scholarly journals In-Process Error-Matching Measurement and Compensation Method for Complex Mating

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7660
Author(s):  
Shih-Ming Wang ◽  
Ren-Qi Tu ◽  
Hariyanto Gunawan
Keyword(s):  
Production Efficiency ◽  
Compensation Method ◽  
Mating Experiment ◽  
Nc Program ◽  
Assembly Accuracy ◽  
Polynomial Curve ◽  
Straight Line ◽  
Process Error ◽  
Polynomial Curve Fitting ◽  
Function Module

This study proposed an error-matching measurement and compensation method for curve mating and complex mating. With use of polynomial curve fitting and least squares methods for error analysis, an algorithm for error identification and error compensation were proposed. Furthermore, based on the proposed method, an online error-matching compensation system with an autorevising function module for autogenerating an error-compensated NC program for machining was built. Experimental verification results showed that the proposed method can effectively improve the accuracy of assembly matching. In a curve-type mating experiment, the matching error without compensation was 0.116 mm, and it decreased to 0.048 mm after compensation. The assembly accuracy was improved by 28%. In a complex-type mating experiment, the verification results showed that the error reductions after compensation for three mating shapes (straight line, triangle, and curve shape) were 81%, 87%, and 79%, respectively. It showed that the proposed method can improve the assembly accuracy for complex mating shapes, which would also be improved without losing production efficiency.

Analysis of Crimping of Large Diameter Welding Pipe

2014 ◽  
Vol 997 ◽  
pp. 517-521
Author(s):  
Li Feng Fan ◽  
Ying Gao ◽  
Jian Bin Yun ◽  
Lin Feng Dong
Keyword(s):  
Analytical Model ◽  
Large Diameter ◽  
Forming Process ◽  
Technical Parameters ◽  
Polynomial Curve ◽  
Welding Pipe ◽  
X80 Steel ◽  
Polynomial Curve Fitting ◽  
Effective Path ◽  
Submerged Arc

Crimping is widely used in production of large diameter submerged-arc welding pipes. Traditionally, the designers obtain the technical parameters for crimping from experience or trial-errors by experiments. To tackle this problem, a theoretical analytical model is proposed to analysis crimping forming process. In this paper, taking the crimping of X80 steel Φ1219mm×22mm×12000mm welding pipe for instance, the theoretical analytical model is constructed by quadratic polynomial curve fitting technique and mechanics theory. And it is verified by a comparison with experiment results. Thus, the presented model of this research provides an effective path to design crimping parameters.

EIGEN-TEMPERATURE MODEL FOR THE ANNUAL AIR TEMPERATURE MOVEMENT EVALUATION AND FORECAST

2013 ◽  
Vol 04 (03) ◽  
pp. 1350008 ◽  
Author(s):  
ZONG-CHANG YANG
Keyword(s):  
Air Temperature ◽  
Principal Component ◽  
Ar Model ◽  
Temperature Model ◽  
Polynomial Curve ◽  
Actual Observation ◽  
Fitting Algorithm ◽  
Global Concern ◽  
Polynomial Curve Fitting ◽  
Result Analysis

Climate variability and its changes are issues of broader global concern. This study addresses the annual air temperature movement evaluation and forecasting based on principal component analysis (PCA). An Eigen-temperature model for describing the annual air temperature movement by employing PCA is introduced. Subspace for evaluation is generated by selecting principal orthogonal eigenvectors of covariance matrix of temperature data. The principal eigenvectors are called "Eigen-temperatures", since they are eigenvectors and each temperature movement is described by them. Each temperature movement is projected onto the subspace of eigenspace, and described by a linear combination of the Eigen-temperatures. Then, a forecast method for the temperature movement by employing the Eigen-temperatures is proposed. Forecast is implemented with polynomial curve fitting algorithm to estimate subsequent representation weights for the subsequent temperature movement with respect to the "Eigen-temperatures" generated by its previous temperature movements. The proposed Eigen-temperature model is applied to evaluation and forecasting for annual temperature movement at Tongchuan observation station of China from 1962 to 1971 and from 1994 to 2002. Experimental results agreeing well with actual observation values show workability of the proposed. Result analysis indicates its effectiveness that the proposed Eigen-temperature model is outperforming the classical AR model and the BP-ANN on the forecast tasks.

End of T-wave determination by polynomial curve fitting on a vector magnitude lead

2009 ◽  
Vol 42 (6) ◽  
pp. 608
Author(s):  
Boško Bojović ◽  
Ljupčo Hadžievski ◽  
Ihor Gussak ◽  
Samuel George ◽  
Branislav Vajdić
Keyword(s):  
Curve Fitting ◽  
T Wave ◽  
Polynomial Curve ◽  
Polynomial Curve Fitting ◽  
Vector Magnitude

Multi-Space Competitive DGA for Model Selection and its Application to Localization of Multiple Signal Sources

2011 ◽  
Vol 15 (9) ◽  
pp. 1320-1328 ◽  
Author(s):  
Shudai Ishikawa ◽  
◽  
Hideaki Misawa ◽  
Ryosuke Kubota ◽  
Tatsuji Tokiwa ◽  
...  
Keyword(s):  
Population Size ◽  
Solution Space ◽  
Optimization Method ◽  
Signal Source ◽  
Polynomial Curve ◽  
Population Sizes ◽  
Polynomial Curve Fitting ◽  
Distributed Genetic Algorithm ◽  
Optimum Solution ◽  
Signal Sources

In this paper, a new optimization method, which is effective for the problems that the optimum solution should be searched in several solution spaces, is proposed. The proposed method is an extension of Distributed Genetic Algorithm (DGA), in which each subpopulation searches a solution in the corresponding solution space. Through the competition between the sub-populations, population sizes are adequately and gradually changed. By the change of the population size, the appropriate sub-population attracts many individuals. The changing population size yield the efficient search for the problems of searching for solutions in multiple spaces. In order to evaluate the proposed method, it is applied to a polynomial curve fitting and signal source localization, in which the number of sources is preliminarily unknown. Simulation results show the effectiveness of the proposed method.

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