Leak Detection in Fluid Networks via Step Testing Optimization
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Solution Overview
Problem
Current methods for detecting hidden leaks in water distribution networks are inefficient and costly, as they often require large-scale acoustic surveys and ongoing maintenance, which can be labor-intensive and wasteful, especially when old but functioning components are needlessly replaced.
Innovation Solution
A computer-implemented method using a step testing procedure to locate leaks by computing the probability and cost of leak location in each section of the network, selecting a step testing procedure with a low expected cost, and applying optimization algorithms to determine the optimal inspection strategy, thereby reducing the cost of leak detection and maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large-scale acoustic surveys are used to detect hidden leaks, then leak detection coverage is improved, but labor intensity and cost increase
Solution Approach 1:
The network is divided into flow monitoring zones (FMZs) and further segmented into sections using valves as boundaries. This segmentation allows the system to focus acoustic surveys on specific sections where leaks are most likely to occur, rather than conducting large-scale surveys across the entire network, thereby reducing labor intensity while maintaining detection coverage.
Solution Approach 2:
The system performs preliminary analysis of flow data to identify FMZs with anomalies before conducting acoustic surveys. By pre-identifying potential leak locations through flow data analysis, the system can target acoustic surveys to specific high-probability areas, avoiding unnecessary surveys in low-risk areas and thus reducing overall labor intensity.
2Reliability
If ongoing maintenance is performed to prevent future leaks, then network reliability is improved, but water and energy waste increase when functioning components are replaced
Solution Approach 1:
The system enables predictive maintenance by continuously monitoring flow data and automatically identifying anomalies that indicate potential leaks. This self-service approach allows the network to detect and address issues before they lead to failures, eliminating the need for routine replacement of old but functioning components and thus reducing water and energy waste.
Solution Approach 2:
The system replaces traditional reactive maintenance mechanisms (scheduled replacements) with an intelligent monitoring and prediction system. By using flow data analysis and anomaly detection algorithms, the system can predict when components are likely to fail and schedule maintenance only when necessary, avoiding unnecessary replacement of functioning components and reducing resource waste.
3Measurement precision
If step testing procedures are optimized using probability and cost computation, then leak location precision is improved, but computational complexity increases
Solution Approach 1:
The system computes probability and cost metrics locally for each section of the network rather than performing global optimization across the entire network. By focusing computations on individual sections and using the decision tree structure to guide localized analysis, the system achieves high leak location precision while keeping computational complexity manageable through distributed, section-level processing.
Data Source
AI summary
Methods and systems are described for providing cost effective leak detection in a fluid network. Step testing procedures are represented by decision trees and associated expected costs are calculated. Selection of step testing procedures is optimized for low expected cost. The total expected cost rate for a network configuration may be calculated from the rate of leak occurrence and the optimal expected costs associated therewith. Network configuration changes may be recommended by optimizing for total expected cost rate for a fluid network.