A method for predicting the overall performance of industrial robots based on feed-forward neural network
A feed-forward neural network and industrial robot technology, applied in neural learning methods, biological neural network models, neural architectures, etc., can solve problems such as disturbance, time-consuming and labor-intensive, and useless work.
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[0054] Step 1: Construct the structure of the industrial robot machine performance impact model:
[0055] The input of the model architecture mainly considers the performance indicators of core components (servo motors, reducers) and the environmental impact parameters during operation, and the output mainly considers the motion performance of industrial robots. The specific implementation plan is as follows: figure 2 , theoretically analyze which performance of the core components (servo motor, reducer) and which environmental factors may affect the performance of the industrial robot during operation, and summarize it into the performance impact of the industrial robot from a broad perspective In the model framework, the input parameters determined in this embodiment are servo motor performance indicators (positive and negative speed difference rate, torque fluctuation coefficient, speed fluctuation coefficient, speed, torque, continuous stall torque, continuous stall curren...
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