Depth flexible peak regulation boiler heating surface irregular wall temperature distributed fiber bragg grating monitoring system

Abstract

The invention relates to the field of temperature measurement and equipment damage analysis, in particular to an irregular wall temperature distributed fiber bragg grating monitoring system for a heating surface of a deep flexible peak regulation boiler. Comprising the steps of preparation and calibration of a fiber grating sensor, irregular layout design of an optical fiber network, distributed data acquisition and signal preprocessing, temperature field reconstruction and anomaly detection, system calibration and long-term stability maintenance, data storage and analysis and system verification and performance test. By adopting the distributed fiber grating sensor technology, the distributed monitoring of the irregular wall temperature of the boiler heating surface is realized. The sensors are reasonably arranged on the heating surface pipe wall, the whole heating surface area can be covered, and the temperature distribution condition of the pipe wall is monitored in real time.

Description

Technical Field

[0001] The present invention relates to the fields of temperature measurement and equipment damage analysis, and more specifically to a non-regularized wall temperature distributed fiber Bragg grating monitoring system for the heating surface of a deep flexible peak-shaving boiler. Background Art

[0002] During the thermal power generation process, the temperature monitoring of the boiler heating surface tubes is crucial for ensuring the safe and efficient operation of the boiler. However, there are many difficulties and deficiencies in the temperature detection of boiler heating surface tubes in the prior art. Traditional temperature detection methods mainly use contact sensors such as thermocouples or thermal resistors. These methods have problems such as low temperature measurement accuracy, slow response speed, and susceptibility to environmental interference. Especially during the deep peak-shaving process of the boiler, the temperature distribution of the heating surface tube wall is uneven and the non-regularization phenomenon is serious, making it difficult for traditional temperature detection methods to meet the monitoring requirements.

[0003] Deficiencies of the Boiler Temperature Monitoring Technology in the Prior Art 1. Due to problems such as temperature measurement delay and error accumulation, it is difficult for traditional contact sensors to achieve high-precision temperature monitoring.

[0004] 2. Traditional temperature monitoring systems require a large number of sensors and wiring, resulting in high system complexity and difficult maintenance.

[0005] 3. Traditional sensors are easily affected by environmental factors such as electromagnetic interference and thermal radiation, resulting in inaccurate temperature measurement results.

[0006] 4. During the deep peak-shaving process of the boiler, the temperature distribution of the heating surface tube wall is complex and variable, and it is difficult for traditional temperature monitoring methods to adapt to this change. Summary of the Invention

[0007] In view of the difficulties and deficiencies in the temperature detection of boiler heating surface tubes in the prior art, the present invention proposes a non-regularized wall temperature distributed fiber Bragg grating monitoring system for the heating surface of a deep flexible peak-shaving boiler, aiming to achieve high-precision, high-reliability, and low-cost temperature monitoring, and is applicable to the temperature monitoring of the heating surface of deep peak-shaving boilers.

[0008] The non-regularized wall temperature distributed fiber Bragg grating monitoring system for the heating surface of a deep flexible peak-shaving boiler includes the preparation and calibration of fiber Bragg grating sensors, the non-regularized layout design of the fiber optic network, distributed data acquisition and signal preprocessing, temperature field reconstruction and anomaly detection, system calibration and long-term stability maintenance, data storage and analysis, and system verification and performance testing.

[0009] Preferably, the steps of preparing and calibrating the fiber Bragg grating sensors include fiber selection, grating writing, exposure parameter setting, grating parameter design, annealing treatment, and temperature calibration of the sensors.

[0010] Preferably, the optical fiber is selected as a single-mode communication-grade optical fiber with a core diameter of 8.2 μm and a cladding diameter of 125 μm. A 248 nm KrF excimer laser is used to write a Bragg grating on the optical fiber by the phase mask method. The grating period Λ = 535 nm, the grating length L = 10 mm, and the central wavelength λ_B = 1550 nm.

