Fast Inspection Image Identification Method for Digital Electromechanical Equipment Based on K-means Algorithm

The research of image recognition method based on K-means algorithm for digital motor equipment rapid inspection has important background and research significance. It represents a major advance in the field of device inspection. The core idea of this method is to detect and recognize equipment state automatically through image clustering and model training, so as to reduce the dependence on manual inspection and reduce the error rate. Firstly, K-means algorithm is used to cluster the images to be detected and divide them into different categories. Then, model training for each category is carried out to realize the classification and recognition of each category. In this way, it can automatically analyze and identify the inspection images of the equipment, quickly and accurately judge the status of the equipment, and reduce the interference of human factors. Experimental results show that this method is efficient and accurate. The recognition time of each image is no more than 21 seconds, the accuracy is higher than 95%, the response time is less than 13 seconds, and the output time is less than 17 seconds. This is a significant improvement over traditional inspection methods. In summary, the image recognition method of digital motor equipment rapid inspection based on K-means algorithm has important application prospect and research significance in the field of equipment inspection. It improves inspection efficiency, accuracy and cost effectiveness, and is expected to promote further improvement and optimization of equipment inspection work..