Fiber grating-based prestress and concrete compactness monitoring system and method

Abstract

This application discloses a prestressing and concrete density monitoring system and method based on fiber Bragg gratings, relating to the field of wind power generation technology. The system is applied to prestressed steel-concrete truss towers and includes a fiber Bragg grating strain sensor integrated inside the steel strands within the prestressing duct of the truss tower, a first fiber Bragg grating temperature sensor deployed on the circumferential surface of the steel strands, a second fiber Bragg grating temperature sensor correspondingly deployed on the inner wall of the prestressing duct, and a data processing device. The data processing device acquires wavelength data from each sensor through demodulation equipment and calculates the concrete density state and the prestress level of the steel strands within the duct. This application enables synchronous and accurate monitoring of the prestress of the steel strands and the concrete density throughout the entire life cycle of the truss tower, timely identification of structural safety hazards, and ensures the structural safety of the truss tower.

Description

Technical Field

[0001] This application relates to the field of wind power generation technology, and in particular to a prestressing and concrete density monitoring system and method based on fiber Bragg grating. Background Technology

[0002] Prestressed steel-concrete composite truss towers have become the preferred support structure for large-capacity onshore wind turbines due to their advantages such as high structural rigidity, convenient transportation and installation, and high material utilization. The truss tower is filled with concrete and prestressed steel strands in the prestressed pipes, forming a steel-concrete-steel strand collaborative force system. The internal structure of this system is complex and invisible. The grouting density and prestressing tension level during the construction phase directly determine the overall bearing capacity of the structure, and the long-term loss of prestress during operation will also significantly affect the structural safety.

[0003] Current monitoring technologies for this structure are mostly focused on monitoring the preload of truss tower bolts during operation, lacking systematic monitoring methods for the density of concrete grouting during construction. At the same time, there is a lack of solutions that can cover the entire life cycle of construction and operation and can simultaneously and accurately monitor the effective prestress of steel strands and the density of concrete. As a result, it is impossible to monitor and warn of potential problems such as insufficient grouting density and inadequate prestress level in a timely manner, making it difficult to ensure the structural safety of the truss tower throughout its entire life cycle. Summary of the Invention

[0004] This application provides a prestressing and concrete density monitoring system and method based on fiber Bragg gratings. It can solve the problem in related technologies where there is a lack of a systematic monitoring scheme covering the entire construction and operation cycle of truss towers, capable of simultaneously monitoring the prestress of steel strands and the density of concrete inside ducts, thus failing to achieve accurate monitoring and timely early warning of structural safety hazards such as insufficient grouting and inadequate prestressing levels.

[0005] According to a first aspect of this application, a prestressing and concrete density monitoring system based on fiber Bragg gratings is provided, comprising:

[0006] A fiber optic strain sensor (14) is integrated inside the steel strand (7) to monitor the strain of the steel strand (7); Multiple first fiber optic temperature sensors (9) are arranged on the circumferential surface of the steel strand (7) along the length direction of the steel strand (7) to monitor the temperature of the surface of the steel strand (7); Multiple second fiber grating temperature sensors (9) are arranged on the inner wall of the prestressed duct (6) of the truss tower, and their positions correspond to those of the first fiber grating temperature sensor (9). The data processing device (1) acquires the wavelength data of the fiber optic strain sensor (14), the first fiber optic temperature sensor (9), and the second fiber optic temperature sensor (9) through the demodulation device (2), and calculates the density state of the concrete in the prestressed duct (6) of the truss tower and the prestress level of the steel strand (7) based on the wavelength data.

[0007] Optionally, the fiber optic strain sensor (14) is combined with a steel strand protective layer (15) to form a special steel strand, which is twisted together with other ordinary steel strands to form the steel strand (7), and the special steel strand is located at the center of the steel strand (7).

[0008] Optionally, four of the first fiber optic temperature sensors (9) are evenly arranged in the circumferential direction at the same monitoring point of the steel strand (7), that is, one is arranged in every quarter circumference.

[0009] Optionally, the second fiber optic temperature sensor (9) is pre-fixed on a thin steel plate (10) by a clamp (11). The thin steel plate (10) extends into the prestressed duct (6) of the truss tower and is fixed by welding both ends of the thin steel plate (10) to the inner wall of the prestressed duct (6) of the truss tower.

[0010] Optionally, the data processing device (1) calculates the prestress level of the steel strand (7) during the construction period by performing the following steps: The measured wavelength change of the fiber optic strain sensor (14) at the end of the tensioning process is obtained; Acquire the wavelength change of the first fiber optic grating temperature sensor (9) at the same monitoring point at the same time due to temperature; By subtracting the wavelength change caused by temperature from the measured wavelength change, the wavelength change caused solely by strain is obtained. The measured stress value of the steel strand (7) was calculated based on the wavelength change caused solely by strain. The measured stress value is weighted and averaged with the theoretical stress value calculated based on the theoretical friction loss formula to obtain the prestress level at the monitoring point when tensioning is completed.

