Distributed Optical Temperature Sensor Rate of Change Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current distributed optical fibre sensors face challenges in accurately detecting the rate of change of temperature due to the difficulty in identifying and tracking frequency components from spectrally broad and noisy coherent Rayleigh backscatter interference signals.
Innovation Solution
The method involves calculating a spectral density profile of the coherent Rayleigh backscatter interference signal and detecting properties such as the position of a decline or peak, which represents the rate of change of temperature, using techniques like threshold detection or fitting functions to determine the rate of change from the spectral density profile.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to detect temperature rate of change by identifying specific frequency components in coherent Rayleigh backscatter signals, then temperature monitoring capability is provided, but measurement precision deteriorates due to spectrally broad and noisy signals making frequency component identification difficult
Solution Approach 1:
The patent extracts the low frequency continuum component from the complex coherent Rayleigh backscatter interference signal. By calculating the spectral density profile and isolating the low frequency continuum (typically below 10 Hz), the method removes distracting high frequency noise and spectral broadening effects, enabling accurate temperature rate of change measurement without needing to identify specific frequency components within the noisy spectrum
Solution Approach 2:
The patent changes the measurement parameter from specific frequency component identification to low frequency continuum analysis. Instead of attempting to identify and track individual frequency peaks in the spectrally broad signal, the method measures the overall low frequency spectral density profile shape and its evolution over time, which directly correlates with temperature rate of change while being immune to spectral broadening effects
2Reliability
If spectral density profile analysis is used to determine temperature changes, then measurement reliability improves, but device complexity increases due to additional signal processing requirements
Solution Approach 1:
The patent applies partial action by focusing computational resources only on the relevant low frequency portion of the spectrum. Instead of analyzing the entire spectral density profile or attempting to resolve all frequency components, the method selectively processes only the low frequency continuum (e.g., 0-10 Hz), achieving reliable temperature detection with reduced computational complexity by ignoring excessive high frequency information
Solution Approach 2:
The patent substitutes complex mechanical frequency tracking and component identification systems with a simplified spectral density profile analysis approach. By using Fourier transform-based spectral density calculation and continuum fitting rather than traditional frequency peak detection algorithms, the method achieves more reliable measurements with less complex processing architecture
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 allows for reliable and accurate determination of temperature changes without needing to identify specific frequency components, providing a more straightforward and effective method for monitoring temperature changes along the sensing optical fibre.
Implementation Method 1
detecting a time varying coherent Rayleigh backscatter interference signal from probe light backscattered within the sensing fibre from the associated position
Implementation Method 2
coherent Rayleigh backscatter interference signal
Data Source
AI summary
Methods and apparatus are disclosed for detecting a rate of change of temperature in the environment around a sensing optical fibre at a position along the fibre, in which a time varying coherent Rayleigh backscatter interference signal is detected using probe light backscattered within the sensing fibre from the position. A spectral density profile is calculated which represents frequency components in time variations of the interference signal. One or more properties of a feature of the spectral density profile are then used to determine the rate of change of temperature. The feature may be, for example, a decline in the spectral density profile with increasing frequency, or a peak in the spectral density profile.