Mining distributed optical fiber temperature measurement method, system and device

Abstract

The invention relates to the technical field of temperature measurement, and discloses a mining distributed optical fiber temperature measurement method, system and device, and the method comprises the steps: synchronously injecting a temperature measurement pulse and a reference pulse, and collecting an optical fiber backscattering signal; strain-free temperature data are obtained through anti-strain demodulation and discrete temperature integration; performing strain compensation according to the real-time difference value to generate strain compensation temperature data; meanwhile, on the basis of optical fiber space distribution, weighting processing is conducted on the reference pulse temperature drift feature space to obtain compensation quantity; and the compensation amount and strain compensation data are fused, a mining global heat supply network is constructed through a temperature field reconstruction algorithm, and an anti-drift temperature field is output. A double-path anti-drift mechanism is realized through double pulse pairs, mechanical interference is eliminated in combination with anti-strain demodulation, and a temperature drift error is corrected in real time by utilizing space weighting and dynamic fusion, so that high-precision and high-stability distributed temperature monitoring is realized in a complex mine environment, and the problems of drift accumulation and precision attenuation in long-distance optical fiber temperature measurement are solved.

Description

Technical Field

[0001] This invention relates to the field of temperature measurement technology, and in particular to a distributed optical fiber temperature measurement method, system and device for mining. Background Technology

[0002] Optical fibers are subject to coupling interference from mechanical strain and temperature changes, making it difficult to effectively distinguish between strain effects and actual temperature changes during backscattered signal demodulation. This results in insufficient adaptability to non-uniform strain, leading to temperature measurement distortion. Furthermore, the uneven distribution of the thermal field in mine spaces and the existence of long-term temperature drift, coupled with a lack of dynamic spatial compensation mechanisms for these drift characteristics, make it difficult to suppress systematic drift errors caused by environmental heat accumulation over long distances. This severely impacts the accuracy of global temperature field reconstruction.

[0003] A single pulse is only used for spatial compensation and has no calibration traceability function. After long-term operation, the pulse characteristic drift cannot be detected. Therefore, it relies too much on historical data to fit the strain coefficient and cannot detect the strain transmissibility change caused by the aging of the optical cable. At the same time, temperature drift is only compensated at the end and no forward feedback link is established, which causes the error to be amplified along the fiber chain and affects the stability of the temperature data output over time. Summary of the Invention

[0004] This invention provides a method, system, and device for distributed optical fiber temperature measurement in mining, the main purpose of which is to solve the problem of low efficiency in generating reference information based on artificial intelligence and smart homes.

[0005] To achieve the above objectives, the present invention provides a distributed optical fiber temperature measurement method for mining, comprising:

[0006] S1. Simultaneously inject temperature measurement pulses and reference pulses into the optical fiber and collect the backscattered light signal of the optical fiber;

[0007] S2. Perform anti-strain interference demodulation on the backscattered light signal, and obtain the strain-free temperature data of the optical fiber by discrete temperature integration.

[0008] S3. Based on the real-time difference of the strain-free temperature data, perform strain compensation calculation on the strain-free temperature data to generate strain-compensated temperature data for the optical fiber.

[0009] S4. Based on the spatial position distribution of the optical fiber, the temperature drift characteristics in the reference pulse are spatially weighted to obtain the spatial distribution compensation amount of the optical fiber.

[0010] S5. Integrate the spatial distribution compensation amount and the strain compensation temperature data, construct the mine-use full-domain heating network through the temperature field reconstruction algorithm, and output anti-drift temperature distribution data.

[0011] In a preferred embodiment, the synchronous injection of the temperature measurement pulse and the reference pulse into the optical fiber, and the acquisition of the backscattered light signal of the optical fiber, includes:

[0012] The phase convergence pulse pair of the optical fiber is obtained by spatiotemporally aligning the temperature measurement pulse and the reference pulse;

[0013] The phase convergence pulse pair is injected into the optical fiber to obtain the optical signal excitation response of the optical fiber;

[0014] The backscattered light signal of the optical fiber is obtained by polarization-based binning of the excitation response of the optical signal.

[0015] In a preferred embodiment, when performing anti-strain interference demodulation on the backscattered light signal and obtaining the strain-free temperature data of the optical fiber through discrete temperature integration, the process includes:

[0016] The backscattered light signal is decoupled using two parameters to obtain the temperature-sensitive frequency shift of the optical fiber.

[0017] The temperature-sensitive frequency shift is differentially smoothed to obtain the temperature change gradient of the optical fiber.

[0018] The temperature gradient is integrated piecewise to obtain the strain-free temperature data of the optical fiber.

[0019] In a preferred embodiment, the step of performing strain compensation calculations on the strain-free temperature data based on the real-time difference of the strain-free temperature data to generate strain-compensated temperature data for the optical fiber includes:

[0020] The strain-free data is subjected to double-pulse stripping to obtain the temperature gradient field of the light.

[0021] Thermal drift balancing of the temperature gradient field yields the strain compensation coefficient of the optical fiber.

[0022] The strain compensation coefficient is fitted with thermal output strain to obtain the strain compensation temperature data of the optical fiber.

[0023] In a preferred embodiment, the step of performing thermal drift balancing on the temperature field to obtain the strain compensation coefficient of the optical fiber includes:

[0024] The temperature gradient field is synthesized by vector magnitude to obtain the global temperature difference distribution matrix of the optical fiber;

[0025] The thermal output strain of the optical fiber is obtained by performing a discrete cosine transform on the global temperature difference distribution matrix.

[0026] The strain compensation coefficient of the optical fiber is obtained by performing a linear regression of thermal expansion on the thermal output strain.

[0027] In a preferred embodiment, the step of performing spatial weighting processing based on the spatial position distribution of the optical fiber and the temperature drift characteristics in the reference pulse to obtain the spatial distribution compensation amount of the optical fiber includes:

[0028] The spatial position distribution of the optical fiber is mapped point by point in the time domain to obtain the spatial position coordinate matrix of the optical fiber;

[0029] The spatial attenuation matrix of the optical fiber is obtained by amplifying the scattering loss of the temperature drift characteristics of the reference pulse.

