The Experts below are selected from a list of 69 Experts worldwide ranked by ideXlab platform
Zude Zhou - One of the best experts on this subject based on the ideXlab platform.
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inverse finite element method for reconstruction of deformation in the gantry structure of heavy Duty Machine tool using fbg sensors
Sensors, 2018Co-Authors: Mingyao Liu, Zude Zhou, Xiong Zhang, Han Song, Shiguang Zhou, Weijian ZhouAbstract:The deformation of the gantry structure in heavy-Duty Machine tools is an important factor that affects machining accuracy. In order to realize real-time monitoring of the deformation of the gantry structure, which is statically indeterminate and complex in shape, the reconstruction algorithm based on inverse Finite Element Method (iFEM) is proposed and fiber Bragg grating (FBG) sensors are used to measure strain data. The elements of the gantry structure are divided and the displacement functions of each element are determined. The shape function is obtained by substituting degree of freedoms (DOF) of element nodes into displacement functions. Through a differential method, the relation between strain and DOF of element nodes is established by the strain matrices. Subsequently, the DOF of element nodes are obtained by minimizing an error functional defined as the least-squares error between the analytic strain data and the corresponding experimental strains. Considering coordinate transformation and problem-specific displacement boundary conditions, the total deformation of the gantry structure is obtained. Following this, the experiment was carried out. The deformation simulated by ANSYS was used to replace the experimentally measured deformation and then compared with the deformation reconstructed by iFEM under the same loading condition. The accuracy of iFEM for reconstructing deformation of the gantry structure in heavy-Duty Machine tools is verified. It provides a new view for improving the machining precision of heavy-Duty Machine tools.
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identification and optimal selection of temperature sensitive measuring points of thermal error compensation on a heavy Duty Machine tool
The International Journal of Advanced Manufacturing Technology, 2016Co-Authors: Quan Liu, Zude Zhou, Junwei Yan, D T Pham, Qing WeiAbstract:Thermal error compensation is considered as an effective and economic method to improve the machining accuracy for a Machine tool. The performance of thermal error prediction mainly depends on the accuracy and robustness of predictive model and the input temperature variables. Selection of temperature-sensitive measuring points is the premise of thermal error compensation. In the thermal error compensation scheme for heavy-Duty computer numerical control (CNC) Machine tools, the identification of temperature-sensitive points still lacks an effective method due to its complex structure and heat generation mechanisms. In this paper, an optimal selection method of temperature-sensitive measuring points has been proposed. The optimal measuring points are acquired through three steps. First, the degree of temperature sensitivity is defined and used to select the measuring points with high sensitivity to thermal error. Then, the first selected points are classified with fuzzy clustering and grey correlation grade. Finally, the temperature-sensitive measuring points are selected with analysis of location of temperature sensors. In order to verify the method above, an experiment is carried out on the CR5116 of flexible machining center. A novel temperature sensor, fiber Bragg grating (FBG) sensor, is used to collect the surface temperature of the Machine. A thermal error compensation model is developed to analyze the prediction accuracy based on four sequences of measuring points, which are generated by different selection approaches. The results show that the number of the measuring points is reduced from 27 to 5 through the proposed selection method, and the thermal error compensation model based on the optimum temperature-sensitive measuring points has the best performance of prediction effect.
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Real-time measurement of temperature field in heavy-Duty Machine tools using fiber Bragg grating sensors and analysis of thermal shift errors
Mechatronics, 2015Co-Authors: Jun Huang, Erlong Zhang, Mingyao Liu, Zude Zhou, Ming Chen, Duc Truong Pham, Chunqian JiAbstract:Temperature is one of the most significant parameters influencing heavy-Duty Machine tool accuracy. In order to model the correlation between temperature field distribution and thermally induced deformation, and compensate thermal errors, it is critical to obtain the temperature field variations of a precision Machine tool in real-time. In this paper, based on fiber Bragg grating (FBG) sensing technology, a novel method for measuring real-time temperature field of a heavy-Duty Machine tool is presented and the spindle thermal shift error is analyzed. Measurement experiments of real-time temperature field and thermal shift error were carried out on a CNC turn-milling Machine tool in shop floor. The variations of ambient and surface temperatures were obtained by the proposed system and the spindle thermal shift errors were monitored by laser displacement sensors at the same time. Experimental results indicate that the surface temperature variations distributed over the Machine structure are non-uniform, and the surface temperature field and spindle thermal error have a similar change trend following the ambient temperature. The proposed real-time measurement system could be utilized to analyze the thermal behavior and improve the accuracy of heavy-Duty Machine tools.
