Real-Time Ultrasonic Welding Quality Monitoring Using VibroMicro
1. Project Background & Challenges
In power battery manufacturing, the quality of ultrasonic welding for electrode tabs directly impacts internal resistance, current-carrying capacity, and long-term reliability. Traditional monitoring methods face significant challenges:
Post-process Inspection: Reliance on manual checks or destructive testing after welding, preventing real-time intervention.
Indirect Parameters: Monitoring only preset parameters (time, pressure, amplitude) rather than actual welding effects.
Contact Limitations: High-frequency vibrations during welding make contact sensor installation difficult and intrusive.
Traceability Issues: Inability to create precise process data records for each weld point.
2. Solution: Non-Contact Direct Measurement System for Ultrasonic Welding Energy
This solution employs the Dynatronic VibroMicro VM-S-100 Laser Doppler Vibrometer as the core sensor to directly measure the real-time dynamic response of the welding tool (sonotrode) or workpiece during ultrasonic vibration, enabling direct quantification of welding energy and quality assessment.
Core System Configuration:
Primary Sensor: Dynatronic VibroMicro VM-S-100 Laser Doppler Vibrometer
System Integration: Industrial PC with embedded intelligent algorithm module
Communication Interface: Support for Modbus/TCP, PROFINET, EtherCAT, and other industrial Ethernet protocols
Installation: Embedded integration within welder or standalone placement at any production line location
3. System Working Principle & Monitoring Process
3.1 Direct Energy Measurement Principle
Non-contact measurement of high-frequency vibrations (typically 15kHz-40kHz) from sonotrode or workpiece surface
Precise acquisition of real-time vibration frequency and amplitude time-domain signals
Calculation of equivalent welding energy: E ∝ ∫A²(t)f(t)dt (where A is amplitude, f is frequency), directly reflecting effective energy transferred to the weld
3.2 Real-Time Monitoring Process
Position Monitoring: Real-time verification of relative positions between ultrasonic welder and welding base
Vibration Acquisition: Continuous laser measurement during welding process
Feature Extraction: Real-time analysis of time-domain (amplitude stability) and frequency-domain (spectral purity, harmonic content) characteristics
Quality Assessment: Machine learning models correlate vibration features with weld quality (e.g., peel force, contact resistance) for real-time judgment
Data Communication: Quality results, process parameters, and alarm signals transmitted to MES via PLC
4. Key Advantages of the Solution
4.1 High Integration & Compatibility
Compact design for seamless integration into existing welders or production lines
Standard industrial communication protocols for real-time data exchange with PLC/MES systems
4.2 Precision Direct Measurement
Non-contact measurement without process interference
Direct measurement of actual vibration response from tool-workpiece system, reflecting true welding state beyond drive signals
4.3 Intelligent Quality Assessment
Machine learning algorithms (Principal Component Regression-PCR, Support Vector Machine-SVM) establish nonlinear mapping between vibration features and weld quality
Big data accumulation enables continuous model optimization and improved defect recognition accuracy
Detection of potential defects difficult to identify with traditional methods (e.g., "cold weld", "over-weld" tendencies)
5. Application Value & Achievements
5.1 Quality Improvement
100% online real-time inspection with immediate rejection of defective products
Significant reduction in defects (cold welds, splashes) through precise welding energy control
5.2 Efficiency & Cost Optimization
Reduction/elimination of offline destructive testing, saving costs and time
Comprehensive process data repository for production optimization and issue tracing
5.3 Process Insights
Revelation of intrinsic relationships between process parameters (pressure, amplitude) and final welding energy for process window optimization
Predictive maintenance of sonotrode wear and equipment aging
Conclusion:
The Dynatronic VibroMicro VM-S-100 based ultrasonic welding monitoring solution elevates quality control from traditional "parameter monitoring" to "energy monitoring" level. Through direct measurement of equivalent welding energy combined with machine learning-based intelligent diagnostics, it provides powerful, reliable, and continuously evolving technical assurance for "zero-defect" production in power battery tab welding, representing an implementation of smart manufacturing in critical process.
