Optimization of propagation in interval constraint networks for tolerance design

This paper proposes a hierarchical internal constraint network and interval propagation techniques for automatic tolerance design. The nodes in interval constraint networks represent the entities, the attributes, and the functional requirements of the mechanical design or the constraint functions. The arcs represent the relationships between the entities, the attributes, the functional requirements and the constraint functions. We developed the forward propagation technique for tolerance analysis and the backward propagation technique for tolerance synthesis. In tolerance analysis, given the entity tolerances, the goal is to ensure that the functional requirement tolerances are met. In tolerance synthesis, given the functional requirement tolerances, the goal is to synthesize a new set of entity tolerances. In backward propagation, the minimization of the manufacturing cost is also considered. During backward propagation, the tolerances of entities, which have a smaller impact on manufacturing costs, will be tightened first. Using this mechanism, we ensure the constraints are satisfied and the manufacturing costs are minimized.published_or_final_versio

Minimizing the probabilistic magnitude of active vision errors using genetic algorithm

Spatial quantization errors are resulted in digitization. The errors are serious when the size of the pixel is significant compared to the allowable tolerance in the object dimension on the image. In placing the active sensor to perform inspection, displacement of the sensors in orientation and location is common. The difference between observed dimensions obtained by the displaced sensor and the actual dimensions is defined as displacement errors. The density functions of quantization errors and displacement errors depend on the camera resolution and camera locations and orientations. We use genetic algorithm to minimize the probabilistic magnitude of the errors subject to the sensor constraints, such as the resolution, field-of-view, focus, and visibility constraints. Since the objective functions and the constraint functions are both complicated and nonlinear, traditional nonlinear programming may not be efficient and trapping at a local minimum may occur. Using crossover operations, mutation operations, and the stochastic selection in genetic algorithm, trapping can be avoided.published_or_final_versio

Error analysis and planning accuracy for dimensional measurement in active vision inspection

This paper discusses the effect of spatial quantization errors and displacement errors on the precision dimensional measurements for an edge segment. Probabilistic analysis in terms of the resolution of the image is developed for 2D quantization errors. Expressions for the mean and variance of these errors are developed. The probability density function of the quantization error is derived. The position and orientation errors of the active head are assumed to be normally distributed. A probabilistic analysis in terms of these errors is developed for the displacement errors. Through integrating the spatial quantization errors and the displacement errors, we can compute the total error in the active vision inspection system. Based on the developed analysis, we investigate whether a given set of sensor setting parameters in an active system is suitable to obtain a desired accuracy for specific dimensional measurements, and one can determine sensor positions and view directions which meet the necessary tolerance and accuracy of inspection.published_or_final_versio

Tolerance analysis and synthesis by interval constraint networks

This paper proposes interval constraint network and interval propagation techniques for automatic tolerance design. A hierarchical representation is utilized in the interval constraint network. The consistency of a constraint is defined for the purpose of tolerance design. Forward and backward propagation techniques are introduced in the interval constraint network for tolerance analysis and synthesis, respectively. Both a propagation technique for a single constraint and a parallel propagation technique for multiple constraints between two adjacent levels in the network are introduced. Experiments conducted to illustrate the procedures of tolerance analysis and synthesis for the tank problem are described.published_or_final_versio

Camera settings for dimensional inspection using displacement and quantization errors

An important aspect of inspection planning involves determining camera poses based on some criterion. We seek to find camera poses where the effects of displacement and quantization errors are minimal. The mean squared error is formulated, including all dependencies, and minimized to determine an optimal camera pose that satisfies the sensor constraints of resolution, focus, field-of-view, and visibility. Dimensional tolerances for line entities are also formulated and exploited to determine the acceptability of a given camera pose for all entities observed.published_or_final_versio