[0030] The spatial distribution compensation amount of the optical fiber is obtained by performing spatial feature convolution on the spatial attenuation matrix and the spatial position coordinate matrix.

[0031] In a preferred embodiment, the step of performing spatial feature convolution between the spatial attenuation matrix and the spatial position coordinate matrix to obtain the spatial distribution compensation amount of the optical fiber includes:

[0032] The temperature drift weighting factor of the optical fiber is obtained by normalizing the spatial attenuation matrix based on the strain compensation coefficient.

[0033] The temperature characteristics of the temperature measurement pulse are convolved and fused with the temperature drift weighting factor to obtain the weighted temperature drift.

[0034] The spatial distribution compensation amount of the optical fiber is obtained by applying a compensation gain to the weighted temperature drift based on the spatial position coordinate matrix.

[0035] In a preferred embodiment, when fusing the spatial distribution compensation amount and the strain compensation temperature data, constructing a mine-use global heating network using a temperature field reconstruction algorithm, and outputting drift-resistant temperature distribution data, the process includes:

[0036] The spatial distribution compensation amount and the strain compensation temperature data are spatially weighted and superimposed to obtain the fused temperature field of the optical fiber;

[0037] The drift residual is filtered on the fused temperature field to obtain the anti-drift temperature field of the optical fiber;

[0038] Deviation extraction is performed on the anti-drift temperature field to obtain the anti-drift temperature distribution data of the optical fiber. The calculation formula for the deviation extraction is as follows:

[0039]

[0040] For drift-resistant temperature distribution data, The temperature characteristics of the temperature measurement pulse, The temperature drift characteristics of the reference pulse, The strain compensation coefficient is... This is the strain-compensated temperature data for the current time. It is the strain compensation temperature data from the previous time point. It is a time interval.

[0041] To address the above problems, the present invention also provides a distributed optical fiber temperature measurement system for mining, the system comprising:

[0042] A backscattered light signal collection module is used to synchronously inject temperature measurement pulses and reference pulses into the optical fiber and collect the backscattered light signal of the optical fiber.

[0043] The strain-free temperature data generation module is used to perform anti-strain interference demodulation on the backscattered light signal and obtain the strain-free temperature data of the optical fiber through discrete temperature integration.

[0044] The strain-compensated temperature data generation module is used to perform strain compensation calculations on the strain-free temperature data based on the real-time difference of the strain-free temperature data, and generate strain-compensated temperature data for the optical fiber.

[0045] The spatial distribution compensation generation module is used to perform spatial weighting processing on the temperature drift characteristics in the reference pulse based on the spatial position distribution of the optical fiber, so as to obtain the spatial distribution compensation of the optical fiber.

[0046] The anti-drift temperature distribution data generation module is used to fuse the spatial distribution compensation amount and the strain compensation temperature data, construct the mine-use full-area heating network through the temperature field reconstruction algorithm, and output the anti-drift temperature distribution data.

[0047] The present invention also provides a distributed optical fiber temperature measurement device for mining, the device including a memory and a processor, the memory storing a computer program that can run on the processor, and the processor executing the computer program to implement the distributed optical fiber temperature measurement method for mining described above.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] 1. This invention employs the synchronous injection of orthogonal polarization diversity reference pulses and acousto-optic modulated temperature measurement pulses. By synchronously forming a cooperative sensing field within the optical fiber, reciprocal symmetry is maintained, eliminating random polarization drift caused by channel curvature. This solves the coupling problem between temperature strain and polarization in the single-pulse scheme from the signal source, ensuring maximum temperature measurement accuracy.

[0050] 2. The dual-pulse pair constructs a closed-loop calibration chain through real-time mutual inspection. Combined with multi-sensor fusion, it monitors the deviation of data and automatically triggers calibration, determines the temperature drift of the acousto-optic modulator and the wavelength drift of the laser, activates the thermoelectric cooler in real time to stabilize the frequency and adjusts the injection current compensation, solves the reference drift problem caused by stress changes and other factors in the mine temperature measurement system, and achieves long-term stability of fiber optic temperature measurement in mines. Attached Figure Description

[0051] Figure 1 This is a schematic flowchart of a distributed optical fiber temperature measurement method for mining, provided in an embodiment of the present invention.

[0052] Figure 2 This is a functional block diagram of a distributed optical fiber temperature measurement system for mining, provided in an embodiment of the present invention.

[0053] Figure 3 This is a schematic diagram illustrating the structural composition of a distributed optical fiber temperature measurement device for mining, as described in an embodiment of the present invention.

[0054] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0055] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0056] This application provides a method for distributed fiber optic temperature measurement in mining. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cluster of cloud servers. The server can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0057] Reference Figure 1 The diagram shown is a flowchart illustrating a distributed optical fiber temperature measurement method for mining according to an embodiment of the present invention. In this embodiment, the reference information generation method based on artificial intelligence and smart home includes:

[0058] In this embodiment of the invention, when the synchronous injection of the temperature measurement pulse and the reference pulse into the optical fiber is used to acquire the backscattered light signal of the optical fiber, it is specifically used for:

[0059] The phase convergence pulse pair of the optical fiber is obtained by spatiotemporally aligning the temperature measurement pulse and the reference pulse;

[0060] The phase convergence pulse pair is injected into the optical fiber to obtain the optical signal excitation response of the optical fiber;

[0061] The backscattered light signal of the optical fiber is obtained by polarization-based binning of the excitation response of the optical signal.

[0062] Specifically, the temperature measurement pulse and the reference pulse are precisely synchronized in terms of pulse transmission timing and propagation path in the optical fiber to ensure that they are detected at the same optical fiber position and time. At the same time, the phase difference information of the two pulses is extracted through the aligned pulses to form a pair of signals with a stable phase relationship, providing basic data for subsequent phase demodulation.

[0063] Specifically, a spatiotemporally aligned phase-converging pulse pair, namely the temperature measurement pulse and the reference pulse, is coupled into the optical fiber under test. During propagation, the pulse pair interacts with the optical fiber medium to generate a backscattered signal carrying temperature strain information.

