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