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作 者:陈越超[1] 周晓军[1] 杨辰龙[1] 李钊[1] 郑慧峰[2]
机构地区:[1]浙江大学流体动力与机电系统国家重点实验室,杭州310027 [2]中国计量学院计量测试工程学院,杭州310018
出 处:《农业机械学报》2015年第6期372-378,共7页Transactions of the Chinese Society for Agricultural Machinery
基 金:国家自然科学基金资助项目(51075358);浙江省自然科学基金资助项目(LY14E050013);浙江省高校重中之重学科开放基金资助项目(JL130112)
摘 要:采用超声脉冲反射法对厚截面复合材料局域孔隙缺陷进行检测,提取超声背散射信号进行分析。结果表明,在材料近表面区域可能产生共振结构噪声,孔隙会导致结构噪声频率降低、幅值减小;在远表面区域的背散射信号恢复正常状态,孔隙则会导致较小幅值回波的出现。在此基础上提出了基于背散射信号处理的局域孔隙识别方法。对近表面信号使用改进S变换生成时频系数矩阵,再计算信号主频极小值及增益来识别孔隙。对远表面信号则先进行小波变换模极大值去噪,再使用改进S变换生成时频系数矩阵,最后计算信号主频极大值及增益来识别孔隙。对厚截面复合材料平板和曲面试块的实验表明,使用该信号处理方法可以有效识别厚截面复合材料局域孔隙缺陷。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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