Based on studying the typical fault characteristics of an electro-hydraulic servo-system which is centered on the electro-hydraulic servo-valve, the wavelet transform is able to detect signal singularities and their signature in accordance with the localization time varying feature on the signals of the system.A practical technique is applied to the feature fault diagnostic for the electro-hydraulic servo-system. The fault feature of the eletro-hydraulic servo-system is recognized by multi-rule criterion.
This paper proposes an improved optimal adaptive control algorithm to accelerate convergence for sine control of general multichannel coupled system, as well as enhance the stability. First of all, the convergence of traditional multi-input multi-output (MIMO) sine control method is analytically investigated in the presence of frequency response function (FRF) error. Then, the controller with the improved optimal adaptive control algorithm is developed, where a high-precision algorithm for amplitude and phase estimation is proposed to guarantee the accuracy of the response vector calculation. Numerical simulation results show that the proposed method possess excellent performance with fast convergence rate and strong robustness.
Positioning accuracy is of great significance for industrial robots in high-end industries. In addition to kinematic parameter errors, there are also some dynamic parameter errors, which are nonlinear. This paper proposes a novel method to improve the positioning accuracy of industrial robot, which takes both kinematics and dynamics parameter errors into account. Firstly, the method uses improved Denavit-Hartenberg (DH) model to establish kinematics model and identifies the geometric errors. Then, the deformation of the joint is analysed, and the angle deviation of each joint due to the end load is compensated. Finally, the accuracy improvement experiment is carried out on 6R robot. The experimental results show that the method is very effective.
Abstract This paper proposes an intelligent technique by combining multilayer feed-forward neural networks (MLFNN) and beetle antennae search (BAS) algorithm for the inverse calibration of a 7R manipulator. First of all, the MLFNN is optimized by BAS. Then, the optimized BAS-MLFNN method is employed for the nonlinear mapping from the true angles of the joint to the errors of the joint. The true angle values of the joints are selected as the inputs and the joint errors as the outputs. The simulation of calibration is implemented on a Kuka’s LWR manipulator. Numerical simulation results show that compared with the commonly used BPNN, the proposed BAS-MLFNN method possesses better performance in terms of higher precision.
Three-parameter control strategy, which incorporates signals of displacement, velocity and acceleration coming from the tested subject, has become a major technology in servo control for seismic simulation shaking table. The three-parameter control strategy allows the system to broaden its response bandwidth and increase its damping property. Normally, trial and error method is used to determine the proper value of each parameter, so the tested system can exhibit favorable frequency response performances. Whereas it can be very labor-intensive to find the optimal parameter values during the parameter trial and error process which also has a certain possibility to fail. To solve this problem, a novel rapid parameter tuning method of three-parameter control strategy has been proposed to consume less time in calculation, but realize the optimal response characteristics at the same time. The servo controller for seismic simulation shaking table is usually made up of three-parameter feedback, feed forward links and signal generator. By deducing the transfer function for each feedback and feed forward link the values of three parameters for the servo controller can be tuned efficiently. Simulation and experiment results have shown the control results of the novel and traditional three-parameter control methods to be virtually identical, proving the feasibility and validity of this novel parameter tuning method proposed in this study. Moreover, this method is proven to have a wide application in different tested system with different vibration characteristics, and it won’t bereave the system of its initial stability.
In this paper, a 3D measurement system for the inner surface of tubular parts with large length-to-diameter ratio based on white light interference is developed. A common-path white light interferometer is built, and a side-looking probe which can obtain the reflected light of fiber end and can change the length freely is designed. In order to meet the requirements of large depth inner surface measurement, an inverted U-shaped combined device is designed and its geometric principle is described. With the aid of high-precision and large stroke 3-axis motion system, the 3D inner surface measurement is realized. The method of creating 3D point cloud, the correction method of probe center position, pose and light direction and the calibration method of system are described. The experimental results show that the system has a good inner diameter measurement accuracy, and is suitable for measuring the inner surface of long tubular parts.
The related theory and algorithm of adaptive inverse control were presented through the research which pointed out the adaptive inverse control strategy could effectively eliminate the noise influence on the system control. Proposed using a frequency domain filter-X LMS adaptive inverse control algorithm, and the control algorithm was applied to the two-exciter hydraulic vibration test system of random shock vibration control process and summarized the process of the adaptive inverse control strategies in the realization of the random shock vibration test. The self-closed-loop and field test show that using the frequency-domain filter-X LMS adaptive inverse control algorithm can realize high precision control of random shock vibration test.
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