Study On Stereo Vision Based Measurement Technology For Position And Attitude Of Wind Tunnel Model

In any wind tunnel test, measuring angle of attack accurately is crucial to improve the accuracy of experiment data. In addition, measuring other motion parameters of a wind tunnel model accurately is also important. For instance, a wind tunnel model in magnetic suspension and balance system is suspended stably by using the feedback signal of position and attitude (P&A) signal of wind tunnel model. Accelerometer and interferometric laser goniometer are usually used to measure angle of attack of a wind tunnel model in most domestic wind tunnel test nowadays, whereas stereo vision technology has been applied in wind tunnel test abroad. Comparing with traditional method for measuring P&A of a wind tunnel model, stereo vision based method can meaure P&A of a wind tunnel model simultaneously. This dissertation tries to explore the stereo vision based mehods for P&A measurement of a wind tunnel model, and study on some key problems associated with this method.Two stereo vision based methods for P&A measurement of wind tunnel models are proposed: active vision based method and passive vision based method. The first method is suitable for measuring P&A of huge wind tunnel models, while the second one is suitable for measuring those of miniature or micro wind tunnel models. The configurations of both P&A measurement systems are presented, and the corresponding P&A determination algorithms are also derived from the definition of Eular angles and the principle of coordinate transformation. Experiments with synthetic data have been made, and the experiment results can provide useful guidance for designing of a P&A measurement system. In addition, experiments with real data have also been made to validate the accuracy of both methods.The methods associated with stereo reconstruction of a point target are studied deeply. A mehod for calibrating camera accurately under broad field of view condition is proposed firstly. Then the methods for image feature detection, stereo matching and stereo reconstruction are also studied deeply. Comparing with other methods for camera calibration, the traditional one can meet the requirment of high accuracy. Whether can meaure the 3D coordinates of control points accurately is crucial to use the traditional method for camera calibration. A new approach to setting control points in three-dimensional space and measuring their 3D coordinates in the world coordinate system is proposed in this dissertation.Uncertainty of image feature detection and stereo reconstruction can be regarded as criterions for optimization of a stereo vision based measurement system. A mathematical model to evaluate the uncertainty associated with pixel intensity is poposed firstly. Once the parameters of the model to evaluate the uncertainty of pixel intensity and the correlation coefficients between the intensity of different pixels used to detect an image feature are determined by a statistical experiment, the uncertainty associated with feature detection can be determined according to the analytical expressions of a feature detection operator. Then an approach to evaluating the uncertainty associated with stereo reconstruction is proposed. The uncertainty propagation while calibrating cameras and reconstructing a 3D point from its image pairs are both taken into account, and the analytical expressions to evaluate the uncertainty of stereo reconstruction are presented. At last, genetic algorithm is used to solve the camera optimal placement problem in order to obtain minimal uncertainty of stereo reconstruction, and experiments with synthetic data have also been made.