A steel structure stress monitoring method based on distributed optical fiber sensing

Abstract

The present application relates to the technical field of structural stress precision measurement, and particularly relates to a steel structure stress monitoring method based on distributed optical fiber sensing, comprising the following steps: step 1: constructing a sensing optical fiber array in a steel structure node area; step 2: injecting an optical pulse into the sensing optical fiber array, and synchronously collecting Brillouin frequency shift signals and Raman scattering signals of each point; step 3: separating temperature and mechanical strain based on a reference optical fiber signal: globally compensating for temperature for a first optical fiber group, and compensating for a temperature gradient along an optical fiber path for a second optical fiber group; step 4: decomposing the compensated mechanical strain into multi-directional strain components according to the spatial orientation of the optical fiber, and reconstructing a three-dimensional stress field through strain component fusion; and step 5: dynamically determining damage risk according to a local stress concentration coefficient in the stress field and a change rate thereof. Through the temperature compensation technology, the influence of environmental temperature change on strain data is eliminated, and the reliability of the monitoring result is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of structural stress precision measurement, and particularly relates to a steel structure stress monitoring method based on distributed optical fiber sensing. BACKGROUND

[0002] The stress state of a steel structure node, which is a force transmission hub of the overall structure, directly determines the safety of the project. The application of existing stress monitoring technology in this field has the following essential defects:

[0003] 1. Stress field blind area caused by insufficient spatial resolution;

[0004] Traditional resistance strain gauges or point-type optical fiber sensors monitor in a discrete point distribution manner, and the spacing between adjacent measuring points is usually greater than 50 mm. However, there is a significant stress gradient mutation in the steel structure node area (such as the beam-column connection), and at key positions such as the periphery of the bolt hole and the end of the weld, the stress changes can be compressed to the millimeter level. The existing technology cannot capture such microscopic stress concentration phenomena due to insufficient spatial sampling density, resulting in the missed location of fatigue cracks. This problem is determined by the geometric discontinuity of the node (such as the cross-section mutation) and the stress diffusion characteristics, and has physical inevitability.

[0005] 2. Measurement reference drift caused by temperature effect;

[0006] The thermal expansion coefficient of steel structure is significant (usually > 12 × 10 -6 / ℃), and under the condition of solar temperature difference, the node surface can produce apparent strain of the same order of magnitude as the mechanical stress. Although the existing sensors (such as FBG fiber Bragg gratings) can monitor the temperature synchronously, only a single temperature compensation coefficient is used for global correction. Due to the differences in material thickness and shadow effect in the node area, there is actually a non-uniform temperature field (the measured gradient can reach 5℃ / cm). This spatial temperature distribution inhomogeneity causes the traditional compensation model to fail, producing a false strain signal of > 50με, which seriously interferes with the true stress evaluation.

[0007] 3. Measurement misalignment caused by curvature adaptability defects;

[0008] Complex nodes often have three-dimensional curved surface characteristics (such as arc stiffening ribs), and the curvature radius is generally less than 100 mm. Due to the high bending stiffness of rigid sensors (such as MEMS strain gauges), micro-gaps or local debonding occur between the sensor and the curved surface during installation, resulting in a decrease of more than 30% in strain transfer rate. Especially in high-curvature areas, the sensor substrate deformation and the steel structure body deformation are decoupled, causing the measured value to deviate from the true surface strain. This problem is caused by the failure of mechanical coupling between the sensor-structure interface, and is unavoidable in special-shaped nodes.

[0009] Therefore, there is an urgent need for a steel structure stress monitoring method based on distributed optical fiber sensing to solve the above problems. SUMMARY

[0010] To achieve the above object, the present application provides a steel structure stress monitoring method based on distributed optical fiber sensing, comprising:

[0011] Step 1: Construct a sensing optical fiber array in the node area of the steel structure, including a first optical fiber group arranged in a spiral ring, a second optical fiber group arranged in a radial pattern, and a reference optical fiber not in contact with the structure surface;

[0012] Step 2: Inject an optical pulse into the sensing optical fiber array, and synchronously collect the Brillouin frequency shift signal and the Raman scattering signal of each point;

[0013] Step 3: Separate the temperature and mechanical strain based on the reference optical fiber signal: use global temperature compensation for the first optical fiber group, and use temperature gradient compensation along the optical fiber path for the second optical fiber group;

[0014] Step 4: Decompose the compensated mechanical strain into multi-directional strain components according to the spatial orientation of the optical fiber, and reconstruct a three-dimensional stress field through strain component fusion;

[0015] Step 5: Dynamically determine the damage risk according to the local stress concentration coefficient and its change rate in the stress field.

[0016] Preferably, the construction of the sensing optical fiber array in step 1 comprises:

[0017] The pitch of the spiral ring arrangement is set according to the minimum curvature radius of the steel structure: measure the minimum curvature radius of the surface of the bar, use a preset multiple of the radius as the maximum pitch reference value, and the actual pitch is an equal interval value smaller than the reference value;

[0018] The included angle of the radial arrangement is adaptively adjusted according to the symmetry of the node: obtain the geometric topology of the node through three-dimensional laser scanning, and reduce the included angle of the optical fiber to a preset lower limit in the stress transfer path turning area;

[0019] The arrangement direction of the reference optical fiber is parallel to the maximum direction of the thermal expansion coefficient of the steel structure, and the gap between the reference optical fiber and the structure surface is determined through thermal deformation simulation to ensure that the optical fiber is not mechanically constrained when the temperature changes.

[0020] Preferably, the implementation of the temperature gradient compensation in step 3 comprises:

[0021] The global temperature compensation formula is: mechanical strain = apparent strain - material thermal expansion coefficient x (current temperature - reference temperature), wherein the reference temperature is taken from the real-time measurement value of the reference optical fiber;

[0022] The temperature gradient compensation formula is: mechanical strain = apparent strain - temperature gradient compensation coefficient x temperature change rate along the length direction of the optical fiber, and the temperature gradient compensation coefficient is calibrated through a step temperature change experiment: in a constant load state, the ambient temperature is increased at a fixed step, and the linear relationship slope of the temperature gradient and the apparent strain is recorded;

[0023] The material thermal expansion coefficient is obtained by a thermal dilatometer.

