###### Abstract  
Degraded electrodes in a resistance spot welding system should be replaced to ensure that weld quality is maintained. Welding electrodes are subjected to different environmental and operational loading conditions during use. When they are replaced with a fixed interval, replacement may occur too early (raising maintenance costs) or too late (leading to quality issues). This motivates condition monitoring strategies for resistance spot welding electrode tips. Thus, this paper proposes a modified recurrence plot (RP) for robust condition monitoring of welding electrode tips in resistance spot welding systems. The overall procedure for the proposed condition monitoring approach consists of three steps: (1) transformation of a one-dimensional signal to a two-dimensional image, (2) unsupervised feature extraction with LeNet architecture-based convolutional neural networks, and (3) health indicator calculation. RP methods convert dynamic resistance waveforms to RPs. The original RP method provides an image with binary-colored pixels (i.e., black or white) that makes this method insensitive to the change of the waveform signal. The proposed RP method is devised to be sensitive to the change of the waveform signal, while enhancing robustness to external noise. The performance of the proposed RP method is evaluated by examining simulated aperiodic waveform signals with and without external noise. A case study is presented to examine the proposed method's ability to monitor the condition of resistance spot welding electrodes. The results show that the proposed method outperforms handcrafted, feature-based condition monitoring methods. This study can be used to accurately determine the lifetime of welding electrodes in real time during the spot welding process. s 2020 10 5860 10.3390/app10175860 24 July  
Spot weld testing methods can be divided into destructive testing and nondestructive testing [2]. Destructive testing can provide a sufficient amount of direct evidence on weld quality. However, it cannot be performed on welds in every product, since samples have to be inspected in a destructive manner. Therefore, destructive testing is only applicable for inspecting a small number of products sampled from a population of products. Nondestructive testing can be conducted by visual inspection. Visual inspection can be conducted with radiographs of the welding pool [3] and images taken from welding electrode tips [4]. The welding pool radiograph can be used to identify discontinuities that correspond to different types of defects. The wearout of welding electrode tips is evaluated by examining the changes in the relative radius of the welding electrode tip in the images. Image data provide information that is useful for monitoring the welding quality during the spot welding process [5]. However, the results from visual inspection can often be unreliable due to adversarial environmental conditions, such as surface contamination [6]. Thus, nondestructive testing by visual inspection has had limited success in industry. Another nondestructive testing method is to analyze waveforms taken from mechanical and electric signals during spot welding, e.g., ultrasonic signals [7], dynamic resistance [8], electrode displacement [9], and electrode force [10]. Among them, dynamic resistance waveforms have commonly been employed to evaluate weld quality since they are robust to external noise [11; 12]. Dynamic resistance directly represents the physical characteristics of the spot welding process. Dynamic resistance waveforms during the spot welding process are divided into three regions. First, the dynamic resistance drops rapidly when the electric current starts to flow. Second, the dynamic resistance of the welding electrode increases due to the increase in the temperature of the welding spot. Finally, the dynamic resistance of the welds decreases as the molten metal bond grows. It should be noted that waveforms contain valuable information regarding the dynamic change in a system.