基于时频分析的离心泵空化状态表征研究

空化检测对于保障离心泵运行的安全性和可靠性具有重要意义,已有研究侧重于信号采集和特征提取,对于空化诱发的振动噪声形成机理研究不够深入.为了实现离心泵空化状态的准确表征和有效识别,本文建立了基于信号调制理论的流体机械振动噪声信号模型,将流体激振信号和调制信号视为空化表征的有效信息成分,在此基础上提出了一种基于频带能量和峭...

Research on Cavitation Characterization of Centrifugal Pumps Based on Time-frequency Analysis

Cavitation detection is important in ensuring the safety and reliability of centrifugal pumps,the existing researches focus on signal acquisition and feature extraction.However,the signal formation mechanism of vibration and noise induced by cavitation hasn’t been investigated fully.In order to realize cavitation state characterization and identification effectively,this study establishes the vibration and noise signal model of fluid machinery based on amplitude-modulated(AM) signal theory.The carrier wave signal induced by hydraulic excitation force and modulation signal are regarded as the active signal components.Thus,this study proposes a dominant frequency bands time-frequency analysis method(DFTF) based on the calculation of energy and kurtosis of frequency bands.Further,cavitation state intelligent identification is realized by combining DFTF with deep convolutional neural network.Finally,the rationality of the proposed signal model and the validity of DFTF are demonstrated by simulation signal and real data.