Research On Detection Method Of Gear Microcrack Based On Tuned Resonance

As an important device for transmitting power and motion in the mechanical system,the gear is prone to fatigue damage and micro-cracks when subjected to cyclic alternating stress,and it is easy to cause the failure of the broken tooth as the crack gradually expands,thus causing huge Economic loss.Therefore,the detection and identification of micro cracks in gears is of great significance for ensuring the safe operation of equipment.In this paper,the detection method and feature extraction algorithm of cylindrical spur gear microcrack signal are studied.The main research contents include:(1)The principle of gear defect vibration and tuning resonance is studied.The gear vibration system model is established.The main factors causing the gear vibration are analyzed.Based on the amplification of the weak vibration signal caused by the microdefect of the gear,a tuning-based resonance is proposed.Gear micro crack detection method.(2)The gear defect detection system is studied,and the modal analysis of the gear defect detection system is carried out by the combination of finite element modal analysis and experimental modal analysis.According to the distribution of the first six modal frequencies of the system,the rotation speed of the detection gear is adjusted so that the gear meshing frequency and its harmonic frequency are close to the modal frequency of the gear fast detection system,so that the detection system reaches the tuning resonance state and the micro crack of the gear The signal is collected.(3)The law and expression of the micro-crack vibration signal of the gear are analyzed.The application of empirical mode decomposition(EMD)in signal denoising is studied.A gear defect feature based on correlation EMD and morphological singular value decomposition is proposed.The extraction algorithm and simulation analysis verify that the loss of useful components of the denoised signal and the defect characteristics are not easily recognized by the modal aliasing phenomenon in EMD decomposition,which highlights the defect characteristics of the original vibration signal and has a strong adaptive.(4)The comprehensive comparison and analysis of the gear microcrack defect signals under the tuned resonance and non-tuned resonance states of the experimental acquisition are carried out to identify the gear defect types,and the effectiveness of the tuning resonance based detection method in detecting the micro cracks of the gears is verified.The feature extraction algorithm based on correlation EMD and morphological singular value decomposition is applied to the processing of gear defect signals collected under non-tuned resonance state,and the effectiveness of the algorithm to accurately extract the characteristic signals of gear defects is verified.In summary,this paper focuses on the detection of micro-cracks in spur gears.and proposes a gear micro-crack detection method based on tuning resonance and a gear defect feature extraction algorithm based on correlation EMD and morphological singular value decomposition.Through simulation and experimental verification,the detection method and feature extraction algorithm are effective,which provides a new method and idea for the diagnosis of gear micro cracks.