A distributed optical fiber temperature measurement system based on Raman scattering

Abstract

The present application relates to the field of optical fiber optics, and more particularly to a distributed optical fiber temperature measurement system based on Raman scattering, comprising a light signal excitation and separation module, a signal acquisition and preprocessing module, a temperature calculation module, a calibration correction module, a real-time monitoring and early warning module, and a management database, wherein the system separates Stokes light and anti-Stokes light, monitors light power in real time, divides spatial positions to digitally accumulate and reduce noise of scattered signals, determines corresponding spatial positions of temperature by calculating temperature, generates a temperature distribution curve, selects a constant temperature reference point to fit a temperature deviation curve to generate a calibration coefficient, corrects temperature and calibrates a standard curve, simultaneously compensates for light intensity attenuation, sets multiple temperature early warning thresholds to monitor abnormal temperature points, and can accurately measure light temperature and timely perform early warning.

Description

Technical Field

[0001] This invention relates to the field of fiber optics, and more specifically, to a distributed fiber optic temperature measurement system based on Raman scattering. Background Technology

[0002] In today's era of digitalization and intelligentization sweeping across industries, accurate temperature monitoring has become a crucial guarantee for stable operation in many fields. In power systems, overheated cable joints can cause fires, and inadequate heat dissipation in data center servers will affect data processing efficiency and equipment lifespan.

[0003] Distributed fiber optic temperature measurement uses optical fibers as sensing units and leverages the scattering characteristics of light to achieve long-distance, continuous, and distributed temperature monitoring. It possesses unique advantages such as resistance to electromagnetic interference, corrosion resistance, and the ability to be embedded in the ground. It can adapt to complex and harsh monitoring environments and provides innovative solutions for fields such as industrial safety monitoring, energy efficiency management, and infrastructure health diagnosis. It has become an important direction for the development of temperature monitoring technology and plays an increasingly important role in promoting the intelligent upgrading of various industries.

[0004] Although distributed fiber optic temperature measurement technology has shown great application potential, there are still many problems that need to be solved in the existing technology. For example, the existing Chinese patent application number 201310017365.0 discloses a distributed fiber optic Raman temperature measurement system. In this scheme, the light enters the sensing fiber under test after passing through a wavelength division multiplexer. During the propagation of the pulsed laser in the fiber, backscattering is continuously generated. The backscattered light returns to the wavelength division multiplexer. After being filtered by the wavelength division multiplexer, the Stokes Raman scattered light and the anti-Stokes Raman scattered light are filtered out and enter a dual-channel avalanche photodiode for photoelectric conversion. The electrical signal output by the dual-channel avalanche photodiode is processed by a DSP digital signal processor to obtain the temperature signal. The processing speed is fast, and the real-time temperature measurement can be achieved without affecting the accuracy.

[0005] However, this scheme has the following shortcomings: First, although the scheme has cumulative processing and wavelet denoising, it lacks a systematic method for spatial location division, and cannot accurately determine the corresponding temperature location, which may miss the hidden danger of local overheating of optical fiber.

[0006] Second, this scheme only calculates the temperature using a fixed formula, without considering the dynamic factors of fiber characteristics changing with time and environment, and lacks a mechanism for updating the parameters of the temperature calculation model. Over long-term use, errors will continue to accumulate.

[0007] Third, the scheme does not mention a complete early warning mechanism, relies solely on temperature calculation results, lacks multi-dimensional anomaly judgment criteria and graded early warning functions, and cannot detect temperature anomalies in a timely and accurate manner. In practical applications, it is difficult to effectively ensure the safety of the monitored objects. Summary of the Invention

[0008] To overcome the shortcomings of the prior art, this invention provides a distributed fiber optic temperature measurement system based on Raman scattering, which can effectively solve the problems mentioned in the prior art.

[0009] The objective of this invention can be achieved through the following technical solution: This invention provides a distributed optical fiber temperature measurement system based on Raman scattering, comprising: an optical signal excitation and separation module, used to separate Stokes light and anti-Stokes light through a beam splitter and a dual-wavelength optical filter, monitor optical power in real time, and automatically adjust the output power of the laser.

[0010] The signal acquisition and preprocessing module is used to divide the spatial location based on the principle of optical time-domain reflection, calculate the minimum accumulation algorithm, and perform digital accumulation and noise reduction on the scattered signal.

[0011] The temperature calculation module is used to calculate the temperature by the intensity ratio of Stokes light and anti-Stokes light, determine the spatial location corresponding to the temperature using the principle of optical time-domain reflection, and generate a temperature distribution curve.

