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作 者:肖鑫龙 杨洪涛[1,2] 陈贺 郭晓军 李莉 沈梅 XIAO Xinlong;YANG Hongtao;CHEN He;GUO Xiaojun;LI Li;SHEN Mei(School of Mechanical Engineering,Anhui University of Science and Technology;Anhui Provincial Key Laboratory of Mine Intelligent Equipment and Technology,Anhui University of Science and Technology,Huainan 232001,Anhui,China;Wuxi Xinjiuyang Machinery Manufacturing Co.,Ltd.,Wuxi 214181,Jiangsu,China)
机构地区:[1]安徽理工大学机械工程学院 [2]安徽理工大学矿山智能装备与技术安徽省重点实验室,安徽淮南232001 [3]无锡市新久扬机械制造有限公司,江苏无锡214181
出 处:《惠州学院学报》2022年第6期22-28,共7页Journal of Huizhou University
基 金:安徽省科技攻关计划项目(202004a07020046);安徽省高校学科拔尖人才学术资助项目(gxbjZD2021049)。
摘 要:针对转子轴心轨迹存在噪声、干扰等问题,提出了一种基于特征频率个数确定有效奇异值(FFT-SVD)来对轴心轨迹进行提纯的算法。在matlab软件里对转子信号构造Hankel矩阵进行奇异值分解(Singular Value Decomposition,SVD),根据快速傅里叶变换(Fast Fourier Transform,FFT)的频域图中特征频率个数确定有效奇异值,然后对矩阵进行重构实现轴心轨迹的提纯。实验结果表明:奇异值和幅值频率从大到小排列,2个奇异值对应一个频率,在转子不对中实验中,利用特征频率选取奇异值来重构信号,能有效提纯转子轴心轨迹,最后和EMD、小波阈值降噪和奇异值差分谱算法相比较,研究的算法对转子轴心轨迹提纯更干净有效,并成功检测出转子不对中故障。Aiming at the noise and interference of the rotor axis trajectory,an algorithm is proposed to purify the axis trajectory based on the number of eigenfrequencies to determine the effective singular value(FFT-SVD). In Matlab software,Singular Value Decomposition(SVD)is used to rotor signal construction Hankel matrices,according to the number of eigenfrequencies in the frequency domain graph of FFT determines the valid singular values,and then reconstructs the matrix to purify the axial trajectory. Experimental results show that from large to small arrangement,two singular value reconstruction signals correspond to a frequency,and the singular values are selected by using the eigenfrequency to reconstruct the signal and synthesize the axial trajectory,and finally compared with the EMD,wavelet threshold noise reduction and singular value difference spectroscopy algorithm,this new algorithm is cleaner and more effectively for optimization of the rotor pivot trajectory,and successfully detected rotor misalignment fault.
分 类 号:TG386[金属学及工艺—金属压力加工]
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