Welding Parameter Optimization Using Sensor-Based Test Seams

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Solution Overview

Problem

Current methods for determining optimal welding parameters are time-consuming, require expert intervention, and often result in suboptimal compromises, necessitating repeated adjustments with changes in workpiece geometry or welding conditions, leading to increased costs and waiting times.

Innovation Solution

Automated method involving test weldings on test pieces where welding parameters are varied along a predetermined path, with sensors measuring and analyzing the resulting welds to calculate quality parameters, determining optimal parameters for achieving optimal welding quality without expert intervention.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If expert specialists manually determine optimal welding parameters through intuition and sample effort, then welding parameters can be set for certain welding tasks, but the process is time-consuming and requires significant specialist involvement and sample effort

Engineering Contradiction:
Improvewelding parameter optimization accuracyVSAvoidtime for determining welding parameters
Core Design Contradiction:
Measurement precisionVSLoss of time

Solution Approach 1:

The system performs self-optimization of welding parameters through automated test weldings and sensor-based quality assessment. The control device automatically determines optimal parameters without requiring external expert intervention, allowing the system to serve itself in the parameter optimization process.

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The system implements a closed-loop feedback mechanism where sensors measure test welding results, the control device analyzes the quality data, and optimal parameters are automatically adjusted based on this feedback. This continuous measurement and adjustment cycle enables rapid parameter optimization without manual intervention.

Inventive Principle:
Principle #23Feedback

2Productivity

If welding parameters are determined intuitively or as compromises without systematic optimization, then welding can be performed quickly, but the welding quality is suboptimal and may require rework

Engineering Contradiction:
Improvewelding execution speedVSAvoidwelding quality
Core Design Contradiction:
ProductivityVSManufacturing precision

Solution Approach 1:

The system performs preliminary test weldings and quality assessments before actual production welding. By pre-determining optimal parameters through automated testing and analysis, the system ensures high welding quality from the start without requiring time-consuming adjustments during production.

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system systematically varies welding parameters during test weldings to identify optimal settings. By automatically adjusting parameters such as welding current, speed, and torch angle based on sensor feedback, the system finds the precise parameter combination that delivers optimal welding quality.

Inventive Principle:
Principle #35Parameter changes

3Reliability

If expert specialists are commissioned to find optimal welding parameters for each welding task, then optimal parameters can be determined, but additional costs and waiting times are incurred

Engineering Contradiction:
Improvewelding parameter qualityVSAvoidcost and complexity of parameter determination
Core Design Contradiction:
ReliabilityVSEase of manufacture

Solution Approach 1:

The system replaces the mechanical process of expert consultation and manual parameter determination with an automated electronic system. Sensors, control devices, and algorithms substitute for human specialists, automatically determining optimal parameters through test weldings and data analysis.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system creates a digital model of the welding process through sensor measurements and test weldings. This virtual representation allows the control device to simulate and optimize parameters without requiring physical expert intervention for each welding task.

Inventive Principle:
Principle #26Copying

4Device complexity

If welding parameters are not automatically optimized, then the process is simpler, but repeated adjustments are necessary when workpiece geometry or welding conditions change

Engineering Contradiction:
Improveparameter determination process complexityVSAvoidadaptability to changing welding conditions
Core Design Contradiction:
Device complexityVSAdaptability or versatility

Solution Approach 1:

The system implements dynamic parameter optimization that automatically adapts to changing welding conditions. When workpiece geometry or welding parameters change, the system performs new test weldings and automatically adjusts parameters in real-time, maintaining optimal performance across varying conditions without manual reconfiguration.

Inventive Principle:
Principle #15Dynamics

Data Source

PatentEP3768454B1Method for automatically determining optimal welding parameters for welding on a workpiece
Publication Date: 2021.10.13 FRONIUS INT GMBH
  • EP3768454B1 patent drawingFigure 1
  • EP3768454B1 patent drawingFigure 2
  • EP3768454B1 patent drawingFigure 3

AI summary

The invention relates to a method for automatically determining optimum welding parameters (Pi,optfor carrying out a weld on a workpiece (4), wherein - a plurality of test welds are carried out on test workpieces (9) along test welding tracks (10), and at each test weld at least one welding parameter (Pi(x)) is changed automatically along the test welding track (10) from a predefined initial value (PI,A) to a predefined final value (Pi,E), - each resulting test weld seam (11) is measured along the test welding track (10) with at least one sensor (12), and at least one sensor signal (Sj(Pi(x)) is received, - at least one quality parameter (Qk (Sj (Pi(x)))) which characterizes each test weld seam (11) is calculated from at least one sensor signal (Sj(Pi(x))), - a quality function (G(Qk (Sj (Pi(x))))) for characterizing the quality of the test weld seams (11) in accordance with the changed weld parameters (Pi(x)) is calculated from the at least one quality parameter (Qk (Sj (Pi(x)))), - an optimum of the quality function (Gopt (Qk (Sj (Pi(x)))) is ascertained, and the values for the optimum welding parameters (Pi,opt) are defined on the basis of each quality parameter (Qk,opt (Sj (Pi(x))) at this optimum of the quality function (Gopt (Qk (Sj (Pi(x)))) and the corresponding locations (x,opt) on the test weld tracks (10) and saved.