[0012] The calibration correction module is used to select constant temperature reference points, fit the temperature deviation curve to generate calibration coefficients, correct the temperature and calibrate the calibration curve, and compensate for light intensity attenuation.

[0013] The real-time monitoring and early warning module is used to set multi-level temperature early warning thresholds, monitor temperature anomalies, record abnormal information, and trigger corresponding level early warning responses.

[0014] The management database stores fiber optic attenuation coefficients, constant temperature reference point temperatures, temperature calibration curves, early warning thresholds, temperature-location mapping tables, and historical temperature data.

[0015] Preferably, the specific analysis method of the optical signal excitation and separation module is as follows: a laser pulse is injected into the sensing fiber, the backscattered light generated when the laser pulse propagates in the sensing fiber is initially separated by a beam splitter, and the Stokes light and anti-Stokes light are further separated by a dual-wavelength optical filter.

[0016] The system monitors the power of the separated Stokes beam and anti-Stokes beam. When the monitored power deviates from the set reasonable range, an alarm mechanism is triggered, and the laser output power is automatically adjusted to compensate.

[0017] Preferably, the specific analysis method for dividing the spatial location is as follows: pre-setting segmentation parameters for a single measurement of the scattered signal, wherein the segmentation parameters include the spatial location range corresponding to each data segment, and the spatial location range is determined based on the principle of optical time-domain reflection and in combination with the length of the sensing fiber.

[0018] Based on the system noise characteristics and the target signal-to-noise ratio, the minimum number of accumulations required to meet the signal quality requirements is calculated. The optical pulse emission module is controlled to inject laser pulses into the sensing fiber to generate a scattered signal containing temperature information. The scattered signal is then transmitted to the digital accumulation unit for photoelectric conversion and digital processing.

[0019] The digitized scattering signal is divided into time-domain segments, with each time window corresponding to a data segment. Each time window is converted into a specific spatial location region on the sensing fiber, and the segmented data segments are stored in the corresponding spatial location buffer according to the correspondence.

[0020] Preferably, the specific analysis method for the minimum accumulation count is as follows: by measuring the system output under no signal input conditions to obtain the white noise power spectral density of the system, and simultaneously determining the system's operating bandwidth and the absolute temperature of the system's operating environment, a target signal-to-noise ratio is set according to the temperature measurement accuracy requirements, and it is converted from decibels to a linear value. This value is then substituted into the calculation formula for the minimum accumulation count to obtain the minimum accumulation count that meets the signal quality requirements.

[0021] Preferably, the specific analysis method for digital accumulation and noise reduction of the scattered signal is as follows: perform multiple measurements according to the minimum number of accumulations, and generate scattered signal data segments corresponding to each spatial location for each measurement and store them in the corresponding buffer area to form multiple sets of scattered signal data segmented by spatial location.

[0022] For the same spatial location buffer, the data segments corresponding to multiple measurements are extracted sequentially. The values ​​of the corresponding data points in the multiple measurement signals of the same spatial location are superimposed and summed. The sum of the superimposed signals is divided by the number of measurements to obtain the mean data point of that spatial location.

[0023] Iterate through the data segments at all spatial locations to generate a mean sequence containing the mean data points for each spatial location.

[0024] Preferably, the specific analysis method for the spatial location corresponding to the temperature is as follows: extract the Stokes light signal intensity value and the anti-Stokes light signal intensity value corresponding to the same spatial location from the mean sequence, calculate the ratio of the Stokes light intensity value to the anti-Stokes light intensity value, and obtain the Raman scattering intensity ratio.

[0025] A preset temperature calibration curve is invoked, which is a mapping relationship between the Raman scattering intensity ratio and the temperature value. The Raman scattering intensity ratio is substituted into the calibration curve to calculate the temperature value at the corresponding spatial location.

[0026] Preferably, the specific analysis method of the temperature calculation module is as follows: record the start time of the laser pulse injected into the sensing fiber by the optical pulse emission module, and at the same time detect the time when the scattered signal arrives at the photoelectric conversion module, and calculate the time difference between the receiving time and the start time.

[0027] The refractive index parameter of the sensing fiber is obtained. Based on the principle of optical time-domain reflection, the time difference is multiplied by the speed of light and divided by twice the refractive index of the material to calculate the spatial location distance corresponding to the scattered signal.

[0028] The spatial location distance is mapped to specific physical location coordinates on the sensing fiber, establishing a one-to-one correspondence between the temperature value and the physical location coordinates.

[0029] The temperature values ​​of all spatial locations calculated within the same measurement period are associated with the corresponding physical location coordinates to generate a temperature-location mapping table. Based on the temperature-location mapping table, a continuous temperature distribution curve is generated with the physical location as the horizontal axis and the temperature value as the vertical axis.