[0024] Preferably, the strain component fusion in step 4 includes:

[0025] The axial strain and the hoop strain of the helical winding optical fiber group are decomposed according to the sine and cosine components of the helical unwinding angle;

[0026] For the radial optical fiber group, three intersecting optical fibers are selected to form a strain sensing unit, and a plane strain conversion matrix is constructed according to the included angle between the optical fibers, which is derived based on the strain compatibility equation of elasticity and meets the displacement field continuity condition.

[0027] The hoop strain component and the plane strain tensor are weighted and superimposed according to the spatial position, and the weight coefficient is dynamically adjusted according to the distance of the node region from the center.

[0028] Preferably, the dynamic threshold for determining damage risk in step 5 includes:

[0029] The local stress concentration coefficient = monitoring point stress value / steel structure design allowable stress;

[0030] The change rate threshold is set by regression analysis of historical damage data: the stress time series of the structure that has occurred damage is extracted, the stress increment distribution per unit time before damage occurs is counted, and the upper quantile of the distribution is taken as the threshold reference;

[0031] The number of continuous alarm points is determined according to the main frequency of the structure vibration: the vibration frequency of the steel structure under environmental excitation is measured, the reciprocal of the frequency is multiplied by a preset period multiple to obtain the minimum continuous alarm time, and then converted to the corresponding sampling point number.

[0032] Preferably, the measurement method of the minimum curvature radius includes:

[0033] The curvature gauge is used to scan the surface of the rod, the curvature value corresponding to the maximum deflection angle of the curvature gauge pointer is recorded, and the minimum value of all measured values is taken as the reference.

[0034] Preferably, the specific process of the step temperature change experiment includes:

[0035] The steel structure specimen with attached optical fiber is placed in the temperature control cabin, and a constant axial load is applied;

[0036] The temperature in the cabin is gradually increased at a fixed temperature interval, and the apparent strain and temperature gradient data are collected after each temperature is stable.

[0037] Draw the temperature gradient-apparent strain scatter plot, and obtain the compensation coefficient by linear fitting.

[0038] Preferably, the dynamic adjustment rule of the weight coefficient comprises:

[0039] In the node centroid area, the weight of the hoop strain component is higher than that of the plane strain tensor;

[0040] At the connection of the rod away from the centroid, the weight of the plane strain tensor is linearly increased with the distance.

[0041] Preferably, the acquisition of the historical damage data comprises:

[0042] In the laboratory, fatigue loading tests are carried out on the same material specimen, and a high-frequency strain gauge is used to record the stress change history in the last hour before damage occurs.

[0043] Preferably, the implementation manner of the synchronous acquisition in step 2 comprises:

[0044] The time division multiplexing technology is used to alternately emit Brillouin scattering and Raman scattering: narrow pulse width light pulses are first emitted to collect Brillouin frequency shift, and then wide pulse width light pulses are emitted to collect Raman anti-Stokes light intensity.

[0045] The beneficial effects of the present application are:

[0046] 1、The present application adopts distributed optical fiber sensing technology, constructs a sensing optical fiber array in the node area of the steel structure, and uses the first optical fiber group arranged in a spiral, the second optical fiber group arranged in a radial, and the reference optical fiber, which significantly improves the spatial resolution. Each measuring point can monitor the stress distribution of the structure in real time, thereby overcoming the stress field blind area problem caused by insufficient spatial sampling density in the prior art. The scheme can capture the small changes of stress gradient mutation, ensure that stress concentration and crack initiation are found in time at key positions, and greatly improve the safety of the steel structure.

[0047] 2、The present application fundamentally solves this problem by adopting global temperature compensation and temperature gradient compensation along the optical fiber path. Specifically, based on the temperature measurement of the reference optical fiber signal, combined with the temperature gradient compensation formula and the real-time measurement of the material thermal expansion coefficient, more accurate temperature correction can be realized. Temperature gradient compensation obtains the temperature compensation coefficient through step temperature change experiment, which ensures that the influence of temperature field non-uniformity is fully eliminated, thereby effectively reducing the false strain signal caused by temperature effect, and ensuring the accuracy of the stress monitoring data.

[0048] 3、The distributed optical fiber sensor adopted by the application has high surface adaptability. Through the spiral winding arrangement of the optical fiber array, the surface of the steel structure can be closely fitted, and the measurement error caused by the micro gap or debonding phenomenon between the sensor and the surface is avoided. In addition, the flexibility and distributed characteristics of the optical fiber enable the optical fiber to respond to strain changes uniformly on the curved surface, ensuring the measurement accuracy in the high curvature area, improving the reliability of stress monitoring, and solving the adaptability defects of traditional rigid sensors. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0050] Fig. 1 The step flow chart of the method of the application;

[0051] Fig. 2 The step flow chart of the strain component fusion in step 4 of the method of the application;

[0052] Fig. 3 The step flow chart of the specific process of the step-by-step temperature change experiment of the method of the application. DETAILED DESCRIPTION

[0053] The application will be described in detail below in combination with the drawings and specific embodiments. It should be noted here that in order to make the embodiments more detailed, the following embodiments are the best and preferred embodiments, and other alternative ways can also be used by those skilled in the art to implement some known technologies; and the drawings are only used to more specifically describe the embodiments, and are not intended to specifically limit the application.

