基于大数据技术的船用柴油发动机零部件故障智能诊断  

Intelligent Fault Diagnosis of Marine Diesel Engine Parts Based on Big Data Technology

作　　者：张虹 崔宇峰 张亮 李卫强 段晔鑫 Zhang Hong;Cui Yu-feng;Zhang Liang;Li Wei-qiang;Duan Ye-xin(Zhenjiang Campus,Army Military Transportation University,Zhenjiang 212000,China)

机构地区：[1]陆军军事交通学院镇江校区,江苏镇江212000

出　　处：《内燃机与配件》2023年第15期73-75,共3页Internal Combustion Engine & Parts

摘　　要：为了提高柴油发动机零部件的故障诊断效果,提出基于大数据技术的船用柴油发动机零部件故障智能诊断方法。依据实际的测定需求及标准,进行故障信号的标定及分解;设计多层级的智能诊断节点部署形式,扩大实际的诊断范围;设计大数据融合诊断结构,构建大数据故障智能诊断模型,建立故障诊断特征识别矩阵,采用分类优化修正实现智能诊断。测试结果表明:此次所设计的诊断方法故障诊断残差控制在1.5以下,故障诊断效果较好,具有实际的应用价值。In order to improve the fault diagnosis effect of diesel engine parts,an intelligent fault diagnosis method of marine diesel engine parts based on big data technology is proposed.Calibrate and decompose the fault signal according to the actual measurement requirements and standards;Design the deployment form of multi-level intelligent diagnosis nodes to expand the actual diagnosis scope;Design the big data fusion diagnosis structure,build the big data fault intelligent diagnosis model,establish the fault diagnosis feature recognition matrix,and use classification optimization correction to achieve intelligent diagnosis.The test results show that the fault diagnosis residual of the designed diagnosis method is controlled below 1.5,and the fault diagnosis effect is good,which has practical application value.

关 键 词：大数据技术 船用柴油发动机 零件检测 

分 类 号：TP391[自动化与计算机技术—计算机应用技术] U664.1[自动化与计算机技术—计算机科学与技术]