Smart Cooling Tower
Digital twin at the core, energy consumption reduced by 20%-50%, opening a new era of intelligent O&M for cooling towers
Digital Twin at the Core, Energy Consumption Reduced by 20%-50%
With the digital twin as its core technological foundation, the LANXUN smart cooling tower integrates eight intelligent systems — AI prediction, self-sensing, self-diagnosis, self-adaptation, self-optimization, self-learning, and remote O&M — achieving digital and intelligent management of the cooling tower throughout its lifecycle. Data-driven performance optimization can reduce system energy consumption by 20%-50%, significantly improving operating efficiency and equipment life.
Digital twin intelligent monitoring dashboard: 3D configuration view of the cooling tower cluster + real-time operating data
Digital Twin Technology Architecture
A four-layer architecture powering the digital twin smart cooling tower
Definition of Digital Twin
A digital twin is a cutting-edge technology that uses digital models to perform real-time mapping, simulation analysis, and optimization control of physical entities. LANXUN applies the digital twin to the full lifecycle management of cooling towers, achieving precise digital reproduction of equipment operating status.
Real-time Data Acquisition Layer
Multi-dimensional sensors for temperature, humidity, pressure, flow, vibration, and noise are deployed; combined with 5G/edge computing gateways, they enable millisecond-level data acquisition and real-time upload, building a comprehensive digital profile of equipment operation.
Four Key Processes
(1) Online thermal performance calculation: real-time monitoring of heat exchange efficiency and dynamic optimization of fan speed and water flow ratio; (2) Structural mechanics simulation: evaluating the impact of wind and seismic loads on the tower structure; (3) Fluid dynamics optimization: CFD simulation to optimize airflow organization; (4) Energy and carbon tracking: quantifying the energy consumption and carbon emissions per cubic meter of cooling water.
Performance Prediction & Optimization
Based on historical operating data and machine learning algorithms, it predicts the cooling load trend for the next 24-72 hours and automatically adjusts operating parameters, reducing energy consumption by 20%-50% and significantly improving overall system energy efficiency.
Eight Intelligent Systems
A full-dimensional intelligent capability matrix that creates the smart brain of the cooling tower
Digital Twin
A real-time digital mirror of the physical entity, visualizing operating status in all dimensions
AI Prediction
Machine learning-based load forecasting and energy optimization
Self-sensing
Multi-dimensional sensor fusion, autonomously sensing environmental and equipment status
Self-diagnosis
Automatic identification of abnormal conditions, fault prediction, and root-cause analysis
Self-adaptation
Automatically adjusting operating parameters based on changes in environment and load
Self-optimization
Multi-objective optimization algorithms balancing energy efficiency and equipment life
Self-learning
Continuously learning operating patterns and optimizing control strategies
Remote O&M
Cloud monitoring and remote operation, reducing O&M labor costs
Related Products & Technologies
Four core technologies support the efficient operation of the smart cooling tower
Application Cases
Smart cooling towers have been deployed and operating in multiple benchmark projects across China
Technology Advantage Data
Let the data speak — the outstanding performance of the smart cooling tower
Explore the Infinite Possibilities of Smart Cooling
Contact the LANXUN technical team for a customized smart cooling tower solution