[0054] Please see Figs. 1-3 The embodiment of the application provides a steel structure stress monitoring method based on distributed optical fiber sensing. In step 1, an array of sensing optical fibers is arranged in the node area of the steel structure, including two groups of optical fibers: one group is a first group of optical fibers arranged in a spiral winding manner, and the other group is a second group of optical fibers arranged in a radial manner. In addition, a reference optical fiber is provided which is not in contact with the surface of the structure. The arrangement of the first group of optical fibers and the second group of optical fibers can cover the multidirectional strain changes in the node area, so that the sensing area can be uniformly distributed, improving the monitoring accuracy of the stress field. The reference optical fiber is used to monitor the temperature change in real time, providing data support for subsequent temperature compensation. This design effectively solves the blind area problem caused by the insufficient spatial resolution of traditional optical fiber sensors, improving the comprehensiveness and accuracy of the monitoring area.

[0055] In step 2, after injecting light pulses into the arranged sensing fiber array, Brillouin frequency shift signals and Raman scattering signals are generated in the optical fibers. These two signals are closely related to strain and temperature changes, respectively. By synchronously collecting these signals, the stress and temperature information of each measurement point can be accurately obtained, providing a basis for subsequent data analysis.

[0056] In step 3, based on the temperature data collected by the reference optical fiber, global temperature compensation is used to correct the signals of the first fiber group, eliminating the strain interference caused by temperature changes. For the second fiber group, temperature gradient compensation along the fiber path is used, considering the uneven temperature distribution in the node area, further improving the accuracy of temperature compensation. This step can effectively eliminate the influence of temperature effects on stress monitoring results, ensuring the accuracy of the stress signal.

[0057] In step 4, the mechanical strain signal after temperature compensation is decomposed into multi-directional strain components according to the orientation of the optical fiber in space. By fusing these strain components, the three-dimensional stress field of the node area can be reconstructed. This step can accurately describe the distribution of the stress field at the node, especially in complex geometric configurations, better revealing the small changes in structural stress, avoiding the limitations of traditional strain sensors, and solving the problem of insufficient spatial resolution.

[0058] In step 5, by analyzing the local stress concentration coefficient and its change rate in the three-dimensional stress field, the possible damage risk can be dynamically determined. When the stress concentration coefficient of a certain area changes significantly, it indicates that cracks or other forms of damage may occur in that area. This step can monitor the health status of steel structures in real time, and detect potential structural damage in advance, providing important basis for the maintenance and safety management of structures.

[0059] Through the above steps, the problems of insufficient spatial resolution, temperature effect interference, and poor curve adaptability in traditional stress monitoring methods are solved. The application of distributed optical fiber sensing technology not only improves the accuracy of stress monitoring, but also comprehensively reflects the stress distribution of steel structure nodes, overcoming the limitations of traditional methods. In addition, the innovation of temperature compensation and strain decomposition technology effectively eliminates the interference of environmental temperature on monitoring data, ensuring the reliability of monitoring results. This method can significantly improve the safety of steel structures, provide early warning of structural damage, and has wide application prospects.

[0060] In one possible implementation, in the node area of the steel structure, in order to realize uniform stress distribution monitoring, the pitch of the spiral wrapped optical fiber needs to be accurately set according to the minimum curvature radius of the steel structure. First, by measuring the minimum curvature radius of the surface of the bar, a preset multiple of the radius is determined as the reference value of the maximum pitch. Then, the actual pitch is taken as an equal interval value smaller than the reference value, so that the distribution of the optical fiber can be matched with the geometric characteristics of the structure, effectively improving the coverage density of the monitoring area and avoiding the omission of local strain information caused by excessive pitch. This design not only improves the accuracy of sensing, but also reduces the monitoring blind area caused by curvature changes.

[0061] In order to maximize the accuracy of stress monitoring in the node area, an adaptive adjustment method of the included angle is adopted. When constructing the optical fiber array, the geometric topology data of the node is obtained by three-dimensional laser scanning technology, especially for the stress transfer path turning area of the node, the arrangement angle of the optical fiber is dynamically adjusted according to the scanning data. Specifically, in the stress transfer path turning area, the included angle of the optical fiber is reduced to a preset lower limit angle to ensure that the optical fiber can capture stress concentration and changes more finely, especially in areas prone to local deformation. This method effectively avoids the monitoring blind area caused by improper included angle and improves the response ability of the optical fiber array to the dynamic changes of the structure.

[0062] In order to further improve the accuracy and anti-interference ability of the monitoring system, the arrangement direction of the reference optical fiber is set to be parallel to the maximum direction of the thermal expansion coefficient of the steel structure. The reference optical fiber is mainly used for temperature compensation, so the optimization of its arrangement direction is crucial. Through thermal deformation simulation calculation, it is ensured that the gap between the reference optical fiber and the structure surface remains consistent when the steel structure is heated and expanded, thereby avoiding mechanical constraints on the optical fiber when the temperature changes. This design can effectively eliminate the interference of temperature changes on the sensing signal of the optical fiber, minimize the impact of temperature changes on the monitoring results, and provide more accurate stress data.

[0063] Through the above optimization design, the present application can provide more accurate stress monitoring data in the complex environment of the steel structure. The accurate setting of the pitch and the adaptive adjustment of the included angle of the optical fiber arrangement enable the optical fiber array to flexibly adjust the layout according to the geometric characteristics of the steel structure and the specific circumstances of the stress transfer path, ensuring that the stress data of the key parts of the structure are not missed. The optimization of the arrangement direction of the reference optical fiber effectively avoids the errors caused by temperature changes and enhances the stability and reliability of the system in different working environments. In summary, this method can more accurately reflect the stress distribution of the steel structure and timely discover potential damage risks, and has wide application prospects, especially for the monitoring of complex and dynamic steel structures.