[0064] Specifically, the backscattered light signal returned by the optical fiber is separated and detected according to different polarization states to avoid signal fading caused by random changes in polarization states. At the same time, the multi-polarized signals after diversity are selected and synthesized by averaging and other methods to generate a stable backscattered light signal and eliminate polarization-related noise.

[0065] Furthermore, the accuracy of temperature measurement is improved by referencing the random phase drift of the temperature measurement pulse during transmission. At the same time, the aligned pulse pair can effectively suppress the influence of non-temperature measurement factors such as inherent birefringence of optical fiber and polarization fluctuations on the phase.

[0066] Furthermore, by injecting pulse pairs, the scattering effect of the optical fiber is excited, and the temperature is converted into measurable characteristics such as phase difference and frequency drift. By utilizing the timing characteristics of the pulse pairs, namely the pulse interval and repetition frequency, the temperature distribution at different locations along the optical fiber can be analyzed.

[0067] Furthermore, by fusing data from multiple polarization channels, complete temperature strain information is preserved, which solves the problem of random fluctuations in polarization state caused by factors such as fiber birefringence and external disturbances, ensuring stable scattering signal intensity and avoiding information loss caused by single polarization detection.

[0068] In summary, phase-converged pulse pairs eliminate common-mode noise through differential processing, accurately improving temperature measurement sensitivity. Spatiotemporal alignment can solve phase mismatch caused by pulse path differences, ensuring signal synchronization in scenarios with rapid temperature changes and avoiding data lag and distortion.

[0069] In summary, the symmetry of the phase-converging pulse pair can suppress common-mode noise and improve the signal-to-noise ratio. At the same time, the excitation response signal is a direct source of temperature information. Its amplitude, phase and spectral characteristics are linearly related to temperature changes. Through time-domain reflection, the scattered signal can be used to locate temperature anomalies by returning to the time.

[0070] In summary, polarization diversity greatly reduces signal fluctuations caused by polarization fading, ensuring the continuity of long-term detection data. At the same time, the signal-to-noise ratio of the synthesized backscattered signal is increased by several decibels, enhancing the sensitivity of weak signal detection. It also ensures the robustness of the distributed temperature measurement system in high birefringence fiber and strong electromagnetic interference environments, providing a high-quality signal foundation for subsequent phase demodulation or frequency domain analysis.

[0071] In this embodiment of the invention, when performing anti-strain interference demodulation on the backscattered light signal and obtaining the strain-free temperature data of the optical fiber through discrete temperature integration, it is specifically used for:

[0072] The backscattered light signal is decoupled using two parameters to obtain the temperature-sensitive frequency shift of the optical fiber.

[0073] The temperature-sensitive frequency shift is differentially smoothed to obtain the temperature change gradient of the optical fiber.

[0074] The temperature gradient is integrated piecewise to obtain the strain-free temperature data of the optical fiber.

[0075] Specifically, temperature-sensitive parameters and strain-sensitive parameters are extracted simultaneously from the backscattered light signal to decouple their cross-influence. Based on the decoupled data, the frequency shift caused solely by temperature changes is accurately calculated, eliminating the influence of interference factors such as strain.

[0076] Specifically, the temperature-sensitive frequency shift is calculated by first-order differentiation along the fiber length to obtain the frequency shift rate per unit distance. High-frequency noise in the differentiation process is suppressed by moving average, wavelet transform, and Savitzky-Golay filtering algorithm, while preserving the impurity-free temperature gradient characteristics.

[0077] Specifically, the temperature change gradient is divided into several continuous intervals along the fiber length direction. The integral operation is performed independently on each interval to restore the absolute temperature change of that interval. Combined with the initial temperature calibration value, the integral result is converted into absolute temperature distribution data under strain-free conditions, eliminating the residual temperature decoupling error caused by fiber deformation.

[0078] Furthermore, it addresses the issue of temperature and strain cross-sensitivity that cannot be distinguished by single-parameter measurement, achieving high-precision extraction of pure temperature information. Through dual-parameter joint analysis, it suppresses the influence of non-temperature factors such as fiber optic mechanical vibration and stress deformation.

[0079] Furthermore, the discrete frequency shift data is transformed into a continuous temperature change rate, revealing abrupt temperature changes along the fiber optic cable. At the same time, the amplification effect of direct differentiation on measurement noise is eliminated, ensuring the reliability of the gradient signal.

[0080] Furthermore, the gradient information is transformed into an intuitively interpretable absolute temperature value, realizing the transformation from relative change to absolute distribution. Based on the strain-insensitive region, a segmentation strategy is used to further reduce the impact of strain-temperature cross-sensitivity on the final result.

[0081] In summary, the error of the temperature-sensitive frequency shift after decoupling can be controlled within a very small range, making it suitable for scenarios involving temperature changes and strain in optical fibers, and providing a data foundation for subsequent multi-parameter fusion.

[0082] In summary, the high absolute value region of the temperature gradient can accurately identify fault points, improve spatial resolution to the meter level, upgrade single-point temperature information to gradient field distribution, support thermodynamic simulation and structural health diagnosis, and achieve ultra-early warning of temperature anomalies through gradient trend analysis.

[0083] In summary, piecewise integration can compensate for the cumulative error over long distances, reduce the overall temperature measurement deviation of optical fibers caused by the temperature measurement variance in the optical fiber region, and convert abstract gradient values ​​into absolute temperature values ​​that can be directly used for subsequent analysis, providing accurate temperature monitoring for non-uniform strain fields.

[0084] In this embodiment of the invention, the step of performing strain compensation calculations on the strain-free temperature data based on the real-time difference of the strain-free temperature data to generate strain-compensated temperature data for the optical fiber is specifically used for:

[0085] The strain-free data is subjected to double-pulse stripping to obtain the temperature gradient field of the light.

[0086] Thermal drift balancing of the temperature gradient field yields the strain compensation coefficient of the optical fiber.

[0087] The strain compensation coefficient is fitted with thermal output strain to obtain the strain compensation temperature data of the optical fiber.

[0088] Specifically, the signal components independently excited by the temperature measurement pulse and the reference pulse are separated from the strain-free temperature data to eliminate common-mode noise and system drift. Based on the stripped dual-pulse data, a high-precision temperature gradient field is reconstructed through differential operations, highlighting the characteristics of local temperature icons.

