Temperature and humidity control system of painting air conditioner based on big data deep learning

Abstract

The invention discloses a temperature and humidity control system for painting air conditioners based on deep learning of big data. The external temperature and humidity sensor; the big data training platform is connected to the temperature and humidity sensor through communication equipment, and is connected to the air-conditioning controller. The air-conditioning controller is connected to the air-conditioning system and has a built-in temperature and humidity control model for The collected real-time temperature and humidity data is input into the temperature and humidity control model, and a control command including the optimized control set value is output to the air-conditioning controller, and the air-conditioning controller responds to the control command to the air-conditioning system actuator. Make adjustments. The invention can quickly shorten the time for the air conditioner to reach a stable state, greatly improve the control precision, and can effectively reduce the operating energy consumption of the air conditioner system.

Description

technical field [0001] The invention relates to the technical field of temperature and humidity control for painting air conditioners, in particular to a temperature and humidity control system for painting air conditioners based on big data deep learning. Background technique [0002] The paint spraying system in the painting workshop has relatively strict requirements for temperature and humidity. The traditional temperature and humidity control is mainly based on the PID adjustment control method. , the control effect is extremely dependent on the experience of the commissioning personnel, and the control switching of the system during the seasonal change is relatively cumbersome and may easily cause excessive system fluctuations and affect the painting quality. Traditionally applied control methods usually have a long commissioning cycle, and it takes a long time to debug and adapt to different seasons, and the stability time in the control system requires a long time. A...

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Problems solved by technology

[0002] The paint spraying system in the painting workshop has relatively strict requirements for temperature and humidity. The traditional temperature and humidity control is mainly based on the PID adjustment control method. , the control effect is extremely dependent on the experience of the commissioning personnel, and the control switching of the system during seasonal changes is relatively cumbersome and may easily cause excessive system fluctuations and affect the painting quality

Traditionally applied control methods usually have a long debugging cycle, and it takes a long time to debug and adapt to different seasons, and the stability time in the control system requires a long time. As a large energy consumer in the painting workshop, the air conditioning system is very important for gas, The consumption of cold water, hot water, etc. is relatively huge, the debugging and stabilization time is relatively long, and the energy consumption and waste are relatively large

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