As a kind of sealing material with good performance, the sealing ring is widely used in the industrial field. It can be seen in many industries such as automobiles, ships, pipelines, and household appliances. The vast market demand promotes the development of the sealing ring industry. Flourish.
Sealing rings are mass-produced, and defective products will inevitably appear during the production process, so the quality of the sealing rings needs to be tested. However, machine vision technology is suitable for the measurement, detection and identification of large quantities and single detection content. Therefore, many seal ring manufacturers have introduced machine vision technology to achieve efficient defect detection of seal rings.
The detection of defects with complex product shapes is facing challenges
Sealing ring is a key mechanical equipment component in industrial production. In order to achieve a complete fit between the sealing ring and the sealing part, its surface needs to be smooth, and flaws such as cracks and dark lines are strictly prohibited. However, the shape of sealing ring products is complex, with various shapes, styles, sizes, and materials, and the types of defects are also very diverse, including cracks, trachoma, peeling, flash, deformation, air bubbles, etc., which seriously affect the sealing performance of the sealing ring.
Sealing ring defect detection based on machine vision technology is to use machine vision detection software to process and analyze the internal and external steps and side wall images of the sealing ring collected by industrial cameras, generate specific report information according to the analysis results, and use the results to control production and waiting Measure the motion of an object.
However, the shape and color of the same type of defect in the sealing ring are different, and there are also situations such as small defect imaging is not obvious, which makes it difficult to accurately determine the traditional machine vision, and the detection of sealing ring defects is facing challenges. Therefore, more and more seal ring manufacturers are integrating deep learning algorithms into traditional machine vision technology to achieve higher precision and higher efficiency seal ring defect detection.
Insist on R&D investment to enable defect detection
Nowadays, domestic machine vision companies continue to increase investment in research and development of deep learning algorithms, and build machine vision-related ecology to achieve continuous iteration and development of related technologies. However, the ecological cycle of deep learning technology is long and the cost is high. At present, only a few companies have realized the integration of "traditional machine vision + deep learning" technology, and Shenmo Technology is one of them.
Since its establishment, Shenmo Technology has been deeply involved in the field of machine vision, and has continuously carried out a differentiated development strategy based on deep learning. Through traditional machine vision and deep learning technology, it has built 2000+ AI industry models and thousands of image algorithm processing models. The technology system focuses on industrial scenarios, innovatively develops application products such as light track vision engine, industrial vision labeling platform, and industrial AI vision system, providing one-stop AI vision solutions for the field of industrial manufacturing.
In the case of sealing ring defect detection, in order to solve the problems of complex types of sealing ring defects, Shenmo Technology uses AI visual inspection technology with deep learning as the core to tap the needs of non-standard environments, so as to provide more reliable solutions for many sealing ring manufacturers. The software and hardware integration solution.
Deep Eye Technology uses deep learning + traditional machine vision technology to detect defects in sealing rings. Based on the neural network, it learns the detailed information of various defects by training the neural network, and establishes a deep learning model that includes defect characteristics. In addition, the deep learning technology can quickly and accurately identify the defect type of the sealing ring from the complex background, and stably detect the small cracks and peeling that are not obvious in the image, so as to realize the rapid identification and detection of defects.
The machine vision system equipped with deep learning technology can also realize the full inspection of the internal and external steps of the sealing ring and the side wall. The detection speed exceeds 10 pieces per second, and the detection accuracy is less than 0.2mm. More stable and accurate detection.
With the acceleration of the transformation and upgrading of my country's industrial manufacturing industry, many manufacturing companies are facing many challenges such as diversified needs, complex manufacturing processes, improved quality and efficiency requirements, increased labor costs, and intensified market competition. The emergence of machine vision innovative technologies and products , making all walks of life have a brighter future.
Deep Eye Technology will also continue to explore "traditional machine vision + deep learning" technology, adhere to innovation-driven, and empower manufacturing companies to accelerate digital transformation and upgrading.