To reduce the impact of machining vibration on the machining quality of the assembly interface of large aircraft in finishing, it is necessary to understand the dynamic characteristics and the modal parameters of the assembly interface. Hence, an optimized Space Time Domain (STD) method is proposed to identify the modal parameters during the dynamic finish machining. Firstly, a Toeplitz matrix is generated by the measured machining vibration data of the assembly interface and is treated as the input of the STD method. Secondly, the relative stable modal parameters are selected as the modal parameters of the assembly interface in terms of the modal confidence factor and the Modal Assurance Criterion (MAC). Finally, the correctness and effectiveness of the optimized STD method are validated through impact tests and cutting experiments. In detail, the results of the impact test are regarded as the referenced modal parameters of the assembly interface. Taking the 1st-order modal identification result as an example, the modal identification accuracy of the optimized STD method is improved by 12.7% and 3.82% compared with the traditional STD and SSI methods. The identification accuracy of the modal parameters of the rest orders can also be improved to a certain extent as well. Therefore, the modal parameters of the assembly interface can be accurately and efficiently identified via the optimized STD method, which can theoretically and technically support the reasonable selection of the finish machining parameters.
[1] LEI P, ZHENG L. An automated in-situ alignment approach for finish machining assembly interfaces of large-scale components[J]. Robotics and Computer-Integrated Manufacturing, 2017, 46:130-143.
[2] 陈仁良, 李攀, 吴伟, 等. 直升机飞行动力学数学建模问题[J]. 航空学报, 2017, 38(7):520915. CHEN R L, LI P, WU W, et al. A review of mathematical modeling of helicopter flight dynamics[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(7):520915(in Chinese).
[3] WAN X J, HUA L, WANG X F, et al. An error control approach to tool path adjustment conforming to the de-formation of thin-walled workpiece[J]. International Journal of Machine Tools & Manufacture, 2011, 51(3):221-229.
[4] 杨毅青, 刘强, Muoa Jokin. 基于实验模态分析的集中参数法建模[J]. 振动、测试与诊断, 2010, 30(6):621-625, 707. YANG Y Q, LIU Q, MUOA J. Investigation of lumped modal based on experimental modal analysis[J]. Journal of Vibration, Measurement & Diagnosis, 2010, 30(6):621-625, 707(in Chinese).
[5] 刘宇飞, 辛克贵, 樊健生, 等. 环境激励下结构模态参数识别方法综述[J]. 工程力学, 2014, 31(4):46-53. LIU Y F, XIN K G, FAN J S, et al. A review of structure modal identification methods through ambient excitation[J]. Engineering Mechanics, 2014, 31(4):46-53(in Chinese).
[6] 史东锋, 许锋, 申凡, 等. 结构在环境激励下的模态参数辨识[J]. 航空学报, 2004, 25(2):125-129. SHI D F, XU F, SHEN F, et al. Modal parameter identification of structure in ambient excitation[J]. Acta Aeronautica et Astronautica Sinica, 2004, 25(2):125-129(in Chinese).
[7] 徐辰奎, 刘国明, 杨亮. 基于随机减量和时域ITD法的重力坝模态参数识别[J]. 水利与建筑工程学报, 2015(6):178-182. XU C K, LIU G M, YANG L. Modal parameter identification of gravity dams based on ITD method and random decrement technique[J]. Journal of Water Resources and Architectural Engineering, 2015(6):178-182(in Chinese).
[8] 孟昭博, 胡博森, 赵庆双, 等. 基于STD法的光岳楼木结构自振频率计算[J]. 聊城大学学报(自然科学版), 2015, 28(4):37-41. MENG Z B, HU B S, ZHAO Q S, et al. Natural frequency calculation of guangyue tower based on the method of STD[J]. Journal of Liaocheng (Natural Science), 2015, 28(4):37-41(in Chinese).
[9] JUANG J N. Applied system identification[M]. Englewood Ciffs, New Jersey:Prentice-Hall Inc, 1994.
[10] 付志超, 仲维国, 陈志平, 等. 大展弦比柔性机翼的结构动力学特性试验研究[J]. 航空学报, 2013, 34(9):2177-2184. FU Z C, ZHONG W G, CHEN Z P, et al. Experimental study on structural dynamic characteristics of flexible high-aspect-ratio wings[J]. Acta Aeronautica et Astronautica Sinica, 2013, 34(9):2177-2184(in Chinese).
[11] 张永祥, 刘心, 褚志刚, 等. 基于随机子空间法的模态参数自动提取[J]. 机械工程学报, 2018, 54(9):187-194. ZHANG Y X, LIU X, CHU Z G, et al. Autonomous modal parameter extraction based on stochastic subspace identification[J]. Journal of Mechanical Engineering, 2018, 54(9):187-194(in Chinese).
[12] BOONYAPINYO V, JANESUPASAEREE T. Data-driven stochastic subspace identification of flutter derivatives of bridge decks[J]. Journal of Wind Engineering and Industrial Aerodynamic, 2010, 98(12):784-799.
[13] 李团结, 刘伟萌, 唐雅琼, 等. 一种改进的识别结构模态参数的随机子空间法[J]. 西安电子科技大学学报(自然科学版), 2017, 44(6):26-30. LI T J, LIU W M, TANG Y Q, et al. Improved stochastic subspace method for identification structural modal parameter[J]. Journal of Xidian University (Natural Science), 2017, 44(6):26-30(in Chinese).
[14] YANG Y, YANG H, LI P, et al. A roller bearing fault diagnosis method based on the improved ITD and RRVPMCD[J]. Measurement, 2014, 55:255-264.
[15] 杜飞平, 谭永华, 陈建华. 基于ITD和STD的液体火箭发动机模态参数辨识方法[J]. 火箭推进, 2012, 38(3):34-39. DU F P, TAN Y H, CHEN J H. ITD and STD based identification for modal parameters of liquid rocket engine[J]. Journal of Rocket Propulsion, 2012, 38(3):34-39(in Chinese).
[16] 杨佑发, 李帅, 李海龙. 环境激励下结构模态参数识别的改进ITD法[J]. 振动与冲击, 2014, 33(1):194-199. YANG Y F, LI S, LI H L. Improved ITD method for structure modal parameter identification under ambient excitation[J]. Journal of Vibration and Shock, 2014, 33(1):194-199(in Chinese).
[17] 张小宁, 段忠东. 一种自动识别结构模态参数的随机子空间方法[J]. 振动工程学报, 2017, 30(4):542-548. ZHANG X N, DUAN Z D. A stochastic subspace identification method for automotive identification of structural modal parameters[J]. Journal of Vibration Engineer, 2017, 30(4):542-548(in Chinese).
[18] 李树侠, 朴松花. 钛合金材料的机械加工工艺综述[J]. 飞航导弹, 2007(7):57-61. LI S X, PIAO S H. A review of mechanical processing technology of titanium alloy materials[J]. Aerodynamic Missiles Journal, 2007(7):57-61(in Chinese).