Corrosion monitoring and evaluation method of underground pipeline gallery structure based on optical fiber sensing

Abstract

The present invention relates to the technical field of structural health monitoring, and discloses a method for monitoring and assessing the corrosion of underground pipe corridor structures based on optical fiber sensing, comprising: constructing a composite optical fiber sensing structure comprising an Fe-C alloy-coated optical fiber and a long-period grating, and synchronously monitoring the chemical composition changes and structural mechanical states of corrosion products through the shift of characteristic peaks of the photoluminescence spectrum and the strain distribution cloud map; dynamically correcting the measurement deviation caused by the loss of the coating layer in combination with the rate of change of the environmental refractive index; embedding a reference grating to eliminate the interference of temperature drift, and triggering the in-situ deposition of iron ions to achieve self-repair of the sensing interface. The present invention avoids the problems of difficult decoupling of chemical-mechanical parameters and signal interruption caused by coating failure in traditional monitoring through the collaborative perception of multiple physical quantities and an adaptive compensation mechanism, significantly improving the long-term stable monitoring capability of the corrosion process in complex environments, and providing high-precision data support for the safety assessment of underground pipe corridor structures.

Description

Technical Field

[0001] The present invention relates to an underground pipe gallery structure corrosion monitoring and evaluation method based on optical fiber sensing, belonging to the technical field of structural health monitoring. Background Art

[0002] Underground pipelines, as a vital component of urban infrastructure, are exposed to complex environments characterized by high humidity and multi-ion corrosion for extended periods. Monitoring their structural corrosion is crucial for ensuring operational safety. Currently, electrochemical sensors or single-point fiber optic sensors are commonly used for corrosion monitoring. Electrochemical sensors indirectly assess corrosion rates by detecting ambient ion concentrations but cannot directly reflect degradation of the structural mechanical properties. Single-point fiber optic sensors (such as Bragg gratings) can monitor local strain but struggle to capture the chemical signatures of corrosion products. Existing technologies typically employ multi-sensor fusion solutions to address the need for multi-parameter coupled monitoring. For example, chemical and mechanical sensors are deployed in parallel. However, these solutions present the following challenges: 1. Material and packaging differences between multiple sensor types make it difficult to precisely synchronize signal acquisition timing and spatial location, introducing data decoupling errors. 2. The sensitive coating of coated fiber optic sensors rapidly degrades in corrosive environments, limiting monitoring cycles and necessitating frequent sensor replacement. 3. Signal drift caused by fluctuations in ambient temperature and humidity is difficult to effectively eliminate with a single reference channel, creating monitoring blind spots, particularly in complex areas such as pipeline corridor corners.

[0003] To address coating lifespan issues, existing technologies attempt to employ gradient coating designs or periodic calibration algorithms. However, gradient coatings only extend the monitoring time of certain sections, and calibration algorithms rely on pre-set models and cannot adapt to the dynamic corrosion process. To address temperature interference, the industry generally uses temperature-compensated gratings, but these only eliminate static temperature offsets and lack the ability to resolve the dynamic thermal effects caused by corrosion exotherm. Furthermore, spatial constraints make it difficult to deploy traditional sensors in hidden areas of the tunnel structure (such as bolted joints), and existing distributed fiber optic solutions struggle to achieve high-precision monitoring due to signal attenuation caused by bending losses. Therefore, the technical challenges addressed by this invention are how to achieve high-precision simultaneous monitoring of chemical and mechanical parameters during the corrosion process, extend the sensor's service life, and eliminate interference from complex environments. Summary of the Invention

[0004] The present invention provides a method for monitoring and evaluating the corrosion of underground pipe gallery structures based on optical fiber sensing, the main purpose of which is to solve the problems of coating failure, difficulty in decoupling multi-source data and insufficient environmental noise suppression.

[0005] To achieve the above objectives, the present invention provides a method for monitoring and evaluating underground pipe gallery structure corrosion based on optical fiber sensing, comprising the following steps:

[0006] Step 1: construct a composite optical fiber sensing structure, which includes at least one Fe-C alloy-coated optical fiber, and the Fe-C alloy-coated optical fiber is provided with at least one long-period grating along its length, for distributed deployment in an underground pipe gallery structure;

[0007] Step 2: Using an Fe-C alloy-coated optical fiber to capture the photoluminescence spectrum characteristics caused by changes in the chemical composition of corrosion products in the underground pipeline corridor structure, and extracting the characteristic peak shift and optical power attenuation rate of the photoluminescence spectrum; using the strain-sensitive characteristics of the long-period grating, the strain distribution at the location of the Fe-C alloy-coated optical fiber is monitored and a strain distribution cloud map is generated; and the refractive index change rate of the environment in which the Fe-C alloy-coated optical fiber is located is simultaneously monitored. The refractive index change rate reflects the change in ion concentration in the corrosive environment;

[0008] Step 3: Based on the optical power attenuation rate of the photoluminescence spectrum and combined with the pre-established coating layer thickness and normalized luminous intensity attenuation The quantitative model of Dynamic self-calibration of measurement deviations caused by coating layer loss, where The calibration coefficient is related to the characteristics of the coating material. At least one reference grating is embedded in the composite fiber optic sensing structure. The reference grating is used to monitor the ambient temperature. Based on the time domain characteristic difference between the ambient temperature and the corrosion exothermic effect, an adaptive noise suppression model is constructed to eliminate the interference of temperature drift on the corrosion characteristic signal.

