Circuit board pin defect identification method based on feature self-learning

A defect identification and circuit board technology, applied in image data processing, instrumentation, computing, etc., can solve problems such as low severity and frequency, and achieve the effect of reducing workload, reducing missed detection rate, and improving efficiency and accuracy.

Pending Publication Date: 2022-04-26
BEIJING SIFANG JIBAO AUTOMATION +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The severity of false positives is relatively low, but they are also frequent. Most of them are caused by fonts and can be eliminated manually.

Method used

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  • Circuit board pin defect identification method based on feature self-learning
  • Circuit board pin defect identification method based on feature self-learning
  • Circuit board pin defect identification method based on feature self-learning

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Embodiment Construction

[0041] The application will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solutions of the present invention more clearly, but not to limit the protection scope of the present application.

[0042] like figure 1 and 2 As shown, the circuit board pin defect recognition method based on feature self-learning of the present invention comprises the following steps:

[0043] Step 1: Obtain the AOI color image of the standard circuit board for feature self-learning corresponding to the circuit board to be tested and the corresponding configuration file, including the chip model and chip position on the circuit board;

[0044] Step 2: Establish the standard solder joint model of the chip in the AOI color image of the standard circuit board, including the solder joint position model and the standard solder feature matrix X, specifically including:

[0045] Step 2.1: Take the center of the ch...

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PUM

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Abstract

The invention discloses a circuit board pin defect identification method based on feature self-learning. The method comprises the steps that a standard circuit board AOI color image and a corresponding configuration file are acquired; establishing a welding spot position model of the standard circuit board and a standard soldering tin characteristic matrix X; acquiring a chip sub-picture of a chip in the circuit board to be tested; based on a welding spot position model, extracting a corresponding sub-welding spot picture from each chip sub-picture, calculating a soldering tin height value of each pixel point in each sub-welding spot picture, and forming a soldering tin feature matrix Y of the corresponding welding spot; and calculating a normalized geometric intersection coefficient gamma of the soldering tin characteristic matrix Y and the corresponding standard soldering tin characteristic matrix X, and judging whether the welding spots have defects one by one according to a geometric intersection coefficient threshold value. According to the method, the omission ratio can be effectively reduced, the efficiency and accuracy are improved, and the workload of manually searching defects is reduced.

Description

technical field [0001] The invention belongs to the technical field of circuit board detection, and relates to a circuit board pin defect recognition method based on feature self-learning. Background technique [0002] The circuit board can make the circuit miniaturized and visualized, and plays an important role in mass production of fixed circuits and optimizing the layout of electrical appliances. [0003] The vast majority of domestic circuit board manufacturers use manual inspection with a magnifying glass or a projector to inspect circuit board defects. Due to the high labor intensity of manual inspection, the eyes are prone to fatigue, and the missed inspection rate is high. Moreover, with the development of electronic products towards miniaturization and digitization, circuit boards are also developing towards high density and high precision, which is basically impossible to achieve by manual inspection. For higher density and precision circuit boards (0.12 ~ 0.10m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/33G06T7/73G06T7/90G06T3/00
CPCG06T7/0004G06T7/337G06T7/74G06T7/90G06T2207/20081G06T2207/20104G06T2207/30141G06T3/147
Inventor 徐延明魏娇龙张利强刘刚李维韩明蕾郭莹莹
Owner BEIJING SIFANG JIBAO AUTOMATION
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