【摘要】：在各類基于振動(dòng)響應(yīng)的工程結(jié)構(gòu)損傷檢測(cè)過程當(dāng)中,由于外在自然環(huán)境或者人為因素的影響,所測(cè)得的振動(dòng)響應(yīng)信號(hào)不僅包含了結(jié)構(gòu)的損傷信息,同時(shí)還存在著大量的噪聲干擾。噪聲的存在嚴(yán)重影響了結(jié)構(gòu)有效振動(dòng)響應(yīng)數(shù)據(jù)的提取,特別是對(duì)于結(jié)構(gòu)初期小損傷狀態(tài),此時(shí)結(jié)構(gòu)損傷響應(yīng)特征相對(duì)微弱,如果不采用合理的降噪辦法就難以得到較好損傷識(shí)別結(jié)果。因此,本文主要研究的是強(qiáng)噪聲背景下基于振動(dòng)響應(yīng)信號(hào)的特征提取及損傷定位。論文針對(duì)振動(dòng)響應(yīng)信號(hào)的特征提取及損傷定位主要完成了以下工作:針對(duì)旋轉(zhuǎn)機(jī)械轉(zhuǎn)子碰摩故障檢測(cè)中存在的噪聲干擾問題,提出了基于二次采樣的大參數(shù)自適應(yīng)隨機(jī)共振算法。該算法很好地解決了傳統(tǒng)隨機(jī)共振算法僅適用于小參數(shù)檢測(cè)的局限性,仿真和試驗(yàn)數(shù)據(jù)分析表明該方法能夠顯著提高測(cè)試數(shù)據(jù)信噪比指標(biāo)。本文基于Duffing混沌振子的結(jié)構(gòu)損傷檢測(cè),提出了一種新的基于Duffing混沌振子和響應(yīng)靈敏度結(jié)合的結(jié)構(gòu)損傷檢測(cè)方法。通過一組特定的參數(shù)選擇對(duì)響應(yīng)信號(hào)進(jìn)行提取,從而避免了繁瑣的傳統(tǒng)Duffing振子參數(shù)的選擇方法。把該方法應(yīng)用于三個(gè)維度的梁模型和橋梁模型,結(jié)果表明該方法可以很好的強(qiáng)噪聲背景下實(shí)現(xiàn)結(jié)構(gòu)的損傷定位,這可以為結(jié)構(gòu)損傷識(shí)別提供一個(gè)更好的思路。為了實(shí)現(xiàn)對(duì)試驗(yàn)參數(shù)的精確識(shí)別,在氣動(dòng)噪聲條件下進(jìn)行了超聲速飛行試驗(yàn)數(shù)據(jù)的相空間重構(gòu)和奇異譜分析相結(jié)合的方法。首先,通過數(shù)值模擬的方法證明了該方法的可行性。然后,通過對(duì)某型超聲無人機(jī)的聲振動(dòng)試驗(yàn),對(duì)試驗(yàn)數(shù)據(jù)進(jìn)行相空間重構(gòu),實(shí)現(xiàn)了對(duì)信號(hào)子空間和噪聲子空間的奇異值分解。通過定義奇異值差分譜來確定真實(shí)信號(hào)子空間維數(shù),并對(duì)現(xiàn)有的最大差分譜理論,提出了一種優(yōu)化差分譜峰值的方法。重構(gòu)結(jié)果表明,該方法適用于飛機(jī)在超音速飛行條件下的聲振動(dòng)試驗(yàn)的數(shù)據(jù)處理。針對(duì)薄板結(jié)構(gòu)(鋁板)損傷檢測(cè)過程中存在的噪聲干擾問題,提出了建立在奇異譜分析上的最大似然性原理分析的損傷檢測(cè)方法。將Lamb波激勵(lì)響應(yīng)信號(hào)進(jìn)行奇異譜分析,通過優(yōu)選差分譜理論選擇最優(yōu)重構(gòu)信號(hào)進(jìn)行重構(gòu),基于最大相似性原則,通過采用遺傳算法(Genetic Algorithms,GA)對(duì)重構(gòu)信號(hào)參數(shù)進(jìn)行優(yōu)化以實(shí)現(xiàn)對(duì)于測(cè)量信號(hào)構(gòu)成部分的分析。鋁板試驗(yàn)結(jié)果有效證明了該方法的實(shí)用性和有效性�？紤]強(qiáng)噪聲背景環(huán)境下的非線性結(jié)構(gòu)損傷檢測(cè)問題,針對(duì)具體的非線性質(zhì)量-彈簧系統(tǒng)設(shè)計(jì)了對(duì)應(yīng)的物理等效模型,通過增加結(jié)構(gòu)自由度的方式將原有非線性系統(tǒng)等效為增強(qiáng)的線性系統(tǒng)進(jìn)行分析,建立了系統(tǒng)非線性項(xiàng)的動(dòng)力平衡方程。通過奇異譜分析、直接參數(shù)識(shí)別方法以及矩陣最小秩擾動(dòng)理論實(shí)現(xiàn)了對(duì)于非線性系統(tǒng)強(qiáng)噪聲背景下的損傷定位及損傷程度判定。
[Abstract]:In the process of damage detection of various engineering structures based on vibration response, due to the influence of external natural environment or human factors, the measured vibration response signal not only contains the damage information of the structure. At the same time, there is also a large number of noise interference. The existence of noise seriously affects the extraction of effective vibration response data of the structure, especially for the initial small damage state of the structure, the damage response characteristics of the structure are relatively weak. If reasonable noise reduction method is not adopted, it is difficult to get better damage identification results. Therefore, this paper mainly studies the feature extraction and damage location based on vibration response signal in strong noise background. Aiming at the feature extraction and damage location of vibration response signal, the main work of this paper is as follows: aiming at the problem of noise interference in rotor rub-impact fault detection of rotating machinery, A large parameter adaptive stochastic resonance algorithm based on quadratic sampling is proposed. The algorithm solves the limitation that the