[0089] Specifically, by analyzing the deviation between the temperature gradient field and the known reference temperature, the system drift error caused by environmental thermal fluctuations is dynamically calibrated, and the accumulated error in long-term monitoring is eliminated. Based on the balanced temperature gradient field and combined with the characteristics of optical fiber materials, the influence ratio of strain on temperature measurement is calculated, and the dynamic compensation coefficient matrix is ​​obtained.

[0090] Specifically, based on the strain compensation coefficient, a polynomial regression model of the coupling relationship between temperature and strain is established to dynamically decouple the interference of strain on temperature measurement. The fitted model is then applied to the original temperature data to output a high-precision temperature value after strain compensation, thus eliminating the temperature measurement deviation caused by fiber deformation.

[0091] Furthermore, by analyzing the time-domain and frequency-domain coherence of the dual-pulse pair, the environmental background noise and system background drift are dynamically separated, and the coherent signal component caused only by temperature transients in the Brillouin frequency shift is accurately extracted. The time-frequency resolution of the transient temperature gradient is enhanced by utilizing the differential response of the inter-pulse frequency shift, thereby improving the signal-to-noise ratio and detection sensitivity for millisecond-level rapid temperature change events.

[0092] Furthermore, by dynamically constructing the strain-temperature coupling transfer matrix, the system intrinsic drift induced by gradual changes in ambient temperature is analyzed in real time, and micro-strain level interference components are quantitatively removed based on the intrinsic orthogonal decomposition algorithm, ultimately achieving millikelvin-level inversion accuracy of the thermodynamic pure temperature field.

[0093] Furthermore, by constructing a dynamic tensor analysis model of the cross-sensitivity factor of strain and temperature, the nonlinear coupling interference between thermal expansion effect and mechanical stress in frequency shift response is decoupled in real time. Based on the dynamic matrix regularization method, the coupling effect of multiple physical fields is separated, realizing the inversion of a single temperature parameter under complex temperature variation environment and eliminating the phase aliasing error in traditional dual-parameter demodulation.

[0094] In summary, the skill-based micro-gradient detection can identify weak temperature gradients with high precision, improve effective sensitivity, suppress common-mode interference such as light source fluctuations and fiber jitter, improve the gradient field signal-to-noise ratio, enhance anti-interference capabilities, and achieve sub-meter level spatial resolution of the gradient field, enabling precise fault location and making it suitable for monitoring local high-density contacts.

[0095] In summary, this technology reduces temperature drift error during continuous monitoring, ensuring long-term monitoring stability. In scenarios where vibration and strain coexist, it adaptively reduces temperature measurement errors, and the compensation coefficient can be correlated with historical data to support fiber optic aging status assessment and lifetime prediction.

[0096] In summary, the compensated temperature error is more accurate, making it suitable for environments with strong vibration and large deformation, avoiding error interference. At the same time, the fitting model parameters can be dynamically updated to adapt to long-term performance changes such as fiber aging and coating damage.

[0097] In this embodiment of the invention, the step of performing thermal drift balancing on the temperature field to obtain the strain compensation coefficient of the optical fiber is specifically used for:

[0098] The temperature gradient field is synthesized by vector magnitude to obtain the global temperature difference distribution matrix of the optical fiber;

[0099] The thermal output strain of the optical fiber is obtained by performing a discrete cosine transform on the global temperature difference distribution matrix.

[0100] The strain compensation coefficient of the optical fiber is obtained by performing a linear regression of thermal expansion on the thermal output strain.

[0101] Specifically, the multi-dimensional data of the temperature gradient field, namely axial, radial, and polarization state differences, are fused into a scalar magnitude through vector operations to eliminate directional interference and highlight the effective temperature difference characteristics. Based on the synthesized magnitude, a temperature difference distribution matrix is ​​constructed along the spatial and temporal dimensions of the optical fiber to quantify the intensity of temperature change at each location relative to the reference standard.

[0102] Specifically, by implementing discrete cosine frequency domain projection on the global temperature difference distribution matrix, the temperature gradient information in the spatial topology and time evolution sequence is decomposed into multi-scale frequency band components, accurately separating the intrinsic modes and random noise basis that characterize the dynamic characteristics of the heat source, and realizing compressed sensing and dynamic baseline reconstruction of the thermodynamic characteristic spectrum.

[0103] Specifically, based on data on thermal output strain and temperature change, a linear regression model is established to quantify the thermal expansion characteristics of optical fiber materials and determine the mathematical relationship between strain and temperature. The slope parameter is extracted through regression analysis and converted into a strain compensation coefficient, which is used to dynamically correct thermally induced strain errors in temperature measurements.

[0104] Furthermore, the complex directional gradient field is transformed into an intuitive scalar temperature difference index, simplifying the analysis process. Spatiotemporal information is integrated in matrix form, supporting the tracking of temperature anomaly propagation paths and the identification of thermodynamic patterns.

[0105] Furthermore, by utilizing the energy compression characteristics of discrete cosine transform, the effective low-frequency thermal signal in the temperature difference matrix is ​​retained, while the temperature-dominated strain component is extracted from the complex global data, avoiding interference from non-thermal factors such as mechanical vibration, and suppressing random noise and short-term interference.

[0106] Furthermore, by dynamically decoupling the temperature-induced strain effect and complex background noise through the thermo-constitutive equation, a multi-field coupling compensation model based on physical mechanisms is constructed to achieve generalized adaptation for different optical fiber materials, laying environments, and service stages. By utilizing the unsteady-state thermal conduction characteristics to strip away time-varying interference in real time, the consistency of the temperature signal evolution trajectory across cycles during long-term monitoring is ensured, thereby improving anti-time drift performance.

[0107] In summary, modulus synthesis can amplify local temperature difference signals and improve the signal-to-noise ratio for detecting minor anomalies. At the same time, matrix data can be combined with real-time monitoring scenarios of optical fibers to classify fault types and predict thermal runaway trends through matrix time series analysis.

