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  本文選題：損傷識別　切入點(diǎn)：小波包變換　出處：《北京交通大學(xué)》2017年碩士論文

【摘要】：在結(jié)構(gòu)的長期健康監(jiān)測過程中,環(huán)境因素的變化會引起結(jié)構(gòu)自身動力參數(shù)的改變,這些改變會使結(jié)構(gòu)的損傷識別發(fā)生誤判。為了避免由于溫度變化而使損傷識別發(fā)生誤判,本文利用結(jié)構(gòu)在不同溫度下的加速度響應(yīng),通過小波包變換提取小波包能量譜,并以此作為樣本,利用多元統(tǒng)計分析中的主成分分析方法剔除或者減少溫度對損傷特征參數(shù)的影響來進(jìn)行損傷識別。本文分別以簡支梁模型、ASCE的Benchmark數(shù)值模型和試驗(yàn)數(shù)據(jù),以及古建監(jiān)測數(shù)據(jù)為對象,運(yùn)用小波包變換和主成分分析法提取特征參數(shù)并去除溫度影響,對其進(jìn)行損傷識別分析,主要工作包括以下幾個方面:1)利用小波包變換構(gòu)建損傷指標(biāo)進(jìn)行損傷識別研究。針對一跨長為5m的簡支梁數(shù)值模型,對其動力響應(yīng)進(jìn)行小波包變換,得到小波包能量譜,并構(gòu)建損傷指標(biāo),對不同位置損傷的進(jìn)行損傷定位,并研究不同程度損傷和噪聲對損傷指標(biāo)的影響。2)以5m跨長的簡支梁模型為對象,加入溫度的影響,對得到動力加速度響應(yīng)進(jìn)行小波包變換和主成分分析,建立損傷指標(biāo)和識別率因子,對不同溫度下結(jié)構(gòu)的損傷進(jìn)行識別,并研究損傷位置、損傷程度及噪聲對損傷指標(biāo)的影響。同時對ASCE提出的第一階段的Benchmark有限元模型加入溫度的變化,得到不同溫度下的加速度響應(yīng)數(shù)據(jù),用上述方法進(jìn)行損傷識別,驗(yàn)證方法的有效性。3)對ASCE第二階段的Benchmark模型試驗(yàn)得到的環(huán)境激勵數(shù)據(jù)進(jìn)行分析,通過自然激勵技術(shù)和小波包變換得到的小波包能量譜,并對其進(jìn)行歸一化處理,構(gòu)建損傷指標(biāo)進(jìn)行結(jié)構(gòu)的損傷識別分析。4)對實(shí)測加速度數(shù)據(jù)樣本利用本文方法進(jìn)行分析。構(gòu)建兩組時間間隔為一年的樣本,對樣本進(jìn)行數(shù)據(jù)的預(yù)處理,通過隨機(jī)減量技術(shù)得到結(jié)構(gòu)自由振動響應(yīng),然后利用小波包變換和主成分分析計算損傷指標(biāo),對結(jié)構(gòu)進(jìn)行損傷的判別,并分析其原因。
[Abstract]:In the process of long-term health monitoring of structure, the change of environmental factors will cause the change of dynamic parameters of the structure itself, and these changes will make the damage identification of the structure misjudge, in order to avoid the misjudgment of the damage identification due to the change of temperature. In this paper, the energy spectrum of wavelet packet is extracted by wavelet packet transform using the acceleration response of structure at different temperatures, and it is used as a sample. The method of principal component analysis (PCA) in multivariate statistical analysis is used to eliminate or reduce the effect of temperature on damage characteristic parameters to identify damage. In this paper, the Benchmark numerical model and experimental data of simply supported beam model ASCE are used, respectively. Using wavelet packet transform and principal component analysis method to extract the characteristic parameters and remove the influence of temperature, the damage identification analysis is carried out. The main work includes the following aspects: (1) damage identification is studied by using wavelet packet transform to construct damage index. For a simple supported beam model with a span of 5 m, wavelet packet transform is applied to the dynamic response of the model, and the wavelet packet energy spectrum is obtained. The damage index is constructed to locate the damage in different positions, and the effects of damage and noise on the damage index are studied. 2) the model of simply supported beam with 5m span is taken as the object, and the effect of temperature is added. The wavelet packet transform and principal component analysis are used to analyze the dynamic acceleration response. The damage index and recognition rate factor are established to identify the damage of structures at different temperatures, and the damage location is studied. The influence of damage degree and noise on the damage index. At the same time, the change of temperature is added to the Benchmark finite element model of the first stage proposed by ASCE, and the acceleration response data at different temperatures are obtained, and the above methods are used to identify the damage. Verify the validity of the method. 3) analyze the environmental excitation data obtained from the Benchmark model test in the second stage of ASCE. Through the natural excitation technique and wavelet packet transform, the wavelet packet energy spectrum is analyzed, and the wavelet packet energy spectrum is normalized. Construction of damage indicators for structural damage identification analysis .4) the actual acceleration data samples are analyzed by the method in this paper. Two groups of samples with a time interval of one year are constructed, and the samples are preprocessed. The free vibration response of the structure was obtained by random decrement technique. Then the damage index was calculated by wavelet packet transform and principal component analysis (PCA). The damage of the structure was judged and the causes were analyzed.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TU317

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本文編號：1681726