复合材料板壳结构载荷识别
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摘要
智能结构是一种能感知周围环境变化,并能针对这种变化做出适当反应的自感知─自适应结构,基于压电、光纤等新型传感器的结构健康监测研究受到国内外学者的广泛关注,本文从航空航天等领域利用压电智能结构进行结构健康监测的工程背景出发,对压电智能结构的载荷识别方法进行了较深入、系统的研究。
论文采用遗传算法和有限元相结合的方法,实现复合材料结构载荷大小和位置的识别,并着重对染色体的编码方式进行了深入研究。以荷载作用位置的结点号和荷载大小为参数的二进制编码方法简单、高效,但存在连续函数离散化时的映射误差,且其编码串的长度取决于所要求的识别精度,过长的染色体会影响算法的计算效率;以二进制编码表征载荷作用位置,浮点数编码表示载荷大小的混合编码方法,大大降低了染色体的长度,显著提高了计算效率和精度,可难以实现非网格结点处的载荷识别;论文首次提出了一种受载单元判别法,根据染色体所对应的载荷作用点的横、纵坐标和每个单元四条边间的几何关系,判断出集中载荷作用的单元,再根据力的等效分配原则,把载荷等效分配到所在单元的结点上,进而基于有限元分析和遗传算法自身优越的全局搜索能力实现作用于复合材料结构网格结点或单元内部任意位置处的载荷识别,与现有的神经网络识别法和有限元反分析法相比,本方法具有能够识别非网格结点处的载荷的优点,且仿真算例表明其识别精度更高;在对静载荷识别研究的基础上,本文研究了作用于任意位置处的冲击载荷时间历程反演和冲击位置判别方法。仿真算例表明了本文方法对冲击载荷历程反演及位置识别的有效性。
Smart structure is a kind of self-sensing and self-adaptive structure that can sense the change of the surrounding environment and can make an appropriate response in response to this change. Structural health monitoring based on the new type of sensors such as piezoelectric, optical fiber sensors, has drawn extensive attention from scholars at home and abroad. In this article, a further and systematic study about the load identification of piezoelectric smart structure was conducted in the engineering background of using piezoelectric smart structures for structural health monitoring in the aviation and aerospace areas.
This paper used the method of combining genetic algorithms and finite element method to achieve the identification of amplitude and location of the load acted on the composite material structure, having a deep research on the chromosome encoding methods. The method that encoded the load amplitude and location with binary encoding method is simple, efficient, but there is a mapping error in the continuous function discretization. The string length depends on the required identification accuracy, and long chromosome will affect the calculation efficiency; The hybrid coding method of encoding the location of load with binary encoding method and encoding the amplitude of load with floating-point encoding method has greatly reduced the length of chromosomes, and significantly improved the computation efficiency and accuracy, but it was difficult to achieve the identification of non-grid node points; A discriminance method was proposed to identify the element where the concentrated load locates, which was judged by the geometrical relationship between the abscissa, vertical coordinates of load point generated from GA and four edges of every element. Furthermore, the load was allocated to nodes of the element by the equivalent distribution principle. Finally, the location of arbitrary concentrated load was identified by finite element analysis and the superior global search capacity of GA. Compared with the identification methods of neural network and inverse finite element analysis method , the present method has the advantage of being able to identify the concentrated load locating at the interior of a element and numerical examples show that this method has higher accuracy. In addition, the inversion equation of dynamic load history and method of location identification are derived based on the identification of static load. The simulation with a specific example shows that the identification of the history and the location of impact load are feasible.
