the structure under the different damage conditions of the simply supported beam structure and the shear frame structure. (2) the sensitivity of static displacement difference curvature, modal mode curvature difference, modal flexibility difference curvature and data fusion of these three structural damage indexes to the damage identification of simply supported beam and frame structure is studied. The numerical simulation results show that the static displacement difference curvature, modal mode curvature difference, modal flexibility difference curvature, data fusion can effectively identify the damage of the structure, and the data fusion has a certain sensitivity, and after data fusion, the sensitivity is higher. (3) the curvature of two adjacent elements of the damage element is obviously prominent when the curvature of static displacement difference curvature, modal mode curvature difference and modal flexibility difference curvature are used to identify the damage of the structure, which will lead to the misjudgment of structural damage. (4) when the static displacement difference curvature is used to identify the damage of simply supported beam and frame structure, the damage location of the structure can be effectively identified under the condition of single damage, double damage and multiple damage. (5) the static displacement difference curvature, modal mode curvature difference and modal flexibility difference curvature of simply supported beam and frame structure are fused, and then the damage of the structure is identified. The damage index after data fusion can highlight the curvature of the damage element and reduce the interference of the non-damage element. (6) the damage degree identification of simple beam structure and frame structure under single damage condition is studied. The results show that the improved curvature method and data fusion method can identify the damage degree of the structure, and the damage degree of the structure can be identified more accurately by cubic curve fitting.
【学位授予单位】:海南大学
【学位级别】:硕士
【学位授予年份】:2015
【分类号】:TU317
【参考文献】
相关期刊论文 前10条
1 吴海;邓宇;卢鹏;;谈基于结构动力响应的结构损伤检测[J];山西建筑;2014年14期
2 许成祥;徐晶金;倪铁权;;震后钢管混凝土结构损伤识别现状及展望[J];长江大学学报(自科版);2013年13期
3 李上明;路新瀛;;基于静态位移的简支桥梁损伤识别方法[J];甘肃科学学报;2011年02期
4 姜绍飞;胡春明;;基于模态指标与数据融合的钢管混凝土拱桥损伤识别[J];振动与冲击;2009年12期
5 姜绍飞;;结构健康监测-智能信息处理及应用[J];工程力学;2009年S2期
6 刘涛;李爱群;缪长青;李枝军;;基于数据融合的结构损伤识别方法研究[J];工程力学;2008年01期
7 王青;易成;王建强;;BP神经网络在悬臂柱损伤位置识别中的应用[J];低温建筑技术;2006年04期
8 谢正义,陈云飞;有限元分析在磁头悬架动态特性研究中的应用[J];机械制造与自动化;2005年05期
9 万小朋,李小聪,鲍凯,赵美英;利用振型变化进行结构损伤诊断的研究[J];航空学报;2003年05期
10 崔飞,袁万城,史家钧;基于静态应变及位移测量的结构损伤识别法[J];同济大学学报(自然科学版);2000年01期
相关博士学位论文 前3条
1 尚鑫;基于动力测试的桥梁损伤识别研究[D];长安大学;2014年
2 唐盛华;混凝土桥梁结构损伤识别试验研究[D];湖南大学;2013年
3 汪梅;基于小波和神经网络的电缆故障诊断方法研究[D];西安科技大学;2006年
相关硕士学位论文 前10条
1 滕亮;桥梁结构损伤识别指标比选及损伤程度识别方法研究[D];吉林大学;2014年
2 唐少玉;基于系统最小实现的结构损伤识别研究[D];兰州理工大学;2014年
3 李彦俊;基于拟静力荷载试验响应的桥梁损伤识别方法研究[D];重庆交通大学;2012年
4 吕淼;空间钢结构损伤识别研究[D];西安建筑科技大学;2010年
5 吕全金;混凝土连续梁桥损伤识别模型试验研究[D];西南交通大学;2009年
6 贾宝印;框架结构损伤识别研究[D];昆明理工大学;2008年
7 姜爱玲;黄河胜利大桥的损伤识别研究[D];大连理工大学;2006年
8 张杨;基于自振频率的梁损伤定位动力检测理论与试验研究[D];同济大学;2006年
9 黄带好;基于动力参数的剪切型结构损伤识别[D];重庆大学;2005年
10 邓苗毅;基于静载试验的梁桥结构损伤系统识别研究[D];郑州大学;2003年
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