[0009] Step 4: Perform spatiotemporal correlation analysis on the characteristic peak displacement of the photoluminescence spectrum, the strain distribution cloud map, and the rate of change of the environmental refractive index to construct a three-dimensional evaluation matrix for evaluating the degree of corrosion of the underground pipeline corridor structure. The three-dimensional evaluation matrix represents the combined effect of the corrosion rate, the degradation of the mechanical properties of the material, and the environmental influencing factors.

[0010] Preferably, the coating layer of the Fe-C alloy coated optical fiber is provided with an Fe content gradient along the axial direction of the optical fiber, and characteristic differences of the photoluminescence spectra at different axial positions are analyzed to achieve graded determination of the corrosion depth.

[0011] Preferably, the adaptive noise suppression model distinguishes between the ambient temperature change and the corrosion exothermic effect by analyzing the time domain correlation between the central wavelength offset of the reference grating and the central wavelength offset of the monitoring grating, and compensates the monitoring signal.

[0012] Preferably, the spatiotemporal correlation analysis includes precise synchronization of the acquisition times of different sensor signals and registration based on their spatial position information in the underground tunnel structure to ensure the accuracy of the three-dimensional evaluation matrix.

[0013] Preferably, a nano-alumina porous dielectric layer is provided on the cladding surface of the Fe-C alloy coated optical fiber. When the thickness of the coating layer decays to a critical threshold, the electrochemical redeposition control module uses the intensity of the reverse transmitted light signal to detect the depletion state of the coating layer, and triggers the in-situ oxidation deposition of residual iron ions in the coating material to form a dynamically updated corrosion-sensitive layer.

[0014] Preferably, when the electrochemical redeposition control module detects that the thickness of the coating layer has decayed to a preset range, it activates the built-in pH-responsive microcapsule to release the buffer solution, and dynamically adjusts the electrochemical deposition voltage according to the change in the power value of the reverse-transmitted light signal to control the residual iron ions to form a dendritic FeOOH deposition structure in the alumina pores.

[0015] Preferably, during the formation of the FeOOH dendritic deposition structure, the vibration spectrum of the pipeline corridor structure is captured in real time by an optical fiber sensor, the characteristic frequency components within a preset frequency range are extracted, and based on the established vibration frequency-deposition voltage dynamic mapping model, the deposition voltage is adaptively adjusted to guide the deposition dendrites to grow in a directional manner along the stress concentration direction.

[0016] Preferably, nano-titanium oxide photocatalytic particles are embedded in the electrolyte microcapsules. Exceeding the preset threshold When the photocatalytic reaction is triggered to generate hydroxyl radicals, the oxidation deposition process of residual iron ions is accelerated, where the preset threshold satisfy , is the humidity sensitivity coefficient, This is the typical environmental humidity of the pipeline corridor.

[0017] Compared with the background technology problems, the beneficial effects of the present invention are:

[0018] 1. Through the synergistic effect of the Fe-C alloy coating and the long-period grating in the composite fiber optic sensing structure, the simultaneous perception of chemical composition changes and structural strain is achieved. The photoluminescence characteristic attenuation of the coating layer and the strain distribution cloud map form a complementary verification. Combined with the dynamic monitoring of the environmental refractive index change, it effectively distinguishes between the phase change of corrosion products and external environmental interference. The coating thickness self-calibration model dynamically corrects the measurement deviation by normalizing the luminescence intensity, allowing the sensor to maintain signal fidelity during the continuous loss of the coating layer, avoiding the monitoring fault problem caused by film depletion in traditional coating sensors.

[0019] 2. The reference grating network accurately separates temperature drift and corrosion exothermic effects through time-domain correlation analysis. The wavelength shift caused by ambient temperature changes and the heat release characteristics of the corrosion process show significant differences in the time-frequency domain. By constructing a nonlinear compensation model, dynamic filtering of millisecond-level interference signals is achieved. This mechanism significantly improves the extraction accuracy of weak corrosion signals without relying on an external reference source, and is particularly suitable for long-term and stable monitoring of complex environments with alternating temperature and humidity in underground pipeline corridors.

[0020] 3. When the coating is exhausted, the nano-alumina porous dielectric layer triggers the in-situ deposition of iron ions to form a dendritic FeOOH structure. This process uses reverse optical signal power feedback to regulate the deposition voltage in real time, so that the new sensitive layer and the residual film layer form an evanescent field coupling effect, achieving autonomous recovery of the optical properties of the sensing interface. Combined with the humidity-responsive photocatalytic reaction, it accelerates deposition, effectively adapts to the high-humidity environment of the pipeline corridor, extends the service life of the sensor, and avoids the frequent replacement problem caused by coating failure in traditional solutions.

