Leak Probability Analysis for Utility Distribution Systems
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Solution Overview
Problem
Existing leak detection systems in utility distribution systems face inaccuracies due to environmental noise and inability to pinpoint precise leak locations, leading to inefficient maintenance efforts.
Innovation Solution
A leak probability analysis apparatus and method that utilizes remote sensors to record spectral data, generate spectral averages, and analyze trends to determine leak probabilities and locations through a communication network, integrating spatial analysis and geographic information for precise leak identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If acoustic sensors detect noise and characteristic sounds to determine leak presence, then leak detection capability is provided, but accuracy deteriorates due to environmental noise
Solution Approach 1:
The patent segments the acoustic signal analysis into multiple frequency bands using spectral analysis. Instead of analyzing the entire acoustic spectrum as a single signal, the system divides it into distinct frequency components, allowing selective analysis of leak-related frequencies while filtering out environmental noise in other frequency ranges. This segmentation enables accurate leak detection despite noisy environments.
Solution Approach 2:
The patent employs partial action by focusing analysis only on specific spectral components that are indicative of leaks rather than processing the complete acoustic signal. The system calculates spectral averages and identifies trends in particular frequency bands where leak signatures appear, ignoring portions of the spectrum dominated by environmental noise. This selective approach maintains detection accuracy while reducing false alarms.
2Reliability
If information from multiple leak detection sensors is gathered to improve detection reliability, then detection coverage is enhanced, but ability to pinpoint precise leak location deteriorates due to noise and interference
Solution Approach 1:
The patent transitions from analyzing acoustic signals in the time domain to analyzing them in the frequency domain through spectral analysis. By converting temporal noise patterns into frequency spectrum representations, the system can identify consistent leak-related frequency signatures across multiple sensors while filtering out time-varying environmental noise. This dimensional transformation enables precise leak localization using multiple sensors.
Solution Approach 2:
The patent creates spectral average representations that copy and consolidate the characteristic frequency patterns from multiple sensor readings. By generating spectral averages across multiple measurements and sensors, the system identifies recurring leak signatures while averaging out random environmental noise. This copying approach allows precise leak location determination even when individual sensor readings are noisy.
3Measurement precision
If spectral analysis and trend generation are performed to determine leak probabilities, then accuracy of leak detection is improved, but computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary spectral analysis to generate spectral averages before conducting detailed leak probability assessment. By pre-processing the acoustic signals to establish baseline spectral characteristics and averages, the system reduces the complexity of subsequent leak detection calculations. This preliminary action organizes the data in a form that simplifies trend identification and leak probability determination.
Solution Approach 2:
The patent transforms the acoustic signal parameters from time-domain characteristics to frequency-domain spectral parameters. By changing the representation parameters from temporal waveforms to spectral distributions, the system enables more efficient pattern recognition and trend analysis. This parameter transformation simplifies the computational task of identifying leak signatures compared to analyzing raw time-series data.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of leak detection by filtering noise, determining leak probabilities, and pinpointing leak locations, thereby optimizing maintenance operations and reducing unnecessary search efforts.
Implementation Method 1
employ leak detection sensors with acoustic sensors that detect noise and/or characteristic sounds
Implementation Method 2
record spectral data, generate spectral averages, and analyze trends to determine leak probabilities
Data Source
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AI summary
Methods and apparatus to detect leaks are disclosed. A disclosed leak probability analysis apparatus associated with a utility distribution system having sensors includes a receiver to receive spectral recording data associated with spectral recordings measured at the sensors, and a storage device to store the spectral recording data. The leak probability analysis apparatus also includes a processor to calculate spectral energies associated with the spectral recording data, calculate deviations of the spectral energies, normalize the spectral energies based on the respective deviations, and generate a leak probability distribution of the utility distribution system based on the normalized spectral energies.