[0108] In summary, the Discrete Cosine Transform (DCT) improves the signal-to-noise ratio of thermal strain signals and enhances the detection capability of weak temperature changes. By retaining a few key DCT coefficients, it improves data compression and accelerates data propagation, providing high-purity input for subsequent joint temperature-strain inversion and supporting structural steady-state monitoring.

[0109] In summary, the accuracy of temperature measurement after compensation has achieved a leap in magnitude. Its core lies in accurately mapping the thermal expansion response characteristics of optical fiber materials through thermo-coupling regression coefficients, adaptively identifying the phase transition threshold and thermal hysteresis curve of different sensing optical fibers, and achieving cross-medium compatibility. At the same time, the abnormal regression coefficients can accurately locate hidden faults such as microcracks and splice loss in optical fibers, forming a self-diagnostic capability.

[0110] In an embodiment of the present invention, the step of performing spatial weighting processing based on the spatial position distribution of the optical fiber and the temperature drift characteristics in the reference pulse to obtain the spatial distribution compensation amount of the optical fiber includes:

[0111] The spatial position distribution of the optical fiber is mapped point by point in the time domain to obtain the spatial position coordinate matrix of the optical fiber;

[0112] The spatial attenuation matrix of the optical fiber is obtained by amplifying the scattering loss of the temperature drift characteristics of the reference pulse.

[0113] The spatial distribution compensation amount of the optical fiber is obtained by performing spatial feature convolution on the spatial attenuation matrix and the spatial position coordinate matrix.

[0114] Specifically, based on the principle of optical time-domain reflection, the signal return time of each scattering point in the optical fiber is converted into the corresponding spatial distance, achieving a precise time-space correspondence. Combined with the optical fiber laying path information, the one-dimensional distance data is mapped into a three-dimensional spatial position coordinate matrix, which includes the absolute position of each monitoring point and the relative optical fiber length.

[0115] Specifically, the signal attenuation characteristics of the reference pulse under different temperature conditions are analyzed, and its scattering loss law with temperature variation is quantified. The temperature-sensitive scattering component is amplified by gain control and signal processing to highlight its correspondence with spatial location. At the same time, the amplified loss data is arranged according to the fiber length dimension to generate a spatial attenuation matrix. The matrix element values ​​reflect the signal attenuation intensity caused by temperature at each location point.

[0116] Specifically, a convolution operation is performed between the spatial attenuation matrix reflecting temperature-related loss and the spatial position coordinate matrix mapping geometric position to establish an attenuation-position coupling model and extract systematic error features related to spatial distribution. A spatial distribution compensation amount is generated using a convolution kernel function to quantify signal deviations at different locations caused by non-temperature factors such as fiber bending and installation stress.

[0117] Furthermore, by constructing a spatial reference framework for fiber optic geometric topology mapping, a high-precision position coding reference is provided for distributed temperature strain data, enabling dynamic correlation between measurement results and real physical coordinates. Based on the spatial registration engine, it seamlessly connects with geographic information systems, building information models, and digital twin platforms, ensuring millimeter-level alignment and dynamic fusion of temperature fields in multi-source heterogeneous spatial data.

[0118] Furthermore, the scattering loss caused by temperature is separated from the inherent attenuation of the optical fiber, providing pure characteristics for subsequent temperature inversion. By using the attenuation matrix of the reference pulse, the signal distortion of the temperature measurement pulse is dynamically corrected, improving the consistency of long-distance monitoring.

[0119] Furthermore, by establishing a location-dependent optical fiber geometric transfer function model, the coupling mechanism of spatial layout factors such as bending deformation, torsional stress, and laying path on temperature drift is accurately decoupled. The differential response characteristics are used to separate the location-dependent attenuation from the real temperature signal, realizing compensation vector field decision-making based on physical mechanism tracing, thereby avoiding misjudgment of temperature gradient caused by spatial heterogeneity.

[0120] In summary, the coordinate matrix can be directly imported into a 3D operations and maintenance platform to achieve three-dimensional localization of temperature anomalies, share coordinate references with other equipment, and trigger targeted anomaly reviews. Simultaneously, as the base data for infrastructure digital twins, the coordinate matrix supports real-time updates and historical traceability.

[0121] In summary, the attenuation matrix can identify weak temperature-related losses, significantly reducing temperature fluctuations in optical fibers. Abnormal attenuation regions can be predicted in advance through matrix mutation points. Furthermore, it can be integrated with multiple parameters to effectively assess the stability of optical fibers.

[0122] In summary, the dynamic update of the compensation amount supports the real-time accuracy maintenance of mobile optical fibers. The spatial compensation amount can be used as a calibration parameter for digital twins to ensure the data consistency between virtual and real sensors. At the same time, after compensation, the temperature measurement error of optical fibers with non-ideal laying is reduced.

[0123] In this embodiment of the invention, the step of performing spatial feature convolution between the spatial attenuation matrix and the spatial position coordinate matrix to obtain the spatial distribution compensation amount of the optical fiber is specifically used for:

[0124] The temperature drift weighting factor of the optical fiber is obtained by normalizing the spatial attenuation matrix based on the strain compensation coefficient.

[0125] The temperature characteristics of the temperature measurement pulse are convolved and fused with the temperature drift weighting factor to obtain the weighted temperature drift.

[0126] The spatial distribution compensation amount of the optical fiber is obtained by applying a compensation gain to the weighted temperature drift based on the spatial position coordinate matrix.

[0127] Specifically, the spatial attenuation matrix is ​​standardized and corrected using a strain compensation coefficient to eliminate non-temperature-dependent attenuation interference caused by fiber deformation or installation stress, ensuring that the matrix data only reflects signal changes caused by temperature. The spatial attenuation is mapped to the [0,1] interval, and the difference between the spatial attenuation value at the current location and the minimum value in the spatial attenuation matrix is ​​divided by the difference between the maximum and minimum values ​​in the spatial attenuation matrix to obtain the temperature sensitivity weights for each spatial location, forming a temperature drift weight factor matrix.

[0128] Specifically, the original temperature characteristics of the temperature measurement pulse are convolved with the temperature drift weighting factor to dynamically adjust the contribution of temperature data at different spatial locations, highlighting high-reliability signals and suppressing noise in low-weight regions. The output is a fused weighted temperature drift, the value of which includes actual temperature change information and reflects the spatial differences in measurement reliability across different fiber optic segments.

