Battery clamp visual inspection system based on virtual instrument technology

　　Machine vision is a science and technology that simulates human visual function. It uses one or more cameras connected to computers to capture images, then converts them into digital signals for storage, and then uses software to process these digital images to obtain the necessary information to make correct judgments and conclusions. Because machine vision systems can accelerate the acquisition of large amounts of information, are easy to process automatically, and are easy to integrate with processing control information, machine vision technology is widely used in industry, agriculture, communications, transportation, biology and other fields.

　　In the mass production of battery clamps, product size detection is a crucial link to ensure product quality. However, traditional detection methods (such as calipers, gauges, three-axis measuring machines, etc.) have low measurement efficiency, high cost, and scattered measurement information. It is difficult to balance the detection speed and accuracy. The contradiction is obvious and cannot meet the requirements of modern electromechanical enterprises to improve productivity and realize informatization. In the mass production of battery clamps, in order to realize production informatization and improve productivity, it is urgent to develop a cost-effective industrial machine vision system to accurately and quickly measure the battery clamps online, and realize automatic recording and statistics of detection data, as well as flexible monitoring functions.

Figure 1 System Structure