Capacitive Imaging Technique for the Inspection of Composite Sucker Rod

Composite sucker rod has been extensively used due to its high strength, light weight and corrosion resistive nature. However, such composite sucker rod is diffcult for conventional non-destructive evaluation(NDE) techniques to inspect because of its complex material and/or structure. It is thus useful to embark research on developing novel NDE technique to comply the inspection requirement. This work demonstrates the feasibility of using the capacitive imaging(CI) technique for the inspection of composite sucker rod. Finite element(FE) models were constructed in COMSOL to simulate the detection of defects in the glass-fiber layer and on the carbon core surface. An FE Model based inversion method is proposed to obtain the profile of the carbon core. Preliminary CI experimental results are then presented, including the detection of surface wearing defect in the glass-fiber layer, and obtaining the profile of the carbon core. A set of accelerated aging experiments were also carried out and the results indicate that the CI technique is potentially useful in evaluating the ageing status of such composite sucker rod. The CI technique described in this work shows great potential to target some challenging tasks faced in the non-destructive evaluation of composite sucker rod, including quality control, defect detection and ageing assessment.

An ECT System Based on Improved RBF Network and Adaptive Wavelet Image Enhancement for Solid/Gas Two-phase Flow

Electrical capacitance tomography(ECT) is a non-invasive imaging technique that aims at visualizing the cross-sectional permittivity distribution and phase distribution of solid/gas two-phase flow based on the measured capacitance.To solve the nonlinear and ill-posed inverse problem:image reconstruction of ECT system,this paper proposed a new image reconstruction method based on improved radial basis function(RBF) neural network combined with adaptive wavelet image enhancement.Firstly,an improved RBF network was applied to establish the mapping model between the reconstruction image pixels and the capacitance values measured.Then,for better image quality,adaptive wavelet image enhancement technique was emphatically analyzed and studied,which belongs to a space-frequency analysis method and is suitable for image feature-enhanced.Through multi-level wavelet decomposition,edge points of the image produced from RBF network can be determined based on the neighborhood property of each sub-band;noise distribution in the space-frequency domain can be estimated based on statistical characteristics;after that a self-adaptive edge enhancement gain can be constructed.Finally,the image is reconstructed with adjusting wavelet coefficients.In this paper,a 12-electrode ECT system and a pneumatic conveying platform were built up to verify this image reconstruction algorithm.Experimental results demonstrated that adaptive wavelet image enhancement technique effectively implemented edge detection and image enhancement,and the improved RBF network and adaptive wavelet image enhancement hybrid algorithm greatly improved the quality of reconstructed image of solid/gas two-phase flow [pulverized coal(PC)/air].