论文采用遗传算法和有限元相结合的方法,实现复合材料结构载荷大小和位置的识别,并着重对染色体的编码方式进行了深入研究。以荷载作用位置的结点号和荷载大小为参数的二进制编码方法简单、高效,但存在连续函数离散化时的映射误差,且其编码串的长度取决于所要求的识别精度,过长的染色体会影响算法的计算效率;以二进制编码表征载荷作用位置,浮点数编码表示载荷大小的混合编码方法,大大降低了染色体的长度,显著提高了计算效率和精度,可难以实现非网格结点处的载荷识别;论文首次提出了一种受载单元判别法,根据染色体所对应的载荷作用点的横、纵坐标和每个单元四条边间的几何关系,判断出集中载荷作用的单元,再根据力的等效分配原则,把载荷等效分配到所在单元的结点上,进而基于有限元分析和遗传算法自身优越的全局搜索能力实现作用于复合材料结构网格结点或单元内部任意位置处的载荷识别,与现有的神经网络识别法和有限元反分析法相比,本方法具有能够识别非网格结点处的载荷的优点,且仿真算例表明其识别精度更高;在对静载荷识别研究的基础上,本文研究了作用于任意位置处的冲击载荷时间历程反演和冲击位置判别方法。仿真算例表明了本文方法对冲击载荷历程反演及位置识别的有效性。
Smart structure is a kind of self-sensing and self-adaptive structure that can sense the change of the surrounding environment and can make an appropriate response in response to this change. Structural health monitoring based on the new type of sensors such as piezoelectric, optical fiber sensors, has drawn extensive attention from scholars at home and abroad. In this article, a further and systematic study about the load identification of piezoelectric smart structure was conducted in the engineering background of using piezoelectric smart structures for structural health monitoring in the aviation and aerospace areas.
This paper used the method of combining genetic algorithms and finite element method to achieve the identification of amplitude and location of the load acted on the composite material structure, having a deep research on the chromosome encoding methods. The method that encoded the load amplitude and location with binary encoding method is simple, efficient, but there is a mapping error in the continuous function discretization. The string length depends on the required identification accuracy, and long chromosome will affect the calculation efficiency; The hybrid coding method of encoding the location of load with binary encoding method and encoding the amplitude of load with floating-point encoding method has greatly reduced the length of chromosomes, and significantly improved the computation efficiency and accuracy, but it was difficult to achieve the identification of non-grid node points; A discriminance method was proposed to identify the element where the concentrated load locates, which was judged by the geometrical relationship between the abscissa, vertical coordinates of load point generated from GA and four edges of every element. Furthermore, the load was allocated to nodes of the element by the equivalent distribution principle. Finally, the location of arbitrary concentrated load was identified by finite element analysis and the superior global search capacity of GA. Compared with the identification methods of neural network and inverse finite element analysis method , the present method has the advantage of being able to identify the concentrated load locating at the interior of a element and numerical examples show that this method has higher accuracy. In addition, the inversion equation of dynamic load history and method of location identification are derived based on the identification of static load. The simulation with a specific example shows that the identification of the history and the location of impact load are feasible.
引文
[1]陶宝祺,智能材料结构[M],北京,国防工业出版社,1997:57~84.
[2] Shi Lihua, Tao Baoqi, Applications of piezoelectric Material sensors in smart structures[J], Transactions of Nanjing University of Aeronautics&Astronautics,1996,13(2):210~213.
[3]石立华等,智能材料结构中埋入压电应变传感技术[J],测控技术,1998,17(6):8~10.
[4]石立华,陶宝祺,埋入压电元件的自诊断智能结构的理论分析与试验研究[J],实验力学,1998,13(9):370~376.
[5] Tracy M, Chang F, Identifying impacts in composite plates with Piezoelectric strain sensors[J], Journal of Smart Material Systems and Structures, 1998,9 (11):920~937.
[6]王书法,邬月琴,李卓球.智能结构载荷识别的有限元反分析方法[J].力学与实践, 2000, 22(5): 17-19.
[7] Haywood J,Coverley P T, Staszewski W J and Worden K. An automatic impact monitor for a composite panel employing smart sensor technology[J]. Smart Materials & Structures, 2005, 14 (1): 265-271.
[8] Chandrashekhara K,Chukwujekwu Okafor A and Jiang Y P. Estimation of contact force on composite plates using impact-induced strain and neural networks[J]. Composites Part B: Engineering, 1998, 29 (4): 363-370.
[9]周晚林,王鑫伟,胡自立.压电智能结构荷载识别方法的研究[J].力学学报, 2004, 36(4): 491-495.
[10] Hagan M T, Demuth H B, Beale M H. Neural Network Design[M].北京,机械工业出版社, 2002.
[11]董会丽,郑世杰(2008).有限元分析与RBF神经网络结合的荷载识别[J].工程力学, 25(3): 64-67.
