| 摘要: | 本文旨在系統性探討振動驅動混合技術中，結構共振對顆粒混合效率之影響，並結合機電參數分析與影像追蹤方法，量化填充物在振動床中的動力行為與隨機動能分佈。首先，使用電流、位移和加速度同步掃頻實驗，辨識填充不同質量、材質（鋼珠、氧化鋁顆粒、水）填充條件下之共振頻率與阻尼比，並根據共振頻率值及半功率點法反推系統等效質量、剛度與阻尼參數。結果顯示，填充質量與顆粒性質對共振頻率具有顯著影響，且不同顆粒因接觸機制差異，使等效動力參數及頻率移動行為各異。
其次，於確定共振頻率後，固定激振電壓，並以高速攝影記錄顆粒運動，接著分別採用粒子影像測速（PIV）與粒子追蹤（PTV）技術重建速度場與顆粒軌跡。
此外，本研究引入「粒子溫度」作為量化顆粒擾動強度及混合狀態的指標，並透過高速影像追蹤結合 PIV／PTV 速度場重建，精準捕捉激振下顆粒的局部擾動與動能分佈。為進一步揭示激振參數對顆粒行為的主導作用，特別設計固定位移、速度與加速度振幅的實驗條件。
最後，本研究不僅驗證了結構共振為促進顆粒混合效率的最佳激振條件，亦提出一套結合電路響應分析與影像追蹤量測的完整流程，可同時定量顆粒系統之動力特性與微觀能量分佈，為未來振動混合設備的優化設計研究提供實證與方法學依據。
;This study systematically investigates the influence of structural resonance on mixing efficiency in vibration-driven mixing systems by integrating electromechanical parameter analysis with imaging-based particle tracking methods to quantify the dynamic behavior and random kinetic energy distribution of granular fill materials within a vibratory bed. First, synchronous frequency-sweep experiments measuring current, displacement, and acceleration were conducted to identify the resonance frequencies and damping ratios under varying fill conditions—steel spheres, alumina particles, and water—with different masses and materials. By applying the anti-resonance frequency and half-power point methods, the system’s equivalent mass, stiffness, and damping parameters were back-calculated. The results demonstrate that both fill mass and particle properties significantly affect the resonance frequency, and that differences in interparticle contact mechanisms lead to distinct equivalent dynamic parameters and frequency-shift behaviors.
After determining the resonance frequency, high-speed imaging was used to record particle motion under a fixed excitation voltage. Velocity fields and individual particle trajectories were then reconstructed using Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry (PTV), respectively. Moreover, this study introduces granular temperature as a metric to quantify particle fluctuation intensity and mixing state. By combining high-speed imaging with PIV/PTV-based velocity reconstruction, local disturbances and energy distributions under excitation were precisely captured. To further elucidate the dominant effects of excitation parameters on particle behavior, experiments were specifically designed to control displacement, velocity, and acceleration amplitudes.
Finally, this research not only confirms that structural resonance provides the optimal excitation condition for enhancing granular mixing efficiency, but also proposes a comprehensive workflow that integrates circuit-response analysis with imaging-based measurements. This framework enables simultaneous quantification of macroscopic dynamic characteristics and microscopic energy distributions within granular systems, offering empirical evidence and methodological guidance for the optimized design of future vibratory mixing equipment. |
