Resistance spot welding quality prediction method based on ensemble learning

Abstract

The invention belongs to the technical field of electric welding quality control, and particularly relates to a resistance spot welding quality prediction method based on ensemble learning, which comprises the following steps: collecting welding process data of a welding spot sample according to process parameters measured by a sensor in a welding process; constructing a database; preprocessing the input data set through features; establishing an ensemble learning model for solder joint governance prediction, wherein each classifier outputs a quality prediction result of a to-be-detected sample; and according to output results of different classifiers and a voting mode, integrating results of the different classifiers for predicting the quality of the welding spot sample to be tested, andtaking most of judgment results as final prediction output. According to the method, the problems of high loss and low efficiency in the traditional welding spot quality detection process can be effectively solved, the welding spot quality can be quickly and accurately identified and predicted based on the welding process parameters, the welding spot quality analysis efficiency of electronic components is greatly improved, and the production cost is saved. The method is used for predicting the resistance spot welding quality.

Description

technical field [0001] The invention belongs to the technical field of electric welding quality control, and in particular relates to a resistance spot welding quality prediction method based on integrated learning. Background technique [0002] With the development of the industrial field, various electronic devices have become a necessity in people's daily life. In the production of electronic equipment, a large number of resistance spot welding of components is required. The quality of welding directly affects the quality, performance and cost of products. Therefore, the inspection of solder joint quality has become an unavoidable problem for major manufacturers. The spot welding process itself is a highly nonlinear, multivariable coupling process accompanied by a large number of random uncertain factors. It is affected by factors such as current, voltage, resistance, and pressure (all of which change with time), resulting in spot welding quality. Unstable and difficult ...

AI Technical Summary

Problems solved by technology

[0003] Aiming at the time-consuming and labor-intensive technical problems of the above-mentioned traditional solder joint quality detection method, the present invention provides a resistance spot welding quality prediction method based on integrated learning with strong stability, high efficiency and low cost

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