Online monitoring method for resistance spot welding quality

A technology of resistance spot welding and dynamic resistance curve, which is applied to measuring devices, instruments, etc., to achieve the effect of improving accuracy

Active Publication Date: 2015-03-25
JILIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This patented technology allows companies to monitor their own products during manufacturing without being able to detect any incorrect connections between them due to poor performance caused by insufficiently trained methods like manual testing. It also includes techniques such as simulating the heat transfer through different materials with varying coefficients, measuring temperature fluctuation over multiple locations at once, analyzing power supply waveforms, etc., resulting in improved reliability and efficiency of these processes.

Problems solved by technology

This patented describes different ways to monitor the quality or stability of electric current spray welds during resistance spot joining (RSW). While traditional techniques like static force balance can provide reliable results with high accuracy, they require expensive equipment that may limit their effectiveness when applied outside certain conditions. There has been some progress towards developing more efficient and effective systems for measuring spot weather impact strength at various points along the joint line between two materials. These new technologies aimed toward improving the efficiency and reliability of resistive spot wires by providing real time feedback about changes caused by external environmental influences while maintaining consistently accurate measurements over multiple processing steps.

Method used

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  • Online monitoring method for resistance spot welding quality
  • Online monitoring method for resistance spot welding quality
  • Online monitoring method for resistance spot welding quality

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Embodiment

[0101] This embodiment takes SUS301-HT, 1+1mm stainless steel plate single-current pulse welding as an example, the spot welding process is: welding current 7KA, electrode pressure 9KN, welding energization time 8cyc (per cycle is 20ms).

[0102] see figure 1 As shown, it is the flow chart of data acquisition and data processing in the present invention. First start the program, and set the spot welding welding parameters according to the actual welding process specification (including: welding current I is 7KA and its power-on time t is 8cyc, electrode pressure P is 9KN) and its allowable range (the allowable upper and lower ranges are respectively 90% and 110% of the set welding parameters); in addition, set other relevant spot welding process information, such as material type SUS301-HT stainless steel, plate thickness 1+1mm, etc. After the setting is completed, Start the welding equipment for data collection.

[0103] During signal collection, the welding signal is automa...

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Abstract

The invention relates to an online monitoring method for resistance spot welding quality and belongs to the field of resistance spot welding quality monitoring techniques. At first, the welding current and inter-electrode voltage for resistance spot welding are collected in real time in the actual production process of resistance spot welding, a dynamic resistance curve is worked out, according to the welding process application principle in actual production, namely a qualified welding spot is a great probability event, a system carries out modeling sample capacity estimation according to the principle of statistics, cluster analysis is conducted on the dynamic resistance curve, and the qualification probability of a new welding spot is predicted according to the analysis result. Modeling is not needed under a specific welding process condition, an automatic modeling mode has the characteristic of universality, welding production data are directly adopted for modeling, and therefore the online monitoring method is more suitable for actual production and greatly improves online monitoring accuracy.

Description

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Claims

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Application Information

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Owner JILIN UNIV
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