农机化研究2025，Vol.47Issue(5)：28-33,42,7.DOI:10.13427/j.issn.1003-188X.2025.05.005
基于TLBO-LIBSVM的联合收割机振动筛螺栓故障诊断
Fault Diagnosis of Vibrating Screen Bolts in Combine Harvester Based on TLBO-LIBSVM
摘要
Abstract
Instantaneous impact and alternating load of vibrating screen of combine harvester during operation easily lead to failure of vibrating screen bolt structure.To solve the problem of fault diagnosis of vibrating screen bolts in combine har-vester,and proposed a fault diagnosis method of bolt failure based on multiple feature fusion TLBO-LIBSVM.By extrac-ting feature matrices,the time-domain features,frequency-domain features,and WOA-VMD energy entropy features were combined and normalized to obtain a multivariate fusion high-dimensional feature matrix,which was imported into the empirical parameter LIBSVM model.The success rates were 64.44％,74.44％,81.11％,and 90％,respectively.With the increasing dimension of the feature matrix,the failure feature information was constantly improved,and the rec-ognition success rate was constantly improved.At the same time,it also verified that the frequency domain feature sensi-tivity of combine harvester vibrating screen bolts was higher than the time domain feature.By using TLBO algorithm to op-timize the hyperparameter of LIBSVM model,the identification success rate under the optimal parameter combination was 98.89％,and the high-precision identification of bolt failure of combine harvester shale shaker was completed.This pro-vided a reference for the accurate diagnosis of combine harvester vibrating screen bolt fault.关键词
振动筛螺栓/变分模态分解/鲸鱼优化算法/支持向量机模型/教与学优化算法/故障诊断Key words
vibrating screen bolts/Variational Mode Decomposition(VMD)/Whale Optimization Algorithm(WO A)/Support Vector Machine(SVM)/Teaching-Learning-Based Optimization(TLBO)/fault diagnosis分类
农业工程引用本文复制引用
李鹏程,顾新阳,梁亚权,章浩,唐忠..基于TLBO-LIBSVM的联合收割机振动筛螺栓故障诊断[J].农机化研究,2025,47(5):28-33,42,7.基金项目
浙江省农作物收获装备技术重点实验室开放课题(2021KY02) （2021KY02）
国家自然科学基金项目(52275253) （52275253）