[0129] Specifically, by combining the geometric information provided by the spatial coordinate matrix, the value from the current position to the fiber optic starting point is obtained and multiplied by the attenuation coefficient of the current fiber material. This product is then multiplied by a weighted drift amount to obtain the spatial distribution compensation of the fiber. Using the data after gain adjustment, a compensation matrix that strictly corresponds to the physical position of the fiber is output, accurately reflecting the temperature correction value required for each fiber segment.

[0130] Furthermore, the strain-temperature hybrid effect in the original attenuation matrix is ​​separated, retaining the pure temperature drift characteristics and improving the accuracy of temperature inversion. At the same time, the temperature calculation weights at different locations are adaptively adjusted according to the actual temperature sensitivity and differences of each fiber segment to avoid local errors caused by homogenization.

[0131] Furthermore, by using weighting factors to distinguish between high-quality fiber segments and high-error segments, intelligent weighting with self-aware data quality is achieved, incorporating the spatial non-uniformity of temperature drift into the calculation model to avoid residual errors caused by global compensation.

[0132] Furthermore, by constructing a position-aware spatial transformation model, a position-dependent compensation surface is dynamically generated for spatial layout parameters such as local bending curvature, torsion angle, and installation stress of the optical fiber. This eliminates the nonlinear coupling interference of geometric distortion on temperature drift, ensuring that the compensation amount of each spatial micro-element is precisely matched with its actual physical position, thereby solving the problem of spatial misalignment correction caused by traditional global mean compensation.

[0133] In summary, by adjusting the weighting factor, the axial consistency error of long-distance fiber optic temperature measurement is reduced, and temperature fluctuations in high-weight areas are monitored more closely, thus improving the sensitivity of local hotspot detection. Simultaneously, the temporal changes in the weighting factor can reflect the aging trend of the fiber, providing a basis for preventative maintenance.

[0134] In summary, the overall temperature uncertainty of complex paths in the weighted system is reduced, while data from high-weighted areas are given priority in control decisions, improving operational response efficiency. The convolution kernel parameters can be iteratively optimized by combining historical data, gradually approaching the optimal temperature calculation model for fiber optic networks.

[0135] In summary, this technology ensures consistent temperature measurement errors in mixed-layout scenarios, automatically compensates for measurement errors introduced by external influences, reduces stringent requirements on fiber optic laying accuracy, and allows spatial distribution compensation to be directly injected into the digital twin system, enabling millimeter-level temperature field synchronization between virtual and real sensors.

[0136] In an example of this invention, when fusing the spatial distribution compensation amount and the strain compensation temperature data, constructing a mine-use full-area heating network using a temperature field reconstruction algorithm, and outputting drift-resistant temperature distribution data, the process includes:

[0137] The spatial distribution compensation amount and the strain compensation temperature data are spatially weighted and superimposed to obtain the fused temperature field of the optical fiber;

[0138] The drift residual is filtered on the fused temperature field to obtain the anti-drift temperature field of the optical fiber;

[0139] Deviation extraction is performed on the anti-drift temperature field to obtain the anti-drift temperature distribution data of the optical fiber. The calculation formula for the deviation extraction is as follows:

[0140]

[0141] For drift-resistant temperature distribution data, The temperature characteristics of the temperature measurement pulse, The temperature drift characteristics of the reference pulse, The strain compensation coefficient is... This is the strain-compensated temperature data for the current time. It is the strain compensation temperature data from the previous time point. It is a time interval.

[0142] Specifically, the spatial distribution compensation amount and strain compensation temperature data are weighted and fused point by point according to spatial location, taking into account both global accuracy and local compensation requirements, and outputting a final temperature field that includes both strain compensation and spatial compensation, thus eliminating fiber deformation interference and correcting system errors introduced by installation geometry.

[0143] Specifically, the residual system drift signal is separated from the fused temperature field, and interference components of non-target temperature changes are identified through time-frequency analysis or adaptive filtering. Wavelet thresholding denoising and Kalman filtering are used to filter out residual drift in real time, preserving the true temperature change characteristics.

[0144] Specifically, It is a raw temperature signal containing the true temperature, strain noise, and system drift, which is directly excited by an acousto-optic modulated temperature measurement pulse. This signal serves as the main information carrier for temperature sensing, and the strain noise is pre-separated at the physical layer. It is a systematic error benchmark carried by the orthogonal polarization reference pulse, which characterizes the cumulative errors such as light source drift and detector aging. As a self-calibration scale, it locks the drift amount through the dual polarization equilibrium point and provides a spatial distribution compensation benchmark in real time. The process involves dividing the optical fiber into multiple discrete points, taking the modulus of the ratio of the temperature difference between two consecutive time points to the spatial resolution of the optical fiber, constructing a global temperature difference distribution matrix, and then applying DCT-II transformation to extract energy in different frequency domains. The energy values ​​are then sorted in descending order, and invalid noise is filtered out, retaining the corresponding percentage of low-frequency components as the principal coefficients of the temperature gradient DCT. The strain component caused by thermal expansion is separated from the original strain distribution demodulated from the Brillouin sensor channel. The difference between the current temperature and the initial temperature when the optical fiber was installed is multiplied by the thermal expansion coefficient of the optical fiber composite structure to obtain the thermal expansion strain value. At non-zero strain points, spatial filtering is used to separate the thermal strain values, which are then arranged into a vector. The thermal strain vector undergoes the same DCT-II transformation as described above, and the same filtering method is used to extract components in the same frequency band as the principal components of the temperature gradient as the principal coefficients of the thermal strain DCT. Finally, the product of the principal coefficients of the temperature gradient DCT and the principal coefficients of the thermal strain DCT is divided by the square of the principal coefficients of the temperature gradient DCT to obtain the strain compensation coefficient. The time derivative of the axial strain of the optical fiber is used to capture millisecond-level strain impacts.

