| Gas-liquid two-phase flow widely exists in nature and industrial process. In recent years, with the extensive application of small-scale industrial devices, small-pipe gas-liquid two-phase flow has attracted more and more attention. However, research on small-pipe gas-liquid two-phase flow is still in the development stage, and corresponding parameter measurement methods are still limited. Therefore, study on parameter measurement techniques for small-pipe gas-liquid two-phase flow is of great academic and engineering value.High speed photography is a commonly used technique for flow characteristic analysis and parameter measurement of gas-liquid two-phase flow. It has the advantages of visualization, non-contact and instantaneity. Multi-vision system, which usually consists of multiple cameras or one camera with several optical components, can capture images from multiple directions. The multi-vision technique can overcome the inadequacy of the acquired space information and provide a new method for parameter measurement of small-pipe gas-liquid two-phase flow.In this thesis, based on multi-vision technique, the flow regime identification and void fraction measurement of gas-liquid two-phase flow in both vertical and horizontal small pipes are investigated. Main works and innovations are listed as follows:1. A multi-vision parameter measurement system for small-pipe gas-liquid two-phase flow is designed and established. This system consists of a fluid control unit, a multi-vision unit and a void fraction calibration unit. With this system, images of small-pipe gas-liquid two-phase flow can be captured simultaneously from two orthogonal directions. Experiments are carried out in horizontal and vertical pipes with the inner diameter of 2.1mm,2.9mm and 4.0mm, respectively. In horizontal pipes, bubble flow, slug flow, wavy flow and annular flow are observed, while in vertical pipes, bubble flow, slug flow and annular flow are observed.2. A flow regime identification method based on multi-vision data fusion technique is presented. Firstly, two image sequences are captured concurrently from two orthogonal directions, and the first four Hu-moments'means and the standard deviations of two image sequences are calculated to form the feature vectors. Secondly, according to the two image sequences, two single-vision flow regime identification models are established respectively based on the Support Vector Machine(SVM) algorithm, and flow regime is identified by the two models, respectively. Finally, the single-vision identification results are fused using D-S evidence theory to achieve the final flow regime identification results. Experimental results show that the identification accuracies of four typical flow regimes are all above 91%, and indicate that the proposed method based on multi-vision technique has higher identification accuracy than that of the method based on single-vision technique.3. A void fraction measurement method based on multi-vision technique is presented. According to the idea of integral accumulation, void fraction calculation models of every flow regime are established. Firstly, digital image processing techniques, such as segmentation, filtering, edge detection and binarization, are applied to the two image sequences captured from two orthogonal directions to get the corresponding binary image sequences. Secondly, the image distortion is corrected. Then, flow regimes are identified by using multi-vision data fusion method mentioned above. Finally, void fraction is determined by selecting the specific void fraction calculation model according to the flow regime identification result. Experimental results of void fraction measurement show that the absolute difference between measurement values and reference values are all less than 6%.This thesis verifies the feasibility of applying the multi-vision technique in small-pipe gas-liquid two-phase flow, and provides a good reference for parameter measurement of small-pipe gas-liquid two-phase flow. |
PDF Full Text Request