AI自监督补偿绳微缺陷检测方法
本发明涉及高速铁路基础设施智能运维技术领域,公开了一种AI自监督补偿绳微缺陷检测方法。该方法构建孪生神经网络,采用对比学习策略对无标签图像进行自监督预训练,使其学习补偿绳的正常外观特征。检测时,通过将待检测图像的特征图与预存的正常样本平均特征图进行比较,计算异常得分图来定位微缺陷。本发明无需像素级缺陷标注,降低了数据成本,并提升了对未知、微小缺陷的检测灵敏度。
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