Pipeline Vibration Waveform Selection for Fluid Leakage Detection
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Solution Overview
Problem
Existing methods for detecting fluid leakage in pipeline networks are prone to errors due to the influence of environmental vibrations, which vary by location and time, making it difficult to determine the most suitable measurement time points and leading to erroneous determinations.
Innovation Solution
A data processing device that evaluates waveform data from vibration sensors using an autocorrelation coefficient to identify periodic characteristics, selects suitable data based on an evaluation value, and determines fluid leakage by analyzing the relationship between periodic characteristics, reducing the impact of environmental vibrations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If measurement is performed at fixed time points using sound pressure values, then the detection method is simple, but the reliability of leakage determination deteriorates due to environmental vibrations
Solution Approach 1:
The patent performs preliminary actions by acquiring multiple waveform data sets at different time points before making the final leakage determination. This allows the system to evaluate multiple measurements and select the most appropriate data for analysis, thereby improving reliability while maintaining reasonable complexity.
Solution Approach 2:
The patent dynamically adjusts the measurement approach by evaluating the suitability of each waveform data set based on environmental vibration conditions. The system can adaptively select which time point's data to use for determination, making the detection process flexible rather than fixed, thus improving reliability without excessive complexity.
2Reliability
If multiple waveform data are acquired and evaluated, then the reliability of leakage determination improves, but the processing complexity increases
Solution Approach 1:
The patent extracts only the necessary information from multiple waveform data sets by evaluating their suitability and selecting the most appropriate one for leakage determination. This extraction approach avoids processing all data equally, reducing overall processing complexity while maintaining high reliability through selective use of the best data.
Solution Approach 2:
The patent changes parameters by introducing an evaluation criterion that assesses waveform data suitability based on environmental vibration characteristics. This parameter change allows the system to efficiently filter and select optimal data, balancing reliability improvement with acceptable processing complexity.
3Ease of operation
If measurement time points are fixed, then the measurement process is simple, but the measurement precision deteriorates due to varying environmental vibrations
Solution Approach 1:
The patent performs preliminary measurements at multiple fixed time points to gather waveform data before making the final determination. This preliminary action maintains operational simplicity while enabling subsequent selection of the most precise measurement, thereby improving detection precision without complicating the measurement process.
Solution Approach 2:
The patent introduces dynamic selection of the optimal waveform data set based on evaluated suitability criteria. This dynamic approach allows the system to adapt to varying environmental conditions while keeping the measurement process itself simple and fixed, thus improving precision without sacrificing ease of operation.
4Measurement precision
If environmental vibrations are considered in data selection, then the accuracy of leakage determination improves, but the processing time increases
Solution Approach 1:
The patent extracts only the critical evaluation metrics from waveform data that are necessary for assessing environmental vibration influence. By focusing on key parameters rather than processing all data aspects equally, the system improves determination accuracy while minimizing additional processing time.
Solution Approach 2:
The patent changes processing parameters by introducing efficiency optimizations in the evaluation and selection process. These parameter changes enable the system to consider environmental vibration factors and select optimal waveform data with reduced computational overhead, balancing accuracy improvement with acceptable processing time.
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
The method effectively detects fluid leakage with reduced interference from environmental vibrations, ensuring accurate detection by selecting optimal measurement waveforms and analyzing autocorrelation peaks, thereby improving the reliability of leakage detection.
Implementation Method 1
calculates an evaluation value for evaluating how suitable or unsuitable the plurality of pieces of waveform data are for determining a presence or absence of a fluid leakage, selects waveform data to be used for determining a presence or absence of a fluid leakage from the plurality of pieces of waveform data based on the evaluation value, extracts a periodic characteristic from an autocorrelation coefficient of a vibration intensity of the selected waveform data
Data Source
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AI summary
Provided is a technique capable of detecting a fluid leakage with a reduced influence of an environmental vibration. A data processing device that determines whether a fluid leaks from a pipeline network of the fluid based on a waveform of a vibration intensity measured from the pipeline network, the data processing device including: a memory configured to store a software program; and a processor configured to execute the software program. The processor acquires a plurality of pieces of waveform data of vibration intensities measured at different times from the pipeline network, calculates an evaluation value for evaluating how suitable or unsuitable the plurality of pieces of waveform data are for determining a presence or absence of a fluid leakage, selects waveform data to be used for determining a presence or absence of a fluid leakage from the plurality of pieces of waveform data based on the evaluation value, extracts a periodic characteristic from an autocorrelation coefficient of a vibration intensity of the selected waveform data, and determines whether the fluid leaks from the pipeline network based on a relationship between periodic characteristics of the selected waveform data.