大型鍛件超聲檢測方法及信號處理算法研究
發(fā)布時間：2018-11-24 14:25
【摘要】：大型鍛件是重大裝備的關(guān)鍵部件,已廣泛應(yīng)用于電力、航空航天、船舶、重型機械等領(lǐng)域,其質(zhì)量直接影響到裝備的整體水平和運行可靠性,需要對其可能存在的裂紋、氣孔和夾雜等缺陷進(jìn)行檢測。超聲檢測具有穿透能力強、缺陷檢測準(zhǔn)確率高、靈敏度高、檢測成本低、對人及環(huán)境無害等優(yōu)點,適合大型鍛件的缺陷檢測。目前,國內(nèi)大型鍛件的超聲檢測大多是手動掃描、人工判讀,易出現(xiàn)漏檢和誤判,檢測效率低、可靠性差,需要研制一種大型鍛件自動超聲檢測系統(tǒng),其中,檢測方法和信號處理是系統(tǒng)涉及的關(guān)鍵技術(shù),但是,目前使用的技術(shù)都有一定的局限性,本文針對這些技術(shù)進(jìn)行理論和實驗研究,主要研究內(nèi)容如下：1.提出了大型圓筒型鍛件及大型中厚鋼板的多通道自動超聲檢測方法。對于大型中厚鋼板,主探頭組(兼作橫邊探頭組)放置在鋼板橫向中間部位,縱邊探頭組放置在鋼板兩個縱邊,檢測橫邊時,鋼板不動,主探頭左右擺動,檢測其它部位時,鋼板沿壓延方向勻速直線運動,主探頭左右擺動,縱邊探頭不動,形成板邊為矩形而板內(nèi)為正弦或余弦的掃描軌跡；對于大型圓筒型鍛件,直探頭組和斜探頭組分別縱向放置在直徑方向上筒壁的兩個外側(cè),檢測時,圓筒型鍛件繞其軸線原地旋轉(zhuǎn),兩組探頭同時沿軸線平移,形成空間螺旋線的掃描軌跡。將超聲探頭分組放置在不同位置,同時對檢測工件按指定路徑進(jìn)行自動全方位掃描,提高了檢測效率和可靠性。2.對超聲反射回波信號降噪的理論和算法進(jìn)行了研究,提出了基于小波變換和獨立分量分析的超聲反射回波信號降噪算法(WICAW)。利用小波變換將原始信號分解,對分解的系數(shù)進(jìn)行獨立分量分析,并對分離出的獨立分量進(jìn)行閾值評估,濾除噪聲,再通過小波重構(gòu)得到降噪后的超聲信號。仿真和實驗結(jié)果表明,該算法既不丟失有用信息又提高了信噪比,性能優(yōu)于小波軟閾值降噪算法。3.對缺陷超聲信號的特征提取與識別技術(shù)進(jìn)行了研究,提出了基于小波系數(shù)聚類和SVM的缺陷超聲信號特征提取與識別算法。利用小波變換對降噪的超聲回波信號進(jìn)行分解,然后以概率統(tǒng)計聚類的方法將分解得到的小波系數(shù)聚類,計算每個聚類的小波系數(shù)能量值并作為SVM分類器的輸入特征向量,實現(xiàn)缺陷識別。通過對典型缺陷試塊進(jìn)行檢測,實驗結(jié)果表明,該算法減少了分類器的計算量,提高了小樣本缺陷識別的準(zhǔn)確率。4.設(shè)計了基于以太網(wǎng)的大型鍛件自動超聲檢測系統(tǒng),搭建了實驗平臺,進(jìn)行了實驗研究,驗證了本文提出的檢測方法和信號處理算法的有效性。
[Abstract]:Large forgings are the key parts of heavy equipment, which have been widely used in electric power, aerospace, ship, heavy machinery and other fields. The quality of forgings has a direct impact on the overall level and operational reliability of the equipment. Defects such as pores and inclusions are detected. Ultrasonic detection has the advantages of strong penetration, high accuracy, high sensitivity, low detection cost and harmless to human and environment. It is suitable for defect detection of large forgings. At present, the ultrasonic inspection of large forgings in China is mostly manual scanning, manual interpretation, easy to be missed and misjudged, low detection efficiency and poor reliability, so it is necessary to develop an automatic ultrasonic detection system for large forgings, among which, Detection methods and signal processing are the key technologies involved in the system. However, the technologies used at present all have some limitations. In this paper, theoretical and experimental research on these technologies is carried out. The main research contents are as follows: 1. A multi-channel automatic ultrasonic detection method for large cylindrical forgings and large medium-thick steel plates is presented. For large medium and thick steel plates, the main probe group (both as the horizontal side probe group) is placed in the transverse middle part of the steel plate, and the longitudinal side probe group is placed in the two longitudinal sides of the plate. When the horizontal edge is detected, the plate does not move, the main probe swinging from side to side, and the other parts are detected, The plate moves in a uniform speed straight line along the calendering direction, the main probe swinging from side to side, and the longitudinal side probe does not move, forming the scanning track with rectangular edge and sinusoidal or cosine in the plate. For large cylindrical forgings, the straight probe group and the oblique probe group are placed longitudinally on the two sides of the upper cylinder wall in the diameter direction, respectively. In the detection, the cylindrical forgings rotate around the axis of the forgings, and the two groups of probes move along the axis at the same time. The scanning trajectory that forms the helix in space. The ultrasonic probe is grouped in different positions, and the inspection workpiece is scanned automatically according to the specified path, which improves the efficiency and reliability of the detection. 2. In this paper, the theory and algorithm of ultrasonic echo signal denoising are studied, and the denoising algorithm of ultrasonic reflection echo signal based on wavelet transform and independent component analysis (WICAW).) is proposed. The wavelet transform is used to decompose the original signal, and the coefficients of decomposition are analyzed by independent component analysis, and the separated independent component is evaluated by threshold to filter the noise, and then the ultrasonic signal after noise reduction is obtained by wavelet reconstruction. Simulation and experimental results show that the proposed algorithm not only does not lose useful information but also improves signal-to-noise ratio (SNR), and its performance is better than wavelet soft threshold denoising algorithm. Based on wavelet coefficient clustering and SVM, the feature extraction and recognition algorithm of defect ultrasonic signal is proposed. The wavelet transform is used to decompose the noise reduction ultrasonic echo signal, and then the wavelet coefficients are clustered by the method of probability and statistics, and the wavelet coefficient energy of each cluster is calculated and used as the input eigenvector of the SVM classifier. The defect recognition is realized. The experimental results show that the algorithm reduces the computation of the classifier and improves the accuracy of small sample defect recognition. An automatic ultrasonic detection system for large forgings based on Ethernet is designed. The experimental platform is built and the experimental research is carried out to verify the effectiveness of the detection method and signal processing algorithm proposed in this paper.