[0021] 4. The low-frequency vibration characteristics of the pipeline corridor are converted into deposition control parameters. Through vibration spectrum analysis and voltage dynamic mapping, the dendrites are guided to grow in the direction of stress concentration. The spatial distribution of the deposition structure forms a bionic match with the mechanical state of the pipeline corridor. Its fractal network characteristics enhance the directionality of strain sensitivity. At the same time, the potential risk of structural loosening is inverted through the deviation of the main vibration frequency. This mechanism converts the interference signal suppressed in traditional monitoring into a control variable that optimizes sensor performance, realizing the deep coupling of monitoring and structural health assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a data processing flow chart of the present invention;

[0023] Figure 2 This is a timing diagram of data interaction between data processing and analysis layer modules of the present invention.

[0024] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0025] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0026] The present invention provides a method for monitoring and evaluating the corrosion of underground pipe gallery structures based on optical fiber sensing, comprising the following steps:

[0027] Step 1: construct a composite optical fiber sensing structure, which includes at least one Fe-C alloy-coated optical fiber, and the Fe-C alloy-coated optical fiber is provided with at least one long-period grating along its length, for distributed deployment in an underground pipe gallery structure;

[0028] Step 2: Using an Fe-C alloy-coated optical fiber to capture the photoluminescence spectrum characteristics caused by changes in the chemical composition of corrosion products in the underground pipeline corridor structure, and extracting the characteristic peak shift and optical power attenuation rate of the photoluminescence spectrum; using the strain-sensitive characteristics of the long-period grating, the strain distribution at the location of the Fe-C alloy-coated optical fiber is monitored and a strain distribution cloud map is generated; and the refractive index change rate of the environment in which the Fe-C alloy-coated optical fiber is located is simultaneously monitored. The refractive index change rate reflects the change in ion concentration in the corrosive environment;

[0029] Step 3: Based on the optical power attenuation rate of the photoluminescence spectrum and combined with the pre-established coating layer thickness and normalized luminous intensity attenuation The quantitative model of Dynamic self-calibration of measurement deviations caused by coating layer loss, where The calibration coefficient is related to the characteristics of the coating material. At least one reference grating is embedded in the composite fiber optic sensing structure. The reference grating is used to monitor the ambient temperature. Based on the time domain characteristic difference between the ambient temperature and the corrosion exothermic effect, an adaptive noise suppression model is constructed to eliminate the interference of temperature drift on the corrosion characteristic signal.

[0030] Step 4: Perform spatiotemporal correlation analysis on the characteristic peak displacement of the photoluminescence spectrum, the strain distribution cloud map, and the rate of change of the environmental refractive index to construct a three-dimensional evaluation matrix for evaluating the degree of corrosion of the underground pipeline corridor structure. The three-dimensional evaluation matrix represents the combined effect of the corrosion rate, the degradation of the mechanical properties of the material, and the environmental influencing factors.

[0031] Preferably, the coating layer of the Fe-C alloy coated optical fiber is provided with an Fe content gradient along the axial direction of the optical fiber, and characteristic differences of the photoluminescence spectra at different axial positions are analyzed to achieve graded determination of the corrosion depth.

[0032] Preferably, the adaptive noise suppression model distinguishes between the ambient temperature change and the corrosion exothermic effect by analyzing the time domain correlation between the central wavelength offset of the reference grating and the central wavelength offset of the monitoring grating, and compensates the monitoring signal.

[0033] Preferably, the spatiotemporal correlation analysis includes precise synchronization of the acquisition times of different sensor signals and registration based on their spatial position information in the underground tunnel structure to ensure the accuracy of the three-dimensional evaluation matrix.

[0034] Preferably, a nano-alumina porous dielectric layer is provided on the cladding surface of the Fe-C alloy coated optical fiber. When the thickness of the coating layer decays to a critical threshold, the electrochemical redeposition control module uses the intensity of the reverse transmitted light signal to detect the depletion state of the coating layer, and triggers the in-situ oxidation deposition of residual iron ions in the coating material to form a dynamically updated corrosion-sensitive layer.

[0035] Preferably, when the electrochemical redeposition control module detects that the thickness of the coating layer has decayed to a preset range, it activates the built-in pH-responsive microcapsule to release the buffer solution, and dynamically adjusts the electrochemical deposition voltage according to the change in the power value of the reverse-transmitted light signal to control the residual iron ions to form a dendritic FeOOH deposition structure in the alumina pores.

[0036] Preferably, during the formation of the FeOOH dendritic deposition structure, the vibration spectrum of the pipeline corridor structure is captured in real time by an optical fiber sensor, the characteristic frequency components within a preset frequency range are extracted, and based on the established vibration frequency-deposition voltage dynamic mapping model, the deposition voltage is adaptively adjusted to guide the deposition dendrites to grow in a directional manner along the stress concentration direction.

[0037] Preferably, nano-titanium oxide photocatalytic particles are embedded in the electrolyte microcapsules. Exceeding the preset threshold When the photocatalytic reaction is triggered to generate hydroxyl radicals, the oxidation deposition process of residual iron ions is accelerated, where the preset threshold satisfy , is the humidity sensitivity coefficient, This is the typical environmental humidity of the pipeline corridor.

[0038] Preferably, it further includes using bend-insensitive optical fiber as a component of the composite optical fiber sensing structure to achieve reliable signal transmission at the corners of the underground pipeline corridor, and the spatial resolution reaches a preset accuracy.

[0039] Preferably, the three-dimensional assessment matrix is ​​used to predict the remaining service life and corrosion risk level of the underground pipeline corridor structure, and provide a decision-making basis for the maintenance and management of the pipeline corridor.

