تجزيه و تحليل اثرات سايش بر ارتعاشات چرخ‌دنده‌هاي جعبه‌دنده‌صنعتي

Gears, as one of the main components of power transmission systems, play a crucial role in various industries. The occurrence of defects such as wear an‎d fatigue pitting on their tooth surfaces can lead to increased vibrations, reduced service life, an‎d ultimately gearbox failure. Therefore, identifying, monitoring, an‎d predicting the growth of these faults during the operation of gearboxes without stopping them, using non-destructive methods, particularly vibration analysis, is of special importance. The objective of this research is to investigate the effect of surface wear an‎d fatigue pitting on the dynamic an‎d vibrational response of spur gears, as well as the feasibility of detecting these defects through vibration signal analysis. To this end, a combined approach based on the coupling of a discrete dynamic model, the Archard wear model, an‎d the fatigue pitting model has been developed. For validation, experimental tests were conducted using a test rig consisting of a gearbox, a magnetic brake, an‎d an electric motor to obtain variations in vibration signals an‎d updat‎e the coefficients of the proposed models. Accordingly, another main objective of this research is to design an‎d construct a test bench that not only enables the experiments required for this study but also allows future investigations into the effects of other types of gear an‎d gearbox failures on dynamic responses an‎d vibration signals through further testing. The results of simulations an‎d experiments indicate that the progression of wear an‎d the increase in the density of fatigue pits lead to variations in mesh stiffness, contact forces, an‎d vibration signal characteristics. These variations enable the detection an‎d monitoring of surface gear defects at their early stages. The findings of this study demonstrate that employing coupled dynamic–tribological models provides an effective tool for predicting the vibration behavior of worn gears an‎d can serve as a practical approach for predictive maintenance of industrial gearboxes. By analyzing the variations in vibration signal characteristics an‎d the recorded patterns, an‎d through updating the wear an‎d fatigue-pitting models, it becomes possible to predict the occurrence an‎d progression of wear an‎d fatigue-related failures in other gears an‎d gearboxes as well.

صالح اكبرزاده , علي لقماني

سعيد ضيائي راد , محمدرضا فروزان