[0030] Preferably, the specific analysis method of the calibration curve is as follows: set constant temperature reference points with known temperatures at the beginning, middle and end of the sensing fiber, respectively, and automatically collect the standard temperature values ​​of the constant temperature reference points according to the set time interval, and record them as the standard temperature values ​​of each constant temperature reference point at each time point.

[0031] The temperature deviation curve is formed by subtracting the standard temperature value of each constant temperature reference point at each time point from the corresponding temperature value on the temperature calibration curve. The temperature deviation curve is fitted to generate a calibration coefficient matrix. The calibration coefficient matrix is ​​substituted into the temperature correction formula. The linear correction mode or nonlinear correction mode is determined in real time according to the temperature fluctuation range. The temperature calibration curve is then recalibrated using the corrected temperature value.

[0032] Preferably, the specific analysis method for compensating for light intensity attenuation is as follows: the sensing fiber is divided into several fixed-length segments, the initial attenuation coefficient of each segment of the sensing fiber is obtained from the management database, a model of the attenuation coefficient changing with temperature is established, and for a certain position on the sensing fiber, the trapezoidal integral method is used to approximately calculate the cumulative attenuation from the beginning of the sensing fiber to that position. The compensation factor is calculated based on the attenuation, and the scattered light intensity at that position is compensated to obtain the final compensated light intensity, thereby correcting the correspondence between temperature value and light intensity.

[0033] Preferably, the specific analysis method of the real-time monitoring and early warning module is as follows: set multiple temperature early warning thresholds respectively; when the temperature at a certain location of the sensing fiber exceeds a certain early warning threshold, determine that the location is a temperature anomaly point, and record the temperature value of the anomaly point and the time when the anomaly was detected.

[0034] Based on the calibrated and corrected temperature data, a multi-level temperature warning threshold is preset. The multi-level temperature warning threshold includes an absolute temperature threshold, a relative temperature threshold calculated based on historical temperature data, and a temperature change rate threshold. The absolute temperature threshold is used to set the specific temperature values ​​for different warning levels. The relative temperature threshold is calculated based on statistical measures such as the mean and standard deviation of historical temperature data. The temperature change rate threshold is used to measure the magnitude of temperature change per unit time.

[0035] The temperature at each location on the sensing fiber is monitored in real time. When the temperature at a certain location meets any of the following conditions, the location is determined to be a temperature anomaly: the temperature exceeds the absolute temperature threshold, the temperature exceeds the relative temperature threshold calculated based on historical temperature data, or the temperature change rate exceeds the set temperature change rate threshold.

[0036] After determining that a certain location is a temperature anomaly point, the temperature value of the anomaly point and the time when the anomaly was detected are recorded. The specific physical location coordinates of the anomaly point on the sensing fiber are obtained according to the temperature distribution curve. Based on the degree of deviation between the temperature value of the anomaly point and the preset multi-level temperature warning threshold, different levels of warning response are triggered.

[0037] Compared with the prior art, the present invention has the following beneficial effects: First, by separating Stokes light and anti-Stokes light and monitoring optical power in real time, the present invention can accurately obtain the intensity information of optical signals. By dividing the spatial position, the scattered signal is digitally accumulated and denoised, which helps to accurately analyze the changes of light during transmission.

[0038] II. This invention calculates temperature by comparing the intensity ratio of Stokes light and anti-Stokes light, determines the spatial location corresponding to the temperature using the principle of optical time-domain reflection, generates a temperature distribution curve, and achieves high-precision spatial positioning of temperature distribution, accurately knowing the temperature conditions at different locations.

[0039] Third, this invention selects constant temperature reference points, fits temperature deviation curves to generate calibration coefficients, corrects the temperature and calibrates the calibration curve, and compensates for light intensity attenuation. This can eliminate the influence of light intensity changes caused by light loss and other reasons during light transmission in optical fibers on temperature measurement, and ensure the stability of light intensity.

[0040] Fourth, this invention sets multi-level temperature warning thresholds, monitors abnormal temperature points, records abnormal information, and triggers corresponding level warning responses, enabling different response measures to be taken according to the severity of the abnormality. Attached Figure Description

[0041] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a system module connection diagram of the present invention.

[0043] Figure 2 for Figure 1 A flowchart illustrating the spatial division of the signal acquisition and preprocessing module.

[0044] Figure 3 for Figure 1 Flowchart of the medium temperature calculation module. Detailed Implementation

[0045] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0046] Please see Figure 1 As shown, a distributed fiber optic temperature measurement system based on Raman scattering includes an optical signal excitation and separation module, a signal acquisition and preprocessing module, a temperature calculation module, a calibration and correction module, a real-time monitoring and early warning module, and a management database.

