Zhaohua Wu

Study on solder joint image segmentation techniques based on Matlab

Due to color image contain more information than grayscale image, color image processing is being paid more and more attention. The methods of grayscale image segmentation just consider the brightness and neglect hue, saturation and other important information. Only using gray information can not extract the correct target area quickly. In this paper, selecting chip components as research object, completing the conversion of the color space based on the theory of Graphic and Image processing and achieving the conversion from the non-uniform RGB color space to HSV space for human eyes observation by means of MATLAB. Choose the better H domain as segmentation object. After that removing noise, filter and image enhancement by using technology of image preprocessing. Combine the operation of mathematical morphological with OTSU method to conduct the segmentation of H domain. The results show that at the same case of using the same segmentation method, using the color image segmentation containing the information of Hue and saturation can obtain better object, while the grayscale method can not. The image of solder joint by utilizing the color image segmentation can provide foundation for the subsequent extraction of solder joint quality information.

SPC System Analysis and Design of Reflow Soldering Process

The reflow soldering process is the key process of SMT. Available control of reflow soldering process is the important process to ensure the SMT product quality and reliability. In this paper, taking reflow soldering process as the object, the SPC system of reflow soldering process is built; the process controlling project is designed; the choice of controlling variable, data collecting and SPC control policy for the reflow soldering process are analyzed; especially the design and realization of SPC control graph is explained. The study has advanced actively the level and capability of reflow soldering process

SMT product character recognition based on BP neural network

In this paper, we present an approach to recognizing characters in surface mount technology (SMT) product. The recognition rate of SMT product character is not very good, because of unexpected noise in SMT the product character image. An improved SMT product character recognition method is proposed which can improve the recognition rate. At first, the character image is changed into a gray image. Some appropriate image processing algorithms are used to eliminate the noise. Then, single character image is obtained after character segmentation and character normalization. Finally, a three-layer back propagation (BP) neural network module is constructed. In order to improve the convergence rate of the network and avoid oscillation and divergence, the BP algorithm with momentum item is used. As a result, the SMT product character recognition system is developed, and its implementation method and steps are introduced with practical examples. Experimental results indicate that the proposed character recognition can obtain satisfactory character-recognition rate and the recognition rate reached over by 98.6%.

Study on intelligent identification technology of solder joints defects based on LMBP neural network

Using Surface Evolver to predict solder joint three dimensional shape of chip components, selecting solder joints characteristic parameters as well the possibility of feature combination corresponding to solder joints defects as training sample of LMBP neural network and simulating excessive solder and other defects to form training samples of solder joints defects based on solder joints virtual technology. We can achieve the table of solder joints quality characteristic parameters and training samples of solder joints intelligent identification by choosing the four key factors of characterizing solder joint defects: solder joint center cross-sectional area S, solder center wetting height H, solder center contact angle 91 and 92. Characteristic information of solder joints quality as network input sample and possibility of solder joints defects as network desired output. We construct the training model of LM network to conduct network training. When error ε <0.01, we stop training and save network structure, weight and other parameters. Then neural network model of intelligent identification actual solder joints defects can be obtained. We can obtain 2-D image of actual chip solder joints by machine vision technology and achieve 3-D image of actual solder joints after solder joint 3D reconstruction. Solder joints cross-sectional shape can be obtained by display of sectional profiles. Utilizing the model of trained BP network to calculate the possibility of solder joints defects and compared with production statistic data. If the result does not beyond error range, we think the test is successful. So the network can be used defects intelligent identification of actual solder joints. Or we should choose samples again, adjust parameters of network structure and conduct new network training until success. The results show that we can see that possibility identification output of solder joints defects are close to the actual possibility. That shows it can meet basic requirements of intelligent identification precision and can use intelligent identification of actual solder joints defect. At the same, the results of intelligent identification will be as the input variable of intelligent analysis of solder joints defects.

Study on intelligent detecting technology for solder joint quality of SMT based on fuzzy diagnosis technique

The paper proposes a method that realized the solder joints assembly quality fault diagnosis. After an analysis of fuzzy fault diagnosis principle of SMT products, geometrical shape parameters which reflected PQFP solder joint quality were studied. Reasonable shape of components solder joint was built based on minimal energy principle. Then through the study of the real solder shape, the graphic token of SMT solder joint shape is abstracted by x-ray optical method. Afterwards, multiple input and output fuzzy systems were designed and developed. Based on the relation of solder joint shape and graphic parameter, combined with the solder shape theory, fuzzy System for fault diagnosis of solder joints quality in SMT is established by using MATLAB fuzzy toolbox and GUI. Finally, a case was studied to testify its correctness. Applying the fuzzy illation, the type and cause of defection is identified quickly and conveniently.

Study on board level solder joints reliability analysis of the copper stud bump flip-chip

In this paper, the investigation focuses on the copper stud bump solder joint thermal-mechanical reliability. The copper stud bump processing is simulated by FEM software Ansys/Ls-dyna, and then the relationship between the copper stud bump and processing parameters (bonding force, ultrasonic power, bonding time and bonding temperature) is studied. Based on the simulation result, the dimension of the bonded copper stud bump is obtained, and then the 3D model of chip with copper stud bump is developed. Only one-fourth model is used to reduce the computer work. The solder alloy, SnPb63/37, is modeled as rate-dependant visco-plastic material using ANAND model. According the JEDEC JESD22-A104, the temperature cycle test is simulated in order to study the distribution of equivalent stress and plastic strain for solder joints array and to located the maximum stress and strain solder joint. Based on modified Manson-Coffin model for life prediction of solder joint, the fatigue life of the key solder joint is predicted. The results show that the dangerous solder joint is located on the corner of the chip, where the max stress and strain is happened.

Research of SMT product assembly quality management system based on J2EE

SMT product assembly quality management system structure and content is designed, according to its characteristics and requirements. A developing method of SMT product assembly quality management system is proposed based on J2EE, in order to improve its reusability, portability and expansibility. An integrated architecture which consists of Struts, Spring and Ibatis is designed based on lightweight framework. Then the integrated architecture is used to develop the SMT product assembly quality management system. During the integrated architecture, Struts is used in presentation layer, Spring is used in business layer and Ibatis is used in persistence layer. The process and implementation of this management system of a function module are introduced. The analysis results have shown that the SMT product assembly quality management system based on J2EE has some advantages in reusability, portability and expansibility.

The Components Layout Optimization of Circuit Module Based on the Artificial Nerve Network

In this paper a model for temperature field analysis is established by FEM (finite element method) and computer aided thermal simulation soft with regard to such factors affecting temperature as heat generation, heat diffusion manner and direction, ratio of length and width of component, thickness of PCB and so on. And the artificial nerve network method for components layout optimization is applied to achieve a reasonable components position in a small space and a best temperature distribution. Also some reference of concrete measure and method for thermal design is hoped to do the PCB designers a favor.