Objectives: To demonstrate in vitro that changes in ultrasound cavitation threshold might be used for non-invasively distinguishing high viscosity mucinous fluid from low viscosity serous fluid in cystic masses, based...Objectives: To demonstrate in vitro that changes in ultrasound cavitation threshold might be used for non-invasively distinguishing high viscosity mucinous fluid from low viscosity serous fluid in cystic masses, based on the facts that cavitation threshold increases with increasing viscosity and that cavitation microbubbles are observable with diagnostic ultrasound. Methods: An in vitro model of a cyst was designed using dilutions of ultrasonic gel, and the cavitation threshold of this model was determined using focused and unfocused ultrasound for bubble initiation and clinical ultrasound b-scan for detection. Results: Viscosities of dilutions between 0% and 30% gel were had viscosities measuring between 1.05 ± 0.08 cP and 6600 ± 875 cP. Inertial cavitation in the latter was determined to require an order of magnitude greater intensity, at 1 MHz and 100% duty cycle, than the former (>2.2 W/cm2 vs. <0.19 W/cm2) using unfocused ultrasound. A four-fold increase in the peak negative pressure was required to initiate significant bubble activity using 1.1 MHz and 50% duty cycle focused ultrasound in the 6600 cP fluid compared with the 1 cP fluid. Based on these results, it was estimated that a threshold could be defined that would result in no bubbles in 99.9% of mucinous cysts and just 22% of serous cysts. The remaining 78% of patients presenting with serous cysts would be positively identified by detection of bubbles, and would be spared an unnecessary biopsy. Conclusions: The cavitation threshold may be used non-invasively to distinguish between high viscosity and low viscosity fluids in cysts and reduce biopsies on serous cysts.展开更多
The radiation pressure signals generated by the bubble oscillation are often utilized to recognize the characteristics of the target objects in many fields.However,these signals are easily contaminated by complex back...The radiation pressure signals generated by the bubble oscillation are often utilized to recognize the characteristics of the target objects in many fields.However,these signals are easily contaminated by complex background noises.In order to accurately extract the effective components of the radiation pressure signal generated by the bubble oscillation,this paper proposes a de-noising procedure for the radiation pressure signal,based on the ensemble empirical mode decomposition(EEMD),the autocorrelation function and the modified wavelet soft-threshold de-noising method.In order to verify the effectiveness of the procedure,the typical radiation pressure signal generated based on the Keller-Miksis model under the acoustic excitation is employed for the subsequent de-noising analysis.The results of the qualitative analysis show that the amplitude and the period of the bubble oscillation can be clearly observed in the time-domain diagram of the de-noised signal based on the EEMD.In the quantitative analysis,the de-noised signal based on the EEMD has better performance with higher signal-to-noise ratio(SNR),smaller root-mean-square error,and larger correlation coefficient than that based on the wavelet transform(WT)and the empirical mode decomposition(EMD).Furthermore,with the increase of the complexity of the radiation pressure signal(e.g.,the increase of the dimensionless pressure amplitude of the acoustic wave and the decrease of the SNR of the input signal),the above three evaluation indexes of the de-noised signal based on the EEMD are all better than those based on the other two methods.When the signal is more complex,the de-noising capabilities of the WT,the EMD are greatly reduced,but the EEMD can still maintain the good de-noising capability,which shows the superiority of the signal de-noising procedure proposed in the present paper.展开更多
选择3个流量工况(80,92,100 m3/h)对离心泵进行空化试验,利用TST6200动态采集系统、Noise A 2.10噪声测试软件和灵敏度为-210 d B的水听器构成的噪声测试系统采集空化噪声信号,并利用照相机同时拍摄3个流量工况下水流中空泡的变化过程....选择3个流量工况(80,92,100 m3/h)对离心泵进行空化试验,利用TST6200动态采集系统、Noise A 2.10噪声测试软件和灵敏度为-210 d B的水听器构成的噪声测试系统采集空化噪声信号,并利用照相机同时拍摄3个流量工况下水流中空泡的变化过程.采用功率谱法对空化噪声信号进行频域分析和处理,将整个频域分为高中低3个频段,统计各频段信号的平均功率,得到信号功率随汽蚀余量之间的关系曲线.研究结果表明:离心泵流动空化信号的特征主要集中在低频段,而在中高频段没有明显特征;利用功率谱法对空化噪声信号进行分析和处理,得到的结果能够很好地反映离心泵流动空化的发展过程;选择了2个功率带分别作为判断离心泵空化初生和临界空化时的阈值,利用该阈值可以对离心泵空化进行实时监测.展开更多
