Raman Sensor Temperature Demodulation via Rayleigh Noise Subtraction
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Solution Overview
Problem
The existing distributed fiber Raman temperature sensing systems face challenges in achieving high precision temperature measurement due to interference from Rayleigh noise, which limits the temperature measurement precision to ±1°C, whereas industrial applications require precision up to ±0.1°C.
Innovation Solution
A high-precision temperature demodulation method is developed using a device comprising a pulsed laser, WDM, APDs, LNAs, and a data acquisition card, with a calibration stage to process Stokes and anti-Stokes light signals, allowing for the subtraction of Rayleigh noise interference and enabling precise temperature measurement along the fiber.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If WDM with 35-40 dB isolation is used to separate anti-Stokes and Stokes signals, then the system meets basic isolation requirements, but residual Rayleigh scattering light becomes serious noise interference that prevents temperature measurement precision from reaching ±0.1°C
Solution Approach 1:
The patent performs preliminary calibration measurements at known temperatures to establish the relationship between Rayleigh scattering intensity and temperature. By pre-characterizing the noise profile, the system can later subtract this known noise component from measurement signals to recover the true anti-Stokes signal for accurate temperature measurement.
Solution Approach 2:
The patent converts the harmful Rayleigh noise into a useful calibration reference. By measuring the Rayleigh scattering signal and using its known temperature dependence, the system transforms the noise source into a tool for characterizing and correcting the measurement system, thereby improving temperature measurement precision to ±0.1°C.
2Measurement precision
If Stokes backscattering light is used as reference channel and anti-Stokes backscattering light as signal channel, then temperature information can be demodulated, but the weak scattering signals are completely submerged in noises making precise measurement difficult
Solution Approach 1:
The patent uses the Rayleigh scattering signal, which has a known and stable relationship with temperature, as a feedback reference. By continuously monitoring the Rayleigh signal and comparing it against calibration data, the system can dynamically correct for noise variations and extract the weak anti-Stokes temperature signal with high precision.
Solution Approach 2:
The patent changes the approach from directly measuring weak anti-Stokes signals to measuring the more robust Rayleigh scattering signal and using parameter transformations (through calibration curves and mathematical relationships) to infer temperature. This parameter transformation allows the system to achieve high precision despite the weakness of the primary temperature-sensitive signals.
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 eliminates Rayleigh noise interference, enabling temperature measurement precision of ±0.1°C, suitable for industrial applications such as petrochemical reactors and smart grids, without the need for additional components or repeated calibration.
Implementation Method 1
a distributed fiber Raman sensor
Implementation Method 2
The system separates the anti-Stokes signals and the Stokes signals via a Raman wavelength division multiplexer (WDM)
Implementation Method 3
passes through the photodetector and the data acquisition card
Data Source
AI summary
A temperature demodulation method oriented toward a distributed fiber Raman temperature sensing system, the method comprising the following steps: step 1 of constructing a high-precision temperature detection device oriented towards a distributed fiber Raman sensing system; step 2 of performing signal processing with respect to Stokes light and anti-Stokes light at a calibration stage; step 3 of performing signal processing with respect to Stokes light and the anti-Stokes light at a measurement stage; and step 4 of obtaining a high-precision temperature demodulation technique oriented toward the distributed fiber Raman sensor. The method is used to effectively resolve the issue of low temperature measuring accuracy caused by Rayleigh crosstalk in existing distributed fiber Raman temperature measurement systems, and temperature measurement accuracy thereof is expected to fall within ±0.1° C. The method is applicable to distributed fiber Raman temperature measurement systems.