[0047] The management database is connected to the signal acquisition and preprocessing module, temperature calculation module, calibration and correction module, and real-time monitoring and early warning module. The temperature calculation module is connected to the signal acquisition and preprocessing module and the calibration and correction module. The optical signal excitation and separation module is connected to the signal acquisition and preprocessing module. The calibration and correction module is connected to the real-time monitoring and early warning module.

[0048] The optical signal excitation and separation module is used to separate Stokes light and anti-Stokes light through a beam splitter and a dual-wavelength optical filter, monitor optical power in real time, and automatically adjust the laser output power.

[0049] The specific analysis method of the optical signal excitation and separation module is as follows: a laser pulse is injected into the sensing fiber, and the backscattered light generated when the laser pulse propagates in the sensing fiber is initially separated by a beam splitter. Then, a dual-wavelength optical filter is used to further separate the Stokes light and the anti-Stokes light. This method can accurately separate the required optical signal, ensure that the monitored optical power is within a reasonable range, thereby improving the system's processing accuracy and stability of the optical signal and providing a reliable optical signal basis for subsequent accurate temperature measurement.

[0050] The system monitors the power of the separated Stokes beam and anti-Stokes beam. When the monitored optical power deviates from the set reasonable range, an alarm mechanism is triggered, and the laser output power is automatically adjusted to compensate. This helps maintain stable optical power, ensures the accuracy and reliability of system measurements, and reduces measurement errors caused by optical power fluctuations.

[0051] The signal acquisition and preprocessing module is used to divide the spatial location based on the principle of optical time-domain reflection, calculate the minimum accumulation algorithm, and perform digital accumulation and noise reduction on the scattered signal.

[0052] Please see Figure 2 As shown, the specific analysis method for dividing the spatial location is as follows: the segmentation parameters of the single measurement scattering signal are preset, the segmentation parameters include the spatial location range corresponding to each data segment, the spatial location range is determined based on the principle of optical time-domain reflection and combined with the length of the sensing fiber; it can accurately divide the spatial location of the sensing fiber, providing a basis for accurately obtaining temperature information at different locations in the future.

[0053] Based on the system noise characteristics and the target signal-to-noise ratio, the minimum number of accumulations required to meet the signal quality requirements is calculated. The optical pulse emission module is then controlled to inject laser pulses into the sensing fiber to generate a scattered signal containing temperature information. This scattered signal is then transmitted to the digital accumulation unit for photoelectric conversion and digital processing. By determining an appropriate number of accumulations, signal quality can be improved, noise interference can be reduced, and the system can more accurately acquire and process the scattered signal, thereby more precisely determining the temperature at each spatial location.

[0054] The digitized scattering signal is divided into time-domain segments, with each time window corresponding to a data segment. Each time window is converted into a specific spatial location region on the sensing fiber, and the segmented data segments are stored in the corresponding spatial location buffer according to the correspondence.

[0055] The specific analysis method for the minimum number of accumulations is as follows: The white noise power spectral density of the system is obtained by measuring the system output under no signal input conditions. Simultaneously, the system's operating bandwidth and the absolute temperature of the system's operating environment are determined. Based on the temperature measurement accuracy requirements, a target signal-to-noise ratio is set and converted from decibels to a linear value. This value is then substituted into the formula for calculating the minimum number of accumulations to obtain the minimum number of accumulations that meets the signal quality requirements. The optimal number of measurements can be determined based on the system's own characteristics and actual needs, optimizing the measurement process. This ensures measurement accuracy while improving measurement efficiency and avoiding resource waste caused by unnecessary measurements.

[0056] It should be noted that the formula for converting the target signal-to-noise ratio from decibels to a linear value is as follows: Substitute it into the formula Minimum number of accumulations to meet signal quality requirements ,in This represents the white noise power spectral density of the system. This indicates the absolute temperature of the system's operating environment. This refers to the system's operating bandwidth.

[0057] The specific analysis method for digital accumulation and noise reduction of the scattered signal is as follows: perform multiple measurements according to the minimum accumulation number, and generate scattered signal data segments corresponding to each spatial location for each measurement and store them in the corresponding buffer area to form multiple sets of scattered signal data segmented by spatial location.

[0058] For the same spatial location buffer, the data segments corresponding to multiple measurements are extracted sequentially. The values ​​of the corresponding data points in the multiple measurement signals of the same spatial location are superimposed and summed. The sum of the superimposed signals is divided by the number of measurements to obtain the mean data point of that spatial location.