[0064] In one possible implementation, the core of global temperature compensation is to correct the apparent value of mechanical strain based on the temperature data collected in real time from the reference optical fiber, combined with the thermal expansion coefficient of the material. The specific temperature compensation formula is:

[0065] Mechanical strain = apparent strain - thermal expansion coefficient of material × (current temperature - reference temperature);

[0066] Where the reference temperature is taken from the real-time measurement value of the reference optical fiber. The purpose of this step is to eliminate the deviation of the optical fiber strain signal caused by temperature changes, so as to more accurately reflect the strain value caused by mechanical load. In this way, the influence of temperature on strain data can be effectively isolated, ensuring the accuracy of the monitoring results.

[0067] Temperature gradient compensation is mainly to deal with the case of uneven temperature distribution, to ensure that the temperature change along the optical fiber path does not affect the accurate measurement of strain. The compensation formula is:

[0068] Mechanical strain = apparent strain - temperature gradient compensation coefficient × temperature change rate along the length direction of the optical fiber;

[0069] Where the temperature gradient compensation coefficient is calibrated through a step temperature change experiment. The specific steps are as follows: under constant load, increase the environmental temperature at a fixed step, and record the apparent strain data under different temperature conditions. Then, analyze the linear relationship between temperature gradient and apparent strain, and obtain the temperature gradient compensation coefficient through linear regression. This coefficient can dynamically compensate the influence of temperature change on strain, especially in the case of uneven temperature distribution in the node area, which can significantly improve the accuracy of strain data.

[0070] Accurate determination of the thermal expansion coefficient of the material is the basis for temperature compensation. The thermal expansion coefficient of the steel is obtained by testing it with a thermal dilatometer, and is used as one of the parameters in the compensation formula. The thermal expansion coefficient of the material is an important physical quantity that reflects the size change characteristics of the material under temperature change. Accurate thermal expansion coefficient helps to ensure more accurate strain correction in the temperature compensation process.

[0071] The present application effectively eliminates the interference of temperature on strain signal through the double measures of global temperature compensation and temperature gradient compensation, and improves the accuracy of stress monitoring. Global temperature compensation eliminates the influence of environmental temperature on optical fiber measurement, while temperature gradient compensation solves the problem of uneven temperature distribution, especially in large-scale steel structures, where local temperature changes may cause significant deviation in strain value. Through accurate temperature compensation, the stress monitoring data obtained is more true and reliable, providing more accurate basis for the health monitoring and maintenance of steel structures. This technology not only improves the accuracy of stress monitoring, but also minimizes the influence of temperature changes that may occur during long-term operation on monitoring data, and has high application value.

[0072] In one possible implementation, for the spiral winding arrangement of fiber groups, the strain data is affected by the fiber arrangement, including both axial and circumferential strain components. To accurately obtain these two strain components, the strain data is first decomposed by the sine and cosine components of the spiral unwinding angle. The spiral unwinding angle is the spiral angle of the fiber around the structure on the surface of the steel structure, and the sine and cosine functions are used to obtain the axial and circumferential strains respectively. The axial and circumferential strains respectively reflect the stress distribution in the direction of the fiber, and can provide detailed data for the stress changes in different directions of the steel structure. This decomposition method can effectively extract the strain information of the spiral fiber group, and make the monitoring data more consistent with the actual stress state.

[0073] For the radial arrangement of fiber groups, three intersecting fibers are selected to form a strain sensing unit. The included angle of the three intersecting fibers is a key factor affecting strain calculation. According to the included angle between the fibers, a plane strain conversion matrix can be constructed. The derivation of this conversion matrix is based on the strain compatibility equations in elasticity, which ensure that the strain in the structure satisfies the basic conditions of mechanics, especially the continuity of the displacement field. On this basis, through matrix conversion, the plane strain tensor can be accurately extracted from the fiber data, reflecting the strain state of the fiber intersection area.

[0074] Combining the circumferential strain component measured by the spiral fiber group with the plane strain tensor obtained by the plane strain matrix requires weighted superposition according to the spatial position. The weighting coefficient is dynamically adjusted according to the distance of the node region from the center of the structure. The farther the node region is from the center, the greater the weight coefficient in the final strain fusion result, so that the stress distribution far from the center can be more accurately reflected. This weighting method can ensure that the strain data is truly reflected at different spatial positions, especially in complex structures, the data fusion result can be adaptively adjusted according to the distance change.

[0075] Through the axial and circumferential strain decomposition of the spiral winding fiber group, the plane strain conversion of the radial fiber group, and the weighted fusion process, the stress state of each region of the steel structure can be more accurately obtained, especially in complex structures or node regions, the local stress concentration can be more accurately revealed. The weighted superposition method of strain data effectively avoids the monitoring error caused by different node positions, making the stress distribution map of the entire structure more realistic and reliable. Overall, this technical method can provide high-precision stress monitoring data, help engineers discover potential structural problems in a timely manner, and improve the safety and stability of steel structures.

[0076] In one possible implementation, the local stress concentration coefficient is a key indicator for measuring the local stress distribution of the steel structure. Its calculation formula is:

[0077] Local stress concentration coefficient = stress value of monitoring point / allowable stress of steel structure design;

[0078] This coefficient compares the real-time stress value of the monitoring point with the allowable stress during the design of the structure to evaluate whether there is a stress concentration phenomenon in the local area. When the local stress concentration coefficient is greater than 1, it indicates that the stress in this area exceeds the design standard, and there may be a risk of damage. This method can dynamically evaluate the stress condition of the local steel structure through real-time monitoring point data, thereby discovering potential damage risks in advance.

[0079] The change rate threshold is obtained by regression analysis of historical damage data. The specific steps are as follows:

[0080] First, extract the stress time series data of the steel structure that has occurred damage. Further, statistics the stress increment distribution per unit time before the occurrence of damage. Further, select the upper quantile of the stress increment distribution as the benchmark of the change rate threshold.

[0081] This method uses historical data to establish a stress change rule related to damage occurrence, and obtains the critical stress change rate of damage occurrence through regression analysis. When the actual monitored stress change rate exceeds this threshold, it may indicate that the structure enters a high-risk state of damage, which needs attention.

