Failure State Identification and Fault Diagnosis Method of Vibrating Screen Bolt Under Multiple Excitation of Combine Harvester

The demanding operational conditions of combine harvesters induce substantial vibrations and component degradation, significantly impacting harvesting efficiency, safety, and overall machine reliability. Bolt loosening, a critical failure mode at the joints of various working parts of combine harvesters, is a prevalent concern. The complexity and heterogeneity of vibration signals in these machines present a considerable challenge for the timely and accurate detection of bolt loosening. This paper proposes a novel methodology for identifying and diagnosing vibrating screen bolt failure states under multiple excitation conditions, specifically tailored for the 4LZY-1.8(PRO688Q) combine harvester. The study initially analyzes the critical torque associated with bolt connection failure. Subsequently, vibration signals are acquired from the bolt connection of the vibrating screen, and time-frequency analysis is performed to characterize the degree of bolt loosening, the predominant vibration direction, and the causative frequency components. A high-dimensional feature matrix is then constructed utilizing a Gaussian kernel function. The efficacy of the proposed methodology is evaluated through training and testing a classification decision model. This study provides a robust theoretical foundation for the vibration-based fault diagnosis of bolt structures in combine harvesters.