发动机连杆恒定机械拉压损伤自适应检测方法
Adaptive Detection Method for Constant Mechanical Tension and Compression Damage of Engine Connecting Rod
杨治 1彭蕾 1涂起龙1
作者信息
- 1. 井冈山大学电子信息工程学院,江西 吉安 343009
- 折叠
摘要
为提高现有发动机连杆拉压损伤检测方法的检测准确率和检测效率,提出发动机连杆恒定机械拉压损伤自适应检测方法.该方法首先研究发动机连杆的机械运动原理及连杆受恒定机械拉压强度影响的分析,然后获取与发动机连杆机械拉压相关的相对损伤分布数据,计算各项相对损伤分布数据所对应的连杆损伤程度,最后利用遗传算法完成概率神经网络模型的优化,基于上述得到的损伤数据建立连杆恒定机械拉压损伤自适应检测模型,实现发动机连杆恒定机械拉压损伤自适应检测.实验结果表明:所提方法检测准确率高于88%,检测时间不超过0.4s,均优于对比方法,具有一定研究价值.
Abstract
In order to improve the detection accuracy and efficiency of the existing detection methods for tensile and compressive damage of engine connecting rods,an adaptive detection method for constant mechanical tensile and compressive damage of en-gine connecting rods is proposed.This method first studies the mechanical movement principle of engine connecting rod and the analysis of the influence of the connecting rod on the constant mechanical tensile and compressive strength,then obtains the rela-tive damage distribution data related to the mechanical tensile and compressive strength of engine connecting rod,calculates the damage degree of connecting rod corresponding to each relative damage distribution data,and finally uses genetic algorithm to complete the optimization of probabilistic neural network model,Based on the above damage data,an adaptive detection model of the constant mechanical tensile and compressive damage of the connecting rod is established to realize the adaptive detection of the constant mechanical tensile and compressive damage of the engine connecting rod.The experimental results show that the de-tection accuracy of the proposed method is higher than 88%,and the detection time is less than 0.4s,which is superior to the com-parison method and has certain research value.
关键词
发动机/连杆/机械拉压强度/相对损伤分布数据/概率神经网络模型Key words
Engine/Connecting Rods/Coercion Strength/Relative Damage Distribution Data/Probabilistic Neu-ral Network Model引用本文复制引用
基金项目
江西省教育厅科学技术研究一般项目(GJJ211031)
吉安市科技支撑项目(吉安市科技局)(吉市科计字2021[8]号基础1)
出版年
2024
NETL
NSTL
维普
万方数据