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welding inspection with laser ultrasonic techniques
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Laser Ultrasonics 2010
Laser-based ultrasonic-emission sensor
for in-process monitoring during
high-speed laser welding
B. Pouet, A. Wartelle and S. Breugnot Bossa Nova Technologies, Venice, CA 90291, USA
S. Ream Edison Welding Institute, Columbus, Ohio 43221, USA
Motivation
Fuel cells Attractive energy alternative Efficient, quiet, non-polluting Run on pure hydrogen, methanol, diesel, other hydrocarbons Applications: Commercial & Military (Electronics / residential / Car & truck Auxillary / Automotive / Heavy Vehicle / Marine / industrial .)
Biggest opportunity for fuel cell is in the automotive sector.
One generic challenge that appears in many fuel cell system designs: To join thin stainless-steel sheet for variety of components (bi-polar plates, recuperators, reformers, cassettes and other heat exchangers)
Manufacturing challenges
Motivation
A fuel cell vehicle includes ~400m long weld - 400 bi-polar plates - 1 meter of laser weld / bi-polar plate
Very high-speed welding needed to achieve high production rate and cost target
Zero tolerance for defect (lack of fusion / lack of penetration)
Post-process inspection is not possible (Slows production rate & Increases cost)
In-process inspection is needed
Manufacturing Challenges
Fuel Cell for Automotive Sector
Laser Welding
Highlights Narrow weld seam Minimum heat affected zone Little metallurgic effect on material Little distortion No filler material required Non-contact and no-wear High process speed
CO2 laser weld @ 10m/min
Nice but too wide & too slow!
Fiber Laser @ 800mm/s
Single mode CW Fiber Laser Best for welding of thin metal sheet Demonstration using a 600W Single mode CW
Ytterbium fiber lasers (l=1070nm) at 800mm/s
Laser Welding
Penetration Welding Thermal Conduction Welding
In-processing monitoring of welding quality by monitoring the AE
Laser Ultrasonic inspection
Laser Ultrasonic in-process inspection
During the welding process, the weld vicinity is subject to high level of strain leading to localized strong elastic and non-elastic behavior of the material that is associated with continuous and/or rapid release of elastic energy: Acoustic Emission (AE).
In-process Inspection limited by the repetition rate of generation laser
Welding Laser acts as the ultrasonic source Using a laser-ultrasonic sensor to follow the welding laser and to listen to the ultrasonic noise emanating from the weld
Airborne Acoustic Emission
Acoustic Emission (AE) emanates from the weld pool as the generated vapor displaces the ambient air
Detected by microphone (100kHz
Propagate in the plate
Carries information about the internal process
Well suited for In-process inspection
Ultrasonic Emission (UE)
Sensor Requirements
Direct detection of the ultrasonic surface displacement
Transverse surface motion up to 1m/s
Unprepared surface
High sensitivity (sufficient for single shot measurement)
Small footprint
Broadband detection [20kHz to 2MHz and higher]
Ability to measure very near the weld and on top of the weld molten pool.
Must be able to be integrated with the welding Laser
Detection of Ultrasonic Emission
Fiberized Random-Quadrature Multi-channel Interferometer
Undesired signals from object motion are filtered out electronically No-stabilization required: Quadrature is achieved via the random distribution of speckle phases
Multi-detector
Spe
ckle
pro
cess
ing
Signal out
Signal beam
Probe beam
Sample Optical path difference
Reference beam
Speckle pattern
Interference principle used in Quartet
Use of a detector array instead of single-element detector to sum all contributions and increase sensitivity
EQUIVALENT TO MANY SINGLE-SPECKLE INTERFEROMETERS IN PARALLEL
Absolute amplitude demodulation
Random-Quadrature Multi-Channel Interferometer
Fiberized Random-Quadrature Multi-channel Interferometer
Laser Ultrasonic Sensor
Welding system - 600W Single mode CW Ytterbium fiber laser (l=1070nm) - Focal spot size = 19mm - Shielding gas injected through coaxial nozzle - Sample is fixed - Laser beam position controlled by XYZ translation
- Thin sheet welding demonstrated at 800mm/s
Sensor integration - Mounted with laser welding head. - Sensor follows the welding laser - Constant offset during welding/measurement (distance between laser welding & detection spots) - Detection can be positioned near or on top of the weld
Laser welding prototype platform
Laser Ultrasonic Sensor- Setup
Stand-off = 10cm
Clamp
Welding Laser Optical Head
Sample to weld To Demodulator
Demodulator
High-Pass Filter - To reject the background noise - 20KHz / 200kHz / 1MHz
Signal Detection & Processing
Computer &
Acquisition Card
- Signal Processing - RMS / sliding window
Display
Multi-channel detector
To correlate with visual/destructive
inspection
SAMPLES
- Stainless steel sheets (2)
- Thickness = 100mm
- Sample length = 10cm
INDUCED DEFECTS
- To introduce a small gap between sheets:
- Small tab (100mm thin & 5mm wide)
- Small wire
- To introduce contaminant between sheets
- Paint, silicone
WELDING PARAMETERS
- Welding length: 70mm
- Welding speed for test: 100mm/s & 200mm/s *
Test Samples
* Sensor demonstrated at 3m/s.
