Water Hammer Prevention via Real-Time Sensor Analysis
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Solution Overview
Problem
Current water-hammering prevention systems face challenges in accurately analyzing operating data in real-time, leading to inefficient equipment operation and increased risk of accidents due to insufficient design factors and reliance on previous experimental data, which results in suboptimal performance and potential safety hazards.
Innovation Solution
A water-hammering prevention system based on an operating state analysis algorithm that uses real-time data from pressure and water level sensors to determine the normal operation of equipment, storing data in a database and computing it to prevent water-hammering through controlled air compressor and air discharger operations, enabling active management and diagnosis of malfunctions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time data analysis algorithm is implemented, then water-hammering prevention accuracy is improved, but device complexity increases
Solution Approach 1:
The patent replaces complex mechanical water-hammering prevention systems with an intelligent algorithm-based system. The operating state analysis algorithm processes sensor data (pressure, flow rate, valve position) computationally to predict and prevent water-hammering, substituting physical complexity with information processing capability.
Solution Approach 2:
The system performs self-diagnosis and self-regulation by continuously monitoring operating parameters and automatically adjusting to prevent water-hammering conditions. The algorithm analyzes real-time data and triggers preventive actions without external intervention, enabling the system to serve itself.
2Reliability
If comprehensive real-time monitoring is implemented, then equipment safety is improved, but energy consumption increases
Solution Approach 1:
The system implements periodic sampling of operating parameters rather than continuous monitoring. The operating state analysis algorithm processes data at optimized intervals, triggering detailed analysis only when parameters approach critical thresholds, thereby reducing energy consumption while maintaining safety.
Solution Approach 2:
The system applies full monitoring intensity only when necessary (when water-hammering risk is detected), and reduces monitoring intensity during normal operation. This partial action approach maintains safety while minimizing energy consumption during stable periods.
Data Source
AI summary
A water hammer prevention system using an operation state analysis algorithm to prevents water hammer. Data is measured in real time by a pressure sensor and a water level sensor are transmitted to a control unit and stored in a database. The control unit includes an air chamber which controls the operations of an air compressor and an air exhauster to prevent water hammer. The control unit performs calculations according to a water hammer algorithm, and determines the operation states of the air compressor and the air exhauster, and whether the water hammer prevention equipment is operating normally. Active operational control of the water hammer prevention equipment can be performed by applying a data analysis technique thereto, and a failure or operation error can be identified.