The gravity center position of truck crane boom is necessary for boom structural design, crane load capacity setting and counterweight design. The position of the boom's gravity center is affected by the deflection caused by gravity. Therefore, firstly, the segment by segment hardening and superposition method is adopted to derive the analytical formula of the boom's deflection, and then the center of gravity coordinates is calculated according to the boom's structure and deflection solution. The center of gravity coordinate calculation program of crane boom is compiled by using Microsoft Visual Studio, and the it is carried out by taking the 5-section boom of XCT25L5 crane as an example. The comparison with the finite element analysis results shows that the algorithm in this paper is satisfied, and the average error is within 10%. In this study, a simple and practical calculation formula of boom center of gravity coordinates is derived through theoretical analysis, and the rapid calculation of boom center of gravity coordinates is realized through software, which can be used in various R & D designs and reduce the development cycle and cost.
In the intelligent fault diagnosis of rolling bearings, the high recognition accuracy is hardly achieved when small training samples and strong noise happen. In this article, a novel fault diagnosis method is proposed, that is radial basis function neural network with power spectrum of Welch method. This fault diagnosis model adopts the way of end-to-end operating mode. It takes the original vibration signal (time-domain signal) as input, and Welch method transforms the data from time-domain signals to power spectrums and suppresses high strength noise. Then the results of Welch method are classified by radial basis function neural network. To test the performance of radial basis function neural network with power spectrum of Welch method, the method is compared with some advanced fault diagnosis methods, and the limit performance test for radial basis function neural network with power spectrum of Welch method is carried out to obtain its ultimate diagnosis ability. The results show that the proposed method can realize the high diagnostic precision without the complex feature extraction from the signal. At the same time, in the case of a small amount of training data, this method also can achieve the diagnosis in high precision. Moreover, the anti-noise performance of radial basis function neural network with power spectrum of Welch method is better than the performance of some fault diagnosis methods proposed in recent years.
In robotics, robot forward and inverse kinematics and dynamics are the foundation of robot research. Aiming at the special working environment and wafer falling off of mag8 vacuum manipulator produced by Shenyang SIASUN Robot Automation Co., Ltd., this paper completes the research on motion planning and compliance control of the manipulator. Firstly, its mechanical structure and motion mode are briefly introduced, which can realize the lifting, rotation and telescopic actions of both arms. Secondly, the robot kinematics model is established by MDH method, and the robot dynamics model is established by Lagrange method. Finally, experiments are carried out through MATLAB robot toolbox to verify the correctness of forward and inverse kinematics and dynamic model. The experimental results show that the dual arm model established in this paper effectively simulates the actual working state, which lays a foundation for further physical platform operation.
In many industrial fields, the triangular mesh had replaced the original CAD models for their simplicity and efficiency. The mesh surfaces have been widely used in the direct machining for the industrial needs. Compared with the general machining methods, the multi-axis machining can achieve the better curved surface processing effect. However, the tool axis vector cannot be accurately obtained from the mesh surface, and the multi-axis NC machining cannot be implemented directly and effectively. Base on the method that the tool axis vector perpendicular to the part, this paper proposes use the normal vector of the facet to approximatively substitute the tool axis vector and achieve the multi-axis NC machining of the mesh surface. To obtain the normal vector of the facet, the operations include facet data acquisition, regenerated triangles area calculation, selected facet judgement and extract the normal vector are introduced. And the proposed method is verified by computer programming and running in IDEL. This method will be benefit of the multi-axis NC machining of the mesh surface and solve the problem of tool axis vector generation.
To further improve the micro texture position tracking precision machine tools,the establishment of ball screw mechani-cal transmission model and dynamic model design of servo control system based on model error compensation scheme for the de-sign of the control system,puts forward a search algorithm based on improved crowd feedforward PID control strategy,estab-lished the ISOA-PID controller of the control structure,completed the design of PID parameter.Matlab is used to build a simula-tion experiment platform.In order to verify the actual effect of the control strategy,Matlab was used to build a simulation experi-ment platform and compared with the traditional intelligent optimization algorithm.The simulation results show that the feedfor-ward compensation PID optimization effect based on ISOA optimization is better,and the speed tracking performance is greatly improved,which verifies its correctness and effectiveness.
