Multi-level intelligent control

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Multi-level Intelligent Control

Release time：2024-03-12 16:52:14

Optimize the control process through the temperature control model based on reinforcement learning algorithm, effectively suppressing the temperature oscillation caused by system response lag. Built-in self-optimization algorithm, with the operation of the equipment to continuously amend the control parameters, further reduce the system control deviation, to achieve optimal energy efficiency.

Multi-dimensional intelligence perception
By collecting information such as power consumption of cabinet equipment, coolant temperature, ambient temperature and humidity, liquid and water flow rate, current time, etc., and based on the integrated operation of the intelligent reliability model, it provides equipment failure prediction, and mentions to find out the operational problems and the sensor readings deviation.