本文選題：鋼管 + 超聲檢測(cè)　； 參考：《鋼鐵研究總院》2014年碩士論文

【摘要】：在利用超聲波在對(duì)鋼管進(jìn)行檢測(cè)時(shí),其中影響超聲檢測(cè)效果的一個(gè)主要因素就是鋼管的表面狀況。如果鋼管材料的表面狀況很差,粗糙度高,超聲波會(huì)在材料的檢測(cè)表面發(fā)生反射、折射作用,這對(duì)超聲波造成很大的衰減并使得超聲回波信號(hào)伴隨有大量噪聲信號(hào),降低了超聲檢測(cè)的靈敏度和信噪比,嚴(yán)重影響后續(xù)對(duì)超聲檢測(cè)缺陷信號(hào)的判別以及定性、定量分析,影響超聲探傷結(jié)果的準(zhǔn)確性。 本文結(jié)合課題的研究目的和方法,利用現(xiàn)有的實(shí)驗(yàn)設(shè)備,自行搭建一套完整的超聲檢測(cè)信號(hào)處理系統(tǒng),并在Windows操作系統(tǒng)下,通過(guò)美國(guó)國(guó)家儀器(NI)提供的LabVIEW開(kāi)發(fā)軟件設(shè)計(jì)出了基于虛擬儀器的超聲檢測(cè)信號(hào)處理平臺(tái)。該系統(tǒng)可以激勵(lì)超聲探頭發(fā)射超聲波信號(hào),利用數(shù)據(jù)采集卡完成超聲檢測(cè)回波信號(hào)的模／數(shù)轉(zhuǎn)換,并通過(guò)USB串口總線把所采集的數(shù)據(jù)上傳到計(jì)算機(jī)內(nèi)。在計(jì)算機(jī)上開(kāi)發(fā)的基于虛擬儀器的超聲檢測(cè)信號(hào)處理平臺(tái)可以對(duì)數(shù)據(jù)采集卡進(jìn)行狀態(tài)控制和參數(shù)設(shè)置,并對(duì)所讀取的超聲檢測(cè)回波信號(hào)做相應(yīng)的處理工作。 利用自行搭建的基于虛擬儀器超聲檢測(cè)信號(hào)處理系統(tǒng),對(duì)表面粗糙鋼管的超聲檢測(cè)信號(hào)進(jìn)行了相關(guān)的處理工作。對(duì)表面粗糙鋼管的信號(hào)處理工作主要包括基于傳統(tǒng)傅立葉變換的信號(hào)分析處理工作和基于小波變換的信號(hào)分析處理工作�；趥鹘y(tǒng)傅立葉變換的信號(hào)分析處理工作主要有：①對(duì)表面粗糙鋼管的超聲檢測(cè)信號(hào)進(jìn)行快速傅立葉變換(FFT),完成表面粗糙鋼管超聲檢測(cè)信號(hào)的頻譜分析；②在頻譜分析的基礎(chǔ)上,對(duì)表面粗糙鋼管的超聲檢測(cè)信號(hào)做有限長(zhǎng)單位沖激響應(yīng)(FIR)加窗濾波處理,并對(duì)所加不同窗函數(shù)的濾波效果進(jìn)行比較分析；③利用短時(shí)傅立葉變換(STFT)對(duì)表面粗糙鋼管的超聲檢測(cè)信號(hào)進(jìn)行時(shí)頻分析.基于小波變換的信號(hào)分析處理工作主要有：①利用小波變換(WT)對(duì)表面粗糙鋼管的超聲檢測(cè)信號(hào)進(jìn)行時(shí)頻分析,并與短時(shí)傅立葉變換的時(shí)頻分析結(jié)果相比較；②利用小波閾值去噪法對(duì)表面粗糙鋼管的超聲檢測(cè)信號(hào)進(jìn)行去噪處理,并對(duì)軟、硬閾值法去噪的結(jié)果進(jìn)行比較分析。 研究結(jié)果表明,在利用超聲檢測(cè)技術(shù)對(duì)表面狀況達(dá)不到標(biāo)準(zhǔn)規(guī)定要求的鋼管材料進(jìn)行檢測(cè)時(shí),如果不進(jìn)行任何降噪處理,由于檢測(cè)信噪比較低,很難實(shí)現(xiàn)缺陷的可靠檢出(工業(yè)探傷的信噪比一般應(yīng)達(dá)到6dB～8dB以上)。而通過(guò)對(duì)檢測(cè)信號(hào)進(jìn)行適當(dāng)?shù)臑V波或去噪處理后,檢測(cè)信噪比得到了明顯的改善。但是傳統(tǒng)的基于傅立葉變換的FIR波技術(shù),在消除噪聲的同時(shí)會(huì)把大量的有用信號(hào)也濾除掉,導(dǎo)致波形的失真；而基于小波變換的信號(hào)去噪處理,幾乎不會(huì)造成有用信號(hào)的損失,而且可以有效保持缺陷信號(hào)的特征形貌,達(dá)到更為理想的效果。這為今后表面粗糙鋼管的超聲檢測(cè)信號(hào)處理技術(shù)提供了很好的解決途徑。
[Abstract]:The surface condition of the steel tube is one of the main factors that affect the effect of ultrasonic testing. If the surface condition of steel tube is very poor and the roughness is high, the ultrasonic wave will reflect and refraction on the testing surface of the material, which will cause great attenuation to the ultrasonic wave and make the ultrasonic echo signal accompanied by a large number of noise signals. It reduces the sensitivity and signal-to-noise ratio of ultrasonic detection, seriously affects the discrimination, qualitative and quantitative analysis of ultrasonic flaw signals, and affects the accuracy of ultrasonic flaw detection results. Using the existing experimental equipment, a complete ultrasonic detection signal processing system is built by ourselves, and under Windows operating system, The ultrasonic signal processing platform based on virtual instrument is designed by LabVIEW software provided by the National instrument of USA. The system can excite