大型复杂环件成形缺陷自适应超声相控阵检测技术基础研究

The large complex ring products have been increasingly used in the industries of energy, petrochemical engineering, aerospace, defense equipment, etc. The ring product’s forming defects like cracks, holes and inclusions will threaten the service safety of the relevant equipment. However, this kind of ring product always has a complex cross-section states, anisotropic microstructure and diverse forming defects, and the conventional method cannot realize the efficient, accurate and thorough detection. This project proposes the new adaptive ultrasonic phrased array detection method of the forming defects of the large complex rings. The adaptive control mechanism of array beam normal emission and dynamic aperture focusing algorithm aiming at the ring’s complex cross-section are studied. The distribution law of the array acoustic field in the coupling medium and ring material is revealed, and the optimization method of the array transducer’s acoustic field is established. Then the response characteristics of the different types, positions and amount of defects under the ultrasonic physical field are revealed through analyzing the mechanisms of interaction between the states of ring’s cross-section, microstructure, defect’s pattern and the ultrasonic physical field. The methods of type recognition and quantitative evaluation of the ring’s forming defects are established based on the echo signal’s time-frequency characteristics and the image segmentation. Finally, the ultrasonic phrased array detection and imaging system of the forming defects of the large complex rings is developed. The research results of this project can provide scientific evidence for guaranteeing the high-quality manufacturing of large complex ring products, and have a significant scientific value and practical importance for solving the key technological problems of the adaptive ultrasonic phrased array detection of the forming defects of the large complex rings and developing the new non-destructive detection theory, technology and method of the large complex rings.

大型复杂环件在能源石化、航空航天和国防装备领域应用日益广泛，其成形过程常产生裂纹、孔洞和夹杂等缺陷，威胁相关装备服役安全。然而，这类环件截面状态复杂、微观结构各向异性、成形缺陷多样，常规方法难以实现高效、准确和全面检测。本项目提出大型复杂环件成形缺陷自适应超声相控阵检测方法，研究环件复杂截面相控阵声束法向入射自适应控制机制和动态孔径聚焦成像算法；揭示阵列声场在耦合层和环件等多层介质中的分布规律，建立阵列换能器声场优化方法；分析环件截面状态、微观结构、缺陷形态与阵列声场之间的作用机制，揭示不同性质缺陷对阵列声场的响应特征；建立基于回波时频特征与图像分割的缺陷类型识别与定量评价方法；最后开发环件缺陷超声相控阵检测系统。研究结果为保障大型复杂环件高质量成形制造提供科学依据，对于解决大型复杂环件自适应超声相控阵无损检测关键技术，发展大型复杂环件无损检测新理论和技术方法具有重要的学术价值和实际意义。

针对能源石化、航空航天和国防装备用大型复杂环件成形过程产生的折叠、裂纹和孔洞等缺陷，突破传统检测方法精度低、柔性差的局限，提出了大型复杂环件成形缺陷自适应超声相控阵检测方法。主要研究内容如下：（1）建立了复杂截面相控阵自适应聚焦算法，实现了环件过渡圆角、沟槽等结构的聚焦成像检测；（2）建立了多介质阵列声场解析模型，设计了典型复杂环件相控阵检测工艺；（3）提出了金属材料多晶结构整体建模方法，揭示了多晶结构对超声传播过程散射和衰减规律；（4）提出了基于自适应滤波和圆弧声场补偿的线性聚焦扫描成像优化算法，以及基于声场阈值分割和矢量相位相干的超声全聚焦成像优化算法，缺陷图像信噪比提高17%~39.4%，横向分辨率提高40%；（5）构建了基于超分辨网络和混合注意力机制的环件缺陷智能识别深度学习网络模型，实现了某航空机匣环件Φ0.3mm微小当量缺陷的高分辨率和高信噪比检测，以及孔洞、裂纹和密集型气孔等多类型缺陷的智能识别。项目执行期间，在Chinese J Aeronaut.、Measurement、Ultrasonics、Appl. Acoust.等期刊发表SCI论文7篇，获授权发明专利5项，软件著作权2项，制定国家标准1项，培养毕业博士研究生2人，毕业硕士研究生5人。研究成果对于发展大型复杂环件无损检测新理论和技术方法具有重要的学术价值，可应用于汽车轮毂轴承环件、风电轴承环件和航空航天特种环件的成形制造质量检测，具有广阔的市场应用前景和巨大的社会经济效益。