Automatic Fault Diagnosis Method for Digital Picture Book Image Sensors Based Data Mining
As an important detection tool in multiple industries,image sensors are usually used for image signal acquisition and information acquisition.However,in harsh working environments,sensors often experience issues such as decreased accuracy.There-fore,in order to improve the fault detection accuracy of image sensors,this study introduces data mining technology into traditional fault detection and recognition algorithms and fault diagnosis algorithms for algorithm improvement.The research results show that the improved detection and recognition algorithm has an accuracy 11.1％higher than traditional algorithms and a faster computational speed;The improved fault diagnosis algorithm significantly improves the accuracy of fault diagnosis and has a relatively high recall rate;The algorithm model also has higher fault recognition accuracy when the signal-to-noise ratio is the same,and the training time for fault recognition is shorter.Therefore,the improved algorithm has significantly improved performance and is of great significance in the fault diagnosis of digital picture book image sensors.
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