工业机器人故障的实时检测与诊断

REAL-TIME FAULT DETECTION AND DIAGNOSIS FOR INDUSTRIAL ROBOTS

  • 摘要: 本文首先建立了直流电机驱动机器人的驱动系统的动态故障模型,它包容了电枢电阻、电感等故障.随后建立了工业机器人传感器的动态故障模型,可包容位置、速度及力传感器的阶跃型和缓变型故障.在此基础上,应用作者提出的可处理一类非线性系统参数偏差型故障的系统性算法,成功地检测并诊断出这些故障.最后进行了数值仿真验证.

     

    Abstract: A dynamic fault model for DC-motor actuators of robot is set up. The faults of the DC torque constant, the armature resistance, the armature inductance, etc., can be described by this fault model. A dynamic fault model for sensors of, industrial robot is also sct up. Based on these models the systematic algorithm for the real-time detection and diagnosis of parameter bias faults for a general class of nonlinear time-varying stochastic systems12,13,is successfully used to detect and diagnose these faults. Finally, the effectivess of the proposed method is demonstrated by computer simulation.

     

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