低速增压风洞测力试验异常数据检测专家系统设计研究  

Design and research on expert system for abnormal data detection in low-speed pressurized wind tunnel force test

作　　者：战慧强 张琦 梅家宁 孙晓宇 林沐 姚顺禹 Zhan Huiqiang;Zhang Qi;Mei Jianing;Sun Xiaoyu;Lin Mu;Yao Shunyu(AVIC Aerodynamics Research Institute,Harbin 150001,China;Key Laboratory of Aeronautical Science and Technology with Low Speed and High Reynolds Number,Harbin 150001,China)

机构地区：[1]航空工业空气动力研究院,哈尔滨150001 [2]低速高雷诺数航空科技重点实验室,哈尔滨150001

出　　处：《电子测量技术》2024年第6期123-130,共8页Electronic Measurement Technology

摘　　要：针对低速增压风洞测力试验,分析气动特性曲线的原始数据源,以天平信号、流场状态和模型姿态为主要对象,结合试验控制流程,从单点数据向量、单车次数据矩阵和同期多车次数据集等维度,研究试验数据的异常检测方法策略,并以此为核心知识库,完成异常数据检测专家系统设计开发。试验过程中系统推理机自动在线执行,经过数据识别、规则推理、逻辑推理和知识迭代,实现原始数据的预检测和预诊断。试验应用结果表明,专家系统对天平桥压异常、线性段跳点和零点检测等异常类型检测敏感度高,为异常数据分析指引方向,提升问题数据排查效率。Aiming at the force test in low-speed pressurized wind tunnel,the original data source of aerodynamic characteristic curve is analyzed.With the balance signal,flow field state and model attitude as the main objects,combined with the test control process,the abnormal detection methods and strategies of the test data are studied from the dimensions of single point data vector,single test data matrix and multi-test data set in the same period,and an expert system for abnormal data detection is designed and developed based on this core knowledge base.The system inference engine automatically detects online during the test,and realizes the pre-detection and pre-diagnosis of the original data through data identification,rule reasoning,logical reasoning and knowledge iteration.The experimental application results show that the expert system is highly sensitive to the detection of abnormal types such as abnormal bridge pressure,linear segment jump point and zero point detection,which guides the direction of abnormal data analysis and improves the efficiency of problem data investigation.

关 键 词：增压风洞 测力试验 异常数据检测 专家系统 

分 类 号：V211.71[航空宇航科学与技术—航空宇航推进理论与工程]