Work

Prediction of machining errors for free-form surfaces based on an improved grey model (1,

Year: 2024

Type: article

Abstract: \nAn improved grey model (GM) for predicting free-form surface machining errors was established to address the low measuring efficiencies of coordinate measuring machines (CMMs) and the low prediction accuracy of the GM(1,1) model. A number of points on a free-form surface are measured with a CMM, and machining errors are obtained. Ideas from metabolic methods and the GM(1,N) prediction model were combined. To reduce the impact of random fluctuations of the machining errors, a Markov prediction model was then used to correct the fitted results for the residuals and obtain the predicted results of the machining errors for free-form surfaces, thus improving the prediction accuracy of the model. The predicted results of the metabolic GM(1,1) and metabolic GM(1,N) models were then compared. The experimental results showed that the combination of metabolic theory, a grey model, and Markov theory effectively improved the prediction accuracy.\n

Source: Springer Link (Chiba Institute of Technology)

DOI: 10.1051/ijmqe/2024011/pdf

Authors: Dayang Ma, Yueping Chen

Institution: Guangxi University of Science and Technology

Language: English

Topic: Grey System Theory Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

Funders: National Natural Science Foundation of China, Natural Science Foundation of Guangxi Province, Guangxi University, Guangxi University of Science and Technology

Award: 基于原位检测的复杂曲面加工-测量的闭环加工方法研究