The axial flow characteristics are crucial for studying flow in pneumatic conveying systems and fluidized beds. The main challenge in electrical capacitance tomography (ECT) axial imaging is the limited number of electrodes, which typically results in only 2-4 planes of axial coverage, leading to a restricted imaging range. This limitation significantly hampers the ability to achieve comprehensive axial imaging, constraining the overall monitoring range in the system. To enhance the axial imaging capability of 3-D ECT, the structure of a 32-electrode, eight-plane ECT sensor is optimized to increase its axial length, thereby extending the imaging range while maintaining imaging quality. Simulations were conducted for three different height-to-diameter ratios (HDRs) of 7.8, 14.3, and 20.7. The sensor structure is optimized in terms of electrode shape, length, spacing, and arrangement. Adaptive total variation regularized-projected gradient descent (ATV-PGD) image reconstruction algorithm is proposed to capture internal structural details accurately while effectively suppressing noise and artifacts. This is achieved by optimizing an objective function that integrates data consistency and image smoothness, and the algorithm is designed to maximize the axial imaging length while ensuring that the overall imaging quality along the sections is maintained. The imaging effectiveness of the sensor for continuous and intermittent flows is validated using predetermined cylinder flow and uniformly spaced sphere flow. Final experiments confirm the efficacy of the proposed algorithm and sensor structure in achieving high-quality axial imaging.