【摘要】：水工結(jié)構(gòu)振動(dòng)信號(hào)在輸送和獲取的過(guò)程中,容易受到環(huán)境激勵(lì)的高頻白噪聲和低頻水流噪聲的干擾,通常表現(xiàn)為低信噪比、非平穩(wěn)隨機(jī)信號(hào),結(jié)構(gòu)振動(dòng)特征信息完全淹沒(méi)在強(qiáng)噪聲中,難以精確識(shí)別其模態(tài)信息,從而影響判斷結(jié)構(gòu)健康狀況及振動(dòng)危害評(píng)價(jià)的精度。因此,需采取有效的信號(hào)分析方法對(duì)實(shí)測(cè)數(shù)據(jù)降噪處理,以獲取結(jié)構(gòu)振動(dòng)信號(hào)的優(yōu)勢(shì)特征信息。本文針對(duì)水工結(jié)構(gòu)振動(dòng)信號(hào)非平穩(wěn)性和特征信息被強(qiáng)噪聲淹沒(méi)的實(shí)際問(wèn)題,以EMD算法的自身特點(diǎn)及其不斷發(fā)展完善為線索,全面探索不同階段EMD算法在水工結(jié)構(gòu)振動(dòng)信號(hào)處理中的應(yīng)用,研究其在水工結(jié)構(gòu)信號(hào)處理中的特點(diǎn)及優(yōu)勢(shì),以期得到較好適應(yīng)于水工結(jié)構(gòu)信號(hào)處理的方法,實(shí)現(xiàn)強(qiáng)噪聲背景下泄流結(jié)構(gòu)工作特性有效信息的提取,為結(jié)構(gòu)下一步健康診斷工作提供幫助。本文所做的主要工作和得到的結(jié)論如下:1、為探索EMD算法在水工結(jié)構(gòu)振動(dòng)信號(hào)處理中的應(yīng)用,針對(duì)水工結(jié)構(gòu)振動(dòng)信號(hào)的特點(diǎn),介紹了一種聯(lián)合運(yùn)用小波閾值與EMD算法對(duì)水工結(jié)構(gòu)振動(dòng)信號(hào)進(jìn)行降噪的新思路。仿真信號(hào)計(jì)算結(jié)果表明,小波閾值與EMD聯(lián)合濾波降噪是相對(duì)優(yōu)越的降噪方法。拉西瓦拱壩工程實(shí)例計(jì)算結(jié)果表明該方法可以有效的完成降噪的任務(wù),準(zhǔn)確得到壩體的振動(dòng)信息和優(yōu)勢(shì)頻率,為大壩的在線監(jiān)測(cè)與安全健康診斷提供幫助。2、充分發(fā)揮正交化經(jīng)驗(yàn)?zāi)B(tài)分解的優(yōu)點(diǎn),介紹了一種基于奇異值分解(SVD)和改進(jìn)EMD聯(lián)合的水工結(jié)構(gòu)振動(dòng)信號(hào)特征信息提取方法。該方法通過(guò)SVD將振動(dòng)信號(hào)中的高頻噪聲濾除,并通過(guò)正交化EMD將低頻水流噪聲濾除,實(shí)現(xiàn)信號(hào)的二次濾波,最終得到水工結(jié)構(gòu)的工作振動(dòng)特征信息。仿真信號(hào)計(jì)算結(jié)果表明該方法的正確性,結(jié)合三峽5號(hào)壩段泄流振動(dòng)實(shí)測(cè)數(shù)據(jù),運(yùn)用該方法進(jìn)行壩體特征信息提取,并與ERA辨識(shí)結(jié)果進(jìn)行比較,說(shuō)明該方法在水工結(jié)構(gòu)振動(dòng)信息分析中的優(yōu)越性,具有良好的降噪能力和工程實(shí)用性,可為水工結(jié)構(gòu)在線監(jiān)測(cè)和安全運(yùn)行提供幫助。3、詳細(xì)介紹了CEEMDAN算法和排列熵的工作原理,并充分發(fā)揮二者優(yōu)勢(shì),提出了基于CEEMDAN和排列熵聯(lián)合提取水工結(jié)構(gòu)特征信息的方法。通過(guò)構(gòu)造仿真數(shù)據(jù),對(duì)比CEEMDAN算法、SVD以及CEEMDAN-PE-SVD算法三者的降噪結(jié)果,計(jì)算結(jié)果表明CEEMDAN-PE-SVD方法能夠有效地濾除信號(hào)中的干擾成分,還原信號(hào)的優(yōu)勢(shì)特征頻率,具有較高的提取精度,屬于更優(yōu)越的信號(hào)降噪方法。將該方法應(yīng)用于三峽重力壩泄流工程,表明該方法能夠精確提取結(jié)構(gòu)的工作特征信息,抗噪性強(qiáng),實(shí)用性強(qiáng),具有極佳的應(yīng)用前景。4、針對(duì)水工結(jié)構(gòu)振動(dòng)信號(hào)的特點(diǎn),以EMD算法的不斷改進(jìn)發(fā)展為線索,研究不同階段EMD算法的自身特點(diǎn)及其在水工結(jié)構(gòu)信號(hào)處理中的應(yīng)用。研究結(jié)果表明經(jīng)驗(yàn)?zāi)B(tài)分解可以很好地應(yīng)用于水工結(jié)構(gòu)振動(dòng)信號(hào)處理中,可為解決水工結(jié)構(gòu)振動(dòng)信號(hào)處理提供新思路。
[Abstract]:The vibration signals of hydraulic structures are easily disturbed by high frequency white noise and low frequency water flow noise in the process of conveying and obtaining the vibration signals of hydraulic structures, which usually appear as low signal-to-noise ratio (SNR) and non-stationary random signals. The vibration characteristic information of the structure is completely submerged in the strong noise, so it is difficult to identify the modal information accurately, thus affecting the accuracy of judging the health condition of the structure and the evaluation of the vibration hazard. Therefore, it is necessary to adopt effective signal analysis method to reduce the noise of the measured data in order to obtain the advantage characteristic information of the structural vibration signal. Aiming at the practical problem that the vibration signal of hydraulic structure is not stationary and characteristic information is submerged by strong noise, this paper takes the characteristic of EMD algorithm and its continuous development and perfection as the clue. This paper probes into the application of EMD algorithm in different stages in the vibration signal processing of hydraulic structures, studies its characteristics and advantages in the signal processing of hydraulic structures, in order to obtain a better method suitable for the signal processing of hydraulic structures. The effective information