摘要
一维随机共振(One-Dimensional Stochastic Resonance,1DSR)被广泛用于轴承故障诊断中。针对传统1DSR对微弱信号的检测效果不够理想,输出信号噪声大,不能准确获得轴承故障特征频率(Fault Characteristic Frequency,FCF)等问题,提出一种新的二维互补随机共振(Two-Dimensional Complementary Stochastic Resonance,2DCSR)方法并应用于轴承故障诊断。将采集到的轴承故障信号根据共振带位置进行带通滤波并解调,随后将解调信号对半分成两个子信号并输入2DCSR的两个输入端,利用输出信号的加权功率谱峭度(WPSK)指标对2DCSR系统参数进行自适应调节优化,得到最优的滤波输出信号及频谱,以识别轴承FCF并诊断轴承故障类型。数值仿真及实验结果表明,提出的方法可以有效地增强轴承FCF并提高轴承故障诊断效果。
One-dimensional stochastic resonance(1DSR)methods have been widely used in bearing fault diagnosis.However,some deficiencies still exist in the traditional 1DSR methods such as limited weak signal detection capacity,obvious output noise,and inaccurate bearing fault characteristic frequency(FCF)for fault recognition,etc.To address these issues,this study proposed a new two-dimensional complementary stochastic resonance(2DCSR)method to enhance bearing fault diagnosis.First,the acquired bearing fault signal was bandpass-filtered according to the location of resonance band and then demodulated.Then the demodulated signal was split into two sub-signals and the sub-signals were sent to the two input channels of the 2DCSR.The weighted power spectral kurtosis(WPSK)of the output signal was used as the criterion to guide parameters tuning in the 2DCSR system adaptively.Finally the optimal output signal and its spectrum were obtained for bearing fault recognition.Numerical and experimental results show that the bearing FCF can be enhanced by the proposed 2DCSR method,thereby improving the performance of bearing fault diagnosis.
作者
陆思良
苏云升
赵吉文
何清波
刘方
刘永斌
LU Siliang;SU Yunsheng;ZHAO Jiwen;HE Qingbo;LIU Fang;LIU Yongbin(College of Electrical Engineering and Automation,Anhui University,Hefei 230601,China;Department of Precision Machinery and Precision Instrumentation,University of Science and Technology of China,Hefei 230026,China)
出处
《振动与冲击》
EI
CSCD
北大核心
2018年第4期7-12,27,共7页
Journal of Vibration and Shock
基金
国家自然科学基金(51605002
51577001)
关键词
轴承故障诊断
二维互补随机共振
加权功率谱峭度
微弱信号检测
bearing fault diagnosis
two-dimensional complementary stochastic resonance
weighted power spectral kurtosis
weak signal detection
