Non-Intrusive Turbine Flowmeter Diagnostics With Acoustic Sensing
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Solution Overview
Problem
Turbine flowmeters suffer from mechanical wear and damage due to exposure to hydrogen and bio-gas, leading to inaccurate measurements and potential malfunctions, necessitating costly and time-consuming manual inspections.
Innovation Solution
Implement non-intrusive sensing and diagnostics using non-invasive sensors to monitor turbine flowmeters, capturing acoustic and acceleration signals through the meter's housing, performing time-frequency analysis, and employing multi-sensor fusion to detect anomalies and predict maintenance needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection methods are used to detect meter defects, then inspection thoroughness can be ensured, but operational downtime increases and inspection efficiency decreases
Solution Approach 1:
The patent replaces manual mechanical inspection with automated acoustic and vibration sensing systems. Sensors mounted on the meter housing automatically detect mechanical fatigue, cracks, and defects through acoustic emissions and vibration patterns, eliminating the need for manual disassembly and visual inspection while maintaining high detection accuracy.
Solution Approach 2:
The meter performs self-diagnosis through integrated sensors that continuously monitor its own mechanical condition. The system automatically detects defects, tracks degradation trends, and generates maintenance alerts without external intervention, enabling continuous operation while ensuring reliable defect detection.
2Measurement precision
If intrusive pulse pickup assemblies are used for measurement, then measurement accuracy can be ensured, but device complexity increases and installation difficulty increases
Solution Approach 1:
The patent uses the meter housing as an intermediary structure to mount sensors externally. Acoustic and vibration sensors are attached to the housing surface, which transmits mechanical signals from internal components without requiring direct contact with moving parts. This approach maintains measurement accuracy while significantly reducing system complexity and installation difficulty.
Solution Approach 2:
The patent replaces intrusive mechanical pulse pickup assemblies with non-contact acoustic and vibration sensing. External sensors detect mechanical vibrations and acoustic emissions through the housing, eliminating the need for internal sensor installation while maintaining measurement precision through advanced signal processing.
3Adaptability or versatility
If mechanical components are exposed to hydrogen and bio-gas, then fuel flexibility is improved, but mechanical strength deteriorates due to embrittlement
Solution Approach 1:
The system performs preliminary detection of mechanical fatigue and micro-cracks before they propagate into critical failures. Continuous monitoring of vibration patterns and acoustic emissions allows early identification of hydrogen-induced embrittlement effects, enabling preventive maintenance before strength degradation becomes critical.
Solution Approach 2:
The system continuously monitors mechanical condition parameters and provides feedback on degradation trends. By tracking changes in vibration characteristics and acoustic emissions over time, the system detects early signs of hydrogen embrittlement and adjusts maintenance schedules to prevent catastrophic failures while maintaining fuel flexibility.
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
Enables real-time, accurate monitoring and predictive maintenance, reducing downtime and improving measurement reliability by identifying issues before they cause significant damage.
Implementation Method 1
capturing acoustic and acceleration signals through the meter's housing
Implementation Method 2
capturing acoustic and acceleration signals through the meter's housing
Data Source
Figure 1A~1D
Figure 2A~2B
Figure 3
AI summary
Methods and systems for non-intrusive sensing and diagnostics of a turbine flowmeter can involve monitoring a turbine flowmeter with non-invasive sensors, extracting blade frequencies associated with turbine blades based on a flow rate, detecting pressure wave frequencies associated with the turbine flowmeter's internal moving parts, and employing multi-sensor fusion with respect to sensor data generated from non-invasive sensors including the extracted blade frequencies and the pressure wave frequencies to identify a health condition of the turbine flowmeter and to predict maintenance for the turbine flowmeter. The non-intrusive sensors can be installed in proximity to positions of moving parts of the turbine flowmeter such as turbine blades, bearings, rotor, and so on.