Combustion Quality Spectrum for Flame Instability Detection
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Solution Overview
Problem
Current technologies in gas turbines struggle to differentiate between the root cause of combustion dynamics, which is flame instability, and secondary effects like acoustic pressure oscillations, leading to component damage and costly repairs, due to limitations in dynamic pressure measurements and the expense and scarcity of tourmaline crystal sensors.
Innovation Solution
A method and system that utilize UV and visible light measurements to create a combustion quality spectrum, identifying anomalies indicative of combustion dynamics frequencies by processing signals at specific wavelengths, allowing for differentiation between flame instability and acoustic effects, and enabling modification of combustion chamber inputs based on detected frequencies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dynamic pressure measurements are used to detect combustion dynamics, then pressure oscillations can be detected, but it is not possible to differentiate between root cause (flame instability) and secondary effect (acoustics)
Solution Approach 1:
The patent segments the measurement approach by using separate sensor types for different measurement purposes: optical sensors (photodiodes, spectrometers) measure flame radiation to detect flame instability, while pressure sensors measure acoustic pressure oscillations. This segmentation allows independent detection and differentiation of the root cause (flame instability) and secondary effect (acoustics), resolving the information loss problem.
2Measurement precision
If tourmaline crystal sensors are used to detect combustion dynamics, then detection capability is improved, but the sensors are expensive and difficult to source
Solution Approach 1:
The patent replaces the expensive tourmaline crystal sensors with optical sensors (photodiodes, spectrometers) that detect flame radiation. This copying approach uses different physical principles (optical detection instead of piezoelectric detection) to achieve the same measurement objective, thereby improving ease of manufacture and sensor availability while maintaining detection capability.
3Loss of information
If UV and visible light measurements are used to create combustion quality spectrum, then differentiation between flame instability and acoustic effects is enabled, but additional signal processing complexity is introduced
Solution Approach 1:
The patent introduces an intermediary processing system that receives signals from both optical sensors (measuring flame radiation) and pressure sensors (measuring acoustic pressure). This intermediary system correlates the two signal types to differentiate between flame instability and acoustic effects, managing the complexity through systematic signal integration and analysis.
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 the detection of combustion dynamics frequencies and differentiation between flame instability and acoustic effects, reducing the reliance on expensive pressure sensors and potentially preventing catastrophic failures by modifying inputs such as air or fuel, thus improving turbine operation and maintenance efficiency.
Implementation Method 1
receiving a first signal indicative of energy from the flame within the combustion chamber at a first wavelength... receiving a second signal indicative of energy from the flame at a second wavelength
Data Source
AI summary
A method and system for identifying combustion dynamics in a combustion chamber, includes an optical sensor that receives energy from a flame within the combustion chamber. A processor is configured to receive a first signal from the sensor indicative of energy at a first wavelength and a second signal indicative of energy at a second wavelength. The processor can generate a data set of combustion quality indicators from the first signal and the second signal. The processor can convert the data set of combustion quality indicators in a time domain to a combustion quality spectrum in a frequency domain. The processor can analyze the combustion quality spectrum to determine anomalies, wherein the anomalies indicate at least one frequency where combustion dynamics occur in the combustion chamber and output a signal indicative of the at least one frequency where combustion dynamics occur.