材料常见的几何非连续的破坏形式，一般表现为缺口，对材料的破坏作用很大。对于带有缺口的金属薄板在断裂破坏时经历裂纹的萌生和扩展两个阶段，特别是当裂纹起源为缺口时，能够精确测量出萌生载荷是优化冲压加工的关键所在。钛及钛合金因其高强度、耐腐蚀性和抗氧化性能、高温强度高，在航空航天领域中成为航空发动机叶片、核反应堆压力容器等重要零件的主要材料。但服役过程中结构在复杂工作环境下早期裂纹扩展引起的疲劳断裂问题，每年使全球蒙受巨大的经济损失。考虑到TC4钛合金表面存在丰富β相微裂纹难以被传统的无损检测手段发现和识别，为此，提出裂纹萌生动态识别新途径。 通过设计具有不同半径凹口的TC4板材试样，在万能试验机上进行了位移控制拉伸试验，加载速率设置为0.2 mm/min。在整个阶段使用高精度声发射系统收集损伤信号。利用表征参数分析法对声发射信号进行表征处理，并比较各种特征参数来预测试样在拉伸断裂过程中的裂纹萌生时间。 本文应用累积振铃计数Shannon熵以及Kullback-Leibler相对熵给出了新的损伤判别准则，熵曲线斜率变小为损伤判据对应于缺口根部微裂纹成核的临界点，且通过拉伸卸载试验设计获得了成核过程中的等效载荷参数，并通过纵向截面金相显微镜分析校核了缺口根部微裂纹的空间定性结果。统计发现成核载荷测得值和理论预测值相对偏差在15%以内，工程上表明信息熵预测方法的可接受。采用扫描电子显微镜纳米尺度下对断口特征进行表征，实现对断口特征与微观变化的关联性研究。 本研究成果开发的在线健康监测算法基于熵值阈值判别原则实现微秒级损伤状态判读，较传统方法的检测灵敏度提升两个数量级。经工程验证该技术在试验中可将裂纹萌生时间预测误差控制在8 min以内，为构建钛合金结构全寿命周期管理体系提供了可靠的技术支撑。

The geometric discontinuity features commonly present in engineering components are usually manifested in the form of notches, which directly affect the fracture behavior of materials during service. Accurately determining the critical load for crack initiation and propagation during the fracture process of metal sheets with notches, especially when the crack originates from the root of the notch, has significant engineering value for optimizing the cutting process. Titanium and titanium alloys have become the core materials for key components such as aerospace engine blades and nuclear reactor pressure vessels due to their high strength, excellent corrosion resistance, and good high-temperature stability. However, the structural failure caused by early crack propagation behavior under complex service conditions results in significant global economic losses every year. In response to the industry difficulty of capturing nanoscale microcracks in the β - phase enrichment zone on the surface of TC4 titanium alloy using conventional non-destructive testing methods, this study proposes a new method for real-time monitoring of crack initiation status.

By designing TC4 sheet specimens with different radius notches, displacement controlled tensile tests were conducted on a universal testing machine with a loading rate set at 0.2 mm/min. Use high-precision acoustic emission systems to collect damage signals throughout the entire stage. Using the characterization parameter analysis method to characterize and process acoustic emission signals, and comparing various characteristic parameters to predict the crack initiation time of the specimen during tensile fracture.

This article proposes a novel damage assessment criterion based on cumulative ringing count Shannon entropy and Kullback Leibler relative entropy. When the slope of the entropy curve decreases beyond the damage criterion, it corresponds to the critical state of microcrack nucleation at the root of the notch. Subsequently, the equivalent load parameters during the nucleation process were obtained through the design of tensile unloading tests, and the spatial positioning accuracy of microcracks at the root of the notch was verified through metallographic analysis of longitudinal sections. The statistical results show that the relative deviation between the measured values of nucleation load and the theoretical predicted values remains within the threshold of 15%, confirming the engineering reliability of the information entropy prediction method. Characterization of fracture morphology at the nanoscale using scanning electron microscopy to achieve correlation analysis between fracture mechanisms and microscopic changes.

The online health monitoring algorithm developed in this research achievement is based on the entropy threshold discrimination principle to achieve microsecond level damage state interpretation, which improves the detection sensitivity by two orders of magnitude compared to traditional methods. Through engineering verification, this technology can control the prediction error of crack initiation time within 8 minutes in experiments, providing reliable technical support for the construction of a full life cycle management system for titanium alloy structures.

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