CAI Teng-fei, PAN Yan, MA Fei, CUI Li-hua, QIU Lin-bin. Detection method of the self-resonating waterjet characteristic based on the flow signal in a pipeline[J]. Chinese Journal of Engineering, 2019, 41(3): 377-383. DOI: 10.13374/j.issn2095-9389.2019.03.011
Citation: CAI Teng-fei, PAN Yan, MA Fei, CUI Li-hua, QIU Lin-bin. Detection method of the self-resonating waterjet characteristic based on the flow signal in a pipeline[J]. Chinese Journal of Engineering, 2019, 41(3): 377-383. DOI: 10.13374/j.issn2095-9389.2019.03.011

Detection method of the self-resonating waterjet characteristic based on the flow signal in a pipeline

  • The self-resonating waterjet has the characteristics of high-frequency pressure oscillation and strong cavitation. Accurately grasping the jet characteristics is a prerequisite for the application research of self-resonating waterjets. The characteristics of the self-resonating waterjet are typically acquired through a test. Traditional test methods primarily include the striking test and signal detection in the nozzle chamber. However, these methods both have the disadvantage of low detection accuracy and the inability to overcome the impact of high ambient pressure. In this article, a detection method for self-resonating waterjet characteristics based on the flow signal in a pipeline was proposed. The pressure sensors were transferred from within the high pressure tank to the outside of the tank and were arranged in the front pipeline outside the tank to avoid the influence of high ambient pressure. Dual-pressure sensors were used to acquire the flow pressure pulse signal, and signal-processing technology was used to effectively suppress noise interference for enhancing the intensity of useful signals and accurately obtaining the pressure fluctuation information of the self-resonating waterjet.The test results show that the spectral characteristics acquired from the flow pressure signal in the pipeline agree with the results obtained from the signal in the chamber and are also consistent with the theoretical calculations. Thus, the pressure oscillation characteristics of the waterjet are fully characterized. Moreover, the acoustic power spectrum obtained from the flow pressure signal in the pipeline is in accordance with the result obtained from the hydrophone in the high pressure tank. Consequently, the cavitation characteristic of the waterjet is well characterized. Therefore, the detection method based on the flow signal in the pipeline is entirely feasible and advanced and provides a new means for the study of the self-resonating waterjet under high ambient pressure.
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