Flat enameled electromagnetic wire surface defect detection method based on deep learning
A surface defect and deep learning technology, applied in the direction of optical test defects/defects, measuring devices, scientific instruments, etc., can solve the problems of low detection accuracy and low degree of automation, and achieve high recognition accuracy, reduce production costs, and recognition speed fast effect
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[0025] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.
[0026] Such as Figure 1-4 Shown, the flat enamelled magnetic wire surface flaw detection method based on deep learning, it comprises the following steps:
[0027] Step 1: Flat enamelled magnet wire image acquisition: use a camera and surface light source installed in a specified way to collect flat enameled magnet wire images in a dark field environment;
[0028] Step 2: flat enamelled magnet wire image preprocessing: utilize the K-means clustering method to remove the part that does not contain flat enameled magnet wire in the image;
[0029] Step 3: Flaw recognition of flat enamelled magnet wire: use label data to train convolutional neural network to recognize the defect of enameled wire, and the training model is called by the inspection sys...
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