[0011] Optionally, the data processing device (1) determines the grout density during the construction period by performing the following steps: After grouting is completed, the surface temperature of the steel strand and the inner wall temperature of the pipe are obtained by the first fiber grating temperature sensor (9) and the second fiber grating temperature sensor (9) at the same monitoring point. Calculate the actual temperature difference between the surface temperature of the steel strand and the inner wall temperature of the pipe; Based on the average surface temperature of the steel strand and the inner wall temperature of the pipe, and a preset temperature difference coefficient, the temperature difference threshold at the monitoring point is calculated. The actual temperature difference is compared with the temperature difference threshold. If the actual temperature difference is less than the temperature difference threshold, the grouting at the monitoring point is determined to be dense; otherwise, it is determined to be indense.

[0012] Optionally, the data processing device (1) monitors cracking of the grouting material during operation by performing the following steps: Acquire the temperature data of the second fiber optic temperature sensor (9) at the same monitoring point during the continuous monitoring time interval during the operation period, and calculate the temperature change rate; The stress change rate is calculated from the monitoring data of the fiber optic strain sensor (14) at the same monitoring point within the same time period. The temperature change rate is compared with a preset temperature change threshold, and the stress change rate is compared with a preset strain change threshold; If the temperature change rate is greater than the temperature change threshold and the stress change rate is greater than the strain change threshold, then it is determined that the grouting material at the monitoring point has cracked.

[0013] According to a second aspect of this application, a method for monitoring prestress and concrete density based on fiber Bragg gratings is provided, comprising: S1, A fiber optic strain sensor (14) is integrated inside the steel strand (7), and a first fiber optic temperature sensor (9) and a second fiber optic temperature sensor (9) are arranged on the surface of the steel strand (7) and the inner wall of the prestressed pipe (6) of the truss tower respectively. S2, During the construction period, acquire the wavelength data of the fiber optic strain sensor (14) and each of the fiber optic temperature sensors (9); S3, Based on the wavelength data, the measured stress of the steel strand (7) is calculated by the strain wavelength change after temperature compensation, and the prestress level during the construction period is calculated in combination with the theoretical friction loss; S4. Determine the density of concrete grouting during the construction period based on the temperature difference between the surface of the steel strand and the inner wall of the pipe. S5, During operation, the cracking of concrete during operation is judged by combining the mutation rate of the pipe inner wall temperature data and the mutation rate of the steel strand (7) stress data.

[0014] Optionally, the step of calculating the measured stress of the steel strand (7) based on the wavelength data through the strain wavelength change after temperature compensation, and calculating the prestress level during the construction period in conjunction with theoretical friction loss, includes: Subtract the wavelength change measured by the fiber optic strain sensor (14) from the wavelength change caused by temperature measured by the first fiber optic temperature sensor (9) to obtain the wavelength change caused only by strain. The measured stress at the monitoring point is calculated based on the wavelength change caused solely by strain. The measured stress is weighted and averaged with the theoretical friction loss stress to obtain the prestress level at the monitoring point when tensioning is completed.

[0015] Optionally, the step of determining the density of concrete grouting during construction based on the temperature difference between the surface of the steel strand and the inner wall of the pipe includes: Based on the wavelength change measured by the first fiber grating temperature sensor (9) and the second fiber grating temperature sensor (9), the surface temperature of the steel strand and the inner wall temperature of the pipe are calculated respectively. Calculate the actual temperature difference between the surface temperature of the steel strand and the inner wall temperature of the pipe; Based on the average surface temperature of the steel strand and the inner wall temperature of the pipe, and a preset temperature difference coefficient, the temperature difference threshold at the monitoring point is calculated. The actual temperature difference is compared with the temperature difference threshold. If the actual temperature difference is less than the temperature difference threshold, the grouting at the monitoring point is determined to be dense; otherwise, it is determined to be indense.

[0016] This application addresses the problem of lacking a systematic monitoring scheme that covers the entire construction and operation cycle of truss towers and can simultaneously monitor the prestress of steel strands and the density of concrete inside the pipes. This solution enables accurate monitoring and timely warning of structural safety hazards such as insufficient grouting and inadequate prestress. By integrating fiber optic strain sensors inside the steel strands of the prestressed concrete truss tower and correspondingly arranging fiber optic temperature sensors on the circumferential surface of the steel strands and the inner wall of the prestressed ducts, the wavelength data of each sensor is acquired through demodulation and data processing equipment, and the density of concrete inside the prestressed ducts and the prestress level of the steel strands are calculated simultaneously. This solves the technical effect of simultaneously and accurately monitoring the prestress of steel strands and the density of concrete inside the ducts throughout the entire life cycle of the prestressed concrete truss tower, promptly identifying structural safety hazards, and effectively ensuring the structural bearing capacity and long-term operational safety of the truss tower.

