In high-power microwave applications, the reflection of energy can be effectively reduced by adjusting the three-stub waveguide. However, most of the existing tuning algorithms do not make an arrangement for the adjustment sequence of stubs, and accurately calculating the depth of the stubs requires a great deal of time via electromagnetic (EM) simulations, which may cause large reflection in the matching process. To solve these problems, we first propose an improved calculation method that can accurately calculate the input impedance of a three-stub waveguide. Then, an impedance matching algorithm is designed based on the equivalent circuit model that can quickly and accurately calculate the optimal depth of the stubs. Finally, we present a low-reflection tuning strategy to suppress the large reflection during the adjustment of the stub process. An experimental system is built to verify the calculation method and the tuning strategy. The results show that the strategy can avoid large reflection in the case of load mutation and can maintain low reflection when the load changes continuously. The algorithm meets the needs of the industry and can be used for automatic and real-time adjustment of three-stub waveguides of different specifications.

In order to improve the uniformity of microwave heating, moving components are often added to the cavity. For higher uniformity or greater industrial processing capacity, samples often perform large-scale movements such as rotating and lifting motion or translational motion on a conveyor belt. The microwave heating algorithm based on the ray-casting method (RCM), as proposed in previous studies, can calculate moving complex-shaped samples, but the calculation efficiency is low when the sample moves on a large scale due to the large refined mesh area. To solve this problem, this study introduced a moving mesh combined with the RCM for calculation purposes. A microwave oven model with a rotating and lifting turntable was selected for the analysis. First, the calculation area was divided into a sliding mesh and a telescopic mesh area. The telescopic mesh area was stretched or compressed at different times, which was equivalent to the translational motion of the sample. Then, the electromagnetic parameters were assigned to each mesh point in combination with the boundary recognition algorithm based on the ray-casting method, and the horizontal motion was calculated while calculating the large-scale translation. The proposed method only needs to refine the mesh in the horizontal motion area, which reduces the number of overall meshes. The electromagnetic field distribution obtained by the model during the heating process was verified by the discrete position method. The surface temperature distribution and the real-time curve of the center point temperature were further compared with the RCM. The results show that the average error of the sample center temperature is 2.5% and the calculation time was reduced to 9.8%, which verified the accuracy and efficiency of the proposed method. Finally, the influence of different lifting and rotating speeds on the heating effect was further explored.