[0082] The number of consecutive alarm points is the key basis for determining whether the steel structure has occurred abnormally. This threshold is determined according to the main frequency of the structure vibration. The specific method is as follows:

[0083] First, measure the vibration frequency of the steel structure under environmental excitation to obtain the main frequency of vibration. Further, multiply the inverse of the main frequency of vibration by the preset period multiple to obtain the minimum continuous alarm duration. Further, convert the alarm duration into the corresponding sampling point number to form the judgment standard of alarm point number.

[0084] This step considers the relationship between the vibration characteristics of the structure and the stress change, ensuring that the damage risk can be judged in real time and accurately under the vibration state of the structure. Through the analysis of the vibration frequency, the false positive rate can be effectively reduced, and the damage state caused by normal vibration of the structure can be avoided.

[0085] By setting a dynamic threshold, the application can accurately determine the damage risk of steel structures under different working conditions, and has significant practical value. The local stress concentration coefficient can reflect whether the local structure is overloaded in real time, and the change rate threshold improves the accuracy of the determination through historical data analysis, while the continuous alarm point number optimizes the alarm mechanism by using the vibration characteristics of the structure. This comprehensive determination method can effectively improve the sensitivity and accuracy of the steel structure health monitoring system, reduce the risk of human interference and misjudgment, and provide more reliable monitoring basis for the long-term operation of steel structures.

[0086] In one possible implementation, first, a curvature gauge is used as a measuring tool to scan the surface of the steel structure member. The curvature gauge is a tool for measuring surface curvature, usually composed of a pointer and a scale. When in use, the curvature gauge is placed smoothly on the surface of the member, and the pointer will deflect according to the bending degree of the member surface. By moving the curvature gauge, the entire member surface is scanned step by step to obtain the curvature data of multiple measurement points.

[0087] At each measurement point, the pointer of the curvature gauge will deflect according to the size of the surface curvature. The maximum angle of the pointer deflection is recorded, and then the corresponding curvature value is calculated through the related formula. Since the surface of the steel structure usually has different bending degrees, the curvature value of each measurement point will be different during the scanning process. These curvature values reflect the curvature changes of the surface of the steel structure member.

[0088] After completing all scanning measurements, all measured curvature values are compared, and the minimum curvature value is selected as the final reference. This minimum curvature value reflects the maximum compactness of the bending of the steel structure surface, i.e. the minimum curvature radius. The minimum curvature radius usually represents the area of the member where local bending is most likely to occur, and is of great significance for analyzing the stress state of the steel structure and evaluating potential damage.

[0089] Through this measurement method, the numerical value of the minimum curvature radius of the steel structure surface can be accurately obtained, which is crucial for subsequent stress analysis. The minimum curvature radius is usually closely related to factors such as deformation and stress concentration of the structure, and can reveal the weak links that may appear in the stress state of the steel structure. Scanning with a curvature gauge has high measurement accuracy, and is simple and easy to operate, with a wide range of applications. In addition, selecting the minimum curvature value as the reference can ensure that the most critical stress parts of the steel structure are monitored, which helps to discover potential deformation problems or damage risks at an early stage, so that maintenance or reinforcement measures can be taken in time to ensure the safety and stability of the structure.

[0090] In one possible implementation, first, the steel structure specimen with the attached distributed fiber optic sensor is placed in the temperature-controlled chamber, and the surface of the specimen is ensured to be well attached, and the fiber can accurately reflect the strain of the steel structure surface. During this process, a constant axial load needs to be applied to ensure that the deformation characteristics of the specimen under load conditions can be monitored. The role of the constant axial load is to simulate the stress state of the steel structure under real working conditions, ensuring the reliability of the experimental data.

[0091] Next, the temperature in the temperature-controlled chamber is gradually increased at fixed intervals, and each level of temperature is kept stable for a certain time after reaching the set value, ensuring that the temperature change is smooth and will not cause rapid strain changes. After each temperature is stable, the apparent strain data and temperature gradient data are recorded. The apparent strain data is monitored in real time by the distributed fiber optic sensor, and the strain data reflects the material expansion or contraction of the steel structure due to temperature changes. The temperature gradient data is used to analyze the differences in temperature changes at different positions of the specimen.

[0092] By collecting the temperature gradient and apparent strain data, a scatter plot of temperature gradient and apparent strain can be drawn. The scatter plot shows the relationship between the deformation response of the steel structure and the temperature change under different temperature conditions. Through the graph, the degree of temperature influence on apparent strain can be observed, and data support for the next step of compensation coefficient calculation is provided.

[0093] In order to eliminate the influence of temperature changes on the strain measurement of the steel structure, linear fitting analysis is needed. By linear fitting the scatter plot of temperature gradient and apparent strain, a compensation coefficient is obtained, which reflects the strain response caused by temperature changes. The calculation of the compensation coefficient is based on the linear relationship between temperature and strain. In practical applications, the compensation coefficient can be used to adjust the error caused by temperature changes during stress monitoring, thereby providing more accurate stress data.

[0094] By systematically simulating the influence of temperature changes on the strain of the steel structure and obtaining the compensation coefficient, the interference caused by temperature changes can be effectively eliminated. This method provides a reliable way to accurately measure the stress state of the structure, especially in environments with large temperature changes, ensuring the accuracy of the monitoring data. The compensation coefficient obtained by linear fitting can be widely used in the long-term monitoring process of steel structures, further improving the accuracy of structural health monitoring, helping engineers to discover potential safety risks in time and take measures.

[0095] In one possible implementation, the centroidal region of a joint in a steel structure is generally the place where the most stress and deformation are concentrated. In this region, due to the presence of multiple stress points and relatively large deformation, the measurement of strain components is particularly important. The hoop strain component mainly reflects the strain characteristics of the steel structure when bending, especially at the centroid of the joint, the stress change of the steel structure is relatively complex, and the hoop strain component is usually more accurate than the plane strain tensor in reflecting the actual stress state of the steel structure. Therefore, in the centroidal region of the joint, the weight of the hoop strain component is set to be higher than that of the plane strain tensor. This adjustment rule helps to strengthen the strain monitoring of this critical area and improve the accuracy of stress analysis.

