基于证据理论的管道损伤识别研究

发布时间：2018-03-07 18:12

本文选题：管道　切入点：损伤识别　出处：《华东理工大学》2015年硕士论文　论文类型：学位论文

【摘要】：管道广泛应用于国民生活与工业生产的各个领域,由于长期承载、环境变化或结构腐蚀老化等使管道逐渐累积裂缝、变形等损伤,因此对管道进行损伤识别与诊断显得日益重要。基于振动模态的结构损伤识别是目前研究的热点。然而工程实践中由于测试噪声、测试条件等限制,任意单一一种损伤识别方法损伤识别能力都是有限的,损伤诊断结果易发生漏判与误判。本文将信息融合技术中的D-S证据理论引入管道损伤识别研究。首先分析探究现行常用结构损伤识别方法的噪声干扰下鲁棒性及工程适用性,数值模拟研究证明了单一损伤识别方法抗噪性均不高且存在各自的使用局限性；然后为提高噪声影响下的管道损伤识别准确率,提出了基于证据理论和单纯形遗传算法的二阶段管道损伤识别方法,通过证据理论将两种损伤识别方法作为信息源进行信息融合来初步确定损伤位置区域,通过单纯形遗传算法进一步精确诊断损伤位置与程度,在较小噪声的影响下进行数值模拟取得了较为满意的结果；最后,为了解决实际工程问题,提出了一种基于多信息源的改进的证据理论来用于管道损伤识别的试验研究,获得了更好管道损伤定位效果,且优于传统证据理论所得的结果。
[Abstract]:The pipeline is widely used in various fields of Yu Guomin's life and industrial production. Due to long-term loading, environmental changes or structural corrosion and aging, the pipeline gradually accumulates cracks, deformation, and other damage. Therefore, it is increasingly important to identify and diagnose the damage of pipelines. Structural damage identification based on vibration mode is a hot topic at present. However, in engineering practice, due to the limitations of test noise and test conditions, Any single damage identification method is limited in its ability to identify damage. The result of damage diagnosis is prone to miss judgment and misjudgment. In this paper, the D-S evidence theory of information fusion technology is introduced into the research of pipeline damage identification. Firstly, the robustness and engineering applicability of the commonly used structural damage identification methods under noise interference are analyzed and explored. The numerical simulation results show that the single damage identification method has not high noise resistance and has its own application limitations, and then in order to improve the accuracy of pipeline damage identification under the influence of noise, A two-stage pipeline damage identification method based on evidence theory and simplex genetic algorithm is proposed. Through evidence theory, two damage identification methods are used as information source for information fusion to preliminarily determine the damage location area. Through simplex genetic algorithm (SGA) to diagnose the location and degree of damage accurately, the numerical simulation results are satisfactory under the influence of less noise. Finally, in order to solve the practical engineering problems, An improved evidence theory based on multiple information sources is proposed for the experimental study of pipeline damage identification. The results obtained are better than those obtained from the traditional evidence theory.
【学位授予单位】：华东理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TE973.6

【参考文献】