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Position gauging of welding joints with an FMCW-based mm-wave radar system

Published online by Cambridge University Press:  18 December 2015

Jochen O. Schrattenecker*
Affiliation:
Institute for Communication Engineering and RF-Systems, Johannes Kepler University, Linz, Upper Austria A-4040, Austria. Phone: +43 732 2468 6390
Stefan Schuster
Affiliation:
Voestalpine Stahl GmbH, Upper Austria, A-4020 Linz, Austria
Christian M. Schmid
Affiliation:
DICE, Upper Austria A-4040, Austria
Werner Scheiblhofer
Affiliation:
Institute for Communication Engineering and RF-Systems, Johannes Kepler University, Linz, Upper Austria A-4040, Austria. Phone: +43 732 2468 6390
Helmut Ennsbrunner
Affiliation:
Fronius International GmbH, Upper Austria, A-4600 Wels-Thalheim, Austria
Andreas Stelzer
Affiliation:
Institute for Communication Engineering and RF-Systems, Johannes Kepler University, Linz, Upper Austria A-4040, Austria. Phone: +43 732 2468 6390
*
Corresponding author: J.O. Schrattenecker Email: [email protected]

Abstract

This paper presents a position gauging system of welding joints. While the principle measurement concept was already introduced by Schrattenecker et al. in 2014, here it is focused on different types of practically used welding materials. The sensor used is based on the frequency-modulated continuous-wave principle operating in the W-band. Position estimation (PoE) of different welding geometries is carried out with polarimetric scattering effects introduced by geometrical discontinuities. For the real-time calculation of the signal models a field simulation tool we developed is used. Aside from a variety of geometries, we introduce a geometrical optimization approach that increases the achievable accuracy of the measurement concept. The optimization and PoE of the different welding materials were examined in various simulations and the results were verified by measurements in the laboratory and in an industrial environment. Simulation and measurement were in good agreement.

Type
Industrial and Engineering Paper
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2015 

