Aosite, since 1993
Door and window hinges play a crucial role in the quality and safety of modern buildings. The use of high-grade stainless steel hinges is essential to ensure durability and reliability. However, the traditional production process for hinges often leads to quality issues, such as poor precision and high defect rates. To address these challenges, a new intelligent detection system has been developed to improve the accuracy and efficiency of hinge inspections.
The system is designed to detect the main components of the hinge assembly, including the total length of the workpiece, the relative position of the workpiece holes, the diameter of the workpiece, the symmetry of the workpiece hole, the flatness of the workpiece surface, and the step height between two planes of the workpiece. Machine vision and laser detection technologies are utilized for non-contact and precise inspections of these two-dimensional visible contours and shapes.
The structure of the system is versatile, capable of accommodating over 1,000 types of hinge products. It integrates machine vision, laser detection, servo control, and other technologies to adapt to the inspection of various parts. The system includes a material table mounted on a linear guide rail, driven by a servo motor connected to a ball screw to facilitate the movement and positioning of the workpiece for detection.
The workflow of the system involves feeding the workpiece into the detection area using the material table. The detection area comprises two cameras and a laser displacement sensor, responsible for detecting the outer dimensions and flatness of the workpiece. The system utilizes two cameras to accurately measure the dimensions of both sides of the T piece, while the laser displacement sensor moves horizontally to obtain objective and accurate data on the workpiece's flatness.
In terms of machine vision inspection, the system employs various techniques to ensure precise measurements. The total length of the workpiece is calculated using a combination of servo and machine vision, where camera calibration and pulse feeding enable accurate length determination. The relative position and diameter of the workpiece holes are measured by feeding the servo system with the corresponding number of pulses and utilizing image processing algorithms to extract the necessary coordinates and dimensions. The symmetry of the workpiece hole is assessed by preprocessing the image to enhance edge clarity, followed by calculations based on the jump points of pixel values.
To further enhance detection accuracy, the system incorporates the sub-pixel algorithm of bilinear interpolation, taking advantage of limited camera resolution. This algorithm effectively improves the stability and accuracy of the system, reducing the detection uncertainty to less than 0.005mm.
To simplify operation, the system classifies workpieces based on the parameters that need to be detected and assigns each type a coded barcode. By scanning the barcode, the system can identify the specific detection parameters required and extract the corresponding thresholds for result judgments. This approach ensures precise positioning of the workpiece during detection and enables automatic generation of statistical reports on inspection results.
In conclusion, the implementation of the intelligent detection system has proven effective in ensuring the accurate inspection of large-scale workpieces, despite limited machine vision resolution. The system offers interoperability, interchangeability, and adaptability for parts of different specifications. It provides efficient inspection capabilities, generates inspection results reports, and supports the integration of detection information into manufacturing systems. This system can greatly benefit various industries, particularly in the precision inspection of hinges, slide rails, and other related products.