Lap joint welding quality defect prediction method and system and computer readable storage medium

A technology for welding quality and lap joints is applied in the field of welding quality defect prediction of lap joints, which can solve the problems of misjudgment of welding defects and fluctuation of welding parameters, and achieve the effect of enhancing the recognition ability and deleting unbelievable data.

Pending Publication Date: 2021-01-26
PURPLE MOUNTAIN LAB
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Problems solved by technology

[0003] At present, the detection of weld quality defects is mainly based on the characteristic transformation of electrical parameters such as welding current and voltage. When the electrical parameters are relatively stable, the welding quality is considered to be better. The fluctuation is also relatively stable, which will lead to misjudgment of welding defects

Method used

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  • Lap joint welding quality defect prediction method and system and computer readable storage medium
  • Lap joint welding quality defect prediction method and system and computer readable storage medium
  • Lap joint welding quality defect prediction method and system and computer readable storage medium

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Embodiment 1

[0027]Such asfigure 1 Shown is a schematic flow diagram of a method for predicting weld offset according to the present invention.

[0028]According to a method for predicting weld migration according to the present invention, the method for improving predictive weld migration includes the following steps:

[0029]1) Training database collection module: Collect 210 arc voltage and welding current data of welding robots through the industrial gateway, and manually label the center of the welding seam offset from the center of the welding wire. When the upper board is offset, it is recorded as a=1, when the lower board is offset The time is recorded as a=2, and the unbiased condition is recorded as a=0. At the same time, the welding quality is manually labeled. When there is a welding defect, it is recorded as y=1, otherwise it is recorded as y=0, and all data and labels are used as training Library

[0030]2) Extract data valid window and characteristics: extract the collected arc voltage and...

Embodiment 2

[0056]This embodiment discloses a system for predicting welding quality defects of lap joints, and the system includes:

[0057]Training database module, the training database module contains the arc voltage and welding current data of the welding robot collected through the industrial gateway, the training data module includes label data on the situation that the center of the weld is offset from the center of the welding wire, and the label of the welding quality Data, the training data module also includes all electrical parameter data;

[0058]Data valid window and feature extraction module, the data valid window and feature extraction module extract the collected arc voltage and welding current data according to the valid window, delete the beginning and end data affected by arc start and end, adopt Greek The Erbert transform method calculates the time variation, and extracts the features of the parameters in the effective window respectively;

[0059]A weld offset model training module...

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Abstract

The invention discloses a lap joint welding quality defect prediction method and system and a computer readable storage medium. The method comprises the steps that firstly, welding electrical parameters, quality defect labels and labels, deviating from the center of a welding wire, of the center of a welding seam in the welding production process are collected as a training library; effective window extraction is carried out on the collected electrical parameter time series data, Hilbert transform is carried out on the extracted data, and feature extraction is carried out respectively on an electrical parameter real value and a complex value; whether the sample weld joint center deviates from the welding wire center or not is learnt by using a gradient boosting tree; whether the predictedweld joint center deviates from a welding wire center label or not serves as a feature, the maximum and minimum standardization and recursive feature elimination method in the packaging method is usedfor selecting the feature, and a decision tree model is used for conducting welding quality defect classification; and welding electrical parameters are collected in real time, window extraction andcorresponding feature transformation and extraction are performed, the welding electrical parameters are substituted into the welding line center offset welding wire center model for prediction, and aprediction result as a feature is substituted into the welding quality prediction model to determine whether the welding quality has defects or not.

Description

Technical field[0001]The invention relates to the technical field of quality inspection of industrial welding products, in particular to a method, system and computer readable storage medium for predicting welding quality defects of lap joints.Background technique[0002]With the rapid development of manufacturing technology, automation and intelligence in welding manufacturing have become an inevitable trend. Because welding robots have the advantages of strong versatility and work reliability, they have become the main means of modernization of welding automation technology. If there are serious welding defects in the welded joint, it may cause part of the structure to break and even cause a major accident in a harsh environment. The main problem in the quality of welded products is the defect of weld quality. Therefore, welding quality inspection is particularly important to find welding defects as early as possible, make an objective evaluation of the quality of welded joints, and...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06F17/18
CPCG06F17/18G06F18/24323G06F18/214
Inventor 陈苗苗祁学豪陈刚
Owner PURPLE MOUNTAIN LAB
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