[0017] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0018] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of a prestressed concrete density monitoring system based on fiber Bragg grating provided in an embodiment of this application. Figure 2 This is a schematic diagram of an overall wind power prestressed truss tower-steel tower support structure provided in an embodiment of this application; Figure 3 A schematic diagram of the cross-sectional arrangement of a prestressed duct based on fiber Bragg grating for monitoring prestressing and concrete density is provided for an embodiment of this application. Figure 4 A schematic diagram of a special steel strand composition for monitoring prestressing and concrete density based on fiber Bragg grating, provided for an embodiment of this application; Figure 5 This is a schematic flowchart illustrating a method for monitoring prestress and concrete density based on fiber Bragg gratings, as provided in an embodiment of this application.

[0020] In the diagram: 1. Data processing equipment, 2. Demodulation equipment, 3. Wind turbine generator set, 4. Fan blade, 5. Tower, 6. Truss tower prestressed duct, 7. Steel strand, 8. Fiber optic lead, 9. Fiber Bragg grating temperature sensor, 10. Thin steel plate, 11. Clamp, 12. Anchor, 13. Jack, 14. Fiber Bragg grating strain sensor, 15. Steel strand protective layer, 16. Corrugated pipe. Detailed Implementation

[0021] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0022] The following describes, with reference to the accompanying drawings, an embodiment of the prestressed concrete density monitoring system and method based on fiber optic gratings.

[0023] Figure 1 This is a schematic diagram of a prestressed concrete density monitoring system based on fiber Bragg grating provided in an embodiment of this application. Figure 2 This is a schematic diagram of an overall wind power prestressed truss tower-steel tower support structure provided in an embodiment of this application; Figure 3 A schematic diagram of the cross-sectional arrangement of a prestressed duct based on fiber Bragg grating for monitoring prestressing and concrete density is provided for an embodiment of this application. Figure 4 This is a schematic diagram illustrating the composition of a special steel strand for monitoring prestressing and concrete density based on fiber Bragg gratings, as provided in an embodiment of this application. Figure 1 , Figure 2 , Figure 3 and Figure 4 As shown, the monitoring system includes: A fiber optic strain sensor (14) is integrated inside the steel strand (7) to monitor the strain of the steel strand (7); Multiple first fiber optic temperature sensors (9) are arranged on the circumferential surface of the steel strand (7) along the length direction of the steel strand (7) to monitor the temperature of the surface of the steel strand (7); Multiple second fiber grating temperature sensors (9) are arranged on the inner wall of the prestressed duct (6) of the truss tower, and their positions correspond to those of the first fiber grating temperature sensor (9). The data processing device (1) acquires the wavelength data of the fiber optic strain sensor (14), the first fiber optic temperature sensor (9), and the second fiber optic temperature sensor (9) through the demodulation device (2), and calculates the density state of the concrete in the prestressed duct (6) of the truss tower and the prestress level of the steel strand (7) based on the wavelength data.

[0024] In some embodiments, the fiber optic strain sensor (14) is fabricated based on the Bragg diffraction principle of the fiber optic grating. It has high sensitivity and high stability response characteristics to strain changes and can convert the strain changes of the measured structure into the offset of its own reflected wavelength, thereby realizing high-precision quantitative monitoring of structural deformation. The fiber optic strain sensor (14) is integrated inside the steel strand (7) and forms an integrated and coordinated force-bearing structure with the main structure of the steel strand (7). It can completely follow the elastic deformation, plastic deformation and stress changes of the steel strand (7) during the prestressing tension stage, the service operation stage of the structure and the long-term stress process to generate synchronous deformation response. It completely avoids the defects of slippage, detachment and inconsistency between the monitoring data and the actual stress state of the steel strand (7) that are easy to occur when the sensor is placed externally. It can collect real-time strain data of the steel strand (7) throughout its entire life cycle without distortion, and provide core basic data support for the calculation of the prestress level of the steel strand (7).

