TY  - JOUR
AU  - MU, Xiaofei
AU  - LI, Bingran
AU  - GAO, Qiantong
AU  - YE, Peiqing
AU  - ZHANG, Hui
PY  - 2025
TI  - Energy consumption optimization strategy for linear motors in multi-leaf collimator
JO  - Journal of Tsinghua University (Science and Technology)
SN  - 1000-0054
SP  - 891
EP  - 900
VL  - 65
IS  - 5
AB  - ObjectiveMedical linear accelerator is a high-end piece of equipment used in cancer radiotherapy. A key component of this system is the multi-leaf collimator (MLC), which considerably influences the accuracy and efficiency of radiotherapy. This study examines the fast MLC, which employs a two-phase permanent magnet synchronous tubular linear motor (PMSTLM) to directly drive the leaves and enhance the precision of radiation dose distribution. However, factors such as inductance, magnetic chain, and resistance in the PMSTLM are influenced by temperature changes, resulting in parameter changes that affect the current loop's steady-state error. Moreover, drastic fluctuations in current result in increased energy consumption. The heightened energy usage negatively impacts the blade motion accuracy, thus compromising the overall quality of radiotherapy. The objective of this study is to address these challenges by reducing the energy consumption of linear motors used in MLC.MethodsThis study proposes a method for optimizing the energy consumption of linear motors in MLC by improving velocity planning at the instruction level of the control system. To address the issue of kinematic constraints not fully utilizing the motor thrust, a dynamic friction coefficient is introduced to determine the moment boundary of the motor thrust. Based on this boundary, an improved exponential acceleration and deceleration speed planning method is developed. Furthermore, acceleration distance and deceleration characteristic coefficients are introduced as independent variables. The mapping relationship between full-stroke energy consumption, the transition time of the displacement section in the middle of the motor travel, and these coefficients is established. Using this relationship, an optimization model for energy consumption, transition time, and speed planning is formulated. The second-generation non-inferiority sorting genetic algorithm (NSGA-Ⅱ) is employed to perform multi-objective optimization of energy consumption and transition time. The result is utilized as commands for the controller and is validated through experimental testing.ResultsThrough the proposed method, this study achieved acceleration and deceleration planning results with constant transition time and relatively low energy consumption for the full stroke. Experimental data indicate that the method reduces energy consumption by 21.5%, compared to trapezoidal acceleration-deceleration planning (TSP) under identical transition time conditions. The proposed method effectively reduces the energy consumption of PMSTLM operation while maintaining the normal functional requirements of the MLC.ConclusionsThe energy consumption optimization method proposed in this paper combines exponential acceleration and deceleration planning, an energy consumption-transition time speed planning model, and the NSGA-Ⅱ algorithm to enhance the performance of MLC. Based on theoretical research and experimental validation, the following conclusions are drawn. The proposed method can optimize the intermediate displacement section corresponding to the transition time by effectively utilizing the velocity peak. This is achieved by choosing appropriate acceleration distances and deceleration characteristic coefficients. Transition time and energy consumption are conflicting optimization objectives. By employing the energy consumption-transition time optimization model, choosing appropriate optimization parameters can considerably reduce energy consumption while ensuring that the transition time meets the performance requirements of the MLC. The experimental results verify the effectiveness of the proposed method. Energy consumption is reduced by 21.5% compared to that of the TSP method.
UR  - https://doi.org/10.16511/j.cnki.qhdxxb.2024.21.038
DO  - 10.16511/j.cnki.qhdxxb.2024.21.038