Mingyao Liu - One of the best experts on this subject based on the ideXlab platform.
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inverse finite element method for reconstruction of deformation in the gantry structure of heavy Duty Machine tool using fbg sensors
Sensors, 2018Co-Authors: Mingyao Liu, Zude Zhou, Xiong Zhang, Han Song, Shiguang Zhou, Weijian ZhouAbstract:The deformation of the gantry structure in heavy-Duty Machine tools is an important factor that affects machining accuracy. In order to realize real-time monitoring of the deformation of the gantry structure, which is statically indeterminate and complex in shape, the reconstruction algorithm based on inverse Finite Element Method (iFEM) is proposed and fiber Bragg grating (FBG) sensors are used to measure strain data. The elements of the gantry structure are divided and the displacement functions of each element are determined. The shape function is obtained by substituting degree of freedoms (DOF) of element nodes into displacement functions. Through a differential method, the relation between strain and DOF of element nodes is established by the strain matrices. Subsequently, the DOF of element nodes are obtained by minimizing an error functional defined as the least-squares error between the analytic strain data and the corresponding experimental strains. Considering coordinate transformation and problem-specific displacement boundary conditions, the total deformation of the gantry structure is obtained. Following this, the experiment was carried out. The deformation simulated by ANSYS was used to replace the experimentally measured deformation and then compared with the deformation reconstructed by iFEM under the same loading condition. The accuracy of iFEM for reconstructing deformation of the gantry structure in heavy-Duty Machine tools is verified. It provides a new view for improving the machining precision of heavy-Duty Machine tools.
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Real-time measurement of temperature field in heavy-Duty Machine tools using fiber Bragg grating sensors and analysis of thermal shift errors
Mechatronics, 2015Co-Authors: Jun Huang, Erlong Zhang, Mingyao Liu, Zude Zhou, Ming Chen, Duc Truong Pham, Chunqian JiAbstract:Temperature is one of the most significant parameters influencing heavy-Duty Machine tool accuracy. In order to model the correlation between temperature field distribution and thermally induced deformation, and compensate thermal errors, it is critical to obtain the temperature field variations of a precision Machine tool in real-time. In this paper, based on fiber Bragg grating (FBG) sensing technology, a novel method for measuring real-time temperature field of a heavy-Duty Machine tool is presented and the spindle thermal shift error is analyzed. Measurement experiments of real-time temperature field and thermal shift error were carried out on a CNC turn-milling Machine tool in shop floor. The variations of ambient and surface temperatures were obtained by the proposed system and the spindle thermal shift errors were monitored by laser displacement sensors at the same time. Experimental results indicate that the surface temperature variations distributed over the Machine structure are non-uniform, and the surface temperature field and spindle thermal error have a similar change trend following the ambient temperature. The proposed real-time measurement system could be utilized to analyze the thermal behavior and improve the accuracy of heavy-Duty Machine tools.
Ying Tang - One of the best experts on this subject based on the ideXlab platform.
