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Can Automatic Laser Welding Machines Monitor the Welding Process?

szhaiwei
2025-09-20
Yes, modern automatic laser welding machines can do more than just run pre-programmed cycles—they can actively monitor the welding process in real time. This capability is increasingly important for manufacturers who need consistent quality, traceability, and minimal operator intervention.
 
Real-Time Monitoring Features
 
Many automatic laser welding machines now integrate sensors to track key aspects of the weld. Common monitoring methods include:
 
Photodiode or spectrometer sensors that detect plasma emission during welding, helping identify instability, spatter, or lack of fusion;
 
Thermal cameras or infrared sensors that measure melt pool temperature and size, providing feedback on penetration depth;
 
Seam tracking systems using laser displacement or vision technology to adjust the beam path if part fit-up varies slightly;
 
Acoustic emission sensors that listen for abnormal sounds during welding, which may indicate porosity or cracking.
 
These signals are processed by the machine’s control system, which can trigger alarms, mark defective parts, or in some cases, adjust parameters on the fly to maintain weld quality.
 
Data Logging and Traceability
 
Beyond real-time detection, automatic laser welding machines typically record process data for each weld—laser power, travel speed, focus position, and sensor readings. This data can be stored with a timestamp or part ID, supporting full traceability for industries like automotive, medical devices, or aerospace.
 
Closed-Loop vs. Open-Loop Systems
 
It’s important to distinguish between systems that only monitor (open-loop) and those that adjust parameters automatically (closed-loop). Most standard machines offer monitoring and alerts. True closed-loop control—where the system self-corrects—is available but often requires additional hardware and calibration.
 
Haiwei Laser equips its automatic laser welding machines with scalable monitoring solutions, helping users achieve reliable, data-driven production.

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