Hybrid tri-stable stochastic resonance system used for fault signal detection
ZHANG Gang12 LI Hongwei1
1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2. Chongqing Key Laboratory of Signal and Information Processing, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China;
Abstract:Aiming at the problem that fault feature signals are often submerged in noise so that difficult to extract, a hybrid tri-stable stochastic resonance system, combining the Woods-Saxon monostable model with the hybrid bistable model was proposed.The system not only retains the advantages of Woods-Saxon’s easiness to detect fault signals but also takes advantage of the high noise utilization characteristic of the tri-stable model.First, the signal-to-noise gain was used as a measure to create an adaptive algorithm for finding the optimal system parameters.Then, harmonic vibration signals, amplitude modulation signals and periodic pulse attenuation signals were detected under the background of α noise.Finally, a signal detection approach using the variational mode decomposition combined with the hybrid tri-stable model was put forward and applied to the actual bearing faults detection.The simulation results show that the hybrid tri-stable stochastic resonance model and the composed model can achieve clear and reliable test results and superior performances in fault signal detection.
张刚12, 李红威1. 混合多稳态随机共振的故障信号检测[J]. 振动与冲击, 2019, 38(18): 9-17.
ZHANG Gang12 LI Hongwei1. Hybrid tri-stable stochastic resonance system used for fault signal detection. JOURNAL OF VIBRATION AND SHOCK, 2019, 38(18): 9-17.
[1] Yanxue Wang, Richard Markert, Jiawei Xiang, Weiguang Zheng, Research on variational mode decomposition and its application in detecting rub-impact fault of the rotor system, [J] In Mechanical Systems and Signal Processing. 60(2015): 243-251
[2] 张雷,宋爱国.随机共振在信号处理中应用研究的回顾与展望[J].电子学报,2009,37(04):811-818.
[3] Lu S, He Q, Kong F. Stochastic resonance with Woods–Saxon potential for rolling element bearing fault diagnosis[J]. Mechanical Systems & Signal Processing, 2014, 45(2):488-503.
[4] 季袁冬, 张路, 罗懋康. 幂函数型单势阱随机振动系统的广义随机共振[J]. 物理学报, 2014, 63(16):164302.
JI Y D, ZHANG L, LUO M K. Generalized stochastic resonance of power function type single-well system [J]. Acta Physica Sinica, 2014, 63(16): 164302.
[5] 赖志慧,冷永刚. 三稳系统的动态响应及随机共振[J]. 物理学报,2015,64(20):81-92.
Lai z h, Leng Y G, Dynamic response and stochastic resonance of a tri-stable system[J]. Acta Physica Sinica, 2015,64 (20):81-92
[6] Zhixiang Wang, Zijian Qiao, Liguang Zhou, Lei Zhang,Array-enhanced logical stochastic resonance subject to colored noise,Chinese Journal of Physics[J],2017,55(2): 252-259
[7] 冷永刚,赖志慧. 基于Kramers逃逸速率的Duffng振子广义调参随机共振研究[J]. 物理学报,2014,63(02):38-46.
Leng Y G,Lai Z H.Generalized parameter-adjusted stochastic resonance of Duffing oscillator based on Kramers rate[J] Acta Physica Sinica, 2014,63(02):38-46.
[8] Lei Ya guo, Qiao Zi jian, Xu Xue fang,Lin Jing. (2017). Weak signal detection based on underdamped multistable stochastic resonance[C]// 2017 IEEE International Instrumentation and Measurement Technology Conference. Turin: IEEE,2017.
[9] 焦尚彬,李佳,张青,谢国. α稳定噪声下时滞非对称单稳系统的随机共振[J]. 系统仿真学报,2016,28(01):139-146
JIAO S B,Li J,Zhang Q,Xie G. Stochastic Resonance in Time-delayed Asymmetric Monostable System with α Stable Noise[J] Journal of System Simulation, 2016,28(01):139-146
[10] 焦尚彬,杨蓉,张青,谢国. α稳定噪声驱动的非对称双稳随机共振现象[J]. 物理学报,2015,64(02):49-57.
JIAO S B,Yang R,Zang Q,Xie G. Stochastic resonance of asymmetric bistable system with αstable noise[J] Acta Physica Sinica, 2015,64(02):49-57.
[11] Jiao, Shang-Bin & Kou, Jie & Liu, Ding & Zhang, Qing. (2016). Stochastic resonance of asymmetric bistable system driven by binary signals under α stable noise. 2016 35th Chinese Control Conference (CCC), Chengdu, 2016, pp. 6649-6654.
