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作 者:吴会咏[1] 靳舒春 金铸[2] WU Huiyong;JIN Shuchun;JIN Zhu(College of Science,Shenyang University of Chemical Technology,Shenyang 110142,Liaoning,China;Neusoft Corporation,Shenyang 110179,Liaoning,China)
机构地区:[1]沈阳化工大学理学院,辽宁沈阳110142 [2]东软集团股份有限公司,辽宁沈阳110179
出 处:《济南大学学报(自然科学版)》2022年第5期580-591,共12页Journal of University of Jinan(Science and Technology)
基 金:国家自然科学基金项目(62073157)。
摘 要:为了有效地识别飞机空气循环系统组件是否发生故障,区分故障类型,并作出对应的维修策略,提出一种基于改进支持向量机的飞机空气循环系统故障诊断方法;首先建立飞机空气循环系统仿真模型,然后将支持向量机运用于飞机空气循环系统,引入蚱蜢优化算法、位置随机偏移机制和模拟退火算法,对支持向量机进行参数优化,最后参考最优参数对飞机空气循环系统仿真模型进行训练。结果表明,建立的飞机空气循环系统仿真模型可以模拟不同情况下飞机空气循环系统主要组件的出口温度以及故障发生时的出口状态,加入蚱蜢优化算法等优化方式的支持向量机系统达到了简化调节参数、加快收敛、提高收敛精度的目的,可以根据多样本数据进行训练,完成故障分析。To effectively identify faults of aircraft air circulation system components, distinguish fault types, and make corresponding maintenance strategies, a fault diagnosis method of aircraft air circulation systems based on improved support vector machine was proposed. A simulation model of aircraft air circulation systems was firstly established, and then the support vector machine was applied to the aircraft air circulation system. Grasshopper optimization algorithm, position random migration mechanism, and simulated annealing algorithm were introduced to optimize parameters of the support vector machine. The simulation model of aircraft air circulation systems was finally trained by referring to optimal parameters. The results show that the established air circulation system simulation model can simulate outlet temperature of main components of aircraft air circulation systems under different conditions and outlet state when fault occurs. The support vector machine system with grasshopper optimization algorithm and other optimization methods achieves the purpose of simplifying adjustment parameters, accelerating convergence, and improving convergence accuracy, which can be trained according to various data to complete fault analysis.
关 键 词:空气循环系统控制 故障分析 支持向量机 参数优化
分 类 号:O23[理学—运筹学与控制论]
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