[0011] Preferably, the steps for the non-regular layout design of the optical fiber network include the modeling of the temperature field on the heated surface and the grating layout strategy. The modeling of the temperature field on the heated surface includes the geometric modeling of the boiler and the thermodynamic simulation. The grating layout strategy includes the gradient partition layout, wavelength allocation, and topology structure optimization.

[0012] Preferably, in the gradient partition layout, the grating pitch in the high-temperature area is 5 cm, covering stress concentration areas such as the elbows and welds of the tube screens; the grating pitch in the medium- and low-temperature areas is 10 cm, evenly distributed along the axis of the tube bundle.

[0013] Preferably, the steps for distributed data acquisition and signal preprocessing include the modulation and demodulation of optical signals and the extraction of the wavelength drift amount. In the modulation and demodulation of optical signals, a broadband SLED light source and a high-speed photodetector are used to receive the reflected spectrum, and an adjustable Fabry-Perot filter is used to separate the signals of each grating.

[0014] Preferably, the steps for temperature field reconstruction and anomaly detection include the spatial interpolation algorithm and anomaly temperature warning. In the spatial interpolation algorithm, the Kriging interpolation is used to construct a variogram model, and the interpolation result is mapped to the three-dimensional model of the boiler to generate an isotherm map; the anomaly temperature warning includes threshold judgment, gradient mutation detection, and trend prediction.

[0015] Preferably, the steps for system calibration and long-term stability maintenance include online dynamic calibration and the health monitoring of the optical fiber network. In the online dynamic calibration, a constant-temperature reference grating is arranged outside the boiler furnace to compare the wavelength drift amount, and the health monitoring of the optical fiber network uses OTDR testing to detect fiber breakage or bending loss.

[0016] Preferably, the steps for data storage and analysis include database design and big data analysis. In the database design, the HDF5 file format is used to store temperature data, and a time-space composite index based on the B+ tree is established; the big data analysis includes temperature distribution statistics and life prediction.

[0017] Preferably, the steps for system verification and performance testing include static accuracy testing and dynamic response testing. In the static accuracy testing, the measurement error is measured by continuously running in a constant-temperature bath for 24 hours, and in the dynamic response testing, the grating response time is measured while heating at a rate of 100 °C / s.

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. By adopting the distributed fiber Bragg grating sensor technology, the present invention realizes the distributed monitoring of the irregular wall temperature of the boiler heating surface. The sensors are reasonably arranged on the heating surface pipe wall, capable of covering the entire heating surface area and monitoring the temperature distribution of the pipe wall in real time.

[0019] 2. The present invention uses the fiber Bragg grating technology for temperature measurement, featuring high precision and high sensitivity. Meanwhile, by eliminating the cross-sensitivity terms introduced by stress and adopting a high-precision data acquisition and processing device, the temperature measurement accuracy and reliability are further improved.

[0020] 3. By adopting the distributed fiber Bragg grating sensor technology, the present invention avoids a large number of sensors and wirings in the traditional temperature monitoring system. The sensors are connected to the data acquisition device through optical fibers, reducing the wiring difficulty and cost. Meanwhile, the system structure is simple and easy to maintain, reducing the operation and maintenance cost.

