Geometric Feature Recognition by Object Decomposition

Author(s):  
C. Karra ◽  
T. A. Phelps

Abstract Design engineers have traditionally have had inadequate manufacturing information. One method of getting that information to them is through its inclusion in computer-based design tools such as geometric solid modelling programs. Analysis of geometry requires methods such as feature recognition. A new approach to feature recognition has been developed which recognizes features by taking apart the original solid object into prismatic primitives. This approach already covers a very large portion of what is currently manufactured. The expected applications of this approach include automatic manufacturability analysis, design for assembly, process planning, etc.

2011 ◽  
Vol 415-417 ◽  
pp. 523-526
Author(s):  
Yan Dong ◽  
Mei Li

This paper put forward a geometry feature recognition method of part drawing based on graph matching. Describe the constraints structure of geometric feature in geometric elements and those constraint relationships. Match sub-graph in contour closure graphics and those combination. Using linear symbol notation of chemical compounds in chemical database for reference, encode to constraint structure of geometry graphics, establish recognition mechanism of geometric characteristics by structure codes. Taking the fine-tune screw and fork parts for example, this method has been proved to be effective.


2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Javier Eduardo Diaz Zamboni ◽  
Daniela Osella ◽  
Enrique Valentín Paravani ◽  
Víctor Hugo Casco

The current report presents the development and application of a novel methodological approach for computer-based methods of processing and analysis of proliferative tissues labeled by ABC-peroxidase method using 3, 3′-diaminobenzidine (DAB) as chromogen. This semiautomatic method is proposed to replace the classical manual approach, widely accepted as gold standard. Our method is based on a visual analysis of the microscopy image features from which a computational model is built to generate synthetic images which are used to evaluate and validate the methods of image processing and analysis. The evaluation allows knowing whether the computational methods applied are affected by the change of the image characteristics. Validation allows determining the method’s reliability and analyzing the concordance between the proposed method and a gold standard one. Additional strongness of this new approach is that it may be a framework adaptable to other studies made on any kind of microscopy.


2011 ◽  
Vol 282-283 ◽  
pp. 683-686
Author(s):  
Yong Ling Yu ◽  
Tao Guan ◽  
Jin Fa Shi

With the expansion of manufacturing information services, visualization service in enterprise resource planning has recently become a hot topic. In this paper, we propose a new approach for job scheduling visualization service and a model of visualization service constructed from the share of production data and job scheduling information. Moreover, the optimization model of visualization service is given. At last, we discuss the optimization algorithm for this model.


Author(s):  
Mohsen Rezayat

Abstract An integral part of implementing parallel product and process designs is simulation through numerical analysis. This simulation-driven design requires discretization of the 3D part in an appropriate manner. If the part is thin or has thin sections (e.g., plastic parts), then an analysis model with reduced dimensionality may be more accurate and economical than a standard 3D model. In addition, substantial simplification of some details in the design geometry may be beneficial and desirable in the analysis model. Unfortunately, the majority of CAD systems do not provide the means for abstraction of appropriate analysis models. In this paper we present a new approach, based on midsurface abstraction, which holds significant promise in simplifying simulation-driven design. The method is user-friendly because very little interaction is required to guide the software in its automatic creation of the desired analysis model. It is also robust because it handles typical parts with complex and interacting features. Application of the method for feature recognition and abstraction is also briefly discussed.


1989 ◽  
Vol 6 (3) ◽  
pp. 109-114 ◽  
Author(s):  
Gary J. Brand ◽  
Margaret R. Holdaway

Abstract Computer based growth projection systems can help foresters evaluate the effect of management prescriptions. However, using projection systems wisely requires information about how accurate they are. Both parts of accuracy, bias and precision, are estimated for volume predictions from a Lake States projection system using data from 822 remeasured plots. Volume tends to be underpredicted for four locations in the northern part of the Lake States but overpredicted for one location in Lower Michigan. The bias is large for dense stands and for northern hardwood and lowland hardwood stands in Lower Michigan. Forests are highly variable, however, and the precision of a projection system must be estimated as well as its bias. Prediction intervals are computed that help estimate the likely range for a given prediction. The interval that has a 90% probability of containing the true volume can be quite large. North. J. Appl. For. 6:109-114, September 1989.


2009 ◽  
Vol 42 (2) ◽  
pp. 347-355 ◽  
Author(s):  
Dominikus Herzberg ◽  
Nicola Marsden ◽  
Peter Kübler ◽  
Corinna Leonhardt ◽  
Sabine Thomanek ◽  
...  

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