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Robot fault detection and remaining life estimation for predictive maintenance

机译:机器人故障检测和预测维护的剩余寿命估计

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In this work some possible solutions to implement a Robotics-oriented predictive maintenance approach are discussed. The data-driven methodology is described from the data collection to the design of an appropriate dataset and finally to the use of some of the most promising algorithms in the field of machine learning. The whole process is composed by several building blocks that can be combined to realize a data analysis on industrial robots. Some of the most promising techniques in Predictive Maintenance for Industrial machines were included in the proposed methodology, together with a Survival Analysis study, and then evaluated with proper performance metrics. Experimenting this methodology on a real use-case with Comau industrial robots showed the validity of the approach and opened to the inclusion of such a process in a service-oriented solution.
机译:在这方面,讨论了实现机器人的预测性维护方法的一些可能的解决方案。数据驱动方法从数据收集描述到适当的数据集的设计,并且最终在机器学习领域中使用一些最有前途的算法。整个过程由多个构建块组成,可以组合以实现工业机器人的数据分析。工业机器预测性维护中的一些最有前途的技术包括在提出的方法中,以及生存分析研究,然后用适当的性能指标进行评估。用Comau Industrial Trobots在真正用例上尝试这种方法显示了方法的有效性,并在面向服务的解决方案中纳入这种过程。

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