[0021] 4. The distributed fiber Bragg grating monitoring system for the irregular wall temperature of the deep flexible peaking boiler heating surface described in the present invention is applicable to the temperature monitoring of the heating surface of the deep peaking boiler. The system can monitor the temperature distribution of the heating surface pipe wall of the boiler in real time during the deep peaking process, providing a strong guarantee for the safe and efficient operation of the boiler. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 is a schematic diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] The following further describes the embodiments of the present invention in detail with reference to the drawings and examples. The following examples are used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0024] The present invention provides a distributed fiber Bragg grating monitoring system for the irregular wall temperature of the deep flexible peaking boiler heating surface, including: S1: Preparation and calibration of fiber Bragg grating sensors S11: Preparation of fiber Bragg gratings ‌Fiber selection‌: Select single-mode communication-grade fiber (SMF-28) with a core diameter of 8.2 μm and a cladding diameter of 125 μm to ensure low transmission loss (≤0.2 dB / km) and high mechanical strength; ‌Grating writing‌: ‌Ultraviolet exposure system setup‌: Adopt a 248 nm KrF excimer laser to write Bragg gratings (FBG) on the fiber through the phase mask method; ‌Exposure parameter setting‌: The laser pulse energy is 80 mJ / cm², the repetition frequency is 50 Hz, and the exposure time is 30 seconds; Raster parameter design: Raster period Λ = 535 nm, raster length L = 10 mm, central wavelength λ_B = 1550 nm (error ±0.1 nm); Annealing treatment: Place the written optical fiber in an oven at 120 °C for 24 hours to eliminate residual stress and improve wavelength stability.

[0025] S12: Temperature calibration of the sensor Calibration device setup: Place the fiber grating in a high-precision temperature control furnace (temperature control accuracy ±0.1 °C) and connect it to an optical spectrum analyzer (OSA, resolution 1 pm).

[0026] Calibration process: Heat up from 20 °C to 600 °C at intervals of 50 °C, record the reflection wavelength λ_B corresponding to each temperature point, and calculate the temperature sensitivity coefficient K_T (unit: pm / °C) through linear regression:

[0027] Cross-sensitivity elimination: Verify through experiments that the influence coefficient of axial strain on wavelength K_ε = 1.2 pm / με, and use the double-grating differential method (the main grating measures temperature, and the compensation grating measures strain) to eliminate strain interference.

[0028] S2: Design of the non-regular layout of the optical fiber network S21: Modeling of the temperature field on the heated surface Boiler geometric modeling: Based on the actual boiler structure (such as membrane water wall, superheater tube bundle), establish a three-dimensional CAD model and divide the mesh elements (side length ≤ 10 cm).

[0029] Thermodynamic simulation: Use ANSYS Fluent to simulate the temperature field distribution of the boiler under deep peak shaving (load rate 30% - 100%) and identify the high-temperature gradient areas (temperature change rate ≥ 5 °C / cm).

[0030] S22: Grating layout strategy Gradient partition layout: High-temperature area (T ≥ 500 °C): Grating spacing 5 cm, covering stress concentration areas such as tube screen elbows and welds.

[0031] Medium and low-temperature area (T < 500 °C): Grating spacing 10 cm, evenly distributed along the axis of the tube bundle.

[0032] Wavelength allocation: The central wavelength interval of each grating Δλ = 0.8 nm (such as 1550.0 nm, 1550.8 nm, 1551.6 nm, etc.) to ensure that the spectra do not overlap.

[0033] Topology optimization: Adopt the "tree-like branch" topology (main optical fiber length ≤ 50m, branch length ≤ 5m) to reduce optical signal attenuation (total loss ≤ 3dB).

[0034] S3: Distributed data acquisition and signal preprocessing S31: Optical signal modulation and demodulation Light source selection: Adopt a broadband SLED light source (wavelength range 1520 - 1570nm, power 20mW).

[0035] Reflected signal acquisition: Use a high-speed photodetector (response time 1ns) to receive the reflected spectrum.

[0036] Separate each grating signal through a tunable Fabry - Perot filter (FSR = 40nm, finesse F = 200).

[0037] Signal noise reduction processing: Wavelet threshold denoising: Select the Daubechies4 wavelet basis, decompose the signal into 5 layers, and perform hard threshold processing on the high-frequency noise.

[0038] Moving average filtering: The window width is 10 sampling points (corresponding to a time resolution of 1ms).

[0039] S32: Wavelength drift amount extraction Spectral peak detection: Use the Gaussian fitting algorithm to locate the center wavelength λ B :

[0040] where σ = 0.2nm is the spectral full width at half maximum, and the fitting error ≤ 0.05nm.