[12]周晚林,王鑫伟,反求压电薄板智能结构荷载的有限元逆逼近方法[J].计算力学学报, 2004, 21(2): 164-168.
[13]姜忠宇,李建康.弹性结构静载荷反问题的遗传算法[J].兰州交通大学学报(自然科学版)2004, 23 (6): 34-37.
[14]姜忠宇,孙建忠,赵常要.弹性薄板载荷反问题分析[J].安徽工程科技学院学报, 2006, 21(1): 61-63.
[15]吴今培,孙德山,现代数据分析[M],北京,机械工业出版社,2006:169~173.
[16]雷英杰,张善文,李续武,周创明等,MATLAB遗传算法工具箱及应用[M],陕西,西安电子科技大学出版社,2005:3.
[17]陈建锋,石振明,陈竹昌,遗传算法在参数反演中的应用[J],土木基础,2001,15(1):1~4.
[18]张景绘,一体化振动控制[M],北京,科学出版社,2005:5~10.
[19]刘正兴,孙燕,王国庆,计算固体力学[M],上海,上海交通大学出版社,2000:363~369.
[20]郑世杰.八节点压电固体单元的再研究[J].压电与声光,2004,26(4):321~324.
[21]曾攀,有限元分析及应用[M],北京,清华大学出版社,2004:144.
[22] Tzou HS, Tseng CI, Distributed piezoelectric sensors/actuators design for dynamic measurement/control of distributed parameter systems: a piezoelectric finite element approach[J]. Journal of Sound and vibration 1990:17~34.
[23]蔡炜,李青山,杨耀文等.压电层合板结构振动控制的有限元法[J].固体力学学报,1998,19:45~51.
[24] Zheng Shijie, Finite element analysis of smart structures with piezoelectric sensors/actu- ators including debonding[J], Chinese Journal of Aeronautics,2004,17(4), 246~250.
[25]王瑁成,邵敏,有限单元法基本原理和数值方法[M],清华大学出版社,1995:3~6.
[26]谢柞水,王自力,吴剑国,计算结构力学[M],华中科技大学出版社,2004:77~78.
[27] Maniatty A, etal, Finite element analysis of some inverse elasticity problems[J], J.Eng.Mech., 1989,115 (6) :1303~1317.
[28]潘正君,康立山.演化计算[M].北京,清华大学出版社,1998,17—19.
[29]刘更.结构动力学有限元程序设计[M],国防工业出版社,1993.
[30]徐士良.数值分析与算法[M],机械工业出版社,2007:246~247.
[31] Ory H,Glaser H,Holzdeppe D . The Reconstruction of Forcing Function Based on Measured structural responses[C].Proceeding of 2nd International symposium on Aero elasticity and Structural Dynamics ,Aachen,FRG,1985:237-246.
[32] Ory H,Glaser H,Holzdeppe D.Quality of Modal Analysis and Reconstruction of Forcing Function Based on Measured Output Data[C]. Proceedings of 4th IMAC,Los Angeles CA,USA,1986:350-357.
[33]唐秀近.动态载荷识别的时域方法[J].大连工学院学报, 1987,26(4):21-27.
[34] N.Hu, H.Fukunaga. An efficient approach for identifying impact force using embedded piezoelectric sensors. International Journal of Impact Engineering [J],International Journal of Impact Engineering, 34 (2007) 1258–1271.
[2] Shi Lihua, Tao Baoqi, Applications of piezoelectric Material sensors in smart structures[J], Transactions of Nanjing University of Aeronautics&Astronautics,1996,13(2):210~213.
[3]石立华等,智能材料结构中埋入压电应变传感技术[J],测控技术,1998,17(6):8~10.
[4]石立华,陶宝祺,埋入压电元件的自诊断智能结构的理论分析与试验研究[J],实验力学,1998,13(9):370~376.
[5] Tracy M, Chang F, Identifying impacts in composite plates with Piezoelectric strain sensors[J], Journal of Smart Material Systems and Structures, 1998,9 (11):920~937.
[6]王书法,邬月琴,李卓球.智能结构载荷识别的有限元反分析方法[J].力学与实践, 2000, 22(5): 17-19.