[0145] Furthermore, by leveraging the dual advantages of dynamic fusion strain compensation and spatial compensation, the temperature drift error and mechanical deformation interference caused by differences in fiber optic paths are synergistically suppressed, eliminating spatial non-uniformity of temperature measurement data caused by uneven optical path length, bending angle, and environmental stress, thereby improving the spatial consistency and temporal stability of the temperature distribution across the entire field.

[0146] Furthermore, by iteratively optimizing the coupling mechanism of the compensation algorithm, the residual multi-order coupling nonlinear error during the fusion process is deeply suppressed, and the physical accuracy boundary determined by the system signal-to-noise ratio is approximated. While eliminating temperature drift interference, the temperature-sensitive frequency shift characteristics are strictly protected, ensuring the fidelity and integrity of the core temperature measurement signal in the spatiotemporal dimension.

[0147] Furthermore, It exhibits high-frequency fluctuations, and its amplitude decreases exponentially due to fiber loss during long-distance transmission. It increases gradually over time, and pulse-like spikes are generated due to abrupt polarization changes. When there is no interference, it is infinitely close to zero; when vibrating, it fluctuates with the variance of the temperature data.

[0148] In summary, the spatial consistency error of the fused temperature field is reduced, which can directly drive the dynamic thermal simulation of the digital twin, providing industrial-grade reliable data for predictive maintenance. Furthermore, by comparing the data before and after compensation, defects in actual temperature anomalies can be distinguished.

[0149] In summary, the self-sustaining reference system based on orthogonal polarization reference pulses is deeply integrated with the dynamic frequency shift tracking mechanism of acousto-optic modulated temperature measurement pulses. At the same time, relying on the online strain transmissibility calibration algorithm and multi-physics coupling model, the cumulative drift error is accurately and continuously monitored, meeting the micro-variation response requirements of composite fiber topology under intelligent adaptation.

[0150] In general, Solving the reference drift problem by relying on dual-pulse physical layer separation By combining online strain transmissibility calibration to resolve transient strain interference, high-precision real-time temperature data is ultimately output under strong interference and long-distance conditions. .

[0151] Compared with the prior art, the present invention has the following beneficial effects:

[0152] 1. This invention employs the synchronous injection of orthogonal polarization diversity reference pulses and acousto-optic modulated temperature measurement pulses. By synchronously forming a cooperative sensing field within the optical fiber, reciprocal symmetry is maintained, eliminating random polarization drift caused by channel curvature. This solves the coupling problem between temperature strain and polarization in the single-pulse scheme from the signal source, ensuring maximum temperature measurement accuracy.

[0153] 2. The dual-pulse pair constructs a closed-loop calibration chain through real-time mutual inspection. Combined with multi-sensor fusion, it monitors the deviation of data and automatically triggers calibration, determines the temperature drift of the acousto-optic modulator and the wavelength drift of the laser, activates the thermoelectric cooler in real time to stabilize the frequency and adjusts the injection current compensation, solves the reference drift problem caused by stress changes and other factors in the mine temperature measurement system, and achieves long-term stability of fiber optic temperature measurement in mines.

[0154] like Figure 2 The diagram shown is a functional block diagram of a reference information generation system based on artificial intelligence and smart home provided in an embodiment of the present invention.

[0155] The distributed fiber optic temperature measurement system 100 for mining described in this invention can be installed in an electronic device. Depending on the functions implemented, the distributed fiber optic temperature measurement system 100 may include a backscattered light signal collection module 101, a strain-free temperature data generation module 102, a strain-compensated temperature data generation module 103, a spatial distribution compensation amount generation module 104, and an anti-drift temperature distribution data generation module 105. The modules described in this invention can also be referred to as units, which are a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0156] In this embodiment, the functions of each module / unit are as follows:

[0157] The backscattered light signal collection module 101 is used to synchronously inject temperature measurement pulses and reference pulses into the optical fiber and collect the backscattered light signal of the optical fiber.

[0158] The strain-free temperature data generation module 102 is used to perform anti-strain interference demodulation operation on the backscattered light signal and obtain the strain-free temperature data of the optical fiber through discrete temperature integration.

[0159] The strain compensation temperature data generation module 103 is used to perform strain compensation calculation on the strain-free temperature data based on the real-time difference of the strain-free temperature data, and generate strain compensation temperature data for the optical fiber.

[0160] The spatial distribution compensation generation module 104 is used to perform spatial weighting processing on the temperature drift characteristics in the reference pulse based on the spatial position distribution of the optical fiber to obtain the spatial distribution compensation of the optical fiber.

[0161] The anti-drift temperature distribution data generation module 105 is used to fuse the spatial distribution compensation amount and the strain compensation temperature data, construct the mine-use full-area heating network through the temperature field reconstruction algorithm, and output the anti-drift temperature distribution data.

[0162] like Figure 3 As shown, this embodiment also provides a distributed optical fiber temperature measurement device for mining. The device may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a distributed optical fiber temperature measurement program.

[0163] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., executing a program to determine the moisture content of saline soil) and calls data stored in the memory 11 to perform various functions of the electronic device and process data.

[0164] The memory 11 includes at least one type of medium, including flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of an electronic device, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc. Furthermore, the memory 11 can include both internal and external storage units of the electronic device. The memory 11 can be used not only to store application software and various types of data installed on the electronic device, such as the code for a program to determine the moisture content of saline soil, but also to temporarily store data that has been output or will be output.

[0165] The communication bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0166] The communication interface 13 is used for communication between the aforementioned electronic device and other electronic devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, Bluetooth interface, etc.), typically used to establish communication connections between the electronic device and other electronic devices. The user interface may be a display, an input unit (such as a keyboard), or optionally, a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device and to display a visual user interface.

[0167] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0168] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0169] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0170] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0171] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0172] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0173] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A distributed optical fiber temperature measurement method for mining, characterized in that, The method includes: S1. Simultaneously inject temperature measurement pulses and reference pulses into the optical fiber to collect the backscattered light signal of the optical fiber; S2. Perform anti-strain interference demodulation on the backscattered light signal, and obtain the strain-free temperature data of the optical fiber by discrete temperature integration. S3. Based on the real-time difference of the strain-free temperature data, perform strain compensation calculation on the strain-free temperature data to generate strain-compensated temperature data for the optical fiber. S4. Based on the spatial position distribution of the optical fiber, the temperature drift characteristics in the reference pulse are spatially weighted to obtain the spatial distribution compensation amount of the optical fiber. S5. Integrate the spatial distribution compensation amount and the strain compensation temperature data, construct the mine-use full-area heating network through the temperature field reconstruction algorithm, and output anti-drift temperature distribution data.

