System Architecture Design
Data Acquisition Layer
Deploy high-precision non-contact sensors
Configure intelligent data acquisition modules
Achieve standardized data processing
Analysis and Early Warning Layer
Establish a liquid level change trend model
Set multi-level early warning thresholds
Achieve intelligent fault diagnosis
Decision Support Layer
Provide maintenance suggestions
Optimize operating parameters
Generate operation and maintenance reports
Key Technologies
Digital Twin: Establish a digital model of the tank system
Machine Learning: Train an early warning model based on historical data
Edge Computing: Achieve preliminary data processing at the device end
Implementation Results
Equipment failure rate reduced by 50%
Maintenance costs reduced by 30%
System availability increased to 99.5%