[0040] Example 1: In this example, a composite fiber optic sensing structure includes at least one Fe-C alloy-coated optical fiber and at least one long-period grating (LPFG) disposed along the length of the optical fiber. This distributed fiber optic sensing structure can capture the corrosion status of underground pipeline corridor structures in real time. The photoluminescence characteristic of the Fe-C alloy coating of the optical fiber will attenuate during the corrosion process, resulting in a shift in the position of the characteristic spectral peak. To ensure high sensor accuracy, the optical fiber sensor performs data processing through the following steps: 1. When the optical fiber is affected by corrosion products, the photoluminescence characteristic of the coating layer in the optical fiber will shift. The optical fiber sensor receives reflected light and extracts the shift of the characteristic peak of the photoluminescence spectrum. This shift reflects the chemical changes of the corrosion products. At the same time, the optical power attenuation rate of the optical fiber also changes with the corrosion process. This attenuation rate is quantified by the optical fiber's transmitted light signal. 2. The long-period grating (LPFG) uses its strain-sensitive properties to monitor the strain distribution at the optical fiber in real time. The change in strain is closely related to the change in mechanical stress caused by corrosion. Therefore, combined with the photoluminescence characteristics of the optical fiber sensor, a dual assessment of the corrosion level and stress state of the structure can be performed.

[0041] In this embodiment, the optical fiber sensor is dynamically self-calibrated by combining the quantitative model of photoluminescence attenuation rate and coating thickness. The specific steps are as follows: Step 1, first, the photoluminescence intensity and coating thickness ( ), using the formula To describe the measurement deviation caused by coating layer loss, The calibration coefficient related to the coating material characteristics is obtained by real-time acquisition of optical power attenuation data ( ), the measurement parameters of the optical fiber sensor can be dynamically adjusted to correct the signal attenuation caused by the loss of the coating layer; step 2, the optical fiber sensor continuously monitors the optical power attenuation, compares the attenuation data with the model, and corrects the change in the coating layer thickness in real time. Through this mechanism, the optical fiber sensor can maintain signal stability during the gradual loss of the coating layer, avoiding the monitoring fault problem caused by the film loss. At the same time, in order to effectively eliminate the interference of temperature changes on the corrosion signal, this embodiment monitors the change of ambient temperature through a reference grating, and combines the thermal effect of the corrosion process to perform noise suppression. The specific steps are as follows: step S1, embedding a reference grating in the composite optical fiber sensing structure, and identifying the temperature change and corrosion exothermic effect by analyzing the offset between the central wavelength of the reference grating and the central wavelength of the monitoring grating. The wavelength offset of the reference grating mainly reflects the change of ambient temperature, while the wavelength offset of the monitoring grating is affected by the corrosion exothermic effect. step S2, constructing a nonlinear noise suppression model based on the time domain characteristic difference between the temperature change and the corrosion exothermic effect. The model can distinguish between temperature fluctuations and the thermal effect of the corrosion process within milliseconds, thereby effectively eliminating the interference caused by temperature drift and ensuring the accurate extraction of the corrosion signal.

[0042] In this embodiment, the iron ion deposition process of the coating layer is guided by vibration spectrum analysis and voltage dynamic mapping, combined with the adaptive adjustment mechanism of the optical fiber sensor. The specific steps are as follows: 1. During the corrosion process, the vibration characteristics of the underground pipeline corridor structure will be captured in real time by the optical fiber sensor. The sensor extracts the characteristic frequency components within the preset frequency range and associates them with the electrochemical deposition process in the corrosion process; 2. Based on the dynamic mapping relationship between the vibration frequency and the deposition voltage, the system can adaptively adjust the deposition voltage so that the iron ion deposition grows directionally along the stress concentration direction to form a dendritic FeOOH deposition structure, which can effectively repair the loss of the coating layer and enhance the corrosion sensitivity of the sensor; 3. Through this adaptive adjustment mechanism, the new sensitive layer forms an evanescent field coupling effect with the original coating layer, thereby enhancing the monitoring capability of the sensor, especially in a high humidity environment, which can extend the service life of the sensor and improve its long-term monitoring capability.

[0043] The photocatalytic reaction triggered by humidity changes is also used to accelerate the deposition process of iron ions. The specific operation is as follows: 1. Nano-titanium oxide photocatalytic particles are pre-embedded in the electrolyte microcapsules of the optical fiber sensor. When the humidity of the tunnel environment reaches the preset threshold, these particles will trigger the photocatalytic reaction and generate hydroxyl radicals; 2. The generated hydroxyl radicals can accelerate the oxidation deposition process of iron ions, improve the deposition efficiency, and thus effectively promote the formation of a new corrosion-sensitive layer.