[0059] It traverses data segments at all spatial locations to generate a mean sequence containing mean data points at each spatial location; this effectively reduces noise in the scattered signal and improves signal stability and accuracy by taking the mean from multiple measurements, making the measurement results more reliable.

[0060] The temperature calculation module is used to calculate the temperature by the intensity ratio of Stokes light and anti-Stokes light, determine the spatial location corresponding to the temperature using the principle of optical time-domain reflection, and generate a temperature distribution curve.

[0061] The specific analysis method for the spatial location corresponding to the temperature is as follows: extract the Stokes light signal intensity value and the anti-Stokes light signal intensity value corresponding to the same spatial location from the mean sequence, calculate the ratio of the Stokes light intensity value to the anti-Stokes light intensity value, and obtain the Raman scattering intensity ratio.

[0062] A preset temperature calibration curve is invoked, which is a mapping relationship between the Raman scattering intensity ratio and the temperature value. The Raman scattering intensity ratio is substituted into the calibration curve to calculate the temperature value at the corresponding spatial location. By utilizing the correspondence between the light signal intensity ratio and the temperature, the temperature at the corresponding spatial location can be accurately calculated using a known temperature calibration curve, thus achieving precise temperature measurement.

[0063] It should be noted that the specific analysis method of the temperature calibration curve is as follows: the sensing fiber is pre-calibrated at multiple points using a standard blackbody furnace, and a piecewise polynomial fitting method is used to establish the mapping relationship between the Raman scattering intensity ratio and the temperature value to form the temperature calibration curve.

[0064] Please see Figure 3 As shown, the specific analysis method of the temperature calculation module is as follows: record the start time of the laser pulse injected into the sensing fiber by the optical pulse emission module, and at the same time detect the time when the scattered signal arrives at the photoelectric conversion module, and calculate the time difference between the receiving time and the start time.

[0065] The refractive index parameter of the sensing fiber is obtained. Based on the principle of optical time-domain reflection, the time difference is multiplied by the speed of light and divided by twice the refractive index of the material to calculate the spatial location distance corresponding to the scattered signal.

[0066] By mapping the spatial location distance to specific physical location coordinates on the sensing fiber, a one-to-one correspondence between the temperature value and the physical location coordinates is established. This allows for the precise determination of the spatial location corresponding to the scattered signal, and provides a clear view of the temperature distribution on the sensing fiber, facilitating comprehensive and accurate monitoring and analysis of the temperature.

[0067] The temperature values ​​of all spatial locations calculated within the same measurement period are associated with the corresponding physical location coordinates to generate a temperature-location mapping table. Based on the temperature-location mapping table, a continuous temperature distribution curve is generated with the physical location as the horizontal axis and the temperature value as the vertical axis.

[0068] The calibration correction module is used to select constant temperature reference points, fit the temperature deviation curve to generate calibration coefficients, correct the temperature and calibrate the calibration curve, and compensate for light intensity attenuation.

[0069] The specific analysis method for the calibration curve is as follows: set constant temperature reference points with known temperatures at the beginning, middle and end of the sensing fiber, respectively, and automatically collect the standard temperature values ​​of the constant temperature reference points according to the set time interval, and record them as the standard temperature values ​​of each constant temperature reference point at each time point.

[0070] The temperature deviation curve is generated by subtracting the standard temperature value of each constant temperature reference point at each time point from the corresponding temperature value on the temperature calibration curve. The temperature deviation curve is then fitted to generate a calibration coefficient matrix. The calibration coefficient matrix is ​​substituted into the temperature correction formula, and the linear or nonlinear correction mode is determined in real time according to the temperature fluctuation range. The temperature calibration curve is then recalibrated using the corrected temperature value. This method can calibrate and correct the temperature calibration curve based on the actual measured temperature value, making the temperature calibration curve more consistent with the actual situation and improving the accuracy and reliability of temperature measurement.

[0071] It should be noted that when the absolute value of the set temperature fluctuation is less than the set threshold, a linear correction mode is adopted. The formula for the linear correction mode is as follows: When the absolute value of the set temperature fluctuation is greater than or equal to a set threshold, a nonlinear correction mode is adopted. The formula for the nonlinear correction mode is as follows: ,in Indicates the standard temperature value. This indicates the corrected temperature. This is the calibration coefficient matrix.

[0072] The specific analysis method for compensating for light intensity attenuation is as follows: the sensing fiber is divided into several fixed-length segments, the initial attenuation coefficient of each segment is obtained from the management database, a model of the attenuation coefficient changing with temperature is established, and for a certain position on the sensing fiber, the trapezoidal integral method is used to approximately calculate the cumulative attenuation from the beginning of the sensing fiber to that position. Based on the attenuation, a compensation factor is calculated, and the scattered light intensity at that position is compensated to obtain the final compensated light intensity. This corrects the correspondence between temperature value and light intensity. This method can effectively compensate for the influence of light intensity attenuation on the measurement results, ensure the accuracy of light intensity, thereby improving the accuracy of temperature measurement and making the correspondence between temperature value and light intensity more accurate.

