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The effect of backlash nonlinear on resonance frequency of electric actuator transmission system (EI CONFERENCE) 会议论文
3rd IEEE International Conference on Advanced Computer Control, ICACC 2011, January 18, 2011 - January 20, 2011, Harbin, China
Han X.; Ge M.; Bai Y.; Jia H.; Ge W.
收藏  |  浏览/下载:14/0  |  提交时间:2013/03/25
In order to study the effect of backlash nonlinear on resonance frequency of electric actuator transmission system  then  Finally  in the premise of meeting the stability  the dynamic equilibrium equation of transmission system with backlash is established  it makes dynamic simulation analysis for the transmission system based on virtual prototype technology  it establishes balanced equation of dynamics system with backlash  the effect of backlash on system natural frequency and resonance frequency  and the theoretical values and simulation values are compared. Theoretical analysis and simulation results show that the theoretical analysis is basically consistent with simulation results when it is zero backlash  and does some theory research and dynamic analysis of backlash nonlinearity and system natural frequency and resonance frequency. First  and the error of theoretical analysis and simulation results is within 10%. Therefore  according to describing function to theoretically model the backlash nonlinear  it can be concluded that considering the transmission system theoretical analysis of backlash nonlinearity is feasible  the relation between describing function and the amount of backlash and input amplitude is analyzed  and it is much closer to the actual system with instructive significance. 2011 IEEE.  
Noise reduction method based on singular value decomposition 期刊论文
Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2011, 卷号: 31, 期号: [db:dc_citation_issue], 页码: 459-463
作者:  Qian, Zhengwen;  Cheng, Li;  Li, Yinghong
收藏  |  浏览/下载:2/0  |  提交时间:2019/12/10
Prediction of concrete strength using fuzzy neural networks 会议论文
Haikou, China, June 18, 2011 - June 20, 2011
作者:  Xu, Jing;  Wang, Xiuli
收藏  |  浏览/下载:7/0  |  提交时间:2020/11/15
Algebra  Building materials  Civil engineering  Compressive strength  Construction equipment  Forecasting  Fuzzy inference  Fuzzy logic  Fuzzy systems  Learning algorithms  Least squares approximations  Mathematical models  Network architecture  Adaptive neuro-fuzzy inference system  Automatic-learning  Average relative error  Compressive strength of concrete  Concrete strength  Concrete strength prediction  Condition parameters  Expert experience  Fuzzy logic inference  Fuzzy Neural Networks (FNN)  Gradient Descent method  Hybrid-learning algorithm  Input and outputs  Input-output data  Intelligent prediction  Least squares methods  Parameter set  Power functions  Practical engineering  Prediction model  Rebound value  Relative standard error  Specific equations  Strength values  Takagi-sugeno  Test results  Training patterns  


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