[0041] Temperature - wavelength mapping: Calculate the real-time temperature T according to the calibration coefficient K_T:

[0042] T0 is the initial temperature, and λ B0 is the initial center wavelength.

[0043] S4: Temperature field reconstruction and anomaly detection S41: Spatial interpolation algorithm Kriging interpolation: Based on the temperature data of the grating points, construct a variogram model:

[0044] where h is the spatial distance, and fit the spherical model (nugget value C_0 = 0.1, sill value C = 5.0, range a = 20cm).

[0045] Temperature field visualization: Map the interpolation results to the 3D boiler model to generate an isothermal line graph (color scale resolution: 1 °C).

[0046] S42: Abnormal temperature warning Threshold judgment: Set the upper limit of the safe temperature T_max (such as 620 °C allowed by the material). If the temperature T of a certain grating ≥ T_max, trigger a first-level alarm.

[0047] Gradient mutation detection: Calculate the temperature difference ΔT_ij between adjacent gratings. If ΔT_ij ≥ 10 °C / cm and lasts for 5 seconds, trigger a second-level alarm.

[0048] Trend prediction: Predict the temperature change in the next 10 minutes based on the ARIMA model. The formula is:[[]]

[0049] where φ1 = 0.85, φ2 = 0.12, θ1 = 0.3, and c is the constant term.

[0050] S5: System calibration and long-term stability maintenance S51 Online dynamic calibration Reference point setting: Arrange 3 constant-temperature reference gratings (temperature 25 ± 0.1 °C) outside the boiler furnace, and automatically compare the wavelength drift every 24 hours.

[0051] Compensation algorithm: If the wavelength offset of the reference grating Δλ_ref ≥ 0.1 nm, perform linear compensation on all measurement values: S52: Optical fiber network health monitoring OTDR test: Use an optical time domain reflectometer (OTDR) to scan once a week to detect fiber breakage or bending loss (threshold: loss ≥ 0.5 dB / km).

[0052] Optical power balance: Adjust the optical power of each branch through a variable optical attenuator (VOA) to ensure that the signal dynamic range is between -30 dBm and -10 dBm.

[0053] S6: Data storage and analysis S61 Database design Storage format: Store the temperature data in three columns of timestamp (accuracy 1 ms), grating ID, and temperature value as an HDF5 file (compression rate ≥ 80%).

[0054] Index optimization: Establish a time-space composite index based on the B+ tree to support millisecond-level query response.

[0055] S62 Big data analysis Temperature distribution statistics: Calculate the standard deviation σ_T and kurtosis of the temperature per hour to evaluate the uniformity of the heated surface.

[0056] Life prediction: Based on the Miner linear cumulative damage model, calculate the creep life of the pipe:

[0057] where t i is the running time of the i-th temperature segment, and t fi is the fracture time under the corresponding temperature-stress.

[0058] S7: System verification and performance testing S71 Static accuracy testing Constant temperature field testing: Place 10 gratings in a constant temperature bath with an accuracy of ±0.1°C and run continuously at 300°C for 24 hours, with the measurement error ≤ ±1°C.

[0059] Repeatability testing: Conduct 10 heating-cooling cycles (20°C - 600°C) on the same grating, with the wavelength repeatability error ≤ 0.05 nm.

[0060] S72 Dynamic response testing Step response: Heat up at a rate of 100°C / s and measure the response time of the grating (10% - 90% rise time ≤ 50 ms).

[0061] Actual working condition verification: Continuously run on a 660MW supercritical boiler for 30 days, with a false alarm rate ≤ 0.1% and a missed alarm rate = 0%.

[0062] The embodiments of the present invention are given for the purpose of illustration and description. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A distributed fiber grating monitoring system for irregular wall temperature of the heating surface of a deep flexible peak-shaving boiler, characterized by: It includes the preparation and calibration of fiber grating sensors, irregular layout design of fiber optic networks, distributed data acquisition and signal preprocessing, temperature field reconstruction and anomaly detection, system calibration and long-term stability maintenance, data storage and analysis, as well as system verification and performance testing.

