| At present, with the improvement of speed and load of power machine such as aerospace, railway transport and highway transport, the extent of damage of safety accidents increasingly grows, where the safety accidents resulting from stress and fatigue life take a great part. Therefore, it is necessary to understand the stress and fatigue life of workpiece. Industrial computer tomography (CT) can get the image of workpiece section or three-dimension image of workpiece, which help for defect detection, stress analysis and fatigue life prediction. In this dissertation, we take industrial CT as research platform and CT image edges extraction as basis of research. A very close research on stress analysis with extended finite element method(XFEM), fatigue life prediction is made, which has significant meaning to improve the safety performance of workpiece.The contribution and novelty of this dissertation are as following:1. The two-dimensional image edges extraction method based on the local robust statistics and region-scalable fitting (RSF) model is studied. Intensity inhomogeneity often takes place in CT images, which may cause considerable difficulties in CT image edges extraction. In order to overcome the difficulties caused by intensity inhomogeneity, RSF model was put forward. This model draws upon intensity information in local regions at a controllable scale. But only using intensity information may lead to slow convergence speed and poor ability of noise reduction. In this dissertation, the intensity information of image in RSF model is replaced with local robust statistics which is the weighted combination of local inter-quartile range, local mean absolute deviation and local intensity median. Specifically, local inter-quartile range and local mean absolute deviation are introduced to sharpen target edges, and local intensity median is introduced to reduce image noise. Compared with the RSF model, the improved RSF model demonstrates the fast convergence rate and robustness to noise.2. The three-dimensional image edges extraction method based on the local robust statistics and three-dimensional C-V model is studied. Since the C-V model is capable of getting closed and accurate target contours, it has been widely applied to image edges extraction and extended to three-dimensional model. However, the existence of forged boundaries and noise may make active contours stop at the undesired boundaries. In order to overcome the difficulties caused by those effects, the three-dimensional C-V model is improved with robust statistics method. In this improved model, the intensity information of image in three-dimensional C-V model is replaced with local robust statistics information which is the weighted combination of local inter-quartile range, local mean absolute deviation and local intensity median. Here, local inter-quartile range and local mean absolute deviation are introduced to sharpen target edges, local intensity median to reduce image noise. Compared with the three-dimensional C-V model, the improved three-dimensional C-V model demonstrates high precision of image edges extraction and robustness to noise.3. A method of stress analysis of the embedded defect based on CT image edges extraction is studied. The software ANSIS of finite element method can draw vector graph of regular defect and analyze its stress. However, the stress distribution of irregular defect is not easy to be got by this software because the vector graph of the irregular defect is drawn with difficulty. In addition, in order to improve the accuracy of stress analysis of defect region, high dense meshes in this region are needed. In order to solve these problems, we design a flow for stress analysis of the casting defect based on CT image edges extraction. To analyze the stress of defect with arbitrary shape, we improve the XFEM used in stress analysis by using the level set function(LSF) in Chan-Vese(C-V) method to constitute enrichment function of XFEM. For regular defect, compared with the software ANSIS of finite element method, the flow for stress analysis of the casting defect in this dissertation can analyze embedded defect with arbitrary shape. The result of stress analysis with XFEM is as accurate as that with ANSIS, while high dense meshes in discontinuous region are not needed in XFEM. For irregular defect, this flow for stress analysis of the casting defect based on CT image edges extraction has been applied in analyzing the stress of defect in the side frame of railway freight car.4. A method for forecasting embedded crack propagation lifetime of work piece in service based on CT image edges extraction is studied. The propagation lifetime of surface cracks can be forecasted by the Paris method. Due to the difficulty of crack detection and the complexity of crack propagation, it is difficult to forecast the propagation lifetime of embedded cracks of work piece in service. In this dissertation , we present a flow for forecasting crack propagation based on CT image edges extraction, whereby the work piece containing the embedded crack is firstly scanned by industrial CT to obtain its images, extracting crack edges with the Canny operator. Secondly, in order to fit crack boundaries that have a large length-to-width ratio with an ellipse, a method of gradually shortening the length of ellipse's minor axis is developed. Finally, in order to improve predictions of crack lifetime durations, we combine this method with the formula of planar crack propagation to track its shape change.5. A method of fatigue life prediction of wheel in service based on CT image edges extraction is studied. Bending fatigue life is the most important performance of the wheel. At present, the fatigue life prediction is mainly applied to design model of the wheel while is not applied to the wheel in service. Here, we design a flow for fatigue life prediction of wheel in service based on CT image edges extraction. Firstly, the wheel is scanned to get a sequence of industrial CT images. After the CT images are processed by Gaussian filter, the 3-D surface model is extracted from the CT images by using Marching Cubes (MC) algorithm, and then simplified and smoothed by Vertex Removing(VR) algorithm and Laplacian algorithm respectively. Then the 3-D surface model is processed by the software UG. Finally, based on finite element method, the stress distribution of the wheel is acquired by simulating its work condition and building up a boundary condition. Moreover, the fatigue life of the wheel is predicted with nominal stress approach. Through this flow, the 3-D CAD model of the wheel can be rebuilt quickly and accurately according to its industrial CT data. The dangerous parts of the wheel can be located and the fatigue life of the wheel is realized.
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