[0044] Example 2: This example combines Figures 1 to 2 , the implementation of the underground pipeline corridor structure corrosion monitoring and evaluation method based on optical fiber sensing is explained. Figure 1 As shown in the figure, at the data acquisition layer, the vibration data, optical signal, strain data, temperature data and environmental refractive index data of the tunnel structure are collected respectively through tunnel structure vibration monitoring, Fe-C alloy coated optical fiber, long period grating, reference grating and environmental refractive index sensor; the collected data are transmitted to the data processing and analysis layer, which includes a photoluminescence spectrum analysis module, a strain analysis module, a temperature monitoring and noise suppression module and an environmental factor analysis module. These modules process the collected photoluminescence spectrum signals, strain signals, temperature signals and environmental factor signals respectively. The processed data are further integrated into the spatiotemporal correlation analysis module for comprehensive analysis of multi-source data. The corrosion assessment modeling module establishes a corrosion assessment model based on the output of the spatiotemporal correlation analysis module; finally, at the decision support layer, the life prediction and risk assessment module uses the corrosion assessment model to perform life prediction and risk assessment, and outputs maintenance and management decisions, providing a decision-making basis for the maintenance and management of underground tunnels.

[0045] like Figure 2 As shown, first, the original sensing data sends spectral signals to the spectral analysis unit, sends strain signals to the strain analysis unit, and sends environmental signals to the environmental factor extraction unit. After receiving the spectral signals, the spectral analysis unit returns spectral feature data; after receiving the strain signals, the strain analysis unit returns strain distribution data; after receiving the environmental signal, the environmental factor extraction unit returns environmental factor data. Then, the spectral analysis unit sends spectral features to the spatiotemporal correlation processing module, the strain analysis unit sends strain data to the spatiotemporal correlation processing module, and the environmental factor extraction unit sends environmental factors to the spatiotemporal correlation processing module. Finally, the spatiotemporal correlation processing module sends correlation analysis results to the evaluation modeling module, and receives and returns the parameters required for modeling from the evaluation modeling module.

[0046] Example 3: The composite optical fiber sensing structure of this embodiment has one or more iron-carbon alloy coated optical fibers as its core component. The substrate of the optical fiber can be made of quartz optical fiber that is insensitive to hydrogen loss to ensure the stability of signal transmission in a hydrogen-rich environment. The specific preparation of the iron-carbon alloy coating can adopt multi-target magnetron sputtering technology. For example, by controlling the sputtering power and time of the iron target and the carbon target respectively, an iron-carbon alloy film with a thickness ranging from hundreds of nanometers to several microns is formed on the surface of the optical fiber. The mass percentage of iron in the film can be controlled between 95% and 99.9%, and the rest is carbon and unavoidable impurities, thereby ensuring its good corrosion sensitivity and certain structural strength. If it is necessary to achieve iron content gradient coating, the relative sputtering rates of the iron target and the carbon target can be programmed and continuously changed during the sputtering process to form a specific section along the axial direction of the optical fiber. The concentration of the iron element is gradually distributed from the inside to the outside or from one end to the other. For example, the iron content is higher in the part close to the incident end of the optical fiber to quickly respond to the initial corrosion. The iron content in the part far from the incident end can be appropriately reduced or other alloying elements can be introduced to adjust its corrosion rate and spectral response characteristics, thereby realizing the differentiated detection of different corrosion depths; the photoluminescence characteristics of the iron-carbon alloy coating layer mainly depend on the changes in its surface chemical state and roughness during the corrosion process, which in turn affects the intensity and characteristic peak position of the photoluminescence signal generated under the irradiation of a specific excitation light source. For example, a semiconductor laser with a central wavelength of 405 nanometers can be used as the excitation light source to monitor the photoluminescence spectrum in the range of 500 to 700 nanometers. The early stage of corrosion may be manifested as a slight blue shift or red shift of a specific peak position and a gradual attenuation of the light power.

[0047] Long-period gratings (LPGs) can be formed at specific locations on optical fibers after the iron-carbon alloy coating is completed by periodic inscription with a carbon dioxide laser or ultraviolet laser exposure combined with a phase mask. The period is typically set at hundreds of microns, and the length is several centimeters, to obtain a resonance peak that is highly sensitive to both strain and the ambient refractive index. The synergistic effect of the LPG and the iron-carbon alloy coating is reflected in the fact that corrosion-induced changes in the physical and chemical properties of the coating (such as thickness reduction, surface roughening, and refractive index changes) directly affect the wavelength and transmission intensity of the LPG resonance peak. Furthermore, structural strain can also cause independent shifts in the resonance peak. By precisely demodulating these spectral changes, the corrosion status and stress information can be acquired synchronously.

[0048] The core of dynamic self-calibration for measurement deviations caused by coating loss lies in establishing a quantitative model between coating thickness and normalized luminous intensity decay. Specifically, the coating thickness is equal to the calibration coefficient multiplied by the normalized luminous intensity decay. Here, the normalized luminous intensity decay can be defined as the relative change in the integrated intensity of the characteristic photoluminescence peak at a specific corrosion time point relative to the integrated intensity of the characteristic peak in the initial uncorroded state. For example, if the initial photoluminescence intensity is the initial luminous intensity and the photoluminescence intensity at a certain moment after corrosion is the current luminous intensity, the normalized luminous intensity decay can be expressed as (initial luminous intensity - current luminous intensity) / initial luminous intensity. The calibration coefficient is determined by conducting accelerated corrosion experiments on iron-carbon alloy-coated optical fiber samples with different known initial thicknesses, simultaneously monitoring the decay process of their photoluminescence intensity and the change in coating layer thickness accurately measured by other means (such as in-situ observation with a scanning electron microscope or measurement with an atomic force microscope), and then obtaining it through data fitting. For example, for a specific batch of coated optical fibers, a group of samples with thicknesses ranging from 50 nanometers to 500 nanometers, with intervals of 50 nanometers, can be prepared. These samples are corroded in a simulated pipeline corridor corrosion environment (such as a 3.5% sodium chloride solution at a temperature of 25 degrees Celsius), and the normalized luminescence intensity decay and the corresponding actual thickness are recorded at regular intervals. Finally, the calibration coefficient for this batch of sensors is obtained through least squares fitting.

