Inspect every weld —
more precisely than the human eye
LINE WELD fuses weld imagery with process signals (current, voltage, power) to classify porosity, undercut, spatter and cracks in real time. Every verdict, coordinate and severity grade is recorded against the cell/part ID — inspection becomes quality data.
Synchronized image + signal
Bead imagery and current/power waveforms aligned to the weld trigger
Image × signal fusion
Surface defects and internal-quality signatures judged together
Classify & locate
Defect type + pixel coordinates + bead geometry
Verdict & traceability
Per-ID verdicts and evidence images pushed to MES
Image alone misses things. Signal alone misses things.
A clean surface can hide internal porosity; a normal waveform can coexist with spatter. LINE WELD fuses both sources in a single verdict, lifting detection rate and confidence together.
Synchronized capture
Bead images and current/voltage/power waveforms collected per weld, aligned to the trigger signal
Fusion analysis
A verdict model combining image features (shape, surface) with signal features (energy, stability)
Classify & measure
Porosity/undercut/spatter/crack classification, pixel-level localization, bead width/height measurement
History & interlock
Per-weld verdict with evidence image stored; NG triggers PLC interlock and MES quality records
* Evidence images are stored with every verdict — ready-made material for customer quality audits and claim responses.
Image × signal verdicts
Bead appearance and weld-energy patterns are judged together. Images catch surface defects; signals reveal signatures of internal quality issues like lack of fusion.
Quantified bead geometry
Beyond pass/fail: bead width, height and continuity are measured numerically. Drifting geometry warns the process before defects appear.
Normal-learning + few labels
Anomaly detection trained on normal welds, topped with a type classifier built from the few defect samples you have — minimal data burden.
No robot or fixture rework
Existing robots and fixtures stay untouched; only cameras and signal taps are added. Zero impact on cycle time.
Use Case Analysis
Laser, arc or spot — the fusion-inspection principle stays the same.
Zero escaped defects for six months
Busbar laser welds were 100% visually inspected, yet micro-porosity and undercut escaped to downstream 2–3 times a month — a direct fire/recall risk for batteries.
Coaxial camera imagery fused with laser-power signals; every weld verdict mapped to the cell ID for full traceability.
Zero escapes in six months. Inspectors moved to verdict auditing and process improvement; weld history became audit-ready evidence.
From sampling to 100% of thousands of spots
Thousands of spot welds per body were managed only by destructive sampling, leaving quality gaps between lots.
Normal-pattern learning on weld current/resistance waveforms enabled per-spot real-time verdicts with instant location flags.
Full-population monitoring reduced destructive testing, and electrode-wear quality drift is now managed proactively.
Reliable verdicts in fume and arc glare
Thick-plate arc welding defeated conventional vision systems due to fume and intense arc light.
Process-specific optics and filtering, with arc signals as a supporting verdict axis in a fusion configuration.
Verdict reliability held under fume/glare, and welder-to-welder quality variation became visible in data.
* Figures and scenarios reflect representative deployments and may vary by process and data conditions.
Specs & Integration
Frequently Asked Questions
Can it detect internal porosity?
Do we need to modify robots or fixtures?
Can verdicts follow our weld specification?
We only have a handful of defect samples.
See the detection rate on your own weld specification
Tell us about your process and data environment — we will come back with a feasibility summary and expected impact.