Planar array capacitance imaging is a feasible solution for detecting defects in composite components. However, the coplanar arrangement of electrodes in the imaging system renders a soft field effect, which results in unstable or susceptible imaging. The inverse problem of a planar array capacitance sensor system is ill-posed. Hence, a wavelet fusion combined multi-objective threshold programming imaging algorithm is proposed for a planar array capacitive imaging system. Furthermore, initial values of conjugate gradient (CG) and Newton–Raphson (NR) algorithms are optimized using the Tikhonov regularization algorithm. Subsequently, wavelet fusion is introduced to fuse images obtained using the CG and NR algorithms to acquire more detailed information. To further improve the reconstructed quality, a multi-objective threshold programming strategy is proposed. The final reconstruction image is obtained using the optimal threshold. Experimental results show a significantly improved quality of the reconstructed image, thereby verifying the effectiveness of the presented algorithm.

平面阵列电容成像是检测复合组件中缺陷的可行解决方案。但是，成像系统中电极的共面布置会产生软场效应，这会导致成像不稳定或敏感。平面阵列电容传感器系统的反问题是不恰当的。因此，提出一种用于平面阵列电容成像系统的小波融合多目标阈值编程成像算法。此外，使用Tikhonov正则化算法优化了共轭梯度（CG）和牛顿-拉夫森（NR）算法的初始值。随后，引入小波融合以融合使用CG和NR算法获得的图像，以获取更多详细信息。为了进一步提高重建质量，提出了一种多目标阈值规划策略。使用最佳阈值获得最终的重建图像。实验结果表明，重建图像的质量明显提高，从而验证了所提出算法的有效性。