[0049] Regarding the adaptive noise suppression model that uses a reference grating to eliminate temperature drift interference, its basic principle is to utilize the differences in time scale and amplitude between the corrosion exothermic effect and the ambient temperature change. The reference grating is preferably encapsulated in an environment as close as possible to the monitoring grating but isolated from the corrosive medium, for example, by sealing it with inert materials so that it only responds to changes in ambient temperature. The wavelength offset of the monitoring grating is affected by the ambient temperature, structural strain, and the weak exothermic effect that may be caused by corrosion. This adaptive noise suppression model can process the wavelength shift signals of the monitoring and reference gratings based on time-frequency analysis methods such as empirical mode decomposition or wavelet transform, extracting the main trend term (representing slow ambient temperature changes) and high-frequency disturbance terms from each signal. Since corrosion exotherm is typically a localized and relatively slow energy release process, it may manifest in the time domain as a slowly varying signal within a specific frequency range or as small fluctuations superimposed on a temperature trend. Daily ambient temperature fluctuations may have broader spectral characteristics or diurnal cycles. By comparing and analyzing the correlation and energy distribution of the two grating signals at different time scales, for example, a time window can be set and the correlation coefficient of the two signals within the window calculated. If the correlation coefficient is high, the offset of the monitoring grating is considered to be mainly caused by temperature. If the correlation coefficient is low or there is a difference in specific frequency components, it may indicate the presence of corrosion exotherm. Furthermore, a filter, such as a Kalman filter or an adaptive minimum mean square error filter, can be constructed with the reference grating signal as the reference input to dynamically filter out the common-mode noise components caused by ambient temperature from the monitoring grating signal, thereby extracting the true signal related to corrosion and strain.

[0050] Regarding the specific implementation of the electrochemical redeposition control module within the sensor interface self-repair mechanism, the module is activated when the coating thickness, as determined by monitoring the intensity of the reverse-transmitted optical signal (e.g., using optical time-domain reflectometry to monitor the optical power return value of a specific sensing area), has decreased to a critical threshold, such as less than 20% of the initial thickness. At this point, if the sensor surface is coated with a nano-alumina porous dielectric layer, its pore structure provides nucleation sites and support for the subsequent deposition of iron ions. Simultaneously, pH-responsive microcapsules, pre-deposited on the fiber surface or in the porous dielectric layer, rupture when corrosion causes a significant change in the local pH (e.g., increased acidity), releasing a buffer solution, such as phosphate buffer, to adjust the pH of the local microenvironment to a range suitable for iron ion deposition, such as a weakly alkaline condition, thereby promoting the formation of iron hydroxide or iron oxyhydroxide. The electrochemical redeposition control module dynamically adjusts the deposition voltage or current applied to a pre-deposited electrode (which can be part of the fiber's own conductive coating or a nearby auxiliary electrode) based on subtle changes in the reverse-transmitted optical signal power (reflecting the growth of the newly deposited layer and changes in its optical properties) as monitored in real time. For example, when it is detected that the deposition rate is too fast and may cause a loose structure, the voltage is appropriately reduced; when the deposition rate is too slow, the voltage is appropriately increased. The voltage range can be initially set between 0.1 volt and several volts, which are all extended implementation methods known to ordinary technicians in this field.

[0051] Furthermore, the vibration-guided directional growth of deposition dendrites is achieved by utilizing the low-frequency vibrations that are inevitably generated during the operation of the corridor structure (for example, caused by nearby traffic, water flow or equipment operation, and the frequency range may be from a few hertz to tens of hertz). The optical fiber sensor itself (such as a long-period grating or distributed acoustic sensing function) can capture these vibration signals in real time and extract their main frequency components and amplitude information through spectral analysis; establishing a dynamic mapping model between vibration frequency and deposition voltage can be a rule-based control logic or machine learning algorithm. The core idea is that specific vibration modes may correspond to stress concentration areas or potential weak links in the structure. By using these vibration characteristics (such as the energy proportion of a specific frequency, the main frequency offset, etc.) as input, the model outputs a fine-tuning signal for the electrochemical deposition voltage. For example, when a significant increase in vibration energy is detected in a certain direction, it may indicate that stress concentration exists in that direction. At this time, the model can adjust the polarity or amplitude of the deposition voltage, attempting to use the influence of the electric field on ion migration and deposition morphology, as well as the disturbance of the vibration itself on the mass transfer process and crystal growth, to indirectly promote the nucleation and growth of deposits such as dendritic iron oxyhydroxide in these areas, thereby achieving targeted repair or enhancement of weak areas to a certain extent.

