厂区工业信号灯的检测和分类（CS CV）---刘持诚

工业制造在过去的几十年里，已经从劳动密集型的人工控制机器，发展到了全自动化的过程。下一个大的飞跃被称为工业4.0，即智能制造。随着工业4.0的到来，IT 系统和工厂车间之间的集成度不断提高，从客户的订单系统到产品的最终交付，都有了更多的集成。这种集成的一个好处是可以大规模生产个性化定制产品。然而，考虑到现有工厂的使用寿命可长达30年，要在现有工厂中实现这一点已被证明是具有挑战性的。工厂中最重要的一个参数是每台机器的运行时间。操作时间会受到机器维护以及不同产品重新配置的影响。对于没有连接的老式机器，其工作状态通常由绿色、黄色和红色的信号灯来指示。因此，我们的目标是开发一种解决方案，它可以利用拍摄工厂车间的视频摄像机的输入来测量运行状态。利用自主汽车中常用的交通信号灯识别方法，提出了一种在指定条件下准确率超过99%的系统。如果有了更多的视频数据，相信人们可以用类似的方法开发出可靠性高、通用性好的系统。

原文题目：Detection and Classification of Industrial Signal Lights for Factory Floors

原文：Industrial manufacturing has developed during the last decades from a labor-intensive manual control of machines to a fully-connected automated process. The next big leap is known as industry 4.0, or smart manufacturing. With industry 4.0 comes increased integration between IT systems and the factory floor from the customer order system to final delivery of the product. One benefit of this integration is mass production of individually customized products. However, this has proven challenging to implement into existing factories, considering that their lifetime can be up to 30 years. The single most important parameter to measure in a factory is the operating hours of each machine. Operating hours can be affected by machine maintenance as well as re-configuration for different products. For older machines without connectivity, the operating state is typically indicated by signal lights of green, yellow and red colours. Accordingly, the goal is to develop a solution which can measure the operational state using the input from a video camera capturing a factory floor. Using methods commonly employed for traffic light recognition in autonomous cars, a system with an accuracy of over 99% in the specified conditions is presented. It is believed that if more diverse video data becomes available, a system with high reliability that generalizes well could be developed using a similar methodology.

原文作者：Felix Nilsson, Jens Jakobsen, Fernando Alonso-Fernandez

原文地址：https://arxiv.org/abs/2004.11187