Research On Sparse Transducer Array And Its Application In Structure Health Monitoring

The health monitoring on plate-like structure such as large oil storage tanks, thewing and skin of aircraft has important economic significance and academic value.In this paper, based on the finite element simulation and experimental researchmethods, the ultrasonic Lamb wave technology is applied to health monitoring oflarge plate structures. Firstly, based on three-dimensional finite element model,Lamb wave propagation characteristics in the structure of plate and the scatteringfield distribution of the defect are studied, which laid a solid foundation for therealization of location and recognition of defects. Secondly, based on support vectormachine (SVM) method implements the classification and recognition of round holedefect with different geometry parameters. Finally, using optimization sparse sensorarrays for detecting a single or double defects at different position, and through thetwo imaging algorithms to achieve accurate positioning of the defect. The specificresearch work are as follows:(1) According to the dual incentive theory of Lamb wave, stimulate the singleS0, A0and SH0modal in three-dimensional finite element model, and use the wavestructure characters to separate the mode of Lamb wave. In order to achieve thehigh-precision extraction of defect scattering field distribution, using the absorbingboundary method based on increasing damping coefficient in three-dimensionalfinite element model, and through the analysis of the characteristic parameterprovides an optimal absorbing boundary.(2) Putting forward high precision recognition method based on support vectormachine (SVM). First of all, using distributed sensor in structure to collect defectsignals, and then scattering coefficient matrix displacement compensation algorithmto solve the defects; Second, by three-dimensional finite element simulation to studythe defect in the round hole diameter and depth parameter changing of S0modalcharacteristics of scattering coefficient, using support vector machine (SVM)method for different depth of the hole feature information classification; On thisbasis, according to the defects of structure health damage defects can be divided intofour categories, more than class support vector machine (SVM) model is established,the classified effect is good, can identify the defect types of structure health risk isbigger. (3) Set the sparse sensor array based structure health monitoring experimentsystem, realized the two kinds of defect imaging localization algorithm based on thewave packet propagation distance, ellipse and hyperbola algorithms. To fully roundhole and slot type crack two typical defects, for example, by analyzing thecharacteristics of the scattering coefficient matrix respectively, and studies thedifferent sensor array distribution of different types of defects detection effect, drawfor different types of defects for the optimal array form.