自动巡检机器人故障检测系统

A Fault Detection System Based on Automatic Inspection Robot

目前,智能巡检机器人已广泛应用于工业生产的诸多领域,但针对特殊极端场景的特种巡检机器人的研发尚未成熟,且传统机器人故障检测存在瓶颈,因此为极地科考设计发电机故障智能检测系统。该系统采用自组织与远程控制互协同的控制策略以应对极地区域网络状况差、通信费用高的问题,并提出基于孪生网络的小样本故障识别算法,旨在解决故障检测中样例较少与正负样本不均衡的问题。通过系统仿真实验,验证了该系统性能的优越性。

At present,intelligent inspection robots have been widely used in many fields of industrial production,the development of special inspection robots for special extreme scenarios is not yet mature,and there are bottlenecks in traditional robot fault detection,this paper aims to design a generator fault detection system for polar scientific research.The designed system firstly adopts the control strategy of self-organization and remote control to cope with the problems of poor network conditions and high communication cost in polar regions;secondly,the designed system proposes a small-sample fault identification algorithm based on siamese network,aiming to solve the problems of small sample size and unbalanced positive and negative samples in fault detection.The superiority of the performance of the proposed system can be verified through extensive system simulations.