[0073] It should be noted that the model for the attenuation coefficient changing with temperature is as follows: ,in For the first The initial attenuation coefficient of the fiber segment, , The temperature-dependent attenuation coefficient (typical value 0.002 dB / km / °C) is used. To approximate the cumulative attenuation from the beginning of the sensing fiber to a specific location on the fiber, considering the change in ambient temperature, the trapezoidal integral method is used. ,in for The sequence number of the section. The first Section, No. The initial attenuation coefficient of the fiber segment is used to calculate the compensation factor based on the attenuation. The intensity of scattered light at this location Provide compensation: Light intensity after final compensation .

[0074] The real-time monitoring and early warning module is used to set multi-level temperature early warning thresholds, monitor temperature anomalies, record abnormal information, and trigger corresponding level early warning responses.

[0075] The specific analysis method of the real-time monitoring and early warning module is as follows: set multiple temperature early warning thresholds respectively. When the temperature at a certain location of the sensing fiber exceeds a certain early warning threshold, the location is determined to be a temperature anomaly point, and the temperature value of the anomaly point and the time when the anomaly was detected are recorded.

[0076] Based on the calibrated and corrected temperature data, a multi-level temperature warning threshold is preset. The multi-level temperature warning threshold includes an absolute temperature threshold, a relative temperature threshold calculated based on historical temperature data, and a temperature change rate threshold. The absolute temperature threshold is used to set the specific temperature values ​​for different warning levels. The relative temperature threshold is calculated based on statistical measures such as the mean and standard deviation of historical temperature data. The temperature change rate threshold is used to measure the magnitude of temperature change per unit time.

[0077] The temperature at each location on the sensing fiber is monitored in real time. When the temperature at a certain location meets any of the following conditions, the location is determined to be a temperature anomaly: the temperature exceeds the absolute temperature threshold, the temperature exceeds the relative temperature threshold calculated based on historical temperature data, or the temperature change rate exceeds the set temperature change rate threshold.

[0078] After identifying a temperature anomaly point, the system records the temperature value of the anomaly point and the time when the anomaly was detected. Based on the temperature distribution curve, the system obtains the specific physical coordinates of the anomaly point on the sensing fiber. Then, based on the deviation of the anomaly point's temperature value from the preset multi-level temperature warning thresholds, different levels of warning responses are triggered. This allows for timely detection of temperature anomalies on the sensing fiber. By setting multi-level thresholds and different levels of warning responses, the system can monitor and warn of temperature changes more precisely, ensuring the safe operation of the system and facilitating timely implementation of appropriate measures to address temperature anomalies.

[0079] It should be noted that the specific content of the different levels of early warning response is as follows: when the proportion of temperature exceeding the absolute temperature threshold or the degree of exceeding the relative temperature threshold reaches the set level one early warning standard, a level one early warning is triggered, a local audible and visual alarm is activated, and a text message notification is sent to relevant operation and maintenance personnel.

[0080] When the temperature exceeds the absolute temperature threshold by a certain percentage or the relative temperature threshold by a certain degree, and reaches the set level-two warning standard, a level-two warning is triggered, emergency lighting is activated, the system monitoring frequency is increased to once per second, and a pop-up reminder is pushed to relevant personnel through the application.

[0081] When the temperature exceeds the absolute temperature threshold by a certain percentage or the relative temperature threshold to the level set for a Level 3 warning, or when the temperature reaches the material's tolerance limit temperature, a Level 3 warning is triggered, which in turn shuts down the power supply to the equipment associated with the anomaly, activates the fire sprinkler system, and sends an emergency notification to all relevant personnel.

[0082] The management database stores fiber optic attenuation coefficients, constant temperature reference point temperatures, temperature calibration curves, early warning thresholds, temperature-location mapping tables, and historical temperature data.

[0083] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention, which are still covered within the protection scope of the present invention.