[0025] Multiple fiber Bragg grating temperature sensors (9) are uniformly arranged along the axial length of the steel strand (7) at a preset monitoring interval, and simultaneously distributed at multiple points along the circumferential surface of the steel strand (7). This group of fiber Bragg grating temperature sensors (9) arranged on the surface of the steel strand (7) is based on the high sensitivity of fiber Bragg gratings to temperature changes. It can accurately convert changes in ambient temperature into offsets in its own reflected wavelength, achieving high-precision real-time monitoring of ambient temperature. It can comprehensively cover the surface temperature of different axial monitoring sections and different circumferential positions of the steel strand (7), effectively eliminating monitoring errors caused by uneven circumferential temperature distribution of the steel strand (7), and accurately collecting real-time temperature data of the steel strand (7). The collected temperature data can, on the one hand, provide accurate temperature compensation for the strain monitoring data of the fiber Bragg grating strain sensor (14), eliminating interference from ambient temperature changes on the strain monitoring results and ensuring the accuracy of the strain monitoring data; on the other hand, it can provide temperature reference data from the steel strand (7) side for judging the density of concrete.

[0026] Multiple fiber Bragg grating temperature sensors (9) are arranged on the inner wall of the prestressed duct (6) of the truss tower. The prestressed duct (6) is the core load-bearing member of the prestressed steel-concrete truss tower. Its internal cavity is used for pouring concrete and for threading prestressed steel strands (7). The fiber Bragg grating temperature sensors (9) arranged on the inner wall of the prestressed duct (6) of the truss tower adopt the same manufacturing principle and monitoring performance as the fiber Bragg grating temperature sensors (9) arranged on the surface of the steel strands (7). They are arranged along the axial length of the prestressed duct (6) of the truss tower, and the axial position of the arrangement corresponds one-to-one with the axial position of the fiber Bragg grating temperature sensors (9) arranged on the steel strands (7). This ensures that the temperature data of the surface of the steel strands (7) and the inner wall of the prestressed duct (6) of the truss tower can be collected synchronously within the same monitoring section, completely avoiding temperature data comparison deviation caused by misalignment of monitoring positions. The fiber optic temperature sensor (9) is directly attached to the inner wall of the prestressed pipe (6) of the truss tower. It can accurately collect the real-time temperature of the inner wall of the pipe. The inner wall of the pipe is the area most prone to defects such as non-density and hollowness during the concrete pouring process. The temperature data at this location can directly reflect the pouring and filling state of the concrete on the inner wall of the pipe, providing core temperature data on the pipe side for judging the density of the concrete.

[0027] The data processing device (1) forms a stable signal transmission connection with the fiber Bragg grating strain sensor (14) and two sets of fiber Bragg grating temperature sensors (9) through the demodulation device (2). The demodulation device (2) has a fixed wavelength detection range and can collect and demodulate the light signals reflected by each fiber Bragg grating sensor in real time, convert the light signals into corresponding digital wavelength data, and stably transmit the demodulated wavelength data to the data processing device (1). The data processing device (1) has built-in adaptive calculation logic, which can systematically process and analyze the received full wavelength data. Based on the wavelength data collected by the fiber optic strain sensor (14), combined with the temperature data collected by the fiber optic temperature sensor (9) deployed on the surface of the steel strand (7), accurate temperature compensation is performed to calculate the real-time prestress level of the steel strand (7). At the same time, based on the wavelength data collected by the two sets of fiber optic temperature sensors (9) deployed on the surface of the steel strand (7) and the inner wall of the prestressed pipe (6) of the truss tower within the same monitoring section, the real-time temperature of the surface of the steel strand (7) and the inner wall of the prestressed pipe (6) of the truss tower is converted respectively. Through the comparative analysis of the two sets of temperature data, the density state of the concrete in the prestressed pipe (6) of the truss tower is calculated, and finally, the synchronous, real-time and high-precision monitoring of the prestress level of the steel strand (7) and the density state of the concrete is realized.

[0028] This solution achieves distortion-free monitoring of the strain of the steel strand (7) by integrating a fiber optic strain sensor (14) inside the steel strand (7). The simultaneous acquisition of temperature data of the monitoring section is achieved by deploying two sets of fiber optic temperature sensors (9) corresponding to the inner wall of the prestressed pipe (6) of the steel strand (7). This eliminates the interference of temperature changes on the strain monitoring results, ensures the accuracy of prestress calculation, and provides dual-reference temperature data for judging concrete density. At the same time, through the cooperation of data processing equipment (1) and demodulation equipment (2), the simultaneous monitoring of prestress and concrete density is achieved, which can identify structural stress defects in a timely manner and effectively ensure the structural safety and long-term service stability of the prestressed steel pipe concrete truss tower.

