Damage Detection On The Simply Supported Beam With Curvature Modal Method

The development direction of modern project structures becomes more large-scale, complex and light-weighted. The operating safety is very important for these structures undergoing complicated service environments. It is necessary to survey the structure, detect and assess the damage grade. The damage detection is the main content for detection and assessment. This thesis has its practical value on the damage detection of a simply supported beam with curvature mode methods, rather than simulating structural damage through the element stiffness reduction approach. This thesis has four chapters.1. Introduced the significance and methods on structure damage detection. The achievements and shortcomings of damage identification at home and abroad is mentioned.2. Described the basic theory of the structure damage detection using modality curvature mode, and the main formulas of curvature mode parameters for damage identification.3. The curvature modes of simply supported beam with symmetry gap injury is studied, using ANSYS, the information of nodes on geometry axis and damage gap is obtained. Estimating parameters such as curvature mode,absolute differences in curvature mode,ratio of the curvature mode,mean curvature mode damage factor are studied with different damage degree. It is concluded that calculating accuracy of curvature mode parameters can be classified from high to low:absolute differences in curvature mode, mean curvature mode damage factor, curvature mode, ratio of the curvature mode. The curvature mode ratio may misjudge the result.4. The experiment results verified that the second derivative of response and its absolute difference are two sensitive indicators of the simple supported beam damage identification under moving loads, whether with single injury location or multiple. The second derivative absolute difference of response is more sensitive than the second derivative of response, and the curves changes more obviously, much easier to be judged, and has more higher accuracy.