Claims

1. A distributed optical fiber temperature sensing system based on Raman scattering, characterized in that, The application relates to a temperature measurement system based on optical fiber distributed temperature sensing technology, which comprises the following modules: an optical signal excitation and separation module for separating Stokes light and anti-Stokes light through a beam splitter and a dual-wavelength optical filter, monitoring optical power in real time, and automatically adjusting laser output power; a signal acquisition and preprocessing module for dividing spatial positions based on an optical time domain reflection principle, calculating a minimum accumulation number algorithm, and performing digital accumulation noise reduction on scattered signals; a temperature solving module for solving temperature through a Stokes light and anti-Stokes light intensity ratio, determining a temperature corresponding spatial position by using an optical time domain reflection principle, and generating a temperature distribution curve; a calibration correction module for selecting a constant temperature reference point, fitting a temperature deviation curve to generate a calibration coefficient, correcting temperature and calibrating a calibration curve, and simultaneously compensating optical intensity attenuation; a real-time monitoring and early warning module for setting multi-stage temperature early warning thresholds, monitoring temperature abnormal points, recording abnormal information and triggering corresponding grade early warning responses; a management database for storing optical fiber attenuation coefficients, constant temperature reference point temperatures, temperature calibration curves, early warning thresholds, temperature-position mapping tables and historical temperature data; a specific compensation method for optical intensity attenuation is as follows: a sensing optical fiber is divided into small segments with fixed lengths according to length, initial attenuation coefficients of each segment of the sensing optical fiber are obtained from a management database, a model of attenuation coefficient change with temperature is established, trapezoidal integral method is used to approximately calculate the cumulative attenuation amount from the beginning of the sensing optical fiber to a position on the sensing optical fiber, a compensation factor is calculated according to the attenuation amount, scattered light intensity at the position is compensated, and finally compensated light intensity is obtained to correct the corresponding relationship between temperature and light intensity; The model of the attenuation coefficient changing with temperature is wherein is the initial attenuation coefficient of the segment fiber, is the initial attenuation coefficient of the segment fiber, , is the temperature-dependent attenuation coefficient, typically 0.002 dB / km / C, is the environmental temperature change amount, for a certain position on the sensing fiber, the cumulative attenuation amount from the beginning of the sensing fiber to the position is approximately calculated by trapezoidal integration method wherein is the serial number of the segment, is the initial attenuation coefficient of the segment fiber, is the initial attenuation coefficient of the segment fiber, is the initial attenuation coefficient of the segment fiber, is the initial attenuation coefficient of the segment fiber, and a compensation factor is calculated according to the attenuation amount , the scattered light intensity at the position is compensated as follows: to obtain the final compensated light intensity .​ 2. A distributed optical fiber temperature sensing system based on Raman scattering according to claim 1, characterized in that, a specific analysis method of the optical signal excitation and separation module is as follows: laser pulses are injected into the sensing optical fiber, backscattered light generated when the laser pulses propagate in the sensing optical fiber is preliminarily separated through the beam splitter, and Stokes light and anti-Stokes light are further separated by using the dual-wavelength optical filter; the powers of the separated Stokes light and anti-Stokes light are monitored, and when the monitored optical power deviates from a set reasonable range of optical power, an alarm mechanism is triggered, and the laser output power is automatically adjusted for compensation.

3. A distributed optical fiber temperature sensing system based on Raman scattering according to claim 1, characterized in that, a specific analysis method of dividing spatial positions is as follows: segmentation parameters of a single measurement scattered signal are preset, the segmentation parameters include spatial position ranges corresponding to each data segment, and the spatial position ranges are determined based on an optical time domain reflection principle and in combination with the length of the sensing optical fiber; based on system noise characteristics and a target signal-to-noise ratio, a minimum accumulation number meeting the signal quality requirement is calculated, a light pulse emission module is controlled to inject laser pulses into the sensing optical fiber, scattered signals containing temperature information are excited and generated, and the scattered signals are transmitted to a digital accumulation unit for photoelectric conversion and digital processing; the digitalized scattered signals are time domain segmented, each time window corresponds to a data segment, each time window is converted into a specific spatial position area on the sensing optical fiber, and each segmented data segment is stored in a corresponding spatial position buffer area according to the corresponding relationship.

4. A distributed optical fiber temperature sensing system based on Raman scattering according to claim 3, characterized in that, a specific analysis method of the minimum accumulation number is as follows: The white noise power spectral density of the system is obtained by measuring the output of the system without signal input, the working bandwidth of the system and the absolute temperature of the working environment of the system are determined, the target signal-to-noise ratio is set according to the temperature measurement accuracy requirement, the target signal-to-noise ratio is converted from decibels to a linear value, and the linear value is brought into a calculation formula of the minimum accumulation number to obtain the minimum accumulation number that meets the signal quality requirement.