[0029] Compared with related technologies, this embodiment integrates fiber optic strain sensors inside the steel strands of the prestressed steel tube concrete truss tower, and arranges fiber optic temperature sensors on the circumferential surface of the steel strands and the inner wall of the prestressed duct of the truss tower, respectively. Wavelength data from each sensor is acquired through demodulation and data processing equipment, and the density of the concrete inside the prestressed duct and the prestress level of the steel strands are calculated simultaneously. Therefore, this solves the problem in related technologies where a systematic monitoring scheme covering the entire construction and operation cycle of the truss tower and simultaneously monitoring the prestress of the steel strands and the density of the concrete inside the duct is lacking. This results in the inability to accurately monitor and promptly warn of structural safety hazards such as insufficient grouting density and inadequate prestress levels. The embodiment achieves the technical effect of synchronously and accurately monitoring the prestress of the steel strands and the density of the concrete throughout the entire life cycle of the prestressed steel tube concrete truss tower, promptly identifying structural safety hazards, and effectively ensuring the structural bearing capacity and long-term operational safety of the truss tower.

[0030] Furthermore, the fiber optic strain sensor (14) is combined with a steel strand protective layer (15) to form a special steel strand, which is twisted together with other ordinary steel strands to form the steel strand (7), and the special steel strand is located at the center of the steel strand (7).

[0031] In this embodiment, the fiber optic strain sensor (14) and the steel strand protective layer (15) are tightly integrated to form a special steel strand with real-time strain monitoring function. The steel strand protective layer (15) is made of a high-strength protective material that matches the mechanical properties of the steel strand substrate. It can form a stable, fully enclosed protective layer for the fiber optic strain sensor (14). Its external dimensions are consistent with the ordinary steel strand used in the steel strand (7), ensuring that the special steel strand formed by the combination has the same stranding adaptability and structural stress performance as the ordinary steel strand. The sensing body of the fiber optic strain sensor (14) is completely attached and fixed to the steel strand protective layer (15), and can form a co-force-bearing overall structure with the steel strand protective layer (15) without the problems of relative slippage and deformation hysteresis.

[0032] The special steel strand is twisted together with multiple ordinary steel strands to form a complete steel strand (7), and the special steel strand is fixedly set at the center of the steel strand (7). The steel strand (7) adopts a multi-layer stranded structure, and the center position is the neutral axis position of the overall structure of the steel strand (7). When the steel strand (7) is subjected to axial tension prestress, alternating loads during service and structural deformation, this position will not be affected by the squeezing interference of the surrounding stranded steel strands, nor will it generate additional shear stress and eccentric stress brought about by the stranded structure. It can most realistically and directly reflect the overall axial force and deformation state of the steel strand (7).

[0033] The steel strand protective layer (15) provides continuous physical protection for the internal fiber optic strain sensor (14) throughout the entire construction process of steel strand (7), including production, stranding, on-site transportation, pipe threading, prestressing tensioning, and concrete pouring. This effectively prevents problems such as fiber bending and breakage, grating structure damage, and signal transmission interruption during construction, ensuring that the fiber optic strain sensor (14) can operate stably and normally throughout the entire life cycle of the steel strand (7), both during construction and operation. Simultaneously, the specially designed steel strands deployed in the center are fully integrated with the overall structure of the steel strand (7), enabling them to generate synchronous strain responses following the overall deformation of the steel strand (7). This ensures that the strain data collected by the fiber optic strain sensor (14) accurately and without distortion corresponds to the actual stress condition of the steel strand (7), providing reliable core data for calculating the prestress level of the steel strand (7).

[0034] This solution combines a fiber optic strain sensor (14) with a steel strand protective layer (15) to form a special steel strand, which is then placed at the center of the steel strand (7) and twisted together with the other ordinary steel strands. This achieves integrated and coordinated force bearing between the strain sensor and the steel strand (7), completely eliminating problems such as slippage, deformation hysteresis, and data distortion that are common with traditional external sensors, and significantly improving the accuracy of strain monitoring. Furthermore, the steel strand protective layer (15) provides full-process protection for the sensor, effectively improving the construction adaptability and long-term operational stability of the monitoring system.

[0035] Furthermore, four of the first fiber optic temperature sensors (9) are evenly arranged circumferentially at the same monitoring point on the steel strand (7), that is, one is arranged for every quarter circumference.

[0036] In this embodiment, at each axial monitoring point of the steel strand (7), corresponding to the same monitoring section, four fiber Bragg grating temperature sensors (9) are evenly arranged along the circumference of the steel strand (7), that is, one sensor is arranged for every quarter circumference. The four fiber Bragg grating temperature sensors (9) are distributed at equal intervals at 90-degree angles in the circumference of the monitoring section, completely covering the entire circumferential range of the monitoring section of the steel strand (7). The four fiber Bragg grating temperature sensors (9) are all stably fixed to the outer surface of the corrugated tube (16) by clamps (11). The corrugated tube (16) is sleeved on the outside of the steel strand (7) and is coaxially arranged with the steel strand (7), ensuring that the four fiber Bragg grating temperature sensors (9) can maintain a stable relative position with the circumferential surface of the steel strand (7), without the risk of displacement or falling off, and can continuously and stably collect surface temperature data at different circumferential positions of the monitoring section of the steel strand (7).

