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Fault Detection and Isolation for Robot Manipulator Using Statistics

机译:机器人机械手使用统计故障检测与隔离

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Robotic systems are widely used in the manufacturing industries to improve high quality products. When a fault occurs in manipulator, the faulty robot operates in abnormal condition, which causes insecurity for devices and human. In general, the dynamic of residual vector consists of fault information. In order to evaluate the residual vector, data-driven technique based on statistical theory is used. This paper presents a method by using the combination between the residual vector and data-driven solution for detecting and isolating actuator, sensor faults in robot manipulator. To achieve the accurate and reliable detection and isolation of sensor and actuator faults, the threshold is proposed to combine with generalized momenta. Simulation results are realized to show the performance of proposed method.
机译:机器人系统广泛用于制造业,以提高高品质的产品。当机器人发生故障时,故障机器人在异常情况下运行,这导致设备和人类的不安全感。通常,残差矢量的动态包括故障信息。为了评估残余载体,使用基于统计理论的数据驱动技术。本文通过使用残余矢量和数据驱动解决方案之间的组合来提供一种方法,用于检测和隔离执行器,机器人操纵器中的传感器故障。为了实现对传感器和执行器故障的准确可靠的检测和隔离,提出了与广义瞬间相结合的阈值。实现仿真结果以显示提出方法的性能。

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