Non-destructive Detection Of The Adhesive Layer Of Spacecrafts Thermal Insulation Material Based On ECT

With the continuous development of space industry, heat damage problem has attracted more and more attention in the aerospace field. The bonding performance of thermal insulation materials is a guarantee to ensure the safe and stable operation of the spacecraft. Continuous development and innovation of thermal insulation materials provides a good thermal insulation protection to the spacecraft, meanwhile, it also brings a new requirement for the adhesive bonding performance of heat insulation materials. Countering the above problems, this paper carries on the following research work to the nondestructive testing method based on(Electrical Capacitance Tomography,ECT).(1)Aiming at the problem of heat insulation adhesive material layer defect detection, the paper puts forward a new method of nondestructive detection of insulation materials adhesive defects based on ECT. The method using electrical capacitance tomography methods for nondestructive testing, utilizing the electrical properties of adhesive natural medium and the physical properties of the dielectric constant change induced by different damage. In view of the plane structure characteristic of space thermal insulation material, the ECT defect detection system based on planar electrode was used.(2)By analyzing the traditional ECT principle and image reconstruction algorithm, an improved Landweber iterative ECT image reconstruction algorithm is proposed, and the initial value of the iteration is introduced. The paper solves the problem of iterative initial value deviation and then improves the quality of image reconstruction.(3) Poiningt at the sensitivity matrix S varies with the difference of the defect field and conventional iterative imaging algorithms are generally more dependent on the initial iterative values, a new detection method based on Improved Particle Swarm Optimization(PSO) for electronic electrical capacitance tomography(ECT) is proposed. The paper introduces the least square support vector machine processing method, and the error caused by the difference of sensitivity matrix is solved using least square support vector machine for data processing of the original measuring capacitance. Then the improved particle swarm algorithm which does not depend on the initial iteration information is used to reconstruct the image. Finally, the effectiveness of the improved algorithm is verified by experiments.