[0037] The method of uniformly arranging four points in the circumference can effectively eliminate the monitoring error caused by the uneven circumferential temperature distribution within the same monitoring section of the steel strand (7). During the construction and operation of the prestressed steel pipe concrete truss tower, the steel strand (7) will have temperature differences at different circumferential positions within the same monitoring section due to various factors such as solar radiation, heat release from concrete hydration in the pipe, changes in ambient temperature, and heat generated by structural stress. If only a single-point temperature sensor is used to collect data, it is very easy to cause the overall temperature judgment of the steel strand (7) to be distorted due to the temperature deviation at the measuring point, which in turn affects the temperature compensation accuracy of the strain monitoring data. By using fiber optic grating temperature sensors (9) uniformly arranged at four points in the same section, real-time temperature data of the four directions of the section can be collected. By averaging the four sets of temperature data, the true average temperature of the steel strand (7) in the monitoring section can be obtained, completely avoiding the randomness and bias of single-point temperature measurement, providing an accurate and reliable temperature compensation benchmark for the strain data of the fiber optic grating strain sensor (14), and ensuring the accuracy of the strain monitoring and prestress calculation results of the steel strand (7).

[0038] Meanwhile, this circumferentially distributed four-point temperature acquisition method can provide a comprehensive steel strand side temperature benchmark for judging the concrete density inside the prestressed duct (6) of the truss tower. During the concrete pouring process, the concrete filling state at different circumferential positions inside the duct varies, and it is very easy for defects such as non-density and hollowness to occur in a certain circumferential position of the duct. This defect will directly cause abnormal deviation between the surface temperature of the steel strand and the inner wall temperature of the duct at the corresponding position. By acquiring four-point temperature data in the full circumference of the same monitoring section of the steel strand (7), the temperature changes in all circumferential positions of the section can be fully covered, and the temperature anomalies caused by non-density of concrete at any circumferential position can be accurately captured. This avoids the missed detection of density defects caused by the blind spots of single-point temperature measurement, and greatly improves the comprehensiveness and accuracy of concrete density monitoring.

[0039] This scheme achieves blind-zone-free temperature acquisition of the entire circumference of the steel strand monitoring section by arranging four fiber optic temperature sensors (9) at equal intervals along a quarter circumference at the same monitoring point of the steel strand (7). This effectively eliminates the temperature measurement deviation caused by uneven circumferential temperature distribution, provides an accurate average temperature benchmark for temperature compensation of strain data, ensures the accuracy of the prestress calculation results of the steel strand, and comprehensively covers the circumferential range of concrete density monitoring, avoiding missed detection of grouting defects and greatly improving the overall monitoring accuracy and operational reliability of the monitoring system.

[0040] Furthermore, the second fiber optic temperature sensor (9) is pre-fixed on the thin steel plate (10) by a clamp (11), the thin steel plate (10) extends into the prestressed pipe (6) of the truss tower, and is fixed by welding both ends of the thin steel plate (10) to the inner wall of the prestressed pipe (6) of the truss tower.

[0041] In this embodiment, before the second fiber Bragg grating temperature sensor (9) is installed on-site, it is first firmly fixed to the suitable thin steel plate (10) by a clamp (11). The clamp (11) is a rigid fixing component that is compatible with the material of the thin steel plate (10). It can synchronously and stably clamp and fix the sensing body of the fiber Bragg grating temperature sensor (9) and the matching fiber optic lead (8) connection section, avoiding problems such as position displacement, structural detachment or fiber bending and breakage during the transportation and installation of the sensor. This not only ensures the accuracy of the sensor's placement position, but also avoids physical damage to the grating sensing area of ​​the sensor, ensuring that the sensor can continuously and accurately respond to temperature changes.

[0042] The outer dimensions of the thin steel plate (10) are perfectly matched with the inner wall shape of the prestressed pipe (6) of the truss tower. Its axial length matches the layout requirements of the corresponding monitoring points. The width of the plate is adapted to the arc contour of the inner wall of the pipe. It can form a tight fit with the inner wall of the prestressed pipe (6) of the truss tower, ensuring that the fiber optic grating temperature sensor (9) fixed on the thin steel plate (10) can maintain a stable surface contact with the inner wall of the pipe without any problems of suspension or excessive gap. This avoids the deviation of temperature measurement data caused by poor contact from the root, and ensures that the collected temperature data can truly reflect the actual temperature state of the inner wall of the pipe.

