矿用对旋风机旋转失速信号特征识别与提取  

Feature Recognition and Extraction of Rotating Stall Signal of Mine Contra-rotating Fan

作　　者：陈庆光[1] 徐延辉 张祯江 郭武 CHEN Qingguang;XU Yanhui;ZHANG Zhenjiang;GUO Wu(College of Mechanical and Electronic Engineering,Shandong University of Science and Technology,Qingdao 266590,Shandong,China)

机构地区：[1]山东科技大学机械电子工程学院,山东青岛266590

出　　处：《机械科学与技术》2024年第9期1505-1513,共9页Mechanical Science and Technology for Aerospace Engineering

基　　金：山东省自然科学基金项目(ZR2021ME242)。

摘　　要：针对旋风机旋转失速信号特征的识别与提取,提出了一种参数优化的变分模态分解(VMD)方法。首先,为了消除人为选择VMD参数的影响,提出一种以平均包络熵为目标函数的蛙跳优化算法,对VMD算法的模态个数K和惩罚因子α进行优化选取,实现了参数K和α的合理自动选取;然后,通过模拟信号验证了参数优化后的VMD方法的有效性;最后,利用参数优化的VMD方法对风机失速信号进行处理和分析,研究风机失速的频谱特性,并与经验模态分解(EMD)结果进行对比分析。研究结果表明:与EMD方法相比,参数优化的VMD方法在处理模态混叠方面更具有优势,其处理效果明显优于EMD,分解得到的IMF分量个数也少于EMD,易区分特征频率;另外,以优化获取的参数组合处理风机的失速信号时,能够很好地揭示失速特征频率在失速发展过程中的变化规律,对应于频率分量的波动,从大尺度的频率波动转变为小尺度的频率波动。Aiming at the identification and extraction of contra-rotating fan rotating stall signal features,a variational mode decomposition(VMD)method for parameter optimization is proposed.First,in order to eliminate the influence of artificial selection of VMD parameters,a shuffled frog leaping optimization algorithm with the average envelope entropy as the objective function is proposed,and the number of modes K and penalty factorαof the VMD algorithm are optimized to realize the reasonable automatic selection of parameters K andα.Then,the effectiveness of the parameter-optimized VMD method is verified by simulation signals.Finally,applying the VMD method of parameter optimization to process and analyze the fan stall signal,the spectral characteristics of the fan stall is studied and compared with results of the empirical mode decomposition(EMD).The research results show that,compared with the EMD method,the parameter-optimized VMD method has more advantages in dealing with modal aliasing,and its processing effect is significantly better than that of the EMD method.The number of IMF components obtained by decomposition is also less than that of EMD,and it is easy to distinguish eigenfrequencies.In addition,when processing the stall signal of the fan with the optimized combination of parameters,it can well reveal the change law of the stall characteristic frequency in the process of stall development,corresponding to the fluctuation of the frequency component,from a large-scale frequency fluctuation to a small-scale frequency fluctuation.

关 键 词：对旋风机 旋转失速 变分模态分解 特征识别与提取 

分 类 号：TD441[矿业工程—矿山机电]