[0052] For the process of using nano-titanium oxide photocatalysis to accelerate the oxidation and deposition of residual iron ions, when the ambient humidity is monitored by the temperature and humidity sensor to exceed the preset threshold, for example, the preset humidity threshold is calculated by the formula equal to the humidity sensitivity coefficient multiplied by the typical ambient humidity of the tunnel, where the humidity sensitivity coefficient can be selected between 0.8 and 1.2 based on experimental data to ensure activation under relatively high humidity but unsaturated conditions. The typical ambient humidity of the tunnel can be the average value of long-term monitoring or a representative higher humidity value, such as 85% relative humidity, and there are certain lighting conditions, which can be weak scattered light in the tunnel, or a micro-light-emitting diode integrated near the sensor as an auxiliary light source, whose wavelength matches the light absorption spectrum of nano-titanium oxide, such as the ultraviolet or blue light region, the nano-titanium oxide particles will produce active oxygen species such as hydroxyl radicals. These strong oxidizing substances can effectively accelerate the oxidation of residual ferrous ions in the environment to trivalent iron ions, and promote their hydrolysis and deposition as ferric hydroxide, thereby improving the formation rate and density of the self-healing layer.

[0053] Finally, regarding the construction of a three-dimensional assessment matrix for evaluating the degree of corrosion of underground pipeline corridor structures, the three dimensions of this matrix can be represented respectively: the first dimension is the degree of chemical evolution of corrosion products represented by the shift of characteristic peaks of the photoluminescence spectrum and the optical power attenuation rate; the second dimension is the degree of deterioration of the local mechanical state of the structure reflected by the strain distribution cloud map monitored by the long-period grating; and the third dimension is the corrosiveness level of the corrosion environment indicated by parameters such as the rate of change of the environmental refractive index. The spatiotemporal correlation analysis module is responsible for fusing and processing data from these three dimensions. In the temporal dimension, precisely synchronized timestamps are assigned to each sensor signal to ensure temporal alignment of data from different sources. In the spatial dimension, chemical corrosion information, mechanical state information, and environmental information from different sensing points are spatially registered based on the distributed deployment locations of the sensor fibers within the tunnel structure. Correlation analysis can employ multivariate statistical methods, such as principal component analysis, to extract key feature vectors that comprehensively reflect the corrosion state. Alternatively, machine learning models, such as neural networks or support vector machines, can be trained on a large amount of historical monitoring data and corresponding structural condition assessment results to establish a mapping from multidimensional sensor data to corrosion levels (e.g., mild, moderate, severe) or mechanical degradation indicators (e.g., percentage of remaining load-bearing capacity). The output of this three-dimensional assessment matrix, for example, can include corrosion growth rate maps, stress concentration evolution maps, and comprehensive corrosion risk distribution maps for the tunnel structure at different locations and times. This provides a quantitative basis for predicting the structure's remaining service life (e.g., by extrapolating corrosion rate and material degradation curves) and formulating maintenance strategies (e.g., determining priority repair areas and timing).

[0054] Example 4: In this example, a composite fiber optic sensing structure is used to monitor the corrosion status of underground pipeline corridor structures. The structure consists of an Fe-C alloy-coated fiber and a long-period grating (LPG). The main function of the Fe-C alloy-coated fiber is to react with corrosion products (such as chlorides) through its surface coating, causing changes in the optical properties of the fiber. The long-period grating is used to monitor the mechanical stress of the structure through the strain characteristics of the fiber. In the specific implementation of the fiber optic sensing structure, the thickness of the Fe-C alloy coating is a key factor affecting the sensitivity of the sensor. To accurately monitor the reaction of the fiber, the following formula is used for dynamic thickness calibration: ,in, is the coating thickness of the optical fiber, is the calibration coefficient, is the optical loss in the fiber, the calibration factor Determined based on experimental conditions and the characteristics of the optical fiber material, usually measured and adjusted experimentally, this formula indicates that the loss of the optical fiber is proportional to its coating thickness, reflecting how the substances produced during the corrosion process affect the loss of the optical fiber.

[0055] Within underground pipe corridor structures, fiber optic sensors provide corrosion signals by detecting the chemical changes of corrosion products in real time. LPFG technology accurately measures the strain of the optical fiber and further corrects the signal through changes in optical properties that react with the corrosion products. After signal acquisition, the following processing steps are applied: 1. Filter the original signal to remove noise. 2. Use a multi-physics collaborative sensing mechanism to compensate for environmental factors such as temperature and humidity. 3. Based on the compensated data, combined with the strain data and optical power loss from the fiber optic sensor, an appropriate algorithm, such as an adaptive compensation mechanism, is used to calculate the corrosion rate of the structure. This method allows the corrosion signal to be correlated with time, generating a time-series diagram of the corrosion degree and further analyzing the corrosion trend.

[0056] On the basis of data collection, a corrosion assessment matrix is ​​established by using multi-physical quantity sensing and strain compensation mechanism. The assessment matrix mainly consists of the following parts: corrosion product concentration (chemical changes measured by optical fiber sensing), corrosion layer thickness (calculated by loss data and thickness formula), and structure strain state (strain data provided by long-period fiber grating). Through the combination of these variables, a data-driven corrosion assessment model can be constructed. The model uses a weighted average method to integrate the contributions of different physical quantities and finally outputs an assessment of the corrosion state of the underground pipeline corridor structure. At the same time, in order to ensure the long-term stability and accuracy of the entire system, the sensor should be calibrated regularly during implementation, and the known corrosion model data should be compared with the sensor output signal to adjust the parameters in the system (such as the calibration coefficient ) to improve the accuracy and stability of the system, which are all extended implementation methods known to ordinary technicians in this field.