[0096] At the connection of the steel structure member far away from the centroid of the joint, the stress and strain are generally uniform and stable, but as the distance from the centroid increases, the distribution of strain will change. In order to ensure that the strain data at different positions are properly considered, the weight of the plane strain tensor at the connection of the member far away from the centroid of the joint is linearly increased with the distance from the centroid. This dynamic adjustment rule can take into account the parts far away from the centroid of the joint, whose strain information may have less contribution to the overall stress analysis, but as the distance increases, the influence of the plane strain tensor on the analysis gradually increases. Therefore, by adjusting the weight coefficient in a linearly increasing manner, the stress state of this region can be more accurately reflected, and the analysis results of the overall data can be optimized.

[0097] By dynamically adjusting the weight coefficient, the method can fully consider the strain characteristics of different regions, thereby more accurately reflecting the stress distribution of the steel structure. In the centroidal region of the joint, the higher weight of the hoop strain component can strengthen the monitoring of the critical region of the structure, avoiding errors caused by ignoring local strain. In the region far away from the centroid, the linearly increasing rule of the weight of the plane strain tensor can reasonably weight the strain data at different positions, thereby obtaining more accurate and comprehensive stress monitoring results in the entire structure. Ultimately, this dynamic adjustment rule of the weight coefficient can improve the accuracy and reliability of the stress monitoring of the steel structure, helping engineers to timely discover potential safety hazards of the structure and take effective maintenance measures.

[0098] In one possible implementation, first, a steel structure specimen of the same or similar material as the actual application environment is selected and placed in the experimental equipment for fatigue loading test. The purpose of the fatigue loading test is to simulate the cyclic stress change of the material during long-term stress, especially the response to high-frequency stress change. This process usually involves periodic loading and unloading, and by repeatedly applying loads of different intensities, the behavior and damage of the material under multiple cyclic stresses are observed. By controlling the frequency and amplitude of the load, the fatigue damage process of the steel structure can be accurately reproduced in the experiment.

[0099] During the fatigue loading process, high-frequency strain gauges are used to monitor and record the stress change history of the steel structure specimen in the last hour before damage occurs. The accuracy of the high-frequency strain gauge is crucial, as it can collect strain data at a high frequency, capturing the subtle fluctuations in stress changes over a short period of time. The strain gauge records will reveal the regularity of stress fluctuations and their relationship with structural damage, providing accurate historical data for subsequent damage assessment.

[0100] By recording the stress change history with high-frequency strain gauges, the stress fluctuations of the material during the fatigue loading process can be analyzed, and periods of stress concentration or abnormal changes can be identified. These data provide a theoretical basis for the regularity of stress changes in steel structures in actual use and provide a reference for assessing the degree and type of structural damage. In the stress change data of the last hour, attention is focused on the stress fluctuations near the time of damage occurrence, especially when the structure approaches the fatigue limit.

[0101] Through this method of obtaining historical damage data, important reference can be provided for stress monitoring and damage prediction of steel structures. In practical applications, by analyzing the stress changes of steel structures before damage under different loads, engineers can more accurately predict and assess the health status of steel structures during service. In particular, the combination of fatigue loading tests and high-frequency strain gauges can provide a comprehensive understanding of the fatigue characteristics of steel structure materials and the initial performance of damage, further improving the accuracy and reliability of stress monitoring. Ultimately, this method can provide scientific basis for long-term health monitoring, maintenance decision-making, and safety warning of steel structures, reducing the risk of sudden damage and accidents.

[0102] In one possible implementation, narrow pulse light pulses are first emitted to excite Brillouin scattering signals. The Brillouin scattering signal mainly reflects the frequency shift in the optical fiber due to changes in stress and temperature. The use of narrow pulse light pulses can ensure that the excitation signal has high time resolution, accurately capturing the small frequency shift caused by external stress changes. This is particularly important for stress monitoring of steel structures, as the stress changes in steel structures during long-term use are relatively weak, and only high-precision time resolution can accurately monitor them.

[0103] After the narrow pulse light pulses are excited, the Brillouin scattering signals are collected by the optical fiber sensor to obtain the frequency shift information. The frequency shift of the Brillouin scattering is proportional to the change in stress (especially tensile stress), so this process can provide key data reflecting the stress state of the steel structure. By accurately measuring the Brillouin frequency shift, the stress state of the steel structure can be monitored in real time, providing a basis for subsequent damage assessment and maintenance decision-making.

[0104] Then, wide pulse light pulses are emitted to excite Raman scattering signals. Raman scattering is mainly related to temperature changes, and by analyzing the changes in anti-Stokes light intensity, accurate information about the temperature can be obtained. Since wide pulse light pulses can cover a larger frequency band, the signals caused by temperature changes can be better captured when Raman scattering is excited. By obtaining the anti-Stokes light intensity, the relationship between the stress distribution of the steel structure and the temperature changes under different temperature conditions can be further analyzed.

[0105] Time division multiplexing technology is used to enable the collection of Brillouin scattering and Raman scattering on the same optical fiber sensor to be performed alternately. In different time windows, the system will first emit narrow pulse light pulses and then wide pulse light pulses to ensure that the collection of the two different scattering signals does not interfere with each other. The use of time division multiplexing greatly improves the efficiency of the optical fiber sensor and avoids time delays and system complexity caused by separate collection of different signals.