[0043] After the sensor pre-fixing work is completed, the thin steel plate (10) equipped with the fiber optic temperature sensor (9) is smoothly inserted into the interior of the prestressed pipe (6) of the truss tower along the axial direction. The circumferential angle and axial position of the thin steel plate (10) are adjusted simultaneously so that the fiber optic temperature sensor (9) on the thin steel plate (10) and the first fiber optic temperature sensor (9) at the corresponding monitoring point on the steel strand (7) form a precise positional correspondence, ensuring that the two sets of sensors are in the corresponding position of the same monitoring section, and completely eliminating the temperature data comparison deviation caused by the misalignment of the monitoring position. After the position calibration is completed, the two ends of the thin steel plate (10) are welded and fixed to the inner wall of the prestressed pipe (6) of the truss tower. By welding and fixing, the thin steel plate (10) and the prestressed pipe (6) of the truss tower form an integrated rigid connection structure, which completely avoids the problem of axial slippage and circumferential deflection of the thin steel plate (10) in the pipe. This ensures that the sensor always maintains the preset deployment position during the concrete pouring, steel strand tensioning and long-term service of the structure, and continuously and stably collects the temperature data of the inner wall of the pipe.

[0044] This pre-fixing and welding installation method effectively solves the construction problem of the narrow internal space of the prestressed duct (6) of the truss tower, which makes it impossible to accurately install and fix sensors directly on the inner wall of the duct. The pre-fixing operation can complete the accurate installation, fixation and early performance debugging of the sensors outside the duct, which greatly reduces the construction difficulty in the narrow space inside the duct and significantly improves the construction efficiency and position accuracy of the sensor installation. At the same time, the signal switching and performance testing of the sensors can be completed before installation, avoiding the problem of being unable to repair the sensor after installation. The welding fixing method at both ends has extremely strong structural stability and can resist the impact of grout during concrete pouring, the vibration interference caused by vibration operation, and the influence of alternating loads during long-term service of the structure. There will be no situation of sensor falling off or shifting, ensuring the stable operation of the monitoring system throughout its entire life cycle. At the same time, the welding fixing of the thin steel plate (10) to the inner wall of the duct is only carried out at both ends of the thin steel plate (10) in the axial direction. It will not damage the main structural strength of the prestressed duct (6) of the truss tower, and will not have an adverse effect on the overall stress performance of the duct. It takes into account both the stability of the sensor installation and the safety of the duct structure.

[0045] This solution achieves precise and stable installation of the second fiber optic temperature sensor (9) on the inner wall of the prestressed pipe (6) of the truss tower by pre-fixing with clamps (11), mounting with thin steel plates (10), and welding and fixing at both ends. This not only greatly reduces the difficulty of sensor installation in the narrow pipe space and improves construction efficiency and installation accuracy, but also ensures the structural stability and data acquisition reliability of the sensor throughout the entire construction process and long-term service, providing accurate and stable pipe-side temperature reference data for concrete density monitoring.

[0046] Furthermore, the data processing device (1) calculates the prestress level of the steel strand (7) during the construction period by performing the following steps: The measured wavelength change of the fiber optic strain sensor (14) at the end of the tensioning process is obtained; Acquire the wavelength change of the first fiber optic grating temperature sensor (9) at the same monitoring point at the same time due to temperature; By subtracting the wavelength change caused by temperature from the measured wavelength change, the wavelength change caused solely by strain is obtained. The measured stress value of the steel strand (7) was calculated based on the wavelength change caused solely by strain. The measured stress value is weighted and averaged with the theoretical stress value calculated based on the theoretical friction loss formula to obtain the prestress level at the monitoring point when tensioning is completed.

[0047] In this embodiment, the data processing device (1) performs a precise calculation of the prestress level of the steel strand (7) after tensioning during the construction period by step-by-step calculation. The calculation process strictly follows the fiber optic grating sensing principle and the requirements of the current concrete structure design specifications. The specific calculation process is as follows.

[0048] The data processing device (1) first acquires the measured wavelength change of the fiber optic strain sensor (14) after tensioning is completed. The initial wavelength of the fiber optic strain sensor (14) at the monitoring point corresponding to the steel strand (7) is recorded as... After tensioning is completed, the sensor collects the measured wavelength change as follows: The measured wavelength change is the result of the combined effect of the structural strain generated by the tension of the steel strand (7) and the change in ambient temperature. It is the basic measured data source for prestress calculation.