2. The distributed optical fiber temperature measurement method for mining as described in claim 1, characterized in that, When synchronously injecting the temperature measurement pulse and the reference pulse into the optical fiber, and acquiring the backscattered light signal of the optical fiber, the process includes: The phase convergence pulse pair of the optical fiber is obtained by spatiotemporally aligning the temperature measurement pulse and the reference pulse; The phase convergence pulse pair is injected into the optical fiber to obtain the optical signal excitation response of the optical fiber; The backscattered light signal of the optical fiber is obtained by polarization-based binning of the excitation response of the optical signal.

3. The distributed optical fiber temperature measurement method for mining as described in claim 1, characterized in that, When performing anti-strain interference demodulation on the backscattered light signal and obtaining the strain-free temperature data of the optical fiber through discrete temperature integration, the process includes: The backscattered light signal is decoupled using two parameters to obtain the temperature-sensitive frequency shift of the optical fiber. The temperature-sensitive frequency shift is differentially smoothed to obtain the temperature change gradient of the optical fiber. The temperature gradient is integrated piecewise to obtain the strain-free temperature data of the optical fiber.

4. The distributed optical fiber temperature measurement method for mining as described in claim 1, characterized in that, When performing strain compensation calculations on the strain-free temperature data based on the real-time difference of the strain-free temperature data to generate the strain-compensated temperature data for the optical fiber, the process includes: The temperature gradient field of the optical fiber is obtained by performing double-pulse stripping on the strain-free temperature data. Thermal drift balancing of the temperature gradient field yields the strain compensation coefficient of the optical fiber. The strain compensation coefficient is fitted with thermal output strain to obtain the strain compensation temperature data of the optical fiber.

5. The distributed optical fiber temperature measurement method for mining as described in claim 4, characterized in that, When performing thermal drift balancing on the temperature gradient field to obtain the strain compensation coefficient of the optical fiber, the process includes: The temperature gradient field is synthesized by vector magnitude to obtain the global temperature difference distribution matrix of the optical fiber; The thermal output strain of the optical fiber is obtained by performing a discrete cosine transform on the global temperature difference distribution matrix. The strain compensation coefficient of the optical fiber is obtained by performing a linear regression of thermal expansion on the thermal output strain.

6. The distributed optical fiber temperature measurement method for mining as described in claim 4, characterized in that, When obtaining the spatial distribution compensation amount of the optical fiber by performing spatial weighting processing based on the spatial position distribution of the optical fiber and the temperature drift characteristics in the reference pulse, the process includes: The spatial position distribution of the optical fiber is mapped point by point in the time domain to obtain the spatial position coordinate matrix of the optical fiber; The spatial attenuation matrix of the optical fiber is obtained by amplifying the scattering loss of the temperature drift characteristics of the reference pulse. The spatial distribution compensation amount of the optical fiber is obtained by performing spatial feature convolution on the spatial attenuation matrix and the spatial position coordinate matrix.

7. The distributed optical fiber temperature measurement method for mining as described in claim 6, characterized in that, When performing spatial feature convolution between the spatial attenuation matrix and the spatial position coordinate matrix to obtain the spatial distribution compensation amount of the optical fiber, the following steps are included: The temperature drift weighting factor of the optical fiber is obtained by normalizing the spatial attenuation matrix based on the strain compensation coefficient. The temperature characteristics of the temperature measurement pulse are convolved and fused with the temperature drift weighting factor to obtain the weighted temperature drift. The spatial distribution compensation amount of the optical fiber is obtained by applying a compensation gain to the weighted temperature drift based on the spatial position coordinate matrix.

8. The distributed optical fiber temperature measurement method for mining as described in claim 1, characterized in that, When fusing the spatial distribution compensation amount and the strain compensation temperature data, and constructing a mine-use full-area heating network using a temperature field reconstruction algorithm to output drift-resistant temperature distribution data, the following steps are included: The spatial distribution compensation amount and the strain compensation temperature data are spatially weighted and superimposed to obtain the fused temperature field of the optical fiber; The drift residual is filtered on the fused temperature field to obtain the anti-drift temperature field of the optical fiber; Deviation extraction is performed on the anti-drift temperature field to obtain the anti-drift temperature distribution data of the optical fiber. The calculation formula for the deviation extraction is as follows: ； For drift-resistant temperature distribution data, The temperature characteristics of the temperature measurement pulse, The temperature drift characteristics of the reference pulse, The strain compensation coefficient is... This is the strain-compensated temperature data for the current time. It is the strain compensation temperature data from the previous time point. It is a time interval.

9. A distributed optical fiber temperature measurement system for mining, characterized in that, The system includes: The backscattered light signal collection module is used to synchronously inject temperature measurement pulses and reference pulses into the optical fiber to collect the backscattered light signal of the optical fiber. The strain-free temperature data generation module is used to perform anti-strain interference demodulation on the backscattered light signal and obtain the strain-free temperature data of the optical fiber through discrete temperature integration. The strain-compensated temperature data generation module is used to perform strain compensation calculations on the strain-free temperature data based on the real-time difference of the strain-free temperature data, and generate strain-compensated temperature data for the optical fiber. The spatial distribution compensation generation module is used to perform spatial weighting processing on the temperature drift characteristics in the reference pulse based on the spatial position distribution of the optical fiber, so as to obtain the spatial distribution compensation of the optical fiber. The anti-drift temperature distribution data generation module is used to fuse the spatial distribution compensation amount and the strain compensation temperature data, construct the mine-use full-area heating network through the temperature field reconstruction algorithm, and output the anti-drift temperature distribution data.

10. A distributed fiber optic temperature measurement device for mining, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes a computer program to implement the distributed optical fiber temperature measurement method for mining as described in any one of claims 1 to 8.

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