电子与信息学报
電子與信息學報
전자여신식학보
JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY
2013年
3期
152-157
,共6页
超声检测%时频估计%Gabor变换%高斯模型%克拉美-罗界
超聲檢測%時頻估計%Gabor變換%高斯模型%剋拉美-囉界
초성검측%시빈고계%Gabor변환%고사모형%극랍미-라계
Ultrasonic testing%Time-frequency estimation%Gabor transform%Gaussian model%Cramer-Rao Low Bound (CRLB)
在无损检测中,超声回波往往是一个重叠较严重,含有噪声的多回波信号.根据Gabor变换时频分析的特点,该文提出一种基于Gabor变换的超声回波信号时频估计方法.该文建立回波信号与Gabor变换分析窗函数相似度(即距离)模型,通过模型相似度最小化问题转化为求解回波信号Gabor变换系数模的最大值来估计回波信号的传播时间(TOF)和中心频率(CF),最后推导它们的克拉美-罗界(CRLB)以评价算法的性能.Monte Carlo仿真和实验结果表明该文提出的算法,无论对低信噪比的单回波信号或重叠的多回波信号都能达到较高的精度,而且估计的均方误差在高信噪比时,达到CRLB,即使在低信噪比,也接近CRLB.
在無損檢測中,超聲迴波往往是一箇重疊較嚴重,含有譟聲的多迴波信號.根據Gabor變換時頻分析的特點,該文提齣一種基于Gabor變換的超聲迴波信號時頻估計方法.該文建立迴波信號與Gabor變換分析窗函數相似度(即距離)模型,通過模型相似度最小化問題轉化為求解迴波信號Gabor變換繫數模的最大值來估計迴波信號的傳播時間(TOF)和中心頻率(CF),最後推導它們的剋拉美-囉界(CRLB)以評價算法的性能.Monte Carlo倣真和實驗結果錶明該文提齣的算法,無論對低信譟比的單迴波信號或重疊的多迴波信號都能達到較高的精度,而且估計的均方誤差在高信譟比時,達到CRLB,即使在低信譟比,也接近CRLB.
재무손검측중,초성회파왕왕시일개중첩교엄중,함유조성적다회파신호.근거Gabor변환시빈분석적특점,해문제출일충기우Gabor변환적초성회파신호시빈고계방법.해문건립회파신호여Gabor변환분석창함수상사도(즉거리)모형,통과모형상사도최소화문제전화위구해회파신호Gabor변환계수모적최대치래고계회파신호적전파시간(TOF)화중심빈솔(CF),최후추도타문적극랍미-라계(CRLB)이평개산법적성능.Monte Carlo방진화실험결과표명해문제출적산법,무론대저신조비적단회파신호혹중첩적다회파신호도능체도교고적정도,이차고계적균방오차재고신조비시,체도CRLB,즉사재저신조비,야접근CRLB.
In non-destructive testing, ultrasonic echo is often an overlapping multi-echoes signal with noise. A time-frequency estimation algorithm for ultrasonic echo signal baesd on Gabor transform is presented according to the characteristics of time-frequency analysis in Gabor transform. The similarity (i.e. distance) for echo signal and the Gabor transform window function is modeled. Time Of Flight (TOF) and Center Frequency (CF) of echo signal are estimated by translating model for solving the minimum into solving the maximum of Gabor transform coefficient modulus. Finally, the CRLB is derived to evaluate the performance of the algorithm. The Monte Carlo simulation and experimental results show that the proposed method is efficient and successful. The estimation of single echo or overlapping echoes obtains high accuracy even in low signal to noise ratio. The Mean Square Error (MSE) of estimation achieves CRLB at high SNR, and is close to CRLB, even in low signal to noise ratio.