文摘利用激光测距仪测得铸造用超声辐射杆端面全局振幅及频率,基于FFT细化分析对所测振幅分析后得到辐射杆端面振幅整体分布特性,在铝熔体中,将钛板竖直置于超声辐射杆正下方,启动超声振动系统运行20 h,通过分析钛板空蚀区域探究超声在铝熔体中的空化区域,得出辐射杆的空化区域分布,空化区域为一椭球形且分界面明显,空化域最远可达变幅杆正下方68 mm,结合铝熔体中超声的空化阈值,推算出20 k Hz铸造用功率超声在铝熔体中传播的衰减系数。
文摘Objectives: To demonstrate in vitro that changes in ultrasound cavitation threshold might be used for non-invasively distinguishing high viscosity mucinous fluid from low viscosity serous fluid in cystic masses, based on the facts that cavitation threshold increases with increasing viscosity and that cavitation microbubbles are observable with diagnostic ultrasound. Methods: An in vitro model of a cyst was designed using dilutions of ultrasonic gel, and the cavitation threshold of this model was determined using focused and unfocused ultrasound for bubble initiation and clinical ultrasound b-scan for detection. Results: Viscosities of dilutions between 0% and 30% gel were had viscosities measuring between 1.05 ± 0.08 cP and 6600 ± 875 cP. Inertial cavitation in the latter was determined to require an order of magnitude greater intensity, at 1 MHz and 100% duty cycle, than the former (>2.2 W/cm2 vs. <0.19 W/cm2) using unfocused ultrasound. A four-fold increase in the peak negative pressure was required to initiate significant bubble activity using 1.1 MHz and 50% duty cycle focused ultrasound in the 6600 cP fluid compared with the 1 cP fluid. Based on these results, it was estimated that a threshold could be defined that would result in no bubbles in 99.9% of mucinous cysts and just 22% of serous cysts. The remaining 78% of patients presenting with serous cysts would be positively identified by detection of bubbles, and would be spared an unnecessary biopsy. Conclusions: The cavitation threshold may be used non-invasively to distinguish between high viscosity and low viscosity fluids in cysts and reduce biopsies on serous cysts.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.51976056,U1965106).
文摘The radiation pressure signals generated by the bubble oscillation are often utilized to recognize the characteristics of the target objects in many fields.However,these signals are easily contaminated by complex background noises.In order to accurately extract the effective components of the radiation pressure signal generated by the bubble oscillation,this paper proposes a de-noising procedure for the radiation pressure signal,based on the ensemble empirical mode decomposition(EEMD),the autocorrelation function and the modified wavelet soft-threshold de-noising method.In order to verify the effectiveness of the procedure,the typical radiation pressure signal generated based on the Keller-Miksis model under the acoustic excitation is employed for the subsequent de-noising analysis.The results of the qualitative analysis show that the amplitude and the period of the bubble oscillation can be clearly observed in the time-domain diagram of the de-noised signal based on the EEMD.In the quantitative analysis,the de-noised signal based on the EEMD has better performance with higher signal-to-noise ratio(SNR),smaller root-mean-square error,and larger correlation coefficient than that based on the wavelet transform(WT)and the empirical mode decomposition(EMD).Furthermore,with the increase of the complexity of the radiation pressure signal(e.g.,the increase of the dimensionless pressure amplitude of the acoustic wave and the decrease of the SNR of the input signal),the above three evaluation indexes of the de-noised signal based on the EEMD are all better than those based on the other two methods.When the signal is more complex,the de-noising capabilities of the WT,the EMD are greatly reduced,but the EEMD can still maintain the good de-noising capability,which shows the superiority of the signal de-noising procedure proposed in the present paper.
文摘选择3个流量工况(80,92,100 m3/h)对离心泵进行空化试验,利用TST6200动态采集系统、Noise A 2.10噪声测试软件和灵敏度为-210 d B的水听器构成的噪声测试系统采集空化噪声信号,并利用照相机同时拍摄3个流量工况下水流中空泡的变化过程.采用功率谱法对空化噪声信号进行频域分析和处理,将整个频域分为高中低3个频段,统计各频段信号的平均功率,得到信号功率随汽蚀余量之间的关系曲线.研究结果表明:离心泵流动空化信号的特征主要集中在低频段,而在中高频段没有明显特征;利用功率谱法对空化噪声信号进行分析和处理,得到的结果能够很好地反映离心泵流动空化的发展过程;选择了2个功率带分别作为判断离心泵空化初生和临界空化时的阈值,利用该阈值可以对离心泵空化进行实时监测.
基金National Basic Research Program(2011CB707900)National Natural Science Foundation of China(11074123,10974095,10904068,10204014)+2 种基金Fundamental Research Funds for the Central Universities(111602040,1095020409)Natural Science Foundation of Jiangsu Province of China(BK2011812)Priority Academic Program Development of Jiangsu Higher Education Institutions
