A large number of existing photovoltaic power plants in China are gradually entering the operation and maintenance cycle. Internal defects such as hidden cracks, broken grids, virtual soldering, PID decay, and black core fragments of battery cells cannot be directly recognized by the naked eye, but they will continue to cause a decline in power generation. In severe cases, they may also trigger hot spots and fire risks. As the core means of determining internal defects in components, EL electroluminescence detection has shortcomings in traditional equipment such as poor imaging quality, cumbersome deployment, dependence on manual image reading, and the need for external power supply on site, which restrict the efficiency of outdoor large-scale detection. Shanghai LAILX has launched the LXG50 portable EL detector, which relies on high-definition infrared imaging, AI intelligent defect recognition, and lightweight wireless control to provide a new solution for component factory quality inspection, power station acceptance, and operation and maintenance inspection. Photovoltaic power station tester

The LXG50 portable EL detector is equipped with a 26 million level full frame industrial CMOS infrared chip, which has excellent infrared sensitivity and high imaging sharpness. It can capture fine cracks and identify component cracks with a width of less than 0.2 μ m. Single to multiple string components can achieve rapid imaging in 3-10 seconds, and the detection efficiency is several times higher than traditional equipment. The equipment is equipped with a professional lens with a large viewing angle, supporting full-time dark light autofocus without the need for manual distance measurement or infrared fill light intervention. Focusing imaging can be completed in inclined, backlit, and low light environments, reducing the difficulty of on-site debugging. Whether it is component incoming inspection in the factory or on-site inspection of power plants under night and low light conditions, high-quality EL images can be output, accurately presenting various internal damage details such as hidden cracks, fragments, virtual welding, hot spots, PID attenuation, etc.

The equipment is equipped with a programmable integrated detection power module, eliminating bulky external power supply equipment. The total weight of the machine's power supply is only 2kg, and it can be operated immediately after opening the box, freeing itself from the constraints of mains power and meeting the demand for all day outdoor detection endurance. Using WIFI wireless linkage control, mobile phones and tablets can remotely control cameras and programmable power supplies through dedicated apps, achieving parameter adjustment, power on/off control, real-time image feedback, and image download. Operators do not need to approach high-voltage live components, greatly improving work safety. The entire set of equipment is stored in a high-strength protective box, paired with a carbon fiber adjustable tripod. It can be transported and deployed by a single person, and equipment assembly and debugging can be completed in 5 minutes. It can be flexibly adapted to various scenarios such as mountainous areas, agricultural photovoltaic complementarity, and rooftop industrial and commercial photovoltaics, without being limited by site conditions.

Intelligence is the core highlight of LXG50, and the device is equipped with LAILX's self-developed AI defect recognition system, which can automatically identify, mark, and classify dozens of component defects without the need for staff to manually read each image, effectively reducing human errors and misjudgments. Equipped with mobile and PC software, it supports image correction, defect statistical analysis, and automatic generation of detection reports. The detection data can also be synchronously uploaded to the LAILX photovoltaic cloud platform, supporting power station modeling. EL images are bound to the position of the power station array one by one to achieve precise defect positioning, making it convenient for operation and maintenance personnel to carry out defect elimination work directly by point. The cloud platform supports massive image batch AI parsing. After the completion of large-scale project detection, the backend can quickly complete batch image processing, output complete project detection documents, and adapt to the needs of third-party detection agencies and large-scale power plant operation and maintenance units for large-scale detection business.

From the perspective of practical application scenarios, the LXG50 portable EL detector has a wide range of uses. Component manufacturers can use it to control the quality of incoming materials and factory products, screen out internal defects in advance, and reduce after-sales risks; During the completion and acceptance stage of a new power station, random inspections can be conducted to identify hidden cracks in components caused by installation and construction; In the operation and maintenance of existing power stations, the root cause of abnormal power generation is quickly identified, damaged components are replaced in a timely manner, and power generation revenue is recovered. Faced with the characteristics of distributed household photovoltaics and scattered locations, the portable body facilitates engineers to go to different locations to complete inspections, breaking the limitation of large equipment that can only be used in fixed sites.

The photovoltaic industry continues to increase its requirements for component quality control, and non-destructive, efficient, and intelligent testing equipment has become a necessity. The Shanghai LAILX LXG50 portable EL detector integrates high-definition imaging, AI intelligent recognition, and portable wireless operation, solving the industry pain points of traditional EL detection operations such as tedious and high image reading costs, helping to upgrade the quality control of the photovoltaic industry chain, and promoting the continuous progress of photovoltaic operation and maintenance towards digitalization and intelligence.

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