基于超聲波的壓力測(cè)量模型研究
發(fā)布時(shí)間：2018-08-18 17:11
【摘要】：壓力容器在日常生活和工業(yè)生產(chǎn)很多領(lǐng)域中都得到廣泛的應(yīng)用,為了使其安全、正常運(yùn)行,對(duì)于其內(nèi)部壓力的檢測(cè)至關(guān)重要。傳統(tǒng)的壓力測(cè)量方法往往需要進(jìn)行開(kāi)孔等可能破壞容器完整性的操作。非介入式壓力檢測(cè)方法具有安全、便攜等優(yōu)點(diǎn),應(yīng)用前景良好�；诔暡ǖ姆墙槿胧綁毫z測(cè),其主要的理論基礎(chǔ)是聲彈性效應(yīng)和薄殼理論。在對(duì)相關(guān)領(lǐng)域的文獻(xiàn)和成果的研究基礎(chǔ)之上,本論文建立了基于臨界折射縱波、反射縱波的線性和非線性壓力測(cè)量模型,對(duì)模型的波形選擇進(jìn)行了研究,并對(duì)各個(gè)模型進(jìn)行了分析和比較。本論文的主要研究成果和創(chuàng)新之處在于:(1)提出了基于最佳子集回歸和逐步回歸算法的多變量壓力測(cè)量模型輸入波形的選擇方法。之前多變量壓力測(cè)量模型輸入波形的選擇只是簡(jiǎn)單的根據(jù)輸入波形的區(qū)分度和信噪比。用于建立模型的波形的選擇至關(guān)重要:一方面,越多的解釋變量更多的自變量可以使信息更加完整、全面,使預(yù)測(cè)更加精確,但也可能造成"過(guò)擬合"的現(xiàn)象,同時(shí)需要估計(jì)的參數(shù)個(gè)數(shù)增加會(huì)導(dǎo)致方差提高;另一方面,過(guò)少的解釋變量可能造成"欠擬合"的現(xiàn)象,預(yù)測(cè)準(zhǔn)確度降低。本文將最佳子集回歸和逐步回歸算法應(yīng)用于輸入信號(hào)波形的選擇,可以建立更優(yōu)、更符合選定準(zhǔn)則的模型。(2)針對(duì)線性壓力測(cè)量模型精度不高的問(wèn)題,提出并建立了基于臨界折射縱波、反射縱波的非線性壓力測(cè)量模型。根據(jù)聲彈性效應(yīng)和薄殼理論,壓力與臨界折射縱波、反射縱波呈線性關(guān)系,但實(shí)驗(yàn)數(shù)據(jù)表明在某些壓力范圍內(nèi),二者存在非線性關(guān)系。本論文嘗試使用非線性方法進(jìn)行建模,包括將傳播時(shí)延的二次項(xiàng)加入測(cè)量模型以及基于神經(jīng)網(wǎng)絡(luò)的測(cè)量模型,實(shí)驗(yàn)結(jié)果表明,非線性壓力測(cè)量模型比線性壓力測(cè)量模型的測(cè)量精度更高,非線性模型中基于BFGS神經(jīng)網(wǎng)絡(luò)的模型測(cè)量精度最高。(3)對(duì)超聲波在容器壁中的傳播過(guò)程的信號(hào)幅值變化機(jī)理進(jìn)行了理論分析。超聲波從發(fā)射探頭到接收探頭傳播過(guò)程中,由于反射、折射等會(huì)引起波型轉(zhuǎn)換和能量分配,另外,在傳播過(guò)程中由于散射、擴(kuò)散和吸收也會(huì)引起能量的衰減,綜合表現(xiàn)為幅值的變化。為了確定合適的探頭間距,以獲取信噪比更高的波形,本論文對(duì)超聲波在圓柱型壓力容器壁的傳播過(guò)程中的幅值變化進(jìn)行了理論分析。
[Abstract]:Pressure vessels are widely used in many fields of daily life and industrial production. In order to make them safe and normal operation, it is very important to detect the internal pressure. Traditional pressure measurement methods often require operations such as opening holes that may damage the integrity of the vessel. The non-interventional pressure detection method has the advantages of safety and portability, and has a good prospect in application. The main theoretical basis of non-interventional pressure measurement based on ultrasonic wave is acoustic elastic effect and thin shell theory. Based on the research of literature and achievements in related fields, the linear and nonlinear pressure measurement models based on critical refraction P-wave and reflected P-wave are established in this paper, and the waveform selection of the model is studied. The models are analyzed and compared. The main achievements and innovations of this thesis are as follows: (1) an input waveform selection method based on optimal subset regression and stepwise regression algorithm for multivariable pressure measurement model is proposed. The selection of input waveform of multivariable pressure measurement model is simply based on the discrimination and signal-to-noise ratio of the input waveform. The choice of waveforms used to build models is crucial: on the one hand, more explanatory variables and more independent variables can make information more complete, more comprehensive, and more accurate predictions, but may also result in "overfitting". On the other hand, too few explanatory variables may cause the phenomenon of "under-fitting", and the accuracy of prediction will be reduced. In this paper, the optimal subset regression and stepwise regression algorithms are applied to the selection of input signal waveforms, which can set up a