2. The distributed fiber grating monitoring system for irregular wall temperature of heating surface of deep flexible peak-shaving boiler according to claim 1 is characterized in that: The preparation and calibration steps of the fiber grating sensor include fiber selection, grating writing, exposure parameter setting, grating parameter design, annealing treatment and temperature calibration of the sensor.

3. The distributed fiber grating monitoring system for irregular wall temperature of heating surface of deep flexible peak-shaving boiler according to claim 2 is characterized in that: The optical fiber is selected as a single-mode communication-grade optical fiber with a core diameter of 8.2 μm and a cladding diameter of 125 μm. A 248 nm KrF excimer laser is used to write a Bragg grating on the optical fiber through a phase mask method. The grating period Λ=535 nm, the grating length L=10 mm, and the central wavelength λ_B=1550 nm.

4. The distributed fiber grating monitoring system for irregular wall temperature of heating surface of deep flexible peak-shaving boiler according to claim 1 is characterized in that: The irregular layout design steps of the optical fiber network include heating surface temperature field modeling and grating arrangement strategy, wherein the heating surface temperature field modeling includes boiler geometry modeling and thermodynamic simulation, and the grating arrangement strategy includes gradient partition arrangement, wavelength allocation and topology structure optimization.

5. The distributed fiber grating monitoring system for irregular wall temperature of heating surface of deep flexible peak-shaving boiler according to claim 4 is characterized in that: In the gradient zoning arrangement, the grating spacing in the high temperature zone is 5 cm, covering stress concentration areas such as tube panel elbows and welds; the grating spacing in the medium and low temperature zones is 10 cm, evenly distributed along the axis of the tube bundle.

6. The distributed fiber grating monitoring system for irregular wall temperature of heating surface of deep flexible peak-shaving boiler according to claim 1 is characterized in that: The distributed data acquisition and signal preprocessing steps include optical signal modulation and demodulation and wavelength drift extraction, wherein the optical signal modulation and demodulation uses a broadband SLED light source and a high-speed photodetector to receive the reflected spectrum, and separates each grating signal through a tunable Fabry-Perot filter.

7. The distributed fiber grating monitoring system for irregular wall temperature of heating surface of deep flexible peak-shaving boiler according to claim 1 is characterized in that: The temperature field reconstruction and anomaly detection steps include a spatial interpolation algorithm and abnormal temperature warning, wherein the spatial interpolation algorithm uses Kriging interpolation to construct a variation function model, and maps the interpolation result to the boiler three-dimensional model to generate an isotherm map; the abnormal temperature warning includes threshold judgment, gradient mutation detection and trend prediction.

8. The distributed fiber grating monitoring system for irregular wall temperature of heating surface of deep flexible peak-shaving boiler according to claim 1 is characterized in that: The system calibration and long-term stability maintenance steps include online dynamic calibration and optical fiber network health monitoring, wherein the online dynamic calibration arranges a constant temperature reference grating outside the boiler furnace to compare the wavelength drift, and the optical fiber network health monitoring uses OTDR testing to detect optical fiber breakage or bending loss.

9. The distributed fiber grating monitoring system for irregular wall temperature of heating surface of deep flexible peak-shaving boiler according to claim 1 is characterized in that: The data storage and analysis steps include database design and big data analysis, wherein the database design uses HDF5 file format to store temperature data and establishes a time-space composite index based on a B+ tree; the big data analysis includes temperature distribution statistics and life prediction.

10. The distributed fiber Bragg grating monitoring system for irregular wall temperature of heating surface of deep flexible peak-shaving boiler according to any one of claims 1 to 9, characterized in that: The system verification and performance test steps include static accuracy test and dynamic response test, wherein the static accuracy test is run continuously in a constant temperature bath for 24 hours to measure the error, and the dynamic response test is measured at a temperature increase rate of 100°C / s to measure the grating response time.

Images