本文關鍵詞：泄流結構損傷診斷的數(shù)據(jù)級與特征級融合方法研究　出處：《南昌大學》2015年碩士論文　論文類型：學位論文

  更多相關文章： 信息融合 泄流結構 數(shù)據(jù)級 特征級 損傷識別

【摘要】：近年來,高水頭、大流量的水工泄流結構的安全問題在水利界受到廣泛關注。在泄流結構服役過程中,其長期受到水流荷載作用,隨之誘發(fā)的振動問題導致結構出現(xiàn)不同程度的病害或損傷,情況嚴重的甚至影響水利樞紐的正常運行�；诙嘣葱畔⑷诤霞夹g的泄流結構性態(tài)監(jiān)測與損傷識別體系的建立,不僅能夠全面系統(tǒng)地監(jiān)測泄流結構的災變演化,更有利于保障大壩的安全運行。在基于信息融合技術的水工泄流結構損傷診斷領域,數(shù)據(jù)級融合是將多個同類型傳感器的振動響應信號,按一定準則,融合為一個更加全面、準確反映結構動力特性(頻率)的信號,為泄流結構損傷敏感特征量的提取奠定基礎;特征級融主要針對結構多個不同類型的損傷敏感特征量,在特征級層面進行融合,獲得對同一損傷的一致性描述,實現(xiàn)對泄流結構實際健康狀態(tài)的評估。目前有關泄流結構損傷診斷的信息融合方法研究不多,為此,本文主要開展以下兩個方面的研究工作:(一)泄流結構多傳感器振動信號的數(shù)據(jù)級信息融合方法研究。針對傳統(tǒng)數(shù)據(jù)級融合方法對振動響應信號相似度要求高,且具有融合系數(shù)固定的缺陷,以及在高拱壩結構泄洪振動測試中,傳感器測試精度受環(huán)境噪聲及測點布置影響等問題,本文提出了基于改進方差貢獻率的高拱壩多傳感器振動響應數(shù)據(jù)級融合方法,該方法通過定義各測點不同時刻信號相對于該測點信號振動總能量的百分比進行修正,使各測點的融合系數(shù)在動態(tài)分配時保持在同一能量水平。并結合某拱壩數(shù)值模擬試驗和二灘高拱壩原型工程實例,驗證了該算法在實際工程中的可行性;與相關函數(shù)的融合算法進行對比分析,該方法在高拱壩振動測試的信息提取上有明顯的優(yōu)勢,且具有更好的動態(tài)融合性和適用性。(二)泄流結構損傷診斷的特征級信息融合方法研究。以水工弧形閘門主框架結構為研究對象,采用基于柔度靈敏度動力損傷識別方法,分別對其單位置、非對稱位置和對稱位置單元三種損傷工況進行識別,發(fā)現(xiàn)該方法在識別對稱結構非對稱位置單元損傷情況下,存在單元誤判和損傷程度識別偏差較大的缺陷;采用基于應變改變率的靜力損傷識別方法,其損傷程度的識別效果依舊不好。本文分別利用D-S證據(jù)理論、Bayes定理,融合動靜力損傷敏感特征量,通過識別效果對比驗證:多源信息比單一信息更能夠準確、全面反映結構的整體特性,特征級信息融合方法能夠很好地應用于水工結構的損傷識別領域,且D-S證據(jù)理論和Bayes方法的融合效果都與實際損傷情況相符合,但Bayes方法具有更好的工程適用性。
[Abstract]:In recent years, the safety of high-head and high-flow hydraulic discharge structures has been widely concerned in the field of water conservancy. In the discharge structure service process, it has been subjected to the effect of water flow load for a long time. The resulting vibration problems lead to different degrees of disease or damage to the structure. Based on the multi-source information fusion technology, the monitoring of leakage structure and the establishment of damage identification system can not only monitor the catastrophic evolution of discharge structure in a comprehensive and systematic way. In the field of damage diagnosis of hydraulic discharge structure based on information fusion technology, data level fusion is the vibration response signal of multiple sensors of the same type, according to certain criteria. The fusion is a more comprehensive and accurate signal reflecting the dynamic characteristics (frequency) of the structure, which lays a foundation for the extraction of the damage sensitive characteristics of the leakage structure. The feature level fusion is mainly aimed at different types of damage sensitive feature quantity of the structure. It is fused at the feature level to obtain the consistent description of the same damage. To realize the evaluation of the actual health state of the discharge structure, there are few information fusion methods about the damage diagnosis of the discharge structure, so for this reason. This paper focuses on the following two aspects of research work: (1). Research on data level information fusion method for multi-sensor vibration signal of discharge structure. Traditional data level fusion method requires high similarity of vibration response signal. It also has the defect of fixed fusion coefficient, and in the high arch dam structure flood discharge vibration test, the sensor testing accuracy is affected by the environmental noise and the location of measuring points and so on. This paper presents a data level fusion method for multi-sensor vibration response of high arch dam based on improved variance contribution rate. The method is modified by defining the percentage of the total vibration energy of the signal at different time points relative to the measured point signal. The fusion coefficient of each measuring point is kept at the same energy level when it is distributed dynamically. The feasibility of the algorithm in practical engineering is verified by combining the numerical simulation test of an arch dam and the prototype project of Ertan high arch dam. Compared with the fusion algorithm of correlation function, this method has obvious advantages in extracting information of vibration test of high arch dam. And has better dynamic fusion and applicability. (2) study on characteristic level information fusion method for damage diagnosis of drainage structure. Take the main frame structure of hydraulic arc gate as the research object. The dynamic damage identification method based on flexibility sensitivity is used to identify the single position, asymmetric position and symmetrical position unit respectively. It is found that in the case of asymmetric position element damage of symmetrical structure, the method has some defects such as large deviation of unit misjudgment and damage degree identification. Using the static damage identification method based on strain change rate, the damage degree identification effect is still not good. In this paper, D-S evidence theory and Bayes theorem are used to fuse the dynamic and static force damage sensitive characteristic. The comparison of recognition results shows that the multi-source information is more accurate than the single information and can reflect the overall characteristics of the structure. The feature-level information fusion method can be applied to the damage identification of hydraulic structures. The fusion effect of D-S evidence theory and Bayes method is consistent with the actual damage, but the Bayes method has better engineering applicability.
【學位授予單位】：南昌大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TV31

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