| dc.description.abstract | 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. | en_US |