[0106] By using time division multiplexing technology, the alternate collection of Brillouin scattering and Raman scattering signals is realized, effectively improving the ability to synchronously acquire stress and temperature information. The use of narrow pulse light pulses ensures high time resolution of the Brillouin frequency shift, allowing the small changes in the stress of the steel structure to be accurately captured. Wide pulse light pulses make the monitoring of temperature changes more comprehensive, thereby providing more accurate environmental change information. By simultaneously collecting stress and temperature data, the working state of the steel structure and its response to external environmental changes can be more comprehensively understood. This technology can improve the collection efficiency while ensuring high precision, which is of great significance for long-term health monitoring of steel structures and helps to timely detect potential structural damage and temperature abnormalities, thereby improving the safety and reliability of the structure.

[0107] The following is described in detail by way of example:

[0108] This embodiment specifically introduces how to apply the steel structure stress monitoring method based on distributed optical fiber sensing technology of the present application to the health monitoring of a certain steel structure bridge. The main goal of the bridge is to monitor the stress and temperature changes in real time during its long-term use, so as to timely detect potential structural damage or abnormalities and take necessary maintenance measures.

[0109] During the long-term operation of the bridge, the steel structure of the bridge will experience different degrees of stress changes due to factors such as traffic load and environmental temperature changes. Traditional stress monitoring methods are often limited to local areas and cannot provide stress distribution information for the entire bridge. The goal of the present application is to use distributed optical fiber sensing technology in combination with Brillouin scattering and Raman scattering signals to monitor the stress and temperature changes of the entire bridge in real time, thereby achieving the effect of full-bridge health monitoring.

[0110] Specifically, first, 6 optical fiber sensors are evenly arranged on the steel structure of the bridge and installed along different parts of the bridge transverse structure. The installation position of the optical fiber should be selected in the area with high stress, such as the connection and support point of the bridge. The length of each optical fiber is 2000 meters, which can cover the entire structure of the bridge.

[0111] The optical fiber sensor uses a single-mode optical fiber, and the sensing area is 1 meter per 1 meter, which can obtain the temperature and stress information of the corresponding position. The diameter of the optical fiber is 125 μm, and it is fixed with the structure by special adhesive, which ensures the close contact of the optical fiber with the steel structure, so as to efficiently transfer the stress change.

[0112] According to the time division multiplexing technology, narrow pulse width optical pulses and wide pulse width optical pulses are alternately emitted. The specific optical pulse parameters are as follows:

[0113] Narrow pulse width optical pulse: pulse width is 10 ns, repetition frequency is 1 kHz, and is used to excite Brillouin scattering.

[0114] Wide pulse width optical pulse: pulse width is 200 ns, repetition frequency is 500 Hz, and is used to excite Raman scattering.

[0115] By alternately emitting two different width pulses, Brillouin frequency shift and Raman anti-Stokes light intensity can be captured respectively, ensuring that the stress and temperature data felt on the same optical fiber do not interfere with each other.

[0116] During the acquisition process, the Brillouin frequency shift and the Raman anti-Stokes light intensity are collected by the optical fiber sensor, and the signal is transmitted to the data acquisition system through the optical fiber.

[0117] Brillouin frequency shift formula:

[0118] ;

[0119] wherein, is the Brillouin frequency shift, is the strain, is the length of the optical fiber sensor, is the laser wavelength.

[0120] Raman anti-Stokes light intensity formula:

[0121] ;

[0122] wherein, is the Raman anti-Stokes light intensity, is the initial light intensity, is the attenuation coefficient of the optical fiber, is the length of the optical fiber.

[0123] Based on the above formula, the stress and temperature changes can be calculated respectively by real-time acquisition of Brillouin frequency shift and Raman light intensity.

[0124] The analysis of the signal is carried out by combining time domain and frequency domain analysis. In the time domain analysis, the change trend of Brillouin frequency shift and Raman anti-Stokes light intensity is related to the stress and temperature change respectively.

[0125] For stress change, the following stress-frequency shift relationship is used:

[0126] ;

[0127] According to the change of Raman light intensity, combined with the linear relationship of temperature change:

[0128] ;

[0129] Through data processing, the real-time stress and temperature distribution of each position of the bridge is obtained.

[0130] The monitoring data is transmitted to the monitoring platform through the real-time data acquisition system, and the stress and temperature values of each position are displayed. The monitoring platform combines external factors such as weather and traffic load to analyze and predict the data, and timely discovers abnormal stress and temperature changes.

[0131] In the implementation process, the stress and temperature monitoring method of the present application shows significant advantages. The following is a comparison with the traditional stress monitoring method:

[0132] Traditional method: such as strain gauge method, only can obtain the stress data of local area, and the precision is greatly influenced by installation position, temperature change and other factors.

[0133] The method of the present application: using distributed optical fiber sensing technology, can real-time monitor the stress and temperature distribution of the whole bridge, no matter in which position of the bridge, can obtain accurate stress and temperature data, and is less affected by environmental interference. Experimental results show that when measuring the stress change of the same position, the error of the method of the present application is less than 5%, while the error of the traditional strain gauge method can reach 10%-15%.

[0134] In practical application, through continuous 24-hour data acquisition and monitoring, the stress distribution of the bridge is real-time monitored. Especially when major traffic load occurs, the monitoring system can discover that the stress of local area of the bridge is too large in advance, issue a warning signal, and take load reduction measures in time to avoid possible structure damage.

[0135] Through this embodiment, the complete application process of the steel structure stress monitoring method based on distributed optical fiber sensing technology is demonstrated. From experimental design, installation of optical fiber sensors, emission of optical pulses and signal acquisition, data analysis and result processing to the final application effect, the application provides an efficient and accurate steel structure stress monitoring scheme. Compared with traditional methods, the application can realize real-time health monitoring of the whole bridge, and has higher measurement accuracy and stronger environmental adaptability. The popularization and application of the technology will greatly improve the efficiency and safety of structure health monitoring, and has wide engineering application prospect.

