In recent years, with the continuous development of artificial intelligence technology, machine vision technology, as an important branch, has accelerated its penetration into the production links of my country's manufacturing industry, covering high-end and complex fields from assembly to testing, and promoting my country's progress from a manufacturing power to a manufacturing power. .
Machine vision technology has a variety of applications in the industrial production process. It can be used to identify the color and shape of objects, locate the position coordinates of objects, detect product surface information and defects, and non-contact measurement of product appearance dimensions. The downstream application requirements of machine vision are emerging in an endless stream. The emergence of innovative machine vision equipment breaks through the shackles of traditional visual inspection. Through digitalization and automation, the manufacturing process is more efficient, intelligent, flexible and sustainable. detection and measurement.
Machine vision penetrates the industrial field to promote the process of intelligent manufacturing
With the new round of scientific and technological revolution and industrial transformation advancing by leaps and bounds, the global industrial structure and layout have been deeply adjusted, and the emergence of new technologies, new processes, and new materials has further increased the difficulty of inspection of industrial products, and put forward new requirements for machine vision inspection. Significantly increased the market size of the machine vision industry.
In the wave of intelligent manufacturing, machine vision systems rely on high detection accuracy, high recognition accuracy, and through the collection and processing of data, as well as the integration of deep learning technology, to realize the self-learning ability of equipment and accelerate the penetration of multiple Each application field and industry, and achieve a wide range of applications.
Machine vision involves many fields in intelligent manufacturing. For example, in the case of defect detection in the 3C industry, some defects are small in size and exceed the limit of human vision. Combined with machine vision equipment, it can detect product appearance defects online, relying on pixel-level detection Accurate detection of small defects and automatic elimination; in the home appliance industry, the application of machine vision technology includes defect detection of sheet metal parts, error prevention and omission detection of accessories, OCR error and omission detection, vision-guided screw locking, etc., through the machine Vision technology can draw conclusions based on relevant information and output them to external actuators such as robotic arms to complete corresponding operations, thereby greatly improving the intelligence and automation of the production line.
With the continuous upgrading of machine vision technology, which is essential for the intelligentization of equipment, it can help manufacturing companies improve detection efficiency and detection accuracy, and empower companies to reduce costs and increase efficiency. At present, machine vision equipment is widely used in the fields of working condition monitoring, finished product inspection and quality control on the production line. The performance of some systems and components has caused manufacturing companies to apply machine vision technology to enhance their competitiveness.
Machine vision technology significantly and efficiently empowers intelligent production
For the increasingly competitive Chinese market, machine vision manufacturers continue to upgrade their technologies and form their own competitiveness with a sense of independent innovation. Judging from the manufacturing-related cases of machine vision applications, the downstream application requirements of machine vision have been further upgraded, and the application fields have been further expanded; while there are also huge technical barriers in the production of upstream core components. Faced with the development opportunities and "stuck neck" problems in the machine vision industry, a large number of emerging machine vision companies are moving quickly and have strong technologies, giving full play to their technical expertise.
Facing the bottleneck, Shenmo Technology has its own innovation consciousness and technology possessed by the rising star, finds out the market positioning, and deeply cultivates the industry. At present, the application of Shenmou Technology has spanned 3C electronics, new energy, home appliances, wood and other industries, enabling the production of many scenarios such as PCB board inspection, battery defect inspection, accessory error prevention and leakage inspection, and wood defect inspection.
In the case of PCB board inspection , the training and learning of a large number of sample data through deep learning technology can fully cover all kinds of defects, and can also build algorithm models as needed to quickly lock small defects and improve the recognition accuracy to more than 99.9%.
In the case of battery defect detection , combined with deep learning technology, it can flexibly apply the needs of different detection scenarios, and integrate artificial intelligence recognition modules to effectively improve the defect detection effect and achieve a missed detection rate of less than 0.01%.
In the case of error prevention and omission detection of accessories , the machine vision system integrates deep learning technology to improve the ability of independent learning and judgment, and solve the randomness of the combination. More than 99.9%.
In the case of wood defect detection , the machine vision system based on deep learning can learn a large number of image samples of various defects, build an accurate algorithm model for each type of defect, and increase the detection speed to 4m/s. The detection rate is less than 0.05%.
In the future, Deepmoon Technology will continue to focus on the field of machine vision, present innovative technologies such as industrial AI vision, deep learning, and 3D vision in an all-round way, and empower the entire industry chain of machine vision and intelligent manufacturing.