ECT-based Image Reconstruction Algorithm Study Of Aero-engine Gas Detection System

As a process tomography technology(PT) with the advantages of non-invasive,non-radiation, fast response speed, simple installation and low cost, electrical capacitance tomography(ECT) has become a very potential technique in the applications of visual detection of industrial process parameters, but it has not yet been applied to aircraft engine monitoring. The complex structure of aero-engine and the high temperature and high pressure working conditions of gas path components have largely restricted the application of traditional monitoring methods to this field. ECT-based aero-engine gas detection system provides the possibility of addressing these problems, providing a new working way for the new generation of aircraft engine exhaust gas monitoring. The images reconstructed with proper reconstruction algorithms on the computer platform can be used as an important reference for assessing aero-engine health. The image accuracy and resolution can directly affect the assessment of the working condition of aero-engine. Therefore, improving the accuracy of image reconstruction is quite necessary. According to the need, the following aspects of work are mainly carried out in this paper:1. The basic principle of ECT technique, the mathematical model of the forward and inverse problem and the principle of the reconstruction algorithm are analyzed. In order to detect the state of gas path, ECT sensor system of 16 plates is designed through the selection of electrode shape and number, the reasonable design of grounding shield and the parameters optimization of senor structure.2. The existing three types of non-iterative image reconstruction algorithms and four kinds of iterative reconstruction algorithms are studied in-depth, the basic idea and characteristics of each algorithm is introduced in brief. The simulation is completed in the way of combining use of MATLAB software and COMSOL software, the advantages and disadvantages and their applicable scope of each image reconstruction algorithm are determined by observing the pictorial diagram and comparing image error, correlation coefficient and evaluation parameters, etc.3. Tikhonov regularization algorithm and particle filter algorithm are studied and improved. Reconstruction results demonstrate that the improved Tikhonov regularization method can effectively reduce influence of the gross error and improve image reconstruction accuracy and spatial resolution; the improved particle filter algorithm compared with the iterative algorithms imaging is of better quality.4. In order to better determine the engine exhaust gas and improve the reliability of image reconstruction, CONTOURLET transform is applied to ECT reconstruction image post-processing, and image de-noising, image enhancement and image fusion processing are implemented.