基于贝叶斯网络的涡轴发动机多目标性能预测  

Multi-objective Performance Prediction of Turboshaft Engine Based on Bayesian Network

作　　者：王宁[1] 王宇航 蔡志强[2] 张帅[2] WANG Ning;WANG Yuhang;CAI Zhiqiang;ZHANG Shuai(School of Automobile,Chang’an University,Xi’an 710064,China;School of Mechanical Engineering,Northwestern Polytechnical University,Xi’an 710072,China)

机构地区：[1]长安大学运输工程学院,陕西西安710064 [2]西北工业大学机电学院,陕西西安710072

出　　处：《运筹与管理》2023年第3期177-183,共7页Operations Research and Management Science

基　　金：国家自然科学基金资助项目(71971030,71871181)。

摘　　要：涡轴发动机是一种高度复杂的精密热力机械,通常作为直升机的动力来源,其性能表现直接影响飞行任务的可靠性以及安全性。针对涡轴发动机的性能表现进行有效预测,可以指导生产,提高其出厂合格率,对于提升直升机的整机可靠性以及确保飞行任务的安全完成都具有重要意义。本文首先在已采集某型号涡轴发动机的数据基础上,结合厂家建议,提取出了影响涡轴发动机两个性能指标——功率与关键截面温度的四个属性变量,分别为零件1、零件2和零件3的尺寸以及气温。然后,引入目标生成、二元关联和分类器链三种多目标转换策略,分别结合贝叶斯网络构建了涡轴发动机多目标性能预测模型。最后,对各个模型的精度进行了对比和验证,选出了最优模型,可以对涡轴发动机的性能表现进行有效预测。The turboshaft engine is a kind of highly complex and precise thermal machinery,which is usually used as the power source of helicopter.Its performance directly affects the reliability and safety of flight missions.Turboshaft engines require a very high level of manufacturing.Typically,a qualified turboshaft engine requires two performance parameters:power and critical section temperature.However,in practice,it is difficult to manufacture an engine that can pass a single test run,often requiring several attempts after reassembly.Accurate and effective prediction of turboshaft engine performance can help to anticipate risks,which is important to improve the reliability of the helicopter and ensure the safe completion of the mission,as well as to guide the production process to improve the qualification rate.In recent years,with the development of computer technology and the rise of artificial intelligence and big data,Bayesian networks are increasingly used in the fields of data analysis and machine learning.Bayesian networks are a new type of probabilistic graphical model that combines the advantages of probability theory and graph theory to make the complex systems under study clear and understandable and to quantify,reconstruct and reason about complex systems.In the turboshaft engine performance prediction problem studied in this paper,two performance parameter target variables need to be considered together,which requires simultaneous determination of whether the two target variables of a turboshaft engine to be predicted can satisfy their respective qualifying conditions.Considering the practical research background,this paper combines each of the three multi-objective transformation strategies with Bayesian networks to construct a multi-objective performance prediction model for turboshaft engines,extend and improve the plain Bayesian classifier,and realize the prediction and analysis of multi-objective classification problems in the Bayesian network model.In this paper,based on the collected data of a cert

关 键 词：可靠性 贝叶斯网络 涡轴发动机 多目标 性能预测 

分 类 号：TB114.3[理学—概率论与数理统计]