extraction of the working characteristics of the discharge structure under the strong noise background is realized, which provides the help for the next health diagnosis of the structure. The main work and conclusions obtained in this paper are as follows: 1. In order to explore the application of EMD algorithm in vibration signal processing of hydraulic structures, the characteristics of vibration signals of hydraulic structures are discussed. A new method for noise reduction of hydraulic structure vibration signal using wavelet threshold and EMD algorithm is introduced. The simulation results show that the wavelet threshold combined with EMD filtering is a relatively superior denoising method. The result of practical example of Laxiwa arch dam project shows that the method can effectively accomplish the task of noise reduction and accurately obtain the vibration information and dominant frequency of the dam body. In this paper, the advantages of orthogonal empirical mode decomposition (EMD) are brought into full play. A method based on singular value decomposition (SVD) and improved EMD is introduced to extract the characteristic information of vibration signals of hydraulic structures. In this method, the high frequency noise in the vibration signal is filtered by SVD, and the low frequency water flow noise is filtered by orthogonal EMD to realize the secondary filtering of the signal. Finally, the working vibration characteristic information of hydraulic structure is obtained. The result of simulation signal calculation shows that the method is correct. Combining with the measured data of discharge vibration of dam section 5 of the three Gorges Dam, the method is used to extract the characteristic information of the dam body, and the result is compared with the result of ERA identification. The advantages of this method in the vibration information analysis of hydraulic structures are illustrated. The method has good noise reduction ability and engineering practicability. It can provide help for on-line monitoring and safe operation of hydraulic structures. 3. The CEEMDAN algorithm and the working principle of permutation entropy are introduced in detail. Based on CEEMDAN and permutation entropy, the method of extracting the characteristic information of hydraulic structure is put forward. By constructing the simulation data and comparing the noise reduction results of CEEMDAN algorithm, SVD algorithm and CEEMDAN-PE-SVD algorithm, the results show that the CEEMDAN-PE-SVD method can effectively filter the interference components in the signal, restore the dominant characteristic frequency of the signal, and have a high extraction accuracy. It belongs to better signal denoising method. The method is applied to the discharge project of the three Gorges Gravity Dam. It shows that the method can extract the working characteristic information of the structure accurately, has strong anti-noise, strong practicability, and has excellent application prospect. 4, aiming at the characteristics of the vibration signal of hydraulic structure, Based on the continuous improvement and development of EMD algorithm, the characteristics of EMD algorithm in different stages and its application in hydraulic structure signal processing are studied. The results show that the empirical mode decomposition can be well applied to the vibration signal processing of hydraulic structures and can provide a new idea for solving the vibration signal processing of hydraulic structures.
【學(xué)位授予單位】：華北水利水電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TV312

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本文編號(hào)：2271951