本文選題：關聯(lián)度 + 鍵能算法　； 參考：《哈爾濱工業(yè)大學》2014年碩士論文

【摘要】：結構健康監(jiān)測作為結構安全評定的一個重要手段，在各類大型復雜工程結構中應用越來越廣泛�？紤]到建筑結構在外部荷載作用時，不同測點處的結構響應存在著相互關聯(lián)，充分認識和利用測點之間的關聯(lián)性規(guī)律，以對健康監(jiān)測系統(tǒng)進行有效的數(shù)據(jù)挖掘及數(shù)據(jù)融合，為結構安全評定提供更全面及可靠的監(jiān)測信息。本文依據(jù)測點響應信息之間的關聯(lián)性分析，對傳感器優(yōu)化布置及故障診斷進行了相關的研究。 為降低測點之間的冗余性，使不同位置處的監(jiān)測信息盡可能保持獨立，讓有限測點發(fā)揮最大作用，為結構安全評定提供全面信息，本文研究了基于關聯(lián)度的傳感器優(yōu)化布置方法。根據(jù)有限元分析結果及關聯(lián)度計算公式計算所選待定測點之間的關聯(lián)度，建立關聯(lián)度矩陣；對關聯(lián)度矩陣進行二元處理，設定關聯(lián)度閾值，以得到等價關聯(lián)度矩陣；采用鍵能算法對等價關聯(lián)度矩陣進行矩陣變換，以達到對待定測點進行分組的目的；根據(jù)兩兩之間平均關聯(lián)度最小的傳感器優(yōu)化布置原則，確定傳感器數(shù)量及位置分布；采用衡量冗余度的相關信息熵對傳感器優(yōu)化布置結果進行驗證，以驗證方法的有效性。 準確的測量信息才能有效地反映結構的響應，為保證結構安全評定的可靠性，本文研究了基于關聯(lián)度的傳感器故障診斷方法。選取歷史正常監(jiān)測數(shù)據(jù)作為故障診斷前的參考數(shù)據(jù)，計算測點的關聯(lián)度矩陣，采用二元變換及鍵能算法對測點進行分組，獲得測點之間的關聯(lián)性信息數(shù)據(jù)庫；選取適當長度的滑動時間窗，利用參考數(shù)據(jù)計算測點之間隨滑動時間步變化的關聯(lián)度向量，進而求得偏離平均關聯(lián)度的偏離率向量，以確定所研究測點任意兩點間的偏離率限值；以關聯(lián)度偏離率限值為依據(jù)建立故障診斷函數(shù)，采用有限元模型仿真故障的識別實驗驗證了方法的有效性，并討論了噪聲對測點關聯(lián)性的影響。 選用深圳灣體育中心結構健康監(jiān)測系統(tǒng)中的三類應力測點為研究對象。對每類應力測點進行關聯(lián)性分析，，獲得了測點間關聯(lián)性強弱的數(shù)據(jù)信息，分別在三類應力測點中的其中一個測點，加入輸出恒定值、漂移及周期性干擾信號以仿真故障測點，采用本文提出的基于關聯(lián)度的故障診斷方法驗證了對于含有噪聲的實測數(shù)據(jù)分析的有效性及實用性。
[Abstract]:As an important means of structural safety assessment, structural health monitoring is more and more widely used in various large and complex engineering structures. Considering that the structural responses at different measuring points are interrelated when the building structure is subjected to external loads, it is necessary to fully understand and make use of the law of correlation between the measured points in order to carry out effective data mining and data fusion for the health monitoring system. Provide more comprehensive and reliable monitoring information for structural safety assessment. Based on the correlation analysis of the response information of measurement points, the optimal arrangement and fault diagnosis of sensors are studied in this paper. In order to reduce the redundancy between the measuring points, to keep the monitoring information at different positions as independent as possible, to allow the limited observation points to play the greatest role, and to provide comprehensive information for structural safety assessment, In this paper, the optimal arrangement method of sensor based on correlation degree is studied. According to the results of finite element analysis and the calculation formula of correlation degree, the correlation degree matrix is established and the correlation degree matrix is established, and the threshold value of correlation degree is set up to obtain the equivalent correlation degree matrix. The matrix of equivalent correlation degree is transformed by the key energy algorithm, and the number and position distribution of sensors are determined according to the principle of optimal arrangement of sensors with minimum average correlation degree between two pairs, and the number of sensors and the location distribution of sensors are determined according to the principle of optimal arrangement of sensors with minimum average correlation degree. In order to verify the effectiveness of the proposed method, the optimal sensor layout is verified by the entropy of information to measure redundancy. The accurate measurement information can effectively reflect the response of the structure. In order to ensure the reliability of structural safety assessment, the method of sensor fault diagnosis based on correlation degree is studied in this paper. Selecting the historical normal monitoring data as the reference data before the fault diagnosis, calculating the correlation degree matrix of the measuring points, grouping the measured points with binary transformation and key energy algorithm, and obtaining the correlation information database between the measured points. By selecting a sliding time window of appropriate length and using the reference data to calculate the correlation degree vector between the measured points with the sliding time step, the deviation rate vector deviating from the average correlation degree is obtained. The fault diagnosis function is established by determining the limit value of deviation rate between any two points of the measured points, and the validity of the method is verified by using the finite element model simulation experiment to identify the faults, and to establish the fault diagnosis function based on the limit value of the correlation degree deviation rate. The effect of noise on the correlation of measurement points is discussed. Three kinds of stress measurement points in the structural health monitoring system of Shenzhen Bay Sports Center were selected as the research object. The correlation analysis of each kind of stress measuring points is carried out, and the data information of the correlation between the measuring points is obtained. In one of the three kinds of stress measuring points, the output constant value, drift signal and periodic disturbance signal are added to simulate the fault measuring points. The method of fault diagnosis based on correlation degree proposed in this paper is used to verify the validity and practicability of the analysis of measured data with noise.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TU317

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