Abstract
The electrode state is an important factor affecting the welding quality in the process of resistance spot welding, but there is still lack of an effective method to monitor the electrode wear state. In this paper, a novel online monitoring method of electrode wear state is proposed by exploring the variation pattern of dynamic resistance. The evaluation method of time series similarity is important for dynamic resistance data processing, and two types of evaluation methods including static evaluation method and dynamic evaluation method are proposed in this paper. The static evaluation methods include shape change factor, dynamic resistance decrease ratio and peak time delay, and the dynamic evaluation method refers to the trend change factor. The welding process parameters and the welding material are kept unchanged during the experiment, the newly polished electrode is used to weld 1300 times continuously, and dynamic resistance is collected. According to the results of data processing, the change of the electrode state can be divided into three stages: The electrode state is stable when the welding number is less than 360. When the welding number is in the range of 360–800, the electrode state is in the transition stage, and the electrode state rapidly deteriorates with the increase of the welding number. When the welding number is more than 800, the electrode state is completely deteriorated, and the electrode needs to be dressed. This study may pave the way for online monitoring of electrode wear state.













Similar content being viewed by others
References
Babu, S. S., Santella, M. L., & Peterson, W. (2004). Modeling resistance spot welding electrode life. Oak Ridge: Oak Ridge National Laboratory.
Dickinson, D. W., Franklin, J. E., & Stanya, A. (1980). Characterization of spot welding behavior by dynamic electrical parameter monitoring. Welding Journal, 59(6), 170.
Fan, Q., Xu, G., & Gu, X. (2016). Expulsion characterization of stainless steel resistance spot welding based on dynamic resistance signal. Journal of Materials Processing Technology, 236, 235–240.
Fukumoto, S., Lum, I., Biro, E., Boomer, D. R., & Zhou, Y. (2003). Effects of electrode degradation on electrode life in resistance spot welding of aluminum alloy 5182. Welding Journal, 82(11), 307–312.
Gürbüz, F., Eski, I., & Denizhan, B. (2017). Prediction of damage parameters of a 3PL company via data mining and neural networks. Journal of Intelligent Manufacturing, 30(3), 1437–1499.
He, K., & Li, X. (2016). A quantitative estimation technique for welding quality using local mean decomposition and support vector machine. Journal of Intelligent Manufacturing, 27(3), 525–533.
Kondo, M., Konishi, T., Nomura, K., & Kokawa, H. (2013). Degradation mechanism of electrode tip during alternate resistance spot welding of zinc-coated galvannealed and uncoated steel sheets. Welding International, 27(10), 770–778
Li, W. (2005). Modeling and on-line estimation of electrode wear in resistance spot welding. Journal of Manufacturing Science and Engineering, 127(4), 709–717.
Masatsune, K., Tokujiro, K., Koji, N., & Hiroyuki, K. (2013). Degradation mechanism of electrode tip during alternate resistance spot welding of zinccoated galvannealed and uncoated steel sheets. Welding International, 27(10), 770–778.
Muhammad, N., Manurung, Y. H., Jaafar, R., Abas, S. K., Tham, G., & Haruman, E. (2013). Model development for quality features of resistance spot welding using multi-objective Taguchi method and response surface methodology. Journal of Intelligent Manufacturing, 24(6), 1175–1183.
Pashazadeh, H., Gheisari, Y., & Hamedi, M. (2016). Statistical modeling and optimization of resistance spot welding process parameters using neural networks and multi-objective genetic algorithm. Journal of Intelligent Manufacturing, 27(3), 549–559.
Peterson W., Pakalnins E., & Carpenter J. A. (2003) Long life electrodes for resistance spot welding of aluminium sheet alloys and coated high strength steel sheet. Department of Energy Vehicle Technology Office FY Progress Report-lightweight materia l R&D, 196–208.
Rokach, L., & Maimon, O. (2006). Data mining for improving the quality of manufacturing: a feature set decomposition approach. Journal of Intelligent Manufacturing, 17(3), 285–299.
Tanaka, Y., Sakaguchi, M., & Shirasawa, H. (1987). Electrode life in resistance spot welding of zinc plated steel sheets. International Journal of Materials and Product Technology, 2(1), 64–74.
Wan, X., Wang, Y., Zhao, D., & Huang, Y. (2017). Weld quality monitoring research in small scale resistance spot welding by dynamic resistance and neural network. Measurement, 99, 120–127.
Wang, B., Hua, L., Wang, X., Song, Y., & Liu, Y. (2016). Effects of electrode tip morphology on resistance spot welding quality of dp590 dual-phase steel. The International Journal of Advanced Manufacturing Technology, 83(9-12), 1917–1926.
Xia, Y. J., Su, Z. W., & Li, Y. B. (2019). Online quantitative evaluation of expulsion in resistance spot welding. Journal of Manufacturing Processes, 46(46), 34–43.
Yang, J., Zhang, D. D., & Frangi, A. F. (2004a). Two-dimensional PCA: A new approach to appearance-based face representation and recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(1), 131–137.
Yang, L. J., Zhang, B. H., & Ye, X. Z. (2004b). Fast Fourier transform and its applications. Guangdian Gongcheng/Opto-Electronic Engineering, 31, 303–350.
Zhang, X. Q., Chen, G. L., & Zhang, Y. S. (2008a). On-line evaluation of electrode wear by servo gun in resistance spot welding. International Journal of Advanced Manufacturing Technology, 36(7–8), 681–688.
Zhang, X. Q., Chen, G. L., & Zhang, Y. S. (2008b). Characteristics of electrode wear in resistance spot welding dual-phase steels. Materials and Design, 29(1), 279–283.
Zhang, W. J., Cross, I., Feldman, P., Rama, S., & Norman, S. (2016). Electrode life of aluminium resistance spot welding in automotive applications: a survey. Science and Technology of Welding and Joining, 22(1), 1–19.
Zhang, Y. S., Wang, H., Chen, G. L., & Zhang, X. Q. (2007). Monitoring and intelligent control of electrode wear based on a measured electrode displacement curve in resistance spot welding. Measurement Science & Technology, 18(3), 867–876.
Zhao, D., Ivanov, M., Wang, Y., & Du, W. (2020). Welding quality evaluation of resistance spot welding based on a hybrid approach. Journal of Intelligent Manufacturing, 1–14.
Zhou, L., Zheng, W., Li, T., Zhang, T., & Zhang, Z. (2020). A material stack-up combination identification method for resistance spot welding based on dynamic resistance. Journal of Manufacturing Processes, 56, 796–805.
Author information
Authors and Affiliations
Corresponding authors
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Zhou, L., Li, T., Zheng, W. et al. Online monitoring of resistance spot welding electrode wear state based on dynamic resistance. J Intell Manuf 33, 91–101 (2022). https://doi.org/10.1007/s10845-020-01650-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10845-020-01650-6