Tab
Wire
weld
weld
Peeled sample weld
Tab
- Record a 1st pass with Welding Laser Off:
To acquire background noise
- Record a 2ndpass with Welding Laser Off & calibration signal ON:
To acquire calibration signal
- 3rd pass, record UE signal from welding
RMS
Calibration Signal @ 240kHz
RMS / 200ms sliding window
Weld length=70mm
Plate length=100mm
Measurement Procedure
Sensor
- Detector Electronic Noise (minimized by design)
- Laser Intensity Noise (rejected by differential detection scheme)
- Shot noise limited detection
Example of EM noise before shielding of acquisition card
Experiment
- Optical noise from transverse speckle motion.
No noise visible at 200mm/s
- Doppler shift due to variation in stand-off distance.
Not an issue: The welding laser beam has tighter stand-off distance requirement than the detection laser .
Noise Sources
Environment
- Electromagnetic noise from the translation stage motor (pickup from the acquisition card)
Solution: shielding of acquisition card
- Vibration noise (motor vibration.)
Rejected if frequency below the detector High-pass filter cut-off frequency.
Results No Defect -
- Sensor: [200kHz 10MHz]
- Welding speed = 100mm/s
- Offset between weld and sensor: 5mm
- Signal strength variation (reflectivity): 50%
- Background noise is low
- Ultrasonic Emission burst visible when welding start & stop
Results induced defects: Gap -
- Sensor: [200kHz 10MHz]
- Welding speed = 100mm/s
- Offset = 5mm
- Sliding window = 200ms
1cm
Results Induced defect: contaminant -
- Sensor: [200kHz 10MHz]
- Welding speed = 200mm/s
- Offset = 2mm
- Sliding window = 800ms
Induced defect: contaminant
- Welding spot: 19mm
- Detection spot =100mm
- Sensor: [1MHz 20MHz]
- Welding speed = 200mm/s
- Sliding window = 800ms
Detection on top of Keyhole
Tested Detector Bandwidth
- Low Frequency [20kHz to 2MHz] Sensitive to background & laser Intensity noises
- Medium Frequency [200kHz 10MHz] Most useful for this demonstration [200kHz-1MHz]
- High Frequency [1MHz 10MHz] Used for detection on top of weld pool
Detection near the weld:
- Closer to weld leads to stronger UE signals
- Strong UE signals clearly correlate with Lack of fusion and partial penetration defects
- Sharp UE bursts caused by random impurities on the top surface getting vaporized
Spatter ejection Recoil force
Detection on top of the Keyhole
- Location of defect corresponds to a loss in the detected signal!
- Despite the 1MHz High frequency cut-off, Strong background noise visible.
- Detection not reliable / too much disturbance
Findings summary
Conclusion
Preliminary results are very promising
For detection near the weld, using very simple signal processing we clearly detected Lack of fusion & partial penetration defects
Some weak UE signals (slightly above the background noise) were correlated with concave weld defects (further processing needed)
Detection on top of the keyhole is very noisy.
Next Step
Detection on the weld seam, behind the weld pool to be tested
Further Signal processing to improve defect detection & characterizations
Further Signal processing to reject unwanted signals (UE bursts from random impurities)
Acknowledgement: This work was supported by the National Science Foundation, DMI-0740241