【學(xué)位授予單位】：天津工業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TG316.193;TB559
本文編號：2354066
[Abstract]:Large forgings are the key parts of heavy equipment, which have been widely used in electric power, aerospace, ship, heavy machinery and other fields. The quality of forgings has a direct impact on the overall level and operational reliability of the equipment. Defects such as pores and inclusions are detected. Ultrasonic detection has the advantages of strong penetration, high accuracy, high sensitivity, low detection cost and harmless to human and environment. It is suitable for defect detection of large forgings. At present, the ultrasonic inspection of large forgings in China is mostly manual scanning, manual interpretation, easy to be missed and misjudged, low detection efficiency and poor reliability, so it is necessary to develop an automatic ultrasonic detection system for large forgings, among which, Detection methods and signal processing are the key technologies involved in the system. However, the technologies used at present all have some limitations. In this paper, theoretical and experimental research on these technologies is carried out. The main research contents are as follows: 1. A multi-channel automatic ultrasonic detection method for large cylindrical forgings and large medium-thick steel plates is presented. For large medium and thick steel plates, the main probe group (both as the horizontal side probe group) is placed in the transverse middle part of the steel plate, and the longitudinal side probe group is placed in the two longitudinal sides of the plate. When the horizontal edge is detected, the plate does not move, the main probe swinging from side to side, and the other parts are detected, The plate moves in a uniform speed straight line along the calendering direction, the main probe swinging from side to side, and the longitudinal side probe does not move, forming the scanning track with rectangular edge and sinusoidal or cosine in the plate. For large cylindrical forgings, the straight probe group and the oblique probe group are placed longitudinally on the two sides of the upper cylinder wall in the diameter direction, respectively. In the detection, the cylindrical forgings rotate around the axis of the forgings, and the two groups of probes move along the axis at the same time. The scanning trajectory that forms the helix in space. The ultrasonic probe is grouped in different positions, and the inspection workpiece is scanned automatically according to the specified path, which improves the efficiency and reliability of the detection. 2. In this paper, the theory and algorithm of ultrasonic echo signal denoising are studied, and the denoising algorithm of ultrasonic reflection echo signal based on wavelet transform and independent component analysis (WICAW).) is proposed. The wavelet transform is used to decompose the original signal, and the coefficients of decomposition are analyzed by independent component analysis, and the separated independent component is evaluated by threshold to filter the noise, and then the ultrasonic signal after noise reduction is obtained by wavelet reconstruction. Simulation and experimental results show that the proposed algorithm not only does not lose useful information but also improves signal-to-noise ratio (SNR), and its performance is better than wavelet soft threshold denoising algorithm. Based on wavelet coefficient clustering and SVM, the feature extraction and recognition algorithm of defect ultrasonic signal is proposed. The wavelet transform is used to decompose the noise reduction ultrasonic echo signal, and then the wavelet coefficients are clustered by the method of probability and statistics, and the wavelet coefficient energy of each cluster is calculated and used as the input eigenvector of the SVM classifier. The defect recognition is realized. The experimental results show that the algorithm reduces the computation of the classifier and improves the accuracy of small sample defect recognition. An automatic ultrasonic detection system for large forgings based on Ethernet is designed. The experimental platform is built and the experimental research is carried out to verify the effectiveness of the detection method and signal processing algorithm proposed in this paper.
【學(xué)位授予單位】：天津工業(yè)大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TG316.193;TB559
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