traditional stochastic resonance algorithm is only suitable for small parameter detection. Simulation and experimental data analysis show that the method can significantly improve the signal-to-noise ratio (SNR) index of the test data. Based on the structural damage detection of Duffing chaotic oscillator, a new structural damage detection method based on Duffing chaotic oscillator and response sensitivity is proposed in this paper. The response signal is extracted by a set of specific parameter selection, thus avoiding the tedious traditional Duffing oscillator parameter selection method. The method is applied to the beam model and bridge model of three dimensions. The results show that the method can realize the damage location of the structure under the background of strong noise, which can provide a better idea for structural damage identification. In order to identify the test parameters accurately, the phase space reconstruction and singular spectrum analysis of supersonic flight test data are carried out under the condition of pneumatic noise. Firstly, the feasibility of the method is proved by numerical simulation. Then, through the acoustic vibration test of a certain ultrasonic UAV, the phase space reconstruction of the test data is carried out, and the singular value decomposition of signal subspace and noise subspace is realized. The dimension of real signal subspace is determined by defining singular value difference spectrum, and a method to optimize the peak value of difference spectrum is proposed for the existing maximum difference spectrum theory. The reconstruction results show that the method is suitable for data processing of aircraft acoustic vibration test under supersonic flight conditions. In order to solve the problem of noise interference in the process of damage detection of thin plate structure (aluminum plate), a damage detection method based on the principle of maximum likelihood based on singular spectrum analysis is proposed. The Lamb wave excitation response signal is analyzed by singular spectrum analysis, and the optimal reconstructed signal is selected by optimal selection difference spectrum theory. based on the principle of maximum similarity, the genetic algorithm (Genetic Algorithms, is adopted. GA) optimize the reconstructed signal parameters to realize the analysis of the measured signal components. The experimental results of aluminum plate show the practicability and effectiveness of the method. In this paper, the problem of nonlinear structural damage detection in strong noise background is considered, and the corresponding physical equivalent model is designed for the nonlinear mass-spring system. By increasing the degree of freedom of the structure, the original nonlinear system is equivalent to the enhanced linear system, and the dynamic equilibrium equation of the nonlinear term of the system is established. Through singular spectrum analysis, direct parameter identification method and matrix minimum rank disturbance theory, the damage location and damage degree of nonlinear system under strong noise background are realized.
【學(xué)位授予單位】：西北工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2016
【分類號(hào)】：O327

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