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decision making method of heavy Duty Machine tool remanufacturing based on ahp entropy weight and extension theory
Journal of Cleaner Production, 2020Co-Authors: Yashi Zheng, Ying TangAbstract:Abstract Heavy-Duty Machine tools are mostly used in bottleneck processes of manufacturing companies, which have high value-added, high technical content, and large remanufacturing value. The various alternative solutions directly affect the implementation of heavy-Duty Machine tool remanufacturing as well as its benefits. However, there is currently no scientific and reasonable quantitative method to compare various options and determine the optimal solution. This paper aims to propose a decision-making method of heavy-Duty Machine tool remanufacturing based on the AHP-entropy weight and extension theory. Firstly, an evaluation criteria system of heavy-Duty Machine tool remanufacturing is established, covering economic criteria (including remanufacturing cost and remanufacturing time) and technical performance criteria (including accuracy, reliability, processing efficiency, processing range, and ergonomics). Secondly, the decision-making model is presented to determine the optimal alternative solution for heavy-Duty Machine tool remanufacturing based on extension theory, in which weight for each evaluation criterion is defined by a method of AHP-entropy weight. Finally, combined with the remanufacturing of a heavy-Duty horizontal lathe, the proposed decision-making method is verified and analyzed. The results show that the alternative for heavy-Duty Machine tool remanufacturing determined by this method can obtain better comprehensive benefits and reduce the potential risk of remanufacturing for various stakeholders.
Weijian Zhou - One of the best experts on this subject based on the ideXlab platform.
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inverse finite element method for reconstruction of deformation in the gantry structure of heavy Duty Machine tool using fbg sensors
Sensors, 2018Co-Authors: Mingyao Liu, Zude Zhou, Xiong Zhang, Han Song, Shiguang Zhou, Weijian ZhouAbstract:The deformation of the gantry structure in heavy-Duty Machine tools is an important factor that affects machining accuracy. In order to realize real-time monitoring of the deformation of the gantry structure, which is statically indeterminate and complex in shape, the reconstruction algorithm based on inverse Finite Element Method (iFEM) is proposed and fiber Bragg grating (FBG) sensors are used to measure strain data. The elements of the gantry structure are divided and the displacement functions of each element are determined. The shape function is obtained by substituting degree of freedoms (DOF) of element nodes into displacement functions. Through a differential method, the relation between strain and DOF of element nodes is established by the strain matrices. Subsequently, the DOF of element nodes are obtained by minimizing an error functional defined as the least-squares error between the analytic strain data and the corresponding experimental strains. Considering coordinate transformation and problem-specific displacement boundary conditions, the total deformation of the gantry structure is obtained. Following this, the experiment was carried out. The deformation simulated by ANSYS was used to replace the experimentally measured deformation and then compared with the deformation reconstructed by iFEM under the same loading condition. The accuracy of iFEM for reconstructing deformation of the gantry structure in heavy-Duty Machine tools is verified. It provides a new view for improving the machining precision of heavy-Duty Machine tools.
Hongzhong Huang - One of the best experts on this subject based on the ideXlab platform.
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bayesian degradation analysis with inverse gaussian process models under time varying degradation rates
IEEE Transactions on Reliability, 2017Co-Authors: Weiwen Peng, Yuanjian Yang, Hongzhong HuangAbstract:Degradation observations of modern engineering systems, such as manufacturing systems, turbine engines, and high-speed trains, often demonstrate various patterns of time-varying degradation rates. General degradation process models are mainly introduced for constant degradation rates, which cannot be used for time-varying situations. Moreover, the issue of sparse degradation observations and the problem of evolving degradation observations both are practical challenges for the degradation analysis of modern engineering systems. In this paper, parametric inverse Gaussian process models are proposed to model degradation processes with constant, monotonic, and S-shaped degradation rates, where physical meaning of model parameters for time-varying degradation rates is highlighted. Random effects are incorporated into the degradation process models to model the unit-to-unit variability within product population. A general Bayesian framework is extended to deal with the degradation analysis of sparse degradation observations and evolving observations. An illustrative example derived from the reliability analysis of a heavy-Duty Machine tool's spindle system is presented, which is characterized as the degradation analysis of sparse degradation observations and evolving observations under time-varying degradation rates.
