【摘要】 应用单因素及主成分分析方法对超声回波信号的统计特征值进行选择,并以两类方法得到的最佳特征子集对实验样本进行识别。结果表明,利用特征值评价进行回波信号的识别是切实可行的。单因素分析中各个特征对回波信号的识别能力有所不同,标准偏差、最大幅值及方均根的识别率依次是67%,33%和67%。相比之下,主成分分析法得到的识别效果最好,可达97%。更多还原

【Abstract】 Single factor analysis and principal component analysis were used to choose the statistical feature value of ultrasonic signals, and the optimum feature subset obtained by the two analysis methods was utilized to distinguish experimental samples. Results showed that it was possible to distinguish ultrasonic signals by feature value evaluation, and the distinguishability of principal component analysis was up to 97% and was much better than that of single factor analysis(standard deviation analysis was 67%, maximum value analysis was 33% and mean square root analysis was 67%).更多还原