Wavelet analysis and flow pattern identification in pulsating heat pipes based on temperature signals
The temperature signals in pulsating heat pipe(PHP)exhibit more complex transient fluctuation characteristics,which can be better analyzed by using continuous wavelet transform(CWT)method.Based on the visualization experiment(glass PHP),the wavelet analysis method was used to investigate the PHP temperature oscillation signal and flow pattern identification.The results revealed that the dominant frequency of the temperature signals is affected by the sampling frequency,wall material and heat flux.A sampling frequency of 1 Hz may lead to temperature signal distortion at high heat flux(q=2.65-3.18 W/cm2),and it is recommended to use a sampling frequency of 10 Hz or higher.The thermal inertia of the glass material introduces signal distortion in wall temperature measurements,particularly at high heat flux.With increasing heat flux(q=0.35-3.18 W/cm2),the fluctuation amplitude of the fluid temperature decreases,the frequency increases,and the dominant frequency of the temperature signal increases(0.02-3.88 Hz).Correspondingly,the internal flow of the PHP has gradually transformed from a slug flow to the annular flow,and the large one-direction circulation flow appears.The dominant frequency derived from the fluid temperature signal inside the tube can be generalized to copper tubes or other metal PHP,which helps to identify the internal flow pattern and the change in the flow regime,and to better understand their heat transfer characteristics.
pulsating heat pipewavelet analysissignal dominant frequencyflowtwo-phase flowheat transfer
万方数据
维普