5. A distributed optical fiber temperature sensing system based on Raman scattering according to claim 4, characterized in that, The specific analysis method of the digital accumulation and noise reduction of the scattering signal is as follows: According to the minimum accumulation number, multiple measurements are performed, each measurement generates a scattering signal data segment corresponding to each spatial position and is stored in a corresponding cache area, and multiple groups of scattering signal data segmented by spatial positions are formed; For the same spatial position cache area, each data segment corresponding to the multiple measurements is extracted in sequence, the values of the corresponding data points in the multiple measurement signals of the same spatial position are superimposed and summed, and the sum of the superimposed signals is divided by the number of measurements to obtain the mean data point of the spatial position; The data segments of all spatial positions are traversed to generate a mean sequence containing the mean data points of each spatial position.

6. A distributed optical fiber temperature sensing system based on Raman scattering according to claim 5, characterized in that, The specific analysis method of the temperature corresponding to the spatial position is as follows: From the mean sequence, the Stokes light signal intensity value and the anti-Stokes light signal intensity value corresponding to the same spatial position are extracted respectively, the ratio of the Stokes light intensity value to the anti-Stokes light intensity value is calculated, and the Raman scattering intensity ratio is obtained; A preset temperature calibration curve is called, the calibration curve is a mapping relationship between the Raman scattering intensity ratio and the temperature value, the Raman scattering intensity ratio is substituted into the calibration curve, and the temperature value of the corresponding spatial position is calculated.

7. A distributed optical fiber temperature sensing system based on Raman scattering according to claim 6, characterized in that, The specific analysis method of the temperature calculation module is as follows: The starting time of the laser pulse injected by the optical pulse emission module to the sensing optical fiber is recorded, and the receiving time of the scattering signal to the photoelectric conversion module is detected, and the time difference between the receiving time and the starting time is calculated; The material refractive index parameter of the sensing optical fiber is obtained, based on the optical time domain reflection principle, the time difference is multiplied by the speed of light and divided by twice the material refractive index, and the spatial position distance corresponding to the scattering signal is calculated; The spatial position distance is mapped to the specific physical position coordinates on the sensing optical fiber, and a one-to-one correspondence between the temperature value and the physical position coordinates is established; All temperature values of the spatial positions calculated in the same measurement period are associated with the corresponding physical position coordinates to generate a temperature-position mapping table, and based on the temperature-position mapping table, a continuous temperature distribution curve is generated with the physical position as the horizontal axis and the temperature value as the vertical axis.

8. A distributed optical fiber temperature sensing system based on Raman scattering according to claim 1, characterized in that, The specific analysis method of the calibration curve is as follows: Known-temperature constant reference points are arranged at the beginning, middle and end positions of the sensing optical fiber, and the standard temperature values of the constant reference points are automatically collected at a set time interval, which are recorded as the standard temperature values of the constant reference points at each time point; The standard temperature value of each constant temperature reference point at each time point is subtracted from the corresponding temperature value on the temperature calibration curve to form a temperature deviation curve, the temperature deviation curve is fitted to generate a calibration coefficient matrix, the calibration coefficient matrix is substituted into a temperature correction formula, the linear correction mode or the nonlinear correction mode is determined in real time according to the temperature fluctuation range, and the temperature calibration curve is recalibrated by using the corrected temperature value.

9. A distributed optical fiber temperature sensing system based on Raman scattering according to claim 1, characterized in that, The specific analysis method of the real-time monitoring and early warning module is as follows: A plurality of temperature early warning thresholds are set, when the temperature of a certain position of the sensing optical fiber is detected to exceed a certain early warning threshold, the position is determined as a temperature abnormal point, and the temperature value of the abnormal point and the time when the abnormality is monitored are recorded; Based on the calibrated and corrected temperature data, a plurality of temperature early warning thresholds are preset, the plurality of temperature early warning thresholds include an absolute temperature threshold, a relative temperature threshold calculated based on historical temperature data, and a temperature change rate threshold, wherein the absolute temperature threshold is used to set the specific temperature value of different early warning levels, the relative temperature threshold is calculated based on statistical quantities such as the mean and standard deviation of the historical temperature data, and the temperature change rate threshold is used to measure the amplitude of the temperature change per unit time; The temperature of each position of the sensing optical fiber is monitored in real time, when the temperature of a certain position meets any of the following conditions, the position is determined as a temperature abnormal point: the temperature exceeds the absolute temperature threshold, the temperature exceeds the relative temperature threshold calculated based on the historical temperature data, and the temperature change rate exceeds the set temperature change rate threshold; After determining that a certain position is a temperature abnormal point, the temperature value of the abnormal point and the time when the abnormality is monitored are recorded, the specific physical position coordinates of the abnormal point on the sensing optical fiber are obtained according to the temperature distribution curve, and different levels of early warning responses are triggered according to the deviation degree of the temperature value of the abnormal point from the plurality of preset temperature early warning thresholds.

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