the ultrasonic probe to transmit the ultrasonic signal, use the data acquisition card to complete the A / D conversion of the ultrasonic detection echo signal, and upload the collected data to the computer through the USB serial port bus. The ultrasonic signal processing platform based on virtual instrument developed on the computer can control the state and set the parameters of the data acquisition card. The ultrasonic signal processing system based on virtual instrument is used to process the ultrasonic signal of rough steel pipe. The signal processing of rough surface steel pipe mainly includes the signal analysis and processing based on the traditional Fourier transform and the signal analysis and processing based on the wavelet transform. The main work of signal analysis and processing based on traditional Fourier transform is to perform fast Fourier transform (FFTT) on ultrasonic detection signal of rough surface steel pipe with 1: 1, and to complete the spectrum analysis of ultrasonic detection signal of rough surface steel pipe. (2) on the basis of spectrum analysis, the ultrasonic detection signal of rough surface steel pipe is filtered by finite length unit impulse response (FIR), and the filtering effect of different window function is compared and analyzed. (3) the short time Fourier transform (STFT) was used to analyze the ultrasonic signal of rough steel pipe. The work of signal analysis and processing based on wavelet transform mainly includes: (1) using wavelet transform (WTT) to analyze the ultrasonic detection signal of rough steel pipe, and comparing the results with that of STFT. 2De-noising the ultrasonic signal of rough surface steel pipe by wavelet threshold de-noising method, and comparing and analyzing the results of soft and hard threshold de-noising. When ultrasonic testing technology is used to detect steel tube material whose surface condition is not up to the standard, if no noise reduction is done, the signal-to-noise ratio (SNR) of the detection is low. It is difficult to detect defects reliably. (the SNR of industrial flaw detection should be above 6 dB or more than 8 dB. The signal-to-noise ratio (SNR) of the detected signal is obviously improved after proper filtering or de-noising of the detected signal. However, the traditional Fir technology based on Fourier transform can eliminate the noise and filter out a large number of useful signals, which results in the distortion of the waveform, while the signal de-noising based on wavelet transform can hardly cause the loss of useful signals. Moreover, it can effectively maintain the feature and morphology of the defect signal, and achieve a more ideal effect. This provides a good solution for ultrasonic signal processing technology of surface rough steel pipe in the future.
【學(xué)位授予單位】：鋼鐵研究總院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TB553;TN911.7

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