[0057] 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.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for monitoring and evaluating underground pipe gallery structure corrosion based on optical fiber sensing, characterized in that: The method comprises the following steps: Step 1: constructing a composite optical fiber sensing structure, wherein the composite optical fiber sensing structure comprises at least one Fe-C alloy coated optical fiber, wherein the Fe-C alloy coated optical fiber is provided with at least one long period grating along its length, for distributed deployment in an underground pipe gallery structure; Step 2: Using an Fe-C alloy-coated optical fiber to capture the photoluminescence spectrum characteristics caused by changes in the chemical composition of corrosion products in the underground pipeline corridor structure, and extracting the characteristic peak shift and optical power attenuation rate of the photoluminescence spectrum; using the strain-sensitive characteristics of the long-period grating, the strain distribution at the location of the Fe-C alloy-coated optical fiber is monitored and a strain distribution cloud map is generated; and the refractive index change rate of the environment in which the Fe-C alloy-coated optical fiber is located is simultaneously monitored. The refractive index change rate reflects the change in ion concentration in the corrosive environment; Step 3: Based on the optical power attenuation rate of the photoluminescence spectrum and combined with the pre-established coating layer thickness and normalized luminous intensity attenuation The quantitative model of Dynamic self-calibration is performed on the measurement deviation of the characteristic peak displacement of the photoluminescence spectrum caused by the loss of the coating layer, wherein is a calibration coefficient related to the properties of the coating material; at least one reference grating is embedded in the composite fiber optic sensing structure, and the reference grating is used to monitor the ambient temperature. Based on the time domain characteristic differences between the ambient temperature and the corrosion exotherm effect, an adaptive noise suppression model is constructed; the adaptive noise suppression model distinguishes between ambient temperature changes and corrosion exotherm effects by analyzing the time domain correlation between the center wavelength offset of the reference grating and the center wavelength offset of the monitoring grating, and compensates for the monitoring signal; In step 4, a spatiotemporal correlation analysis is performed on the characteristic peak displacement of the photoluminescence spectrum self-calibrated in step 3, the strain distribution cloud map after noise suppression in step 3, and the rate of change of the environmental refractive index to construct a three-dimensional evaluation matrix for evaluating the degree of corrosion of the underground pipeline corridor structure. The three-dimensional evaluation matrix represents the comprehensive effect of the corrosion rate, degradation of the mechanical properties of the material, and environmental influencing factors.

2. The method for monitoring and evaluating underground pipe gallery structure corrosion based on optical fiber sensing according to claim 1 is characterized in that: The coating layer of the Fe-C alloy-coated optical fiber is provided with an Fe content gradient along the axial direction of the optical fiber, and the characteristic differences of the photoluminescence spectra at different axial positions are analyzed.

3. The method for monitoring and evaluating underground pipe gallery structure corrosion based on optical fiber sensing according to claim 1 is characterized in that: The spatiotemporal correlation analysis includes accurately synchronizing the acquisition time of different sensor signals and aligning them based on their spatial position information in the underground pipeline corridor structure.

4. The method for monitoring and evaluating underground pipe gallery structure corrosion based on optical fiber sensing according to claim 1 is characterized in that: A nano-alumina porous dielectric layer is provided on the cladding surface of the Fe-C alloy-coated optical fiber. When the coating layer thickness decays to a critical threshold, the electrochemical redeposition control module uses the reverse transmission light signal intensity to detect the coating layer depletion state and trigger the in-situ oxidation deposition of residual iron ions in the coating material, forming a dynamically updated corrosion-sensitive layer.

5. The method for monitoring and evaluating underground pipe gallery structure corrosion based on optical fiber sensing according to claim 4 is characterized in that: When the electrochemical redeposition control module detects that the coating layer thickness has decayed to a preset range, it activates the built-in pH-responsive microcapsule to release the buffer solution and dynamically adjusts the electrochemical deposition voltage according to the change in the power value of the reverse-transmitted optical signal to control the residual iron ions to form a dendritic FeOOH deposition structure in the alumina pores.

6. The method for monitoring and evaluating underground pipe gallery structure corrosion based on optical fiber sensing according to claim 5 is characterized in that: During the formation of FeOOH dendritic deposition structures, the vibration spectrum of the pipeline corridor structure is captured in real time by optical fiber sensors, and the characteristic frequency components within a preset frequency range are extracted. Based on the established vibration frequency-deposition voltage dynamic mapping model, the deposition voltage is adaptively adjusted to guide the deposition dendrites to grow directional along the direction of stress concentration.

7. The method for monitoring and evaluating underground pipe gallery structure corrosion based on optical fiber sensing according to claim 6 is characterized in that: Nano-titanium oxide photocatalytic particles are embedded in the electrolyte microcapsules. Exceeding the preset threshold When the photocatalytic reaction is triggered to generate hydroxyl radicals, the oxidation deposition process of residual iron ions is accelerated, where the preset threshold satisfy , is the humidity sensitivity coefficient, This is the typical environmental humidity of the pipeline corridor.

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