[0136] The present application encompasses any substitutions, modifications, equivalent methods and schemes made on the essence and scope of the present application. In order to make the public have a thorough understanding of the present application, specific details are described in the following preferred embodiments of the present application, and the present application can also be fully understood without the description of these details to those skilled in the art. In addition, in order to avoid unnecessary confusion to the essence of the present application, well-known methods, processes, procedures, elements and circuits, etc. are not described in detail.

[0137] The above is only the preferred embodiment of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can also be made, which should be considered as the protection scope of the present application.

Claims

1. A method for monitoring stress of a steel structure based on distributed fiber sensing, characterized in that, The method comprises the following steps: Step 1: constructing a sensing fiber array in the node area of the steel structure, including a first fiber group in a spiral arrangement, a second fiber group in a radial arrangement, and a reference fiber not in contact with the structure surface; Step 2: injecting light pulses into the sensing fiber array, and synchronously collecting the Brillouin frequency shift signals and Raman scattering signals of each point; Step 3: separating the temperature and mechanical strain based on the reference fiber signal: using global temperature compensation for the first fiber group, and using temperature gradient compensation along the fiber path for the second fiber group; Step 4: decomposing the compensated mechanical strain into multi-directional strain components according to the spatial orientation of the fiber, and reconstructing a three-dimensional stress field through strain component fusion; Step 5: dynamically determining the damage risk according to the local stress concentration coefficient and its change rate in the stress field; The construction of the sensing fiber array in step 1 comprises: The pitch of the spiral arrangement is set according to the minimum curvature radius of the steel structure: the minimum curvature radius of the surface of the bar is measured, a preset multiple of the radius is taken as the maximum pitch reference value, and the actual pitch is an equal interval value smaller than the reference value; The included angle of the radial arrangement is adaptively adjusted according to the symmetry of the node: the geometric topology of the node is obtained through three-dimensional laser scanning, and the included angle of the fiber is reduced to a preset lower limit at the turning area of the stress transmission path; The arrangement direction of the reference fiber is parallel to the maximum direction of the thermal expansion coefficient of the steel structure, and the gap between the reference fiber and the structure surface is determined through thermal deformation simulation to ensure that the fiber is not mechanically constrained when the temperature changes; The implementation of the temperature gradient compensation in step 3 comprises: The global temperature compensation formula is: mechanical strain = apparent strain - material thermal expansion coefficient × (current temperature - reference temperature), wherein the reference temperature is taken from the real-time measurement value of the reference fiber; The temperature gradient compensation formula is: mechanical strain = apparent strain - temperature gradient compensation coefficient × temperature change rate along the fiber length direction, and the temperature gradient compensation coefficient is calibrated through a step temperature change experiment: in a constant load state, the environmental temperature is increased at a fixed step, and the linear relationship between the temperature gradient and the apparent strain is recorded; The material thermal expansion coefficient is obtained through a thermal dilatometer; The strain component fusion in step 4 comprises: For the strain data of the spiral arrangement fiber group, the axial strain and the hoop strain are decomposed according to the sine and cosine components of the spiral unwinding angle; For the radial fiber group, three intersecting fibers are selected to form a strain sensing unit, and a plane strain conversion matrix is constructed according to the included angle between the fibers, which is derived based on the strain compatibility equation of elasticity and meets the displacement field continuity condition; The hoop strain component and the plane strain tensor are weighted and superimposed according to the spatial position, and the weight coefficient is dynamically adjusted according to the distance of the node area from the centroid; In the dynamic determination of the damage risk in step 5, the determination of the threshold value comprises: Local stress concentration coefficient = stress value of monitoring point / design allowable stress of steel structure; The change rate threshold is set through regression analysis of historical damage data: the stress time series of the structure with damage is extracted, the stress increment distribution per unit time before damage is counted, and the upper quantile of the distribution is taken as the threshold reference. The continuous alarm point number is determined according to the structural vibration main frequency: the vibration frequency of the steel structure under environmental excitation is measured, the vibration main frequency is obtained, the reciprocal of the vibration main frequency is multiplied by a preset period multiple to obtain the minimum continuous alarm time length, and then the minimum continuous alarm time length is converted into corresponding sampling point number.

2. The method for monitoring stress of steel structure based on distributed optical fiber sensing according to claim 1, characterized in that, The measurement method of the minimum curvature radius comprises: A surface of the rod member is scanned by using a curvature gauge, a curvature value corresponding to a maximum deflection angle of a pointer of the curvature gauge is recorded, and a minimum value in all measurement values is taken as a reference.

3. The method of claim 1, wherein the method is characterized by, The specific process of the stepwise temperature change experiment comprises: The steel structure test piece with the attached optical fiber is placed in a temperature control cabin, and a constant axial load is applied; The temperature in the cabin is gradually increased at a fixed temperature interval, and apparent strain and temperature gradient data are collected after each temperature is stable; A temperature gradient-apparent strain scatter plot is drawn, and a compensation coefficient is obtained through linear fitting.

4. The method of claim 1, wherein the method is a method of monitoring stress of a steel structure based on distributed optical fiber sensing. The dynamic adjustment rule of the weight coefficient comprises: In the nodal centroid region, the weight of the hoop strain component is higher than that of the plane strain tensor; At the rod member connection away from the centroid, the weight of the plane strain tensor linearly increases with distance.

5. The method of claim 4, wherein the method further comprises, The acquisition of the historical damage data comprises: In the laboratory, fatigue loading tests are performed on test pieces of the same material, and a high-frequency strain gauge is used to record the stress change history in the last hour before damage occurs.

6. The method of claim 1, wherein the method is a method of monitoring stress in a steel structure based on distributed optical fiber sensing. The implementation manner of the synchronous acquisition in step 2 comprises: Time division multiplexing technology is used to alternately emit Brillouin scattering and Raman scattering: narrow pulse width light pulses are first emitted to collect Brillouin frequency shift, and then wide pulse width light pulses are emitted to collect Raman anti-Stokes light intensity.

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