基于EMD的离心泵空化初生的研究

空化对离心泵的性能有重要影响,而在实际当中,只有在空化处于很严重的情形下才能判断离心泵空化所处的状态。为了能够提前对离心泵空化进行判断,就有必要对离心泵空化初生进行研究。首先采用数值模拟的方法,从理论上找出离心泵发生空化初生点,而后对该离心泵进行空化噪声测试实验,采集空化噪声信号,采用经验模态分解算法(EMD)对空化噪声信号进行分解,找出离心泵空化初生时的信号特征。研究表明,利用EMD算法可以很好地检测到离心泵空化形态的转变,同时实验得到的空化初生点同模拟得到的空化初生点是相一致的。

Cavitation inception in centrifugal pumps based on empirical mode decomposition

Cavitation has an important influence on the performance of centrifugal pumps, but in practice it cannot be detected by monitoring the operation state of a centrifugal pump until it has developed into a very serious case. To develop a practical technique for detecting such cavitation in advance, we should examine the behavior of cavitation inception in centrifugal pumps. This study first used a numerical simulation method to predict the cavitation inception point for a centrifugal pump, and then conducted experimental tests on cavitation noises at this inception point and collected the cavitation noise signals. Finally, empirical mode decomposition algorithm (EMD) was used to decompose the signals and find out their characteristics that describe the cavitation inception points. Results show that EMD is an effective algorithm for detection of the changes in cavitation morphology of a centrifugal pump and the cavitation inception points predicted by our numerical simulations agree well with those measured in the experiment.