中文摘要：

用小波变换获取超声波能量的时间-尺度分布,研究衰减系数随尺度的分布规律,定义加权的超声多尺度衰减系数,结合粒子群算法设计的最优尺度组合及其归一化权重分配策略,建立晶粒尺寸的超声多尺度衰减评价模型.选用304不锈钢进行实验,其衰减系数-尺度分布图表明超声波在小尺度下衰减迅速,体现了高散射材料中衰减的频率特征;而随着试样晶粒尺寸增大,整个尺度范围内的衰减都明显加剧.实验结果显示,声速法、传统衰减法与本方法的最大系统误差分别是＋12.57%,＋5.85%和-1.33%.对金相法测得平均晶粒尺寸为103.5 mm的验证试样用3种方法进行评价,结果分别为（110.4±7.8）,（98.2±6.6）和（101.7±3.9）mm.本方法不仅可降低系统误差,且随机误差也被小波变换的恒Q滤波特性有效抑制.

英文摘要：

To solve such problems as sensitivity to noise and low accuracy of grain size evaluation using traditional ultrasonic time-domain attenuation method, an ultrasonic nondestructive evaluation model based on multiscale attenuation coefficient was proposed. The distribution of time- scale of ultrasonic energy was obtained by means of wavelet transformation, then to calculate the distribution of attenuation coefficient with scale, and to make a comprehensive analysis of attenuation characteristics of various scales. After the weighted multi-scale ultrasonic attenuation coefficient was defined, a multi-scale ultrasonic attenuation evaluation model was established on the basis of combination of optimal dimension and normalized weight distribution strategy designed by particle swarm optimization. 304 stainless steel was used in the test. The distribution of attenuation coefficient with scaleshows that ultrasonic wave of small scales attenuates fast, presenting the frequency characteristics of ultrasonic attenuation among high scattering materials. Following increase of the sample grain size, ultrasonic attenuation of all scales was intensified significantly. Test results show that the sound velocity method, the traditional evaluation method and the proposed method have maximum systematic errors of ＋12.57%, ＋5.85% and-1.33%, respectively.With these 3 methods, evaluation results of the sample with a mean grain size of 103.5 mm measured by metallographic method are（110.4±7.8）,（98.2±6.6） and（101.7±3.9） mm, respectively, showing that the presented method can not only reduce the systemic error, but also can effectively control the random error by constant Q filtering properties of wavelet transformation. This model can be extended to grain size evaluation of other metals.