Refrigerator Lighting Module Contact Failure Detection Dataset

The current industrial sector faces significant challenges, particularly in the reliability of refrigerator lighting modules. Contact failures often lead to flickering or complete light outages, which can disrupt operations and impact customer satisfaction. Existing solutions are limited by their inability to effectively identify and address these failures in a timely manner. This dataset aims to provide a robust foundation for developing machine learning models that can detect contact failures through image analysis. The data was collected using high-resolution cameras in controlled environments to ensure consistency. Quality control measures included multi-round annotations, consistency checks among annotators, and expert reviews to confirm accuracy. The dataset is stored in JPG format, organized by labeled folders corresponding to each type of failure scenario.