| 1. | A simulation study of stress of aircraft structures subjected to acoustic excitation
航空结构声激励应力的仿真研究 |
| 2. | Measurement of the electrical properties of electronic tubes ; measurement of noises due to mechanical or acoustic excitations
电子管电气性能测量.第19部分:由于机械或声激励引起 |
| 3. | Measurements of the electrical properties of electronic tubes . part 18 : methods of measurement of noises due to mechanical or acoustic excitations
电子管电性能的测量.第18部分:机械或声激发的噪声的测量方法 |
| 4. | In these experiments acoustic excitations were employed to play the role of the feedback of the upstream - propagating disturbances of pressure in the impinging shear flow
实验中，以声激励代替在撞击剪切流中向上游转播的压力扰动的反馈作用。 |
| 5. | By the method of double - frequency acoustic excitations , experiments were conducted on the influences of phase differences between the fundamental and subharmonic waves upon the " subharmonic resonance " - the nonlinear interaction between the waves
用双频声激励方法，实验研究了剪切流中基波及其亚谐波的相位差对“亚谐共振”非线性过程的影响。 |
| 6. | Under different positions of a tripping wire or speeds of the side jet , the controlled experiments were made , including the receptivity of the shear layer near jet exit to acoustic excitations , the spatial development of fluctuating velocity and the profiles of mean velocity
在不同绊线位置或不同旁射流流速条件下，研究了射流出口临近剪切层对声激励的感受性，脉动流速向下游的空间演化及平均流速剖面。 |
| 7. | Test technique of acoustic excitation presented in this paper can discriminate if the adhesive structure is intensional enough to endure certainty draw strength , through a series of process , for example bringing draw strength to bear on adhesive structure . testing signal through microphone array , choosing signal ' s character , recognizing automatically through manual nerve network , and so on
本文介绍的粘接构件声激励检测方法，通过对粘结结构施加微力、阵列传声器检测信号、信号的特征提取、人工神经网络的分类识别等一系列过程，完成了粘接结构承受拉脱力合格与否的无损预报。 |
| 8. | Acoustic excitation signal is processed with wavelet analysis in this paper , and chooses characters related to adhesive capacity from acoustic signal in the time domain and frequency domain . these characters is the input of nerve network which is used to non - mangle test about mechanics capacity of adhesive structure , and establish the base for classify distinguishing effectively and forecast
本文采用小波变换的方法对采集到的声激励信号进行分析，在时-频域提取出与粘接性能有关的特征量，用于粘接结构力学性能无损检测的神经网络输入，从而为有效进行分类判别和预报奠定了基础。 |
