基于主动声发射的覆冰绞线结构损伤协同反演成像机理及识别方法研究

Facing damage detections of stand wire structures in the wide range icing environment , which has been an enormous challenge for existing monitoring methods, the new active acoustic emission damage monitoring mode integrating many PZTs in the project is put forward. What is more, the key scientific problems for synergetic inversion imaging and its identification of damage of icing stand wire structures based on Synergetics are explored originally. The active acoustic emission evolutionary path from disorder to order for icing stand wire structural damage identification is studied to establish cooperative inversion monitoring mechanism model. Then the relationships between the boundary parameters of the model and its damage focusing characteristics are studied, which can guide to achieve highest focus gain for damages with cooperative inversion stress wave. From the time-domain perspective，equivalent energy imaging recognition of multidimensional damage location is presented ，which aims to overcome the traditional method's shortcoming that can detect only biggest scattering goal ,but ignore the smaller target. Moreover, based on the space energy distribution with experiments in the icing experimental platform which has been established by authors, original feature vector formation law of different damage types is explored to establish the feature database for different damage types . Based on the self-organization evolution principle of Synergetics, the global optimization of collaborative network parameters for different damages identification will be finished under the unbalanced synergetic coefficient, which can adapt to dynamic identification process of deformation signals for different damages because of the complex external environments. The cooperative identification mechanism should be tested in the icing experimental platform through simulating actual icing process. So this project has important academic values and practical significances on complicated mechanical structural health monitoring and nondestructive testing technologies' development.

面对覆冰环境下绞线结构损伤监测新型测量问题，现有检测方法受到了极大挑战。项目提出集成多PZT主动声发射损伤监测新方式，原创性探索基于协同论的覆冰绞线结构损伤协同反演成像及识别关键科学问题。通过寻找覆冰绞线结构损伤识别中无序到有序的主动声发射演化途径，建立协同反演监测机理模型，研究模型各边界参数与损伤聚焦特性关系，指导获得多传感协同反演损伤聚焦最高增益；从时域协同聚焦角度研究多维损伤位置成像，克服传统方法容易只发现散射信号较大的目标而忽略小目标问题，结合实验在空间能量分布模式下探索不同损伤类型特征向量形成规律，建立不同损伤类型特征库；进一步基于协同论自组织效应，在非平衡协同系数下对不同损伤类型识别的协同认知网络参数整体优化，使能适应复杂外界环境下损伤信息变形动态识别，最后在覆冰环境平台进行识别系列实验。项目研究对复杂机械结构健康监测技术应用及发展具有重要学术价值和实际意义。

面对覆冰环境下绞线结构损伤监测新型测量问题，现有检测方法受到了极大挑战。项目提出集成多PZT主动声发射损伤监测新方式，探索基于协同论的覆冰绞线结构损伤协同反演成像及识别关键科学问题。通过寻找覆冰绞线结构损伤识别中无序到有序的主动声发射演化途径，建立协同反演监测机理模型；创新性将扩频理论引入多传感信息应力波通信中，构建面向绞线结构健康监测多传感信息应力波通信集成系统；提出基于虚拟合成的时间聚焦TRM技术，包括虚拟合成时间反演技术以及时间聚焦TRM技术，确定模型各边界参数与损伤聚焦特性关系，指导获得多传感协同反演损伤聚焦最高增益；针对绞线结构被覆盖区域难以检测问题，提出基于双向时间反演的缺陷聚焦成像方法，从时域协同聚焦角度研究多维损伤位置成像，克服传统方法容易只发现散射信号较大的目标而忽略小目标问题，结合实验在空间能量分布模式下探索不同损伤类型特征向量形成规律，建立不同损伤类型特征库；进一步基于协同论三大效应，提出绞线结构损伤协同识别技术方法框架，主要动态决策机制与反馈优化机制。引入虚拟向量机，提出了基于时频及变换域分析的结构损伤信号特征提取方法；采用信号特征向量的聚类、训练样本融合修正、在线检测信号的信息叠加这三种最优损伤状态向量的重构方法，在非平衡协同系数下对不同损伤类型识别的协同认知网络参数整体优化，确定了反馈的准则，实现了误识别样本的修正，使能适应复杂外界环境下损伤信息变形动态识别，最后在覆冰环境平台进行识别系列实验。项目研究绞线结构及其在覆冰介质环境下给损伤监测带来新的测量难题，对复杂机械结构健康监测技术应用及发展具有重要学术价值和实际意义。

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