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厚截面復合材料局域孔隙超聲檢測方法
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國家自然科學基金資助項目(51075358)、浙江省自然科學基金資助項目(LY14E050013)和浙江省高校重中之重學科開放基金資助項目(JL130112)


Ultrasonic Testing Method for Localized Void Defect Identification in Thick Section Composites
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    摘要:

    采用超聲脈沖反射法對厚截面復合材料局域孔隙缺陷進行檢測,提取超聲背散射信號進行分析。結(jié)果表明,在材料近表面區(qū)域可能產(chǎn)生共振結(jié)構(gòu)噪聲,孔隙會導致結(jié)構(gòu)噪聲頻率降低、幅值減?。辉谶h表面區(qū)域的背散射信號恢復正常狀態(tài),孔隙則會導致較小幅值回波的出現(xiàn)。在此基礎(chǔ)上提出了基于背散射信號處理的局域孔隙識別方法。對近表面信號使用改進S變換生成時頻系數(shù)矩陣,再計算信號主頻極小值及增益來識別孔隙。對遠表面信號則先進行小波變換模極大值去噪,再使用改進S變換生成時頻系數(shù)矩陣,最后計算信號主頻極大值及增益來識別孔隙。對厚截面復合材料平板和曲面試塊的實驗表明,使用該信號處理方法可以有效識別厚截面復合材料局域孔隙缺陷。

    Abstract:

    The ultrasonic pulse echo method was adopted to test the localized void defects in thick section composites and the extracted ultrasonic backscattered signal was analyzed. The results showed that the resonance structure noise may appear in the near surface region of the material. The voids can result in frequency reduction and amplitude decrease of the structure noise. The backscattered signal was back to normal state in the far surface region and the voids can lead to the appearance of low amplitude echo. The localized void identification method based on the backscattered signal processing was proposed. The near surface signal was processed by a modified S-transform to generate time-frequency coefficient matrix. The minimum and gain of the signal main frequency can be calculated to identify the voids. For the far surface signal, the wavelet transform modulus maximum denoising method was applied firstly, and then the denoised signal was processed by the modified S-transform to generate time-frequency coefficient matrix. Finally, the maximum and gain of the signal main frequency could be calculated to identify the voids. The experiments were implemented for the thick section composite plate specimen and curved surface specimen, respectively. The results showed that the localized void defects in thick section composites could be effectively identified by this signal process method.

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陳越超,周曉軍,楊辰龍,李釗,鄭慧峰.厚截面復合材料局域孔隙超聲檢測方法[J].農(nóng)業(yè)機械學報,2015,46(6):372-378. Chen Yuechao, Zhou Xiaojun, Yang Chenlong, Li Zhao, Zheng Huifeng. Ultrasonic Testing Method for Localized Void Defect Identification in Thick Section Composites[J]. Transactions of the Chinese Society for Agricultural Machinery,2015,46(6):372-378.

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  • 收稿日期:2014-06-26
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  • 在線發(fā)布日期: 2015-06-10
  • 出版日期: 2015-06-10