better model, which is more consistent with the selected criteria. (2) the accuracy of the linear pressure measurement model is not high enough. A nonlinear pressure measurement model based on critical refraction P-wave and reflected P-wave is proposed and established. According to the acoustoelastic effect and thin shell theory, the pressure is linearly related to the critical refraction longitudinal wave and the reflected longitudinal wave, but the experimental data show that there is a nonlinear relationship between them in some pressure range. This thesis attempts to use nonlinear method to model the model, including adding the quadratic term of propagation delay into the measurement model and the measurement model based on neural network. The experimental results show that, The accuracy of nonlinear pressure measurement model is higher than that of linear pressure measurement model. In the nonlinear model, the model based on BFGS neural network has the highest measurement accuracy. (3) the mechanism of signal amplitude variation in the process of ultrasonic wave propagation in the vessel wall is analyzed theoretically. In the process of ultrasonic wave propagation from transmitting probe to receiving probe, wave type conversion and energy distribution will be caused by reflection and refraction. In addition, energy attenuation will also be caused by scattering, diffusion and absorption during the propagation process. The comprehensive performance is the change of amplitude. In order to determine the appropriate probe spacing and obtain the higher signal-to-noise ratio (SNR) waveform, the amplitude variation of ultrasonic wave during the propagation of cylindrical pressure vessel wall is theoretically analyzed in this paper.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TH49;TB559
本文編號(hào)：2190134
[Abstract]:Pressure vessels are widely used in many fields of daily life and industrial production. In order to make them safe and normal operation, it is very important to detect the internal pressure. Traditional pressure measurement methods often require operations such as opening holes that may damage the integrity of the vessel. The non-interventional pressure detection method has the advantages of safety and portability, and has a good prospect in application. The main theoretical basis of non-interventional pressure measurement based on ultrasonic wave is acoustic elastic effect and thin shell theory. Based on the research of literature and achievements in related fields, the linear and nonlinear pressure measurement models based on critical refraction P-wave and reflected P-wave are established in this paper, and the waveform selection of the model is studied. The models are analyzed and compared. The main achievements and innovations of this thesis are as follows: (1) an input waveform selection method based on optimal subset regression and stepwise regression algorithm for multivariable pressure measurement model is proposed. The selection of input waveform of multivariable pressure measurement model is simply based on the discrimination and signal-to-noise ratio of the input waveform. The choice of waveforms used to build models is crucial: on the one hand, more explanatory variables and more independent variables can make information more complete, more comprehensive, and