An Optical Inspection System for the Solder Balls of BGA using Support Vector Machine Classification
In this paper, the Support Vector Machine (SVM) is utilized to classify the defective solder ball of ball grid array (BGA) so as to promote the accuracy and efficiency of the optical inspection. The terms of inspections include the ball displacement, the ball over scale, the ball undersize, the ball absence, and ball bridging. There are two step of the SVM processing: the training step and the real testing step. The SVM is more efficiency because of the calculation in testing step is no relation to the number of the input vector. As this point, SVM is fit to build up the high dimension input recognize system such as BGA inspection. From the real testing results, the Support Vector Machine is proved to properly identify and classify the shape defects. The two dimensional BGA optical inspecting system is implemented by Visual Basic as the developing tool incorporated with the Halcon's function which is the database of the image processing on Windows operation system. For the development of the processing procedure of the automatic optical inspecting system with the designed lighting system, the precise geometrical information of the solder ball is evaluated by the sub-pixel method to identify the shape of solder ball and its location under the BGA board is offset and rotated at any angle.
Locating and checking of a BGA pin's position using gray level
A machine vision system for SMT-mounting machine applications is usually a two-stage algorithm. It first measures the centroid and rotation angle of the SMD, and then checks each pin's area, position error, and grid coordinate location. In this paper, a set of complete procedures is proposed to locate and check the BGA image. During the locating procedures, we first calculate a threshold of the frame using an iterative threshold algorithm. If an object is found under this threshold, then the pin's area is calculated by the local threshold by using a momentum algorithm. After that, whether this object is a pin or not is decided by its neighbors' relative positions, the approximate rotation angle for finding the outer pins is calculated, and the centroid as well as the rotation angle of a BGA component is calculated by the rectangular least squares algorithm. The checking procedure also measures each pin's area using the momentum algorithm, then it calculates the radius of the moving sum using each pin's area, and finally measures the position error using a moving sum algorithm and judges each pin's type by gray level. The new method uses the gray level statistic information to solve the empty pad's problem and utilizes the symmetrical property of a circle to deal with the shape problem. Lastly, the CRC algorithm is used to check the correspondence between each pin and its pin type. This new method has a high accuracy and a low execution time. It can meet the crucial timing requirement of a high-speed SMT machine through experimental verification.
Three-dimensional inspection of ball grid array using laser vision system
An inspection process of the ball grid array (BGA) is proposed using a laser vision system which provides range image. This study suggests an inspection algorithm using the range images for evaluating the height of the solder ball, coplanarity and lead pitch, which are major factors in the BGA surface mounting technology. A feature-based algorithm was used in implementing region segmentation of range images. By deciding the BGA orientation using plane modeling, the errors of the range finding system were compensated and the reference of the height of the solder ball was found. Also, a method for measuring the height of the solder ball using free-form surface modeling was proposed. And, from the measured heights, the pitches and coplanarity were calculated.