Under the new industry cycle, the new energy industry has come to the fore. The demand for new energy battery products in modern society is increasing, and the quality and safety of products are also more important. At present, traditional detection methods can no longer meet the development of the new energy battery industry. More and more manufacturers have begun to apply innovative machine vision technology and products in the production process, focusing on improving the quality of batteries.
In order to help new energy manufacturers improve the quality of batteries faster and better, the AI visual inspection system innovatively developed by Shenmo Technology has established a differentiated advantage based on deep learning, and continues to empower automatic defect detection of battery appearance to achieve higher standards for enterprises. High quality and efficient production to help the large-scale development of the new energy industry.
The detection difficulty is relatively high, and the vision technology needs to be upgraded urgently
With the explosive growth of the new energy industry, related companies such as new energy batteries have accelerated production expansion. However, in recent years, new energy battery safety issues have occurred frequently, and more and more people have gradually paid attention to the quality of batteries. Relevant manufacturers have also increased their defect detection efforts to ensure the pass rate of products leaving the factory.
Detection difficulty
Lead-acid batteries: There is a lack of uniform industry standards, the boundaries of defects are blurred, and there is no clear data to determine whether it is a defective product, resulting in missed inspections and wrong inspections. At the same time, in the production process, new defects will continue to occur, involving virtual soldering, desoldering, pole group installation reversed, pole deformation, busbar bending, and a large number of tabs.
Lithium battery: The defect types of lithium batteries are complex and diverse, and the positions are random, and some subtle defects are slightly different from the background color, so it is difficult to accurately extract defect features. The defect types include poor packaging, damage, short circuit, corrosion, excessive water content in the battery core, etc. .
These defects seriously affect the quality and product stability of new energy batteries, and even cause the risk of explosion.
To sum up, relying on the traditional manual visual inspection method, there is a high risk of false detection and missed detection. The emergence of AI visual inspection system not only greatly improves the accuracy, speed and accuracy of detection, but also adapts to the use in dangerous environments. At the same time, with the complexity of the new energy battery process and the accelerated iteration of raw materials, the requirements for machine vision are gradually increasing, which also poses challenges for machine vision manufacturers to meet the market demand of the new energy battery industry and accelerate adaptation to new changes. Promote the continuous upgrading of machine vision technology.
In the entire production process of new energy batteries, although appearance defect inspection only accounts for a small part of its production, it is a key step to ensure the product qualification rate and plays a vital role in the entire production process. And with the continuous upgrading of machine vision-related technologies such as 3D vision and AI algorithms, the performance advantages of the AI vision inspection system have been further increased, fully realizing the efficient detection of new energy battery defects.
Enterprises are accelerating the layout of the new energy industry and are ready to go
With the improvement of China's industrial automation technology level and rapid economic development, the machine vision industry has ushered in new opportunities for development. Development creates great opportunity. Deep Eye Technology is well aware of the coexistence of opportunities and challenges. Over the years, through the accumulation and precipitation of relevant industry cases, it has deeply analyzed the actual needs of customers in the new energy battery industry, and continues to make efforts in this field.
In the battery defect detection project, Shenmo Technology insists on technological innovation and product iteration, and uses a one-stop AI vision solution to accurately solve the pain points of new energy battery production and ensure the detection of battery appearance defects. It has strong technical advantages, including Through the combination of deep learning technology , it can flexibly respond to the needs of different detection scenarios; through the integration of artificial intelligence classification and recognition modules , the defect detection effect can be effectively improved; through full-frame real-time dynamic video monitoring , monitoring and detection can work in parallel; through standard embedded industrial design , Standard imported hardware unit , easy to upgrade and expand at any time.
In addition to technical advantages, Deep Eye Technology has also carried out in-depth cooperation with Intel. Its focus is to realize the rapid deployment of deep learning models on the CPU platform through the Intel OpenVINO tool suite, speed up the development of solutions, and provide more efficient solutions. Excellent CPU reasoning performance, fully unleashing the potential of its AI computing power.
At present, the new AI visual inspection solution of Shenmo Technology has achieved excellent detection results. It can not only accurately identify the appearance defects of batteries, the detection accuracy exceeds 98%, but also quickly eliminate defective products, and the qualified rate of ex-factory products reaches 99%, achieving a missed detection rate of less than 0.01%.
With the further upgrading of the new energy industry, related new energy battery manufacturers have increasingly clear demands for machine vision. In the future, with the further upgrade of the AI algorithm, Deepmoon Technology will continue to enhance its ability to cope with new energy battery technology, and further develop the AI visual inspection system, with advanced technology and solutions, to achieve in more industry scenarios landing and large-scale application.
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