In recent years, photovoltaic (PV) power generation has attracted considerable attention as a new eco-friendly and renewable energy generation technology. With the recent development of semiconductor manufacturing technologies, PV power generation is gradually increasing. In this paper, we analyze the types of defects that form in PV power generation panels and propose a method for enhancing the productivity and efficiency of PV power stations by determining the defects of aging PV modules based on their temperature, power output, and panel images. The method proposed in the paper allows the replacement of individual panels that are experiencing a malfunction, thereby reducing the output loss of solar power generation plants. The aim is to develop a method that enables users to immediately check the type of failures among the six failure types that frequently occur in aging PV panels—namely, hotspot, panel breakage, connector breakage, busbar breakage, panel cell overheating, and diode failure—based on thermal images by using the failure detection system. By comparing the data acquired in the study with the thermal images of a PV power station, efficiency is increased by detecting solar module faults in deteriorated photovoltaic power plants.

Structural-adhesive-assisted DeltaSpot welding was used to improve the weldability and mechanical properties of dissimilar joints between 6061 aluminum alloy and galvannealed HSLA steel. Evaluation of the spot-weld-bonded surfaces from lap shear tests after long-term exposure to chloride and a humid atmosphere (5% NaCl, 35 °C) indicated that the long-term mechanical reliability of the dissimilar weld in a corrosive environment depends strongly on the adhesive–Al6061 alloy bond strength. Corrosive electrolyte infiltrated the epoxy-based adhesive/Al alloy interface, disrupting the chemical interactions and decreasing the adhesion via anodic undercutting of the Al alloy. Due to localized electrochemical galvanic reactions, the surrounding nugget matrix suffered accelerated anodic dissolution, resulting in an Al6061-T6 alloy plate with degraded adhesive strength and mechanical properties. KrF excimer laser irradiation of the Al alloy before adhesive bonding removed the weakly bonded native oxidic overlayers and altered the substrate topography. This afforded a low electrolyte permeability and prevented adhesive delamination, thereby enhancing the long-term stability of the chemical interactions between the adhesive and Al alloy substrate. The results demonstrate the application of excimer laser irradiation as a simple and environmentally friendly processing technology for robust adhesion and reliable bonding between 6061 aluminum alloy and galvannealed steel.

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.