Temperature Regulation of Machine Tools Using Neural Network
碩士 === 長庚大學 === 機械工程研究所 === 92 === The main purpose of this paper is to study the neuro-control strategy in the temperature regulation of machine tools to reduce thermal effects on machining accuracy. The nonlinear and time-varying relationship between heat generated in the shaft motors a...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2004
|
| Online Access: | http://ndltd.ncl.edu.tw/handle/79327906724843007115 |
| Summary: | 碩士 === 長庚大學 === 機械工程研究所 === 92 === The main purpose of this paper is to study the neuro-control strategy in the temperature regulation of machine tools to reduce thermal effects on machining accuracy.
The nonlinear and time-varying relationship between heat generated in the shaft motors and cooling system renders the temperature regulation problem difficult to model and analyze.
An experimental system is built with a heater driven by PWM signals to simulate the heat source. The cooling subsystem is constructed with helix pipe driven by a 370 W pump. Temperature is collected from a thermocouple for feedback. Data sets of pump control signals, temperature of target position, and on/off signals of heat sources are collected to train two artificial neural networks of feedforward configuration using the standard back-propagation algorithm. One of the neural networks is used for determination of system order. The other neural network is used for closed-loop control, which combines the feedforward signal of the heat sources.
Experimental results show that the neuro-control approach is both effective and relatively easy to apply.
|
|---|