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作 者:张飞[1] 李凯翔[1] 白春玉[1] 刘继军[1] 李益萱[1] ZHANG Fei;LI Kaixiang;BAI Chunyu;LIU Jijun;LI Yixuan(Aircraft Strength Research Institute of China Xi'an,710065,China)
出 处:《振动.测试与诊断》2024年第3期589-593,625,共6页Journal of Vibration,Measurement & Diagnosis
摘 要:为了提高炮击振动环境谱编制精度,提出了基于遗传算法(genetic algorithm,简称GA)的炮击振动环境谱特征点确定方法。首先,介绍了现有标准的预估炮击振动谱的编制方法;其次,以炮舱结构模拟件为对象,开展了炮击振动试验并获取了实测谱,基于飞机飞行振动环境测量数据的归纳方法对实测谱进行了归纳处理;然后,以特征点构成的环境谱与实测数据归纳谱的能量最接近为目标建立目标函数,采用遗传算法对目标函数进行优化以确定炮击振动谱特征点坐标,在对数坐标下通过折线将特征点连接以实现炮击振动环境谱的编制;最后,将基于遗传算法得到的环境谱与基于标准得到的预估谱进行对比,分析验证了所提方法的有效性。结果表明,所采用的方法获得的炮击振动环境谱在均方根值(rootmean square,简称RMS)和谱形特征上都更接近实测数据归纳谱。In order to improve the preparation accuracy of the gunfire vibration environmental spectrum,a method for determining the feature points of gunfire vibration spectrum based on genetic algorithm(GA)is proposed.Firstly,the standard of the compilation method of the estimated gunfire vibration spectrum is introduced.Secondly,taking the simulator of the shell structure as the object,the gunfire vibration test is carried out and the actual measurement spectrum is obtained.The measured spectrum is summarized and processed based on the induction method for measuring data of aircraft flight vibration environment.Then,the objective function is established with the goal that the environmental spectrum composed of feature points is closest to the energy of the measured data induction spectrum.The objective function is optimized by the GA to determine the coordinates of the feature points of the gunfire vibration spectrum.Under logarithmic coordinates,the feature points are connected by lines to realize the compilation of the gunfire vibration environmental spectrum.Finally,through comparative analysis of the environmental spectrum and the prediction spectrum based on the GA and the prediction spectrum based on standard verifies the effectiveness of the proposed method.The results show that the gunfire vibration environmental spectrum obtained by the GA method is closer to the measured data in terms of root mean square(RMS)value and spectral characteristics.
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