Tao Jianfeng

Research on feed-forward PIDD 2 control for hydraulic continuous rotation motor electro-hydraulic servo system with long pipeline

In the applications of hydraulic continuous rotation motors used in the valve control electro-hydraulic servo system, the long distance between the electro-hydraulic servo valves and the hydraulic motors causes long pipeline effect, which results in a decreased natural frequency and delayed dynamic response of the hydraulic system. This paper presents the mathematical model and characteristic analysis of the dynamic characteristic of the system, as well as the long pipeline effect. A second order differential term is added to the traditional PID control method to decrease/eliminate the load torque fluctuation of the hydraulic motor, which is denoted by PIDD2. Based on the mathematical model and analysis of the system, a control strategy combining PIDD2 and feed-forward of velocity and acceleration is proposed. Both the traditional PID control method and the above-mentioned control method for the electro-hydraulic servo system were simulated in the simulation environment AMESim. The experiment results show that the PIDD2 control with feed-forward of velocity and acceleration will reduce the time delay and stability margin decline of the system response to some extent, and improve the dynamic performance of the system.

Multifractal characterization of mechanical vibration signals through improved empirical mode decomposition-based detrended fluctuation analysis:

A novel multifractal detrended fluctuation analysis based on improved empirical mode decomposition for the non-linear and non-stationary vibration signal of machinery is proposed. As the intrinsic mode functions selection and Kolmogorov–Smirnov test are utilized in the detrending procedure, the present approach is quite available for contaminated data sets. The intrinsic mode functions selection is employed to deal with the undesired intrinsic mode functions named pseudocomponents, and the two-sample Kolmogorov–Smirnov test works on each intrinsic mode function and Gaussian noise to detect the noise-like intrinsic mode functions. The proposed method is adaptive to the signal and weakens the effect of noise, which makes this approach work well for vibration signals collected from poor working conditions. We assess the performance of the proposed procedure through the classic multiplicative cascading process. For the pure simulation signal, our results agree with the theoretical results, and for the contaminated time series, the proposed method outperforms the traditional multifractal detrended fluctuation analysis methods. In addition, we analyze the vibration signals of rolling bearing with different fault types, and the presence of multifractality is confirmed.

Multifractal characterization of plunger pump vibration signal through improved empirical mode decomposition based detrended fluctuation analysis

Promptly and accurately detecting the plunger pump fault in the hydraulic system is a serious issue in terms of improving reliability and decreasing accidents. A main work is analyzing the character of the collected samples. We used an improved empirical mode decomposition (EMD) based multifractal detrended fluctuation analysis (MFDFA) to extract the multifractal characters. The current method utilizes intrinsic mode functions (IMFs) selection and Kolmogorov - Smirnov test (K-S test) in the detrending procedure. The IMFs selection is used to deal with the undesired IMFs, and the two-sample K-S test works on each IMF and Gaussian noise to detect the noise-like IMFs. The proposed method adaptive to the nature of data and weakening the effect of noise make this approach work well for the non-stationary signal from the real system. We used the proposed method on the plunger pump vibration signal in the hydraulic system to verify the present of multifractal.