[7] Haywood J,Coverley P T, Staszewski W J and Worden K. An automatic impact monitor for a composite panel employing smart sensor technology[J]. Smart Materials & Structures, 2005, 14 (1): 265-271.
[8] Chandrashekhara K,Chukwujekwu Okafor A and Jiang Y P. Estimation of contact force on composite plates using impact-induced strain and neural networks[J]. Composites Part B: Engineering, 1998, 29 (4): 363-370.
[9]周晚林,王鑫伟,胡自立.压电智能结构荷载识别方法的研究[J].力学学报, 2004, 36(4): 491-495.
[10] Hagan M T, Demuth H B, Beale M H. Neural Network Design[M].北京,机械工业出版社, 2002.
[11]董会丽,郑世杰(2008).有限元分析与RBF神经网络结合的荷载识别[J].工程力学, 25(3): 64-67.
[12]周晚林,王鑫伟,反求压电薄板智能结构荷载的有限元逆逼近方法[J].计算力学学报, 2004, 21(2): 164-168.
[13]姜忠宇,李建康.弹性结构静载荷反问题的遗传算法[J].兰州交通大学学报(自然科学版)2004, 23 (6): 34-37.
[14]姜忠宇,孙建忠,赵常要.弹性薄板载荷反问题分析[J].安徽工程科技学院学报, 2006, 21(1): 61-63.
[15]吴今培,孙德山,现代数据分析[M],北京,机械工业出版社,2006:169~173.
[16]雷英杰,张善文,李续武,周创明等,MATLAB遗传算法工具箱及应用[M],陕西,西安电子科技大学出版社,2005:3.
[17]陈建锋,石振明,陈竹昌,遗传算法在参数反演中的应用[J],土木基础,2001,15(1):1~4.
[18]张景绘,一体化振动控制[M],北京,科学出版社,2005:5~10.
[19]刘正兴,孙燕,王国庆,计算固体力学[M],上海,上海交通大学出版社,2000:363~369.
[20]郑世杰.八节点压电固体单元的再研究[J].压电与声光,2004,26(4):321~324.
[21]曾攀,有限元分析及应用[M],北京,清华大学出版社,2004:144.
[22] Tzou HS, Tseng CI, Distributed piezoelectric sensors/actuators design for dynamic measurement/control of distributed parameter systems: a piezoelectric finite element approach[J]. Journal of Sound and vibration 1990:17~34.
[23]蔡炜,李青山,杨耀文等.压电层合板结构振动控制的有限元法[J].固体力学学报,1998,19:45~51.
[24] Zheng Shijie, Finite element analysis of smart structures with piezoelectric sensors/actu- ators including debonding[J], Chinese Journal of Aeronautics,2004,17(4), 246~250.
[25]王瑁成,邵敏,有限单元法基本原理和数值方法[M],清华大学出版社,1995:3~6.
[26]谢柞水,王自力,吴剑国,计算结构力学[M],华中科技大学出版社,2004:77~78.
[27] Maniatty A, etal, Finite element analysis of some inverse elasticity problems[J], J.Eng.Mech., 1989,115 (6) :1303~1317.
[28]潘正君,康立山.演化计算[M].北京,清华大学出版社,1998,17—19.
[29]刘更.结构动力学有限元程序设计[M],国防工业出版社,1993.
[30]徐士良.数值分析与算法[M],机械工业出版社,2007:246~247.
[31] Ory H,Glaser H,Holzdeppe D . The Reconstruction of Forcing Function Based on Measured structural responses[C].Proceeding of 2nd International symposium on Aero elasticity and Structural Dynamics ,Aachen,FRG,1985:237-246.
[32] Ory H,Glaser H,Holzdeppe D.Quality of Modal Analysis and Reconstruction of Forcing Function Based on Measured Output Data[C]. Proceedings of 4th IMAC,Los Angeles CA,USA,1986:350-357.
[33]唐秀近.动态载荷识别的时域方法[J].大连工学院学报, 1987,26(4):21-27.
[34] N.Hu, H.Fukunaga. An efficient approach for identifying impact force using embedded piezoelectric sensors. International Journal of Impact Engineering [J],International Journal of Impact Engineering, 34 (2007) 1258–1271.
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