Papers by Author: Zhen Ya He

Abstract: The purpose of this article is to select the most appropriate sensor for the crane structural health monitoring. We used three kinds of sensors to do an equal strength beam test: The original sensor R₂ and R₄ which have been calibrated, American MOI FBG sensor and wireless strain sensor. After derived the formula of maximum normal strain, we have done equal strength beam test for 3 times. Then calculated their average and contrasted their linearity to see the accuracy of MOI FBG os3110 and wireless sensor. Compared with the experimental value theoretical value, the wireless sensor has the highest accuracy, it is even more accuracy than the original sensor R₂ and R₄ which have been calibrated; Departure from linearity aspect, the wireless sensor, the original sensor R₂ and R₄,all of them have small relative error rate, it is less than 10%, but MOI FBG os3110 has very large relative error rate; In order to compare the overall performance of the sensor, we can also compare the sensors from the sensitivity aspect, zero drift, detection range, and so on.

Abstract: An error mapping modeling and identification technology for the circular path test of NC machine tools is proposed. First, geometric error modeling of the NC machine tool was established and the theory of the laser measurement method was introduced. Then through further analyzing the influence of the geometric errors to circular path deviations, the error items were identified, such as the displacement errors, backlashes and squareness errors. Finally measurement and compensation experiment of circular path was conducted. The experimental results show that the geometric error modeling is feasible, and the measurement method can be set up easily and rapidly, even can be used to measure smaller radius circular path under a high feed rate condition. After compensation, the accuracy of the circular path of the machine tool is improved by 50.88%.

Abstract: Wireless sensors are increasingly adopted in mechanical systems to acquire and wirelessly transmit sensed information for machine condition monitoring. For wireless sensors on spindle, the reliability of the sensors system at high rotary speed is the key factor to guarantee the validity of monitoring. How to identify sensor failure accurately and timely is essential to enhance reliability of monitoring system. To address this issue, a novel method based on the BNs was presented to distinguish sensor failure from other transmission errors. The method described causal relationships of factors inducing sensor failure by graph theory and deduced sensor failure by Bayesian statistical techniques. Experiments carried on NC machining center prove the validity of this approach.

Abstract: Bed is a main component of a large precision linear rolling guide CNC grinding machine tool Its dynamic characteristics impact on machine tool’s machining precision and stability directly. In this paper, boundary conditions on the bed of a machine tool factory’s production are analyzed. By using FEA method, the bed finite element models for dynamic analysis model are established and calculated. It provides guidance in investigating the effect factors of machining precision, the machine tool’s structure optimization and error compensation.

Abstract: With the development of the CNC precision machining and the ultra-precision machining, machine tools error issue has became the most active research topics and concerned by more and more experts. In this paper, a rapid simulation software platform based on multi-body system theory and Matlab software for measurement and analysis geometric errors of CNC machine tool is presented, which includes the generation of simulated measurement data, data processing, error separation and error compensation etc. To verify the feasibility of the developed software, the sequential step diagonal vector measurement method has been analyzed. The experimental results show that after error compensation the machine performance is improved by 39%. It demonstrates that the sequential step diagonal vector measurement method could significantly improve the machine accuracy and the developed software platform is reliable. This platform is not only effective for step diagonal vector measurement method, but also can be applied to other measurements. Therefore, the software platform provides a fast, reliable and objective tool for machine error measurement and analysis.