Stamping frame cooperative detection system and detection method thereof

Abstract

The invention discloses a stamping frame cooperative detection system and a detection method thereof, the stamping frame cooperative detection system comprises a user management module, a product editing management module, an automatic detection module, a data statistics module and a software setting module, wherein the user management module manages responsibility account types and account number; the product management module comprises a newly-built product sub-module and a product detection function editing sub-module; the data statistics module comprises a database data watching sub-moduleand a database data modification sub-module. The software setting module comprises an NG alarm strategy sub-module and a storage position selection sub-module. The detection method comprises the following steps: S1, shooting a selected reference image; S2, setting product and detection parameters; s3, shooting an image of a to-be-detected product; s4, correcting the image; s5, detecting the image. On-line detection of continuously conveyed products is achieved through automatic image correction and automatic image detection, difference judgment is completed through regional analysis, defective products are automatically screened, and the detection quality and efficiency are effectively improved.

Description

technical field [0001] The invention relates to the field of appearance defect detection, in particular to a stamping frame cooperative detection system and a detection method thereof. Background technique [0002] Stamping products are a common metal processing product, which is a metal part obtained by stamping; in the field of integrated circuits, it is often necessary to obtain substrate frames by stamping and electroplating to form stamped and electroplated products. Various defects will appear in the process of product processing, including indentation, missing punch, dirt, foreign matter, overshoot, etc.; the existence of the above defects directly affects the quality of the product, so it is necessary to carry out real-time defect detection on the product during the production process. In order to spot check out defective products. During the stamping production process, the substrate frame is continuously conveyed forward along a straight line, and the stamping pus...

AI Technical Summary

Problems solved by technology

During the stamping production process, the substrate frame is continuously conveyed forward along a straight line, and the stamping pushes forward a distance of one frame width at a time, so that the continuous action forms a continuous substrate frame. Therefore, the defect detection of the above substrate frame needs to use On-line detection method, that is, while the product is continuously stamped, the defect detection after stamping is completed synchronously; at present, the detection method adopted by the substrate frame is mostly manual detection, and the detection method is relatively primitive, and the quality inspector uses the naked eye scanning method. This detection method requires a large number of mature quality inspectors, and it is difficult to find small defects

In addition, to achieve comprehensive and high-quality quality inspection, quality inspectors need to work for a long time and with high concentration; but in fact, manual inspection is difficult to achieve; costs, and will cause certain labor injuries, and will lead to a series of detection problems

It is difficult to realize full product inspection, because the product is continuously flowing forward on the assembly line, and its production has continuity. In the process of manual inspection, the speed and range of naked eye scanning, and the responsibility of the staff determine that the inspection is difficult to achieve. Full inspection, resulting in the risk of counterfeiting in product production, that is, unqualified and defective products will be regarded as qualified products and flow into the next production and use link

Defect record information is difficult to digitize in real time. A major shortcoming of manual inspection results is that the records cannot be digitized in real time and synchronized to the database, which brings certain difficulties to the classification, grading and statistics of defects.

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