CNC machine tools play important role in industries. The dynamic characteristics of the machine tools are the main factor which affected the status of a machine tools. A three-dimensional model of a five-axis CNC mach...
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It is necessary to test the reliability of the operation of the machine itself for meeting the high-speed, ultra-precision, flexible, and other modern manufacturing and processing needs. In practical applications, the...
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Objected to influences of impact to the whole body with sitting posture, the inverse dynamical analysis is carried out. Firstly by using the high-speed video camera, the images of the marked points on the body and the...
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Machine chatter phenomenon has a great influence on the stability during the machining process of the machine tool. It has a great limitation on the machining efficiency of the machine tool and the machining accuracy ...
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‘S’ specimen through its unique profile features makes it possible to fully mobilise the five-axis linkage function in the five-axis finishing stage. The continuous rotation direction of the rotating axis not only r...
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Objected to the planetary gear transmission, research on the fault diagnosis of gear cracks is mainly carried out with method of EEMD decomposition and Envelope demodulation. During the process, EEMD decomposition is ...
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Currently, some five-axis CNC machine tools have almost achieved the same advanced level of the western countries in terms of functionality and performance. However, the reliability of system is much lower than simila...
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A real-time calibration method for six-DoF industrial robot is presented. It aims to address the issue that calibration always suspends the work of robot and is quite costly due to repeated utilization of expensive me...
A real-time calibration method for six-DoF industrial robot is presented. It aims to address the issue that calibration always suspends the work of robot and is quite costly due to repeated utilization of expensive measurement instrument. For this, a pose measurement strategy with cost-effective cameras is proposed where the work trajectory of robot is considered as a strict constraint on configurations to meet the requirement of real time. However, such efficiency improvement is accompanied by the accuracy decrease because the camera brings large measurement error and the trajectory constraint results in the reduced parameter identifiability. Firstly, to pull up the camera performance to the same level of precise instrument like the laser tracker, a set of neural networks are designed to map the inaccurately measured poses by camera to the accurate poses of concerned joints. Secondly, a dimension-reducing method is proposed to truncate the constrained kinematic-error model into two, which commonly achieve high parameter identifiability. Simulation shows that the prediction accuracy of joint pose with the well-trained networks is much higher than the measurement accuracy of laser tracker. Besides, the calibration accuracy with the dimension-reduced models is validated to be higher than that with the single high-dimension model of typical calibration. Finally, a generation strategy of training data with deeper regularity is proposed to meet the accuracy requirement in real scene, and the comparative results in the experiment validate a good potential of the real-time calibration method in manufacturing that requires high accuracy of robot and no suspension of work.
In low field NMR multiphase flow measurement, the magnetization time and magnetization length are affected by the two-phase flow velocity and water fraction, so it is difficult to realize the complete magnetization of...
In low field NMR multiphase flow measurement, the magnetization time and magnetization length are affected by the two-phase flow velocity and water fraction, so it is difficult to realize the complete magnetization of multiphase flow with fixed length magnet. In this paper, an adaptive magnetization structure for two-phase flow is proposed. The pre-magnetization model of the adaptive structure is established based on the magnetization theory of nuclear magnetic resonance. And parameters of the adaptive magnetization structure are determined by analyzing the influence of two-phase flow parameters such as velocity and water fraction on magnetic susceptibility. Finally, the simulation analysis shows that the adaptive magnetization structure can achieve complete magnetization effect for two-phase flow in the range of water fraction 0-36% and flow rate 0-4.66m/s, which provides the necessary conditions for the accurate measurement of NMR two-phase flow and provides a new idea for the design of NMR two-phase flow measurement sensor.
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