Work

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

Year: 2025

Type: article

Abstract: 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.

Source: Agriculture

DOI: 10.3390/agriculture15050455

Authors: Jiaojiao Xu, Tiantian Jing, Meng Fang, Pengcheng Li, Zhong Tang

Institutions: Shanghai University of Engineering Science, Jiangsu University

Language: English

Topic: Machine Fault Diagnosis Techniques

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Zero hunger, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $3,137