Industrial robots, as a structurally sophisticated mechatronics system, have a high cost of routine maintenance and repair. Repairs after fault require the corresponding manpower and material resources, and have hysteresis. If the fault can be predicted in a timely and accurate manner, the maintenance process can be carried out in advance, and the hidden dangers can be eliminated to fundamentally solve the fault problem. Based on the self-organised critical theory (SOC theory), this article draws lessons from its self-organisation evolution model and uses the self-organised criticality of industrial robot fault to establish an autoregressive moving average model (ARMA model) for industrial robots. According to the analysis of residual value and the explanation for the faults of industrial robots, find ways and means to prevent and reduce faults.

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Fault analysis of industrial robots based on self-organised critical theory

References

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