[12] 谢有浩,刘晓乐,刘后广,程刚,陈曦晖. 基于改进移频变尺度随机共振的齿轮故障诊断[J]. 农业工程学报,2016,32(08):70-76.
Xie Y H, Liu X L, Liu H G, Cheng G, Chen XS H. Improved frequency-shifted and re-scaling stochastic resonance for gear fault diagnosis[J] Transactions of the Chinese Society of Agricultural Engineering .2016, 32(8): 70-76.
[13] 冷永刚, 王太勇. 二次采样用于随机共振从强噪声中提取弱信号的数值研究[J]. 物理学报, 2003, 52(10):2432-2437.
LENG Y G, WANG T Y. Numerical research of twice sampling stochastic resonance for the detection of a weak signal submerged in a heavy Noise [J]. Acta Physica Sinica, 2003, 52(10): 2432-2437.
[14] 张刚,胡韬,张天骐. 基于频率控制的自适应随机共振系统研究[J]. 振动与冲击,2016,35(02):91-96.
ZHANG G,HU T,ZHANG T Q,Adaptive stochastic resonance system based on frequency control [J]Journal of Vibration and Shock2016,35(02):91-96.
[15] 赖志慧,饶锡新,刘建胜,冷永刚. 基于Duffing振子的信号频谱重构随机共振研究[J]. 振动与冲击,2016,35(21):9-16.
[16] 张刚,宋莹,张天骐. Levy噪声驱动下指数型单稳系统的随机共振特性分析[J]. 电子与信息学报,2017,39(04):893-900.
ZHANG G,SONG Y ZHANG T Q. Characteristic Analysis of Exponential Type Monostable Stochastic Resonance under Levy Noise[J] Journal of Electronics & Information Technology2017,39(04):893-900.
[17] LU S L, HE Q B, KONG F R. Effects of underdamped step-varying second-order stochastic resonance for weak signal detection[J].Digital Signal Processing.36(2015):93-103.
[18] 韩东颖, 丁雪娟, 时培明. 基于自适应变尺度频移带通随机共振降噪的EMD多频微弱信号检测[J]. 机械工程学报, 2013, 49(8):10-18.
HAN D Y, DING X F, SHI P M. Multi-frequency weak signal detection based on EMD after de-noising by adaptive re-scaling frequency-shifted band-pass stochastic resonance [J]. Journal of Mechanical Engineering, 2013, 49(8):10-18.
[19] Zhang Haibin, He Qingbo,Lu Siliang, Kong Fanrang.Stochastic Resonance with a Joint Woods-Saxon and Gaussian Potential for Bearing Fault Diagnosis. Mathematical Problems in Engineering. (2014):17
[20] Zijian Qiao, Yaguo Lei, Jing Lin, Feng Jia,An adaptive unsaturated bistable stochastic resonance method and its application in mechanical fault diagnosis,Mechanical Systems and Signal Processing[J], 2017,84(A): 731-746
[21] Weron R. On the Chambers-Mallows-Stuck method for simulating skewed stable random variables[J] Statist. Prob. Lett. 1996, 28(2):165-171
[22] Zhi-hui Lai, Yong-gang Leng, Weak-signal detection based on the stochastic resonance of bistable Duffing oscillator and its application in incipient fault diagnosis[J], In Mechanical Systems and Signal Processing, Volume 81(2016):60-74
[23] 贺利芳,崔莹莹,张天骐,张刚,宋莹. 基于幂函数型双稳随机共振的故障信号检测方法[J]. 仪器仪表学报,2016,37(07):1457-1467.
HE L F,CUI Y Y,ZHANG T Q,ZHANG G,SONG Y. Fault signal detection method based on power function type bistable stochastic resonance [J] Chinese Journal of Scientific Instrument.2016,37(07):1457-1467.
[24] Qin, Yi & Tao, Yi & He, Ye & Tang, Baoping. (2014). Adaptive bistable stochastic resonance and its application in mechanical fault feature extraction[J]. Journal of Sound and Vibration.2014,333(26):7386-7400.
[25] Jardine, Andrew Lin, Daming,Banjevic, Dragan. A review on machinery diagnostics and prognostics implementing condition-based maintenance.[J] Mechanical Systems and Signal Processing.2006,20(7),1483-1510