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References

REFERENCES

[1] Schrattenecker, J.O.; Schuster, S.; Scheiblhofer, W.; Reinthaler, G.; Ennsbrunner, H.; Stelzer, A.: Hardware and signal processing for a novel multi-lap-joint measurement system for automated welding applications. IEEE Trans. Instrum. Meas., 63 (12) (2014), 30963110.Google Scholar
[2] Jahn, M.; Aufinger, K.; Stelzer, A.: A 140-GHz single-chip transceiver in a SiGe technology, in 7th Europena Microwave Integrated, October 2012, 361–364.Google Scholar
[3] Fischer, A.; Tong, Z.; Hamidipour, A.; Maurer, L.; Stelzer, A.: 77-GHz multi-channel radar transceiver with antenna in package. IEEE Trans. Antennas Propag., 62 (3) (2014), 13861394.Google Scholar
[4] Ghasr, M.T.; Case, J.T.; Zoughi, R.: Novel reflectometer for millimeter-wave 3-D holographic imaging. IEEE Trans. Instrum. Meas., 63 (5) (2014), 13281336.Google Scholar
[5] Ascione, M.; Buonanno, A.; D'Urso, M.; Angrisani, L.; Schiano Lo Moriello, R.: A new measurement method based on music algorithm for through-the-wall detection of life signs. IEEE Trans. Instrum. Meas., 62 (1) (2013), 1326.Google Scholar
[6] Catarinucci, L.; Donno, D.D.; Colella, R.; Ricciato, F.; Tarricone, L.: A cost-effective SDR platform for performance characterization of RFID tags. IEEE Trans. Instrum. Meas., 61 (4) (2012), 903911.Google Scholar
[7] Feger, R.; Pfeffer, C.; Scheiblhofer, W.; Schmid, C.M.; Lang, M.J.; Stelzer, A.: A 77-GHz cooperative radar system based on multi-channel FMCW stations for local positioning applications. IEEE Trans. Microw. Theory Tech., 61 (1) (2013), 676684.CrossRefGoogle Scholar
[8] Byoung-Oh, K.; Yang-Bae, J.; Sang-Bonh, K.: Motion control of two-wheeled welding mobile robot with seam tracking sensor, in IEEE Int. Symp. Ind. Electron., June 2001, 851–856.Google Scholar
[9] Suwanratchatamanee, K.; Saegusa, R.; Matsumoto, M.; Hashimoto, S.: A simple tactile sensor system for robot manipulator and object edge shape recognition, in IEEE Ind. Electron. Soc., November 2007, 245–250.Google Scholar
[10] Li, Y.; Li, Y.F.; Wang, Q.L.; Xu, D.; Tan, M.: Measurement and defect detection of the weld bead based on online vision inspection. IEEE Trans. Instrum. Meas., 59 (7) (2010), 18411849.Google Scholar
[11] Zhang, L.; Ye, Q.; Yang, W.; Jiao, J.: Weld line detection and tracking via spatial-temporal cascaded hidden markov models and cross structured light. IEEE Trans. Instrum. Meas., 63 (4) (2014), 742753.Google Scholar
[12] Chen, H.: Application of visual servoing to an X-ray based welding inspection robot, in International Conference on Control and Automation, Budapest, Hungary, June 2005, 977–982.Google Scholar
[13] Schuster, G.; Doctor, S.; Bond, L.: A system for high-resolution, nondestructive, ultrasonic imaging of weld grains. IEEE Trans. Instrum. Meas., 53 (6) (2004), 15261532.Google Scholar
[14] Matthes, K.J.; Kohler, T.: Miniradarsensorik in der Schweißtechnik – Grundlagen und Stand der Technik (Use of Radar Sensors in Welding Technology – Basics and State-of-the-Art). Schweißen undSchneiden, 52 (10) (2000), 604609.Google Scholar
[15] Kohler, T.: Ein Beitrag zum Einsatz von Mikrowellensensoren im industriellen Umfeld am Beispiel der Schweißtechnik (A Contribution of Microwavesensors in Industrial Applications, using the Example of Welding Technology). PhD dissertation, Technische Universität Chemnitz, Chemnitz, 2003.Google Scholar
[16] Kusch, M.; Wallig, M.; Bürkner, G.: Anwendungsmöglichkeit der Radarsensorik beim Metall- Schutzgasschweißen (Speculative Applications of Radar Sensors in Gas-Shielded Metal-Arc Welding). Schweißen und Schneiden, 60 (1) (2008), 2428.Google Scholar
[17] Nakamura, M.; Yamaguchi, Y.; Yamada, H.: Real-time and full polarimetric FM-CW radar and its application to the classification of targets. IEEE Trans. Instrum. Meas., 47 (2) (1998), 572577.Google Scholar
[18] Soumekh, M.: Synthetic Aperture Radar Signal Processing with MATLAB Algorithms, Wiley, New York, 1999.Google Scholar
[19] Cumming, I.G.; Wong, F.H.: Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation, Artech House, Boston, 2005.Google Scholar
[20] Schmid, C.M.; Fischer, A.; Feger, R.; Stelzer, A.: A 77-GHz FMCW radar transceiver MMIC/waveguide integration approach, in International Microwave Symposium (IMS 2013), June 2013, 1–4.Google Scholar
[21] Fischer, A.; Tong, Z.; Hamidipour, A.; Maurer, L.; Stelzer, A.: A 77-GHz antenna in package, in Microwave Conference (EuMC 2011), October 2011, 1316–1319.Google Scholar
[22] Stove, A.G.: Linear FMCW radar techniques. IEE Proc. F, Commun. Radar Signal Process., 139 (5) (1992), 343350.Google Scholar
[23] Michaeli, A.: Equivalent edge currents for arbitrary aspects of observation. IEEE Trans. Antennas Propag., 32 (3) (1984), 252258.Google Scholar
[24] Wiesbeck, W.; Kahny, D.: Single reference, three target calibration and error correction for monostatic, polarimetric free space measurements. Proc. IEEE, 79 (10) (1991), 15511558.Google Scholar
[25] Knott, E.: RCS reduction of dihedral corners. IEEE Trans. Antennas Propag., 25 (3) (1977), 406409.CrossRefGoogle Scholar
[26] Tong, Z.; Stelzer, A.: A millimeter-wave transition from microstrip to waveguide using a differential microstrip antenna, in Microwave Conf. (EuMC), 2010 European, Paris, September 2010, 660–663.Google Scholar
[27] Kay, S.M.: Fundamentals of Statistical Signal Processing: Estimation Theory, Prentice Hall PTR, Upper Saddle River, NJ, 1993.Google Scholar