Dynamic errors compensation of high-speed coordinate measuring machines using ANN-based predictive modeling

Echerfaoui, Younes; Ouafi, Abderrazak El; Karganroudi, Sasan Sattarpanah

doi:10.1007/s00170-022-10007-7

Cited by 5 publications

(4 citation statements)

References 24 publications

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“…Based on Equation (11) in Section 4.1 and the tracking error of the model output in Section 4.3, the actual position point location information can be calculated. We propose an adaptive error compensation method to find the machining trajectory error, calculate the compensation length, and compensate the position using an adaptive method.…”

Section: Adaptive Error Compensation Methodsmentioning

confidence: 99%

“…To improve the machining accuracy and enhance the machining performance of CNC systems, researchers have proposed a variety of CNC machining trajectory error prediction and compensation methods, which can be categorized into model-based and data-based methods [11,12]. A model-based method mainly describes the error characteristics by establishing a mathematical model, such as using polynomials, wavelet functions, etc., to represent the error change curve, and, through the optimal fitting of the model parameters, the machining trajectory error can be predicted and compensated for in the subsequent processing.…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid-Model-Based CNC Machining Trajectory Error Prediction and Compensation Method

He,

Zhang,

et al. 2024

Electronics

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Intelligent manufacturing is the main direction of Industry 4.0, pointing towards the future development of manufacturing. The core component of intelligent manufacturing is the computer numerical control (CNC) system. Predicting and compensating for machining trajectory errors by controlling the CNC system’s accuracy is of great significance in enhancing the efficiency, quality, and flexibility of intelligent manufacturing. Traditional machining trajectory error prediction and compensation methods make it challenging to consider the uncertainties that occur during the machining process, and they cannot meet the requirements of intelligent manufacturing with respect to the complexity and accuracy of process parameter optimization. In this paper, we propose a hybrid-model-based machining trajectory error prediction and compensation method to address these issues. Firstly, a digital twin framework for the CNC system, based on a hybrid model, was constructed. The machining trajectory error prediction and compensation mechanisms were then analyzed, and an artificial intelligence (AI) algorithm was used to predict the machining trajectory error. This error was then compensated for via the adaptive compensation method. Finally, the feasibility and effectiveness of the method were verified through specific experiments, and a realization case for this digital-twin-driven machining trajectory error prediction and compensation method was provided.

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Section: Adaptive Error Compensation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Hybrid-Model-Based CNC Machining Trajectory Error Prediction and Compensation Method

He,

Zhang,

et al. 2024

Electronics

View full text Add to dashboard Cite

show abstract

“…In order to realize independent measurement of geometric error of each axis of machine tool [25] , traditional measurement method of geometric error data of three-axis machine tool mainly uses laser interferometer to identify the change of grating when each axis moves independently. However, in reality, the machine tool realizes the processing of the work piece through the coordinated movement of the three axes.…”

Section: Cnc Spatial Error Modeling Methods 21data Acquisition Method...mentioning

confidence: 99%

A data-driven high-precision modeling method of machine tool spatial error under the influence of Abbe error

Zhang

jiang²,

Chen³

et al. 2023

Preprint

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Due to the complex mechanism of the influence of Abbe error on spatial accuracy, the Abbe error accumulated in the traditional spatial accuracy model is hard to be identified and cannot be eliminated, which affects the modeling accuracy and restricts the effect of accuracy improvement. This paper presents a data-driven spatial accuracy modeling method for machine tool under the influence of Abbe error, using a three-axis coupling measurement optical path to directly measure the comprehensive spatial accuracy data of machine tool containing Abbe error. In addition, in order to effectively identify the Abbe error in the comprehensive spatial accuracy, the Abbe error quantization function is established to eliminate the Abbe error in the spatial accuracy data of machine tool by analyzing its formation mechanism in the measurement process. Further, aiming at the problem of small data samples after eliminating Abbe error, the data samples are extended based on the degradation mechanism of machine tool spatial accuracy at different coordinate positions, and a high-precision spatial error model for machine tool is given. Finally, the experiment is conducted on a three-axis CNC machine tool with the model accuracy of over 95%, and the example application verification shows that the developed model scheme is feasible and effective.

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“…The top-down modeling tries to directly summarize the characteristics of the dynamic error, e.g. modeling with neural networks [39]. But this kind of method requires precisely detecting the position of the end effector, which is still difficult to realize, especially for rotary axes.…”

Section: Dynamic Errormentioning

confidence: 99%

Surface form inspection with contact coordinate measurement: a review

Shen

Ren

Huang

et al. 2023

Int. J. Extrem. Manuf.

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Parts with high-quality freeform surfaces have been widely used in industries, which require strict quality control during the manufacturing process. Among all the industrial inspection methods, contact measurement with coordinate measuring machines or computer numerical control machine tool is a fundamental technique due to its high accuracy, robustness, and universality. In this paper, the existing research in the contact measurement field is systematically reviewed. First, different configurations of the measuring machines are introduced in detail, which may have influence on the corresponding sampling and inspection path generation criteria. Then, the entire inspection pipeline is divided into two stages, namely the pre-inspection and post-inspection stages. The typical methods of each sub-stage are systematically overviewed and classified, including sampling, accessibility analysis, inspection path generation, probe tip radius compensation, surface reconstruction, and uncertainty analysis. Apart from those classical research, the applications of the emerging deep learning technique in some specific tasks of measurement are introduced. Furthermore, some potential and promising trends are provided for future investigation.

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Dynamic errors compensation of high-speed coordinate measuring machines using ANN-based predictive modeling

Cited by 5 publications

References 24 publications

A Hybrid-Model-Based CNC Machining Trajectory Error Prediction and Compensation Method

A Hybrid-Model-Based CNC Machining Trajectory Error Prediction and Compensation Method

A data-driven high-precision modeling method of machine tool spatial error under the influence of Abbe error

Surface form inspection with contact coordinate measurement: a review

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