more accurate predictions, but may also result in "overfitting". On the other hand, too few explanatory variables may cause the phenomenon of "under-fitting", and the accuracy of prediction will be reduced. In this paper, the optimal subset regression and stepwise regression algorithms are applied to the selection of input signal waveforms, which can set up a better model, which is more consistent with the selected criteria. (2) the accuracy of the linear pressure measurement model is not high enough. A nonlinear pressure measurement model based on critical refraction P-wave and reflected P-wave is proposed and established. According to the acoustoelastic effect and thin shell theory, the pressure is linearly related to the critical refraction longitudinal wave and the reflected longitudinal wave, but the experimental data show that there is a nonlinear relationship between them in some pressure range. This thesis attempts to use nonlinear method to model the model, including adding the quadratic term of propagation delay into the measurement model and the measurement model based on neural network. The experimental results show that, The accuracy of nonlinear pressure measurement model is higher than that of linear pressure measurement model. In the nonlinear model, the model based on BFGS neural network has the highest measurement accuracy. (3) the mechanism of signal amplitude variation in the process of ultrasonic wave propagation in the vessel wall is analyzed theoretically. In the process of ultrasonic wave propagation from transmitting probe to receiving probe, wave type conversion and energy distribution will be caused by reflection and refraction. In addition, energy attenuation will also be caused by scattering, diffusion and absorption during the propagation process. The comprehensive performance is the change of amplitude. In order to determine the appropriate probe spacing and obtain the higher signal-to-noise ratio (SNR) waveform, the amplitude variation of ultrasonic wave during the propagation of cylindrical pressure vessel wall is theoretically analyzed in this paper.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TH49;TB559
【參考文獻(xiàn)】
相關(guān)期刊論文 前10條
1 陳學(xué)東;崔軍;章小滸;關(guān)衛(wèi)和;壽比南;謝鐵軍;;我國(guó)壓力容器設(shè)計(jì)、制造和維護(hù)十年回顧與展望[J];壓力容器;2012年12期
2 秦叔經(jīng);;壓力容器標(biāo)準(zhǔn)和規(guī)范中分析設(shè)計(jì)方法的進(jìn)展[J];化工設(shè)備與管道;2011年01期
3 林韶峰,張宏建;基于Rayleigh表面波的無(wú)損測(cè)壓方法[J];儀器儀表學(xué)報(bào);2005年09期
4 沈功田,李金海;壓力容器無(wú)損檢測(cè)——聲發(fā)射檢測(cè)技術(shù)[J];無(wú)損檢測(cè);2004年09期
5 沈功田,張萬(wàn)嶺;壓力容器無(wú)損檢測(cè)技術(shù)綜述[J];無(wú)損檢測(cè);2004年01期
6 祁樹(shù)勝;應(yīng)變片測(cè)量的誤差分析[J];西安航空技術(shù)高等專(zhuān)科學(xué)校學(xué)報(bào);2003年03期
7 李戎;壓力傳感器靈敏度特性的研究[J];鑄造技術(shù);2003年05期
8 潘泉,于昕,程詠梅,張洪才;信息融合理論的基本方法與進(jìn)展[J];自動(dòng)化學(xué)報(bào);2003年04期
9 王耀南,李樹(shù)濤;多傳感器信息融合及其應(yīng)用綜述[J];控制與決策;2001年05期
10 吳守正,胡慶超;超聲波管外壓力測(cè)量[J];液壓與氣動(dòng);1989年03期
相關(guān)博士學(xué)位論文 前2條
1 凌張偉;基于臨界折射縱波和表面波的壓力容器壓力測(cè)量方法研究[D];浙江大學(xué);2010年
2 林韶峰;基于超聲波的非侵入式壓力測(cè)量方法研究[D];浙江大學(xué);2005年
相關(guān)碩士學(xué)位論文 前4條
1 趙延杰;基于多元回歸算法的非介入式壓力檢測(cè)技術(shù)研究[D];浙江大學(xué);2016年
2 周漢華;基于多個(gè)轉(zhuǎn)換波形的非介入式壓力檢測(cè)方法研究[D];浙江大學(xué);2015年
3 畢瑤;基于反射縱波的壓力容器壓力測(cè)量方法研究[D];浙江大學(xué);2014年
4 劉芮君;一種新型殼體電容式壓力檢測(cè)系統(tǒng)的研究[D];中北大學(xué);2013年
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