碳纤维复合材料构件缺陷脉冲涡流成像与图像分析的基础理论和关键技术研究

Accurate detection and quantitative evaluation of defects and damages in carbon-fiber reinforced composite material structures is an essential and crucial frontier issue in a range of technological applications, such as maintaining the integrity, enhancing the safety, and assuring the reliability of structures. The scientific key problems are the prior statistical model of ill-posed inverse problems, nonlinear optimization algorithms, high quality and fast imaging, image analysis, defect intelligent identification and quantitative evaluation. The main research contents are as follows: ① constructing the new nonlinear optimization algorithms guided by the prior statistical model of pulsed eddy current imaging and image analysis for detecting defects in carbon-fiber reinforced composite material structures, for providing the theoretical basis for the realization of high quality and fast processing the detection information; ② developing TMR array probe, and researching on the high quality and fast pulsed eddy current imaging for detecting defects in carbon-fiber reinforced composite material structures, for providing high quality image information; ③ researching on pulsed eddy current image analysis and defect intelligent identification and quantitative evaluation for carbon-fiber reinforced composite material structures, for completing accurately quantitative evaluation of defects; ④ constructing the prototype for validating the novel theories and methods and evaluating the engineering suitability. Finally, currently urgent need theories and technologies of pulsed eddy current imaging and image analysis for detecting defects in carbon-fiber reinforced composite material structures are established. It will promote the theories and technologies development of eddy current testing. The study and application of carbon-fiber reinforced composite materials are also accelerated.

准确检测和定量评估碳纤维复合材料构件缺陷和损伤，确保其完整、可靠、安全是许多重要领域急需解决的具有基础性、关键性和先导性的极具挑战的前沿问题。围绕病态反问题的先验统计模型及非线性优化、优质快速成像、图像分析与缺陷智能识别及定量化评估关键科学问题，主要研究内容是：①建立由碳纤维复合材料构件缺陷脉冲涡流成像与图像分析先验统计模型导引的新的非线性优化算法，为实现检测信息的优质快速处理提供理论基础；②开发TMR 阵列探头，研究优质快速的碳纤维复合材料构件缺陷脉冲涡流成像方法，以提供高质量的图像信息；③研究碳纤维复合材料构件缺陷脉冲涡流图像分析与缺陷智能识别及定量化评估方法，实现缺陷的精确定量评估；④构建原理样机，完成新理论和方法的原理性验证和工程适用性评估。最终形成完整的碳纤维复合材料构件缺陷脉冲涡流成像与图像分析的基础理论和关键技术，推动涡流检测理论和技术发展，促进碳纤维复合材料的研发及应用。

准确检测和定量评估碳纤维复合材料构件缺陷和损伤，确保其完整、可靠、安全是许多重要领域急需解决的具有基础性、关键性和先导性的极具挑战的前沿问题。项目开展了以下研究工作：①采用有限元分析法建模求解三维涡流场计算问题，为后续研究非线性优化算法、碳纤维复合材料构件缺陷脉冲涡流成像方法，缺陷智能识别及定量化评估方法、开发脉冲涡流成像系统提供理论基础。②研究了碳纤维复合材料构件缺陷脉冲涡流成像与图像分析中的先验统计模型的构建、反问题求解算法、少量数据的图像重建方法、TMR阵列探头电磁计算理论及设计方法、广义模糊优化模型与高维检测数据可视化的多核加速算法，收集了大量碳纤维复合材料构件典型缺陷脉冲涡流检测图像资料，设计、构建了本项目的缺陷图像信息数据库。③研究了由先验统计模型导引的新的非线性优化算法及其全局参数的自适应非线性估计方法、快速成像的TMR阵列探头的设计与非线性校正、涡流图像稀疏性质，进而完成相应的先验模型设计与快速优化算法，给出适用于碳纤维复合材料构件缺陷脉冲涡流图像的基于广义模糊相似性的配准测度准则，开展了碳纤维复合材料构件缺陷脉冲涡流图像隐式有效特征获取与描述的研究。④研究了局部最优解和全局最优解的性质与针对碳纤维复合材料构件缺陷脉冲涡流成像与图像分析的先验统计模型的最优解的快速收敛算法，在稀疏采样的基础上，研究了碳纤维复合材料构件缺陷脉冲涡流图像精确、快速分割方法与相似性特征提取方法和检测数据的可视化分析技术。⑤对碳纤维复合材料构件缺陷脉冲涡流检测图像进行分析推理，开展了碳纤维复合材料构件缺陷脉冲涡流成像与图像分析的实验方法和实验设计研究，建立实验验证系统，提出性能和工程适用性评估分析方法，开展科学实验，完成原理性验证。最终形成一套当前亟需的碳纤维复合材料构件稀疏脉冲涡流阵列成像的理论与方法，推动涡流检测理论和技术发展，促进碳纤维复合材料的研发及应用。