本論文將衰減係數架構應用於實際工業機台上，透過該機台的振動變化量計算機台之衰減係數，不只可以判斷出機台現在所處的狀態與行為，還能依照不同的狀態與行為來判斷機台當下的健康程度。在同機型但不同個體的機台情況下還能對其健康程度做排序，由於衰減係數的計算，是透過振動變化量的自我比對，因此該計算模型可以套用在不同的機台上。 本論文將感測器與工業上的機台做結合，透過感測器來接收機台的振動數據，再依照振動數據來分析計算該機台的衰減係數，並與工廠端所提供的機台生產瑕疵來做對應，光是看振動很難直接看出差異，但透過衰減係數量化後，可以直接看出差異性。且衰減係數不止能對單一機台做狀態判斷，還可以對運作行為相同的機台做健康程度的比較，判斷出機台間的差異，如第一台的衰減係數為0.000166、第二台的衰減係數為0.000336，代表第二台較第一台更需要被維修，可以讓工廠端更準確對機台進行維修及換料等。實驗結果證明，透過振動衰減係數量測分析，(1)對新舊鑽石片切削力與工件破裂情況的比對100%吻合，(2) 加工機器的穩定狀況與工件破裂情況的比對100%吻合。 ;This paper applies the decay coefficient on practical industrial machinery. By calculating the vibration variation of the machine, the decay coefficient can be determined, enabling the identification of the current state and behavior of the machine, as well as assessing its health condition based on different states and behaviors. It is also possible to rank the health conditions of machines of the same model but different units. Since the calculation of the decay Coefficient involves self-comparison of vibration variations, this model can be applied to different machines. The paper combines sensors with industrial machinery. Vibration data from the machine is collected through sensors, and the decay coefficient of the machine is calculated based on this data. This coefficient is then correlated with the provided information on production defects by the factory. It is difficult to directly discern differences just by observing vibration patterns, but quantifying them through the decay coefficient allows for direct comparison. Furthermore, the decay coefficient can not only determine the status of an individual machine but also compare the health conditions of machines with similar operating behaviors, highlighting the differences between them. For example, the decay coefficient of the first machine is 0.000166, and decay coefficient of the second machine is 0.000336, which means that the second machine needs to be repaired more than the first machine, which allows the factory to more accurately repair and refuel the machine. The experimental results have demonstrated that through the analysis of vibration damping coefficients, (1) a 100% correlation was observed between the cutting forces of new and used diamond blades and the occurrence of workpiece fractures, and (2) a 100% correlation was observed between the stability of the machining equipment and the occurrence of workpiece fractures.
