Quantitative evaluation method for machining accuracy retention of CNC machine tools considering degenerate trajectory fluctuation

Feng, Cong; Yang, Zhaojun; Chen, Chuanhai; Guo, Jinyan; Tian, Hailong; Meng, Fanning

doi:10.1007/s12206-022-0543-6

Cited by 4 publications

(4 citation statements)

References 23 publications

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“…For subsequent calculations, it needs to be simplified into a one-dimensional machining accuracy degradation amount through a mathematical model. 41 The specific process is described as follows:…”

Section: Performance Degradation Index Acquisition and Processingmentioning

confidence: 99%

“…This indicator will have components in three directions of XYZ, so it is a vector form. For subsequent calculations, it needs to be simplified into a one‐dimensional machining accuracy degradation amount through a mathematical model 41 . The specific process is described as follows: Step 1: R t represents the coordinates of the tool forming point in the tool coordinate system, L i ( j ) represents the i th‐order low‐order body of body j , T ijp represents the static feature matrix between two adjacent bodies of ij , T ijs represents the motion feature matrix between two adjacent bodies of ij and the feature matrix between adjacent bodies is represented by the relevant geometric error source.…”

Section: Case Analysismentioning

confidence: 99%

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Reliability evaluation of a complex system that considers the influence of the fluctuation degree of the performance degradation trajectory

Feng,

Yang,

Chen

et al. 2023

Quality & Reliability Eng

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In this paper, a reliability evaluation method based on the hidden Markov model (HMM) considers the influence of degradation trajectory fluctuation. To address the problem in which the performance degradation trajectory modelling of complex systems is limited by sampling time points, this method constructs an approximate degradation trajectory model based on effective discrete data points through a radial basis function to realize the degradation data expansion of small samples. Then, the average degradation rate is defined, and the fluctuation degree of the degradation trajectory is quantitatively evaluated to obtain the evaluation function of the fluctuation degree of the degradation trajectory. In addition, to determine the relationship between the fluctuation degree of the degradation trajectory and the operating state of the system, the method combines HMM with the evaluation function of the fluctuation degree of the degradation trajectory and obtains the transition probability matrix of different operating states of the system affected by the fluctuation degree of the degradation trajectory. On the basis of the probability matrix of the failure state, the reliability change curve of the system is derived. Finally, the effectiveness of the proposed method is verified via an example of a computer numerical control machine tool.

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Section: Performance Degradation Index Acquisition and Processingmentioning

confidence: 99%

Section: Case Analysismentioning

confidence: 99%

Reliability evaluation of a complex system that considers the influence of the fluctuation degree of the performance degradation trajectory

Feng,

Yang,

Chen

et al. 2023

Quality & Reliability Eng

View full text Add to dashboard Cite

show abstract

“…Computer numerical control (CNC) have gradually become an important equipment for workshop processing, because CNC can achieve intelligent control and improve productivity. However, CNC still have the same problem as traditional CNC, that is, with the increase of running time, machining errors will gradually occur [1][2]. A large number of studies that the errors of CNC include geometric errors and thermal errors (TE), among which TE are the reduction of processing accuracy caused by the temperature rise of CNC after a long time of operation, and the temperature change of CNC is difficult to control.…”

Section: Introductionmentioning

confidence: 99%

Intelligent CNC control with improved adaptive thermal error compensation model

Shen,

Yang

2023

J. vibroeng.

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The thermal errors (TE) of computer numerical control (CNC) in workshop production seriously reduces the productivity. Therefore, to improve the productivity of CNC and enhance production intelligence, an improved adaptive TE compensation model (TECM) is proposed. The model is based on an online temperature measurement system (OTMS), which improves the adaptive learning rate of back-propagation neural network (BPNN) for temperature prediction. Finally, the correlation value between temperature changes and TEs is used for thermal error compensation. The performance verification of the model shows that the proposed OTMS can achieve effective temperature acquisition and processing, and the prediction ability of the improved BPNN is significantly higher than that of other prediction algorithms. Finally, it is found in the test that the improved adaptive TECM can reduce the contour error of workpiece machining to within 0.02×10-3 mm, the machining accuracy of CNC is significantly improved. The above results show that using the improved adaptive TECM can promote the intelligent development of CNC and improve their machining accuracy, which is of great significance to the development of workshop manufacturing.

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“…At present, research on the evaluation of machining accuracy retention of CNC machine tools mainly focuses on the accuracy value of a fixed time point or different periods. Based on the theory of multi-body systems, Feng et al 36 established the volume error model of CNC machine tools. By calculating the offset distance between the space error and the origin, the three-dimensional volume error vector is transformed into one-dimensional machining accuracy degradation.…”

Section: Introductionmentioning

confidence: 99%

Accuracy reliability analysis of CNC machine tools considering manufacturing errors degrees

Zhang

2023

Proceedings of the Institution of Mechanical Engineers, Part O:

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To evaluate the accuracy reliability of machine tools, an evaluation method of accuracy reliability considering the machining error out of tolerance is proposed, and an accurate mathematical description is given to realize the quantitative evaluation of machining accuracy under different machining loads. On this basis, the basic connotation and mathematical model of accuracy retention are analyzed, and the influence of different machining loads on the accuracy retention is studied. Finally, experiments are carried out to detect the variations of machining errors of machine tools under different loads and the quantitative evaluations of accuracy reliability and retention of machine tools are completed, which verify the validity of the proposed methods.

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Quantitative evaluation method for machining accuracy retention of CNC machine tools considering degenerate trajectory fluctuation

Cited by 4 publications

References 23 publications

Reliability evaluation of a complex system that considers the influence of the fluctuation degree of the performance degradation trajectory

Reliability evaluation of a complex system that considers the influence of the fluctuation degree of the performance degradation trajectory

Intelligent CNC control with improved adaptive thermal error compensation model

Accuracy reliability analysis of CNC machine tools considering manufacturing errors degrees

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