有別於其他的研究方法以量測訊號分析的方式，本論文嘗試以主動輸入訊號的方式，藉由觀察機械手臂末端點位置輸出，判斷系統是否有異常。本論文使用平面三連桿手臂為例，分別對三個關節設計不同的軌跡，三個關節同時依軌跡指令移動。選擇移動的過程手臂的末端點維持在相同的位置之路徑軌跡，一旦馬達出現異常使角度輸出產生變化，造成輸出的軌跡偏移原先預設的軌跡，即末端點位置移動，藉此判斷出為故障狀態。本論文針對機械手臂中直流馬達的五種參數(電阻、電感、馬達常數、轉動慣量和黏滯係數)進行模擬，這五種參數因為不同的異常而產生數值上微小的變動，在模擬結果中也會使軌跡產生偏移造成末端點位置有大小不同的變化量。研究中最後再比較何種參數易造成末端點最大的位移量，探討所提方法對不同異常之靈敏度。
本論文的想法源自於Suhada Jayasuriya的文獻，用系統零點的觀念去觀察系統動態的變化。以系統零點輸入條件當作系統指令時，當系統輸出不再為零，就能判斷出系統出現問題。由於機械手臂是ㄧ種高度非線性的系統，其零點求解複雜。本研究改用彼此關節幾何軌跡的組合去達到手臂輸出為零，也就是末端點的位移量為零的輸入指令方式，去判斷是否出現異常。最後經由動態模型異常模擬得知馬達常數異常會導致不同程度的端點位移變化，其程度依序是電阻、轉動慣量、摩擦係數與電感。

Different from other research methods used in signal based analysis, this research attempted to observe the end point output position in a robotic arm to detect system anomaly. Designed input signal actively used to determine whether a system is faulty or not. In the simulation, a three joints planar three-links robot moved according to designed command inputs which guarantee the end point trajectories being still for a healthy robot. If a fault exists, it should cause robot’s motion to deviate from the desired trajectories and thus signals an anomaly condition. This property is actively used to determine a robot’s condition. In the study, the resistance, the inductance, the motor constant, the moment of inertia and the viscosity coefficient of a permanent magnet motor is varied to simulate real faults in a robot arm. These five parameters cause output change due to respective faulty conditions and the results are compared.
The idea of this research is inspired from previous work of Suhada Jayasuriya, who actively detect system fault with zero property. Under zero inputs commands, the system output will not be “zero” while system dynamics change due to faults. Because of the highly nonlinearity of robot’s dynamics, it is complicate and tedious to find zeros and zero inputs directly via its equation of motions. Instead, a set of desired input command is designed which generate zero endpoint output by solving robot geometric equations and curve-fitting.

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