[0049] The data processing device (1) synchronously acquires the wavelength change caused by temperature at the same time and the same monitoring point of the first fiber optic grating temperature sensor (9). The initial wavelength of the first fiber optic grating temperature sensor (9) circumferentially arranged on the steel strand (7) at this monitoring point is recorded as... The change in wavelength caused by temperature after tensioning is This value is obtained by processing the measured data of four circumferentially evenly distributed first fiber optic temperature sensors (9) on the same monitoring section. It can accurately reflect the real temperature change of the steel strand (7) at the monitoring point and eliminate the monitoring deviation caused by uneven circumferential temperature distribution.

[0050] Subsequently, the data processing device (1) obtains the wavelength change caused only by strain by subtracting the wavelength change caused by temperature from the measured wavelength change, thus completing the temperature compensation of the strain monitoring data. The specific calculation formula is as follows:

[0051] In the formula The wavelength change caused solely by strain. This represents the measured wavelength change acquired by the sensor after tensioning is complete. The wavelength change caused by temperature after tensioning is obtained. This step can completely eliminate the interference of ambient temperature change on the monitoring results of fiber optic strain sensor (14) and obtain the wavelength shift caused purely by the tensioning strain of steel strand (7), providing accurate basic data for subsequent stress calculation.

[0052] Next, the data processing device (1) calculates the measured stress value of the steel strand (7) based solely on the wavelength change caused by strain. The specific calculation formula is as follows:

[0053] In the formula, Let E be the measured stress value of the steel strand (7) at the monitoring point, and let E be the elastic modulus of the steel strand (7). The wavelength change caused solely by strain. The coefficient is the strain constant coefficient of the steel strand. This coefficient is the factory calibration coefficient of the fiber optic strain sensor (14). Through this formula, the strain-related wavelength change can be directly converted into the actual stress value of the steel strand (7), which can intuitively reflect the tension stress state of the steel strand at the monitoring point.

[0054] Finally, the data processing device (1) performs a weighted average of the measured stress value and the theoretical stress value calculated based on the theoretical friction loss formula to obtain the prestress level at the monitoring point when tensioning is completed. The calculation of theoretical friction loss follows the relevant provisions of the "Code for Design of Concrete Structures" GB50010, and the specific calculation formula is as follows:

[0055] In the formula The tension control stress is the value after deducting the friction loss at the anchor joint, k is the friction coefficient considering the local deviation per meter of duct length, and l is the arc length of the steel strand from the tensioning end to the monitoring point. The coefficient of friction between the prestressed steel strand and the duct wall. This is the sum of the angles between the tangents of each part of the curved duct from the tensioning end to the monitoring point. After calculating the theoretical stress value at the monitoring point using this formula, a weighted average is taken with the measured stress value to finally obtain the prestress level at that monitoring point after tensioning. The specific calculation formula is as follows:

[0056] In the formula, i represents the i-th monitoring point. Let be the prestress level after tensioning at the i-th monitoring point, k be the friction coefficient considering local deviations per meter of duct length, and l be the arc length of the steel strand from the tensioning end to the monitoring point. The coefficient of friction between the prestressed steel strand and the duct wall. It is the sum of the angles between the tangents of each part of the curved duct from the tensioning end to the monitoring point of the prestressed steel strand. Let E be the strain constant coefficient of the steel strand, and E be the elastic modulus of the steel strand (7). Let represent the wavelength change at the i-th monitoring point caused solely by strain. This calculation method combines the theoretical friction loss law specified in the standard with the actual measured data from on-site tensioning. It can effectively avoid the problems of neglecting on-site construction deviations in single theoretical calculations and the random errors in single measured data, thus obtaining prestress level calculation results that are more in line with the actual engineering situation.

[0057] This calculation method eliminates the interference of ambient temperature changes on monitoring results through a temperature compensation step. It combines theoretical calculations from current standards with on-site measured data to complete the prestress level calculation, achieving accurate quantification of the prestress level of steel strand tensioning during the construction period. This provides reliable data support for the quality control of prestressing tensioning construction, can promptly identify problems of insufficient prestressing tensioning, guide on-site supplementary tensioning operations, and ensure the quality of prestressing application and structural safety of prestressed steel tube concrete truss towers.

[0058] Furthermore, the data processing device (1) determines the grout density during the construction period by performing the following steps: After grouting is completed, the surface temperature of the steel strand and the inner wall temperature of the pipe are obtained by the first fiber grating temperature sensor (9) and the second fiber grating temperature sensor (9) at the same monitoring point. Calculate the actual temperature difference between the surface temperature of the steel strand and the inner wall temperature of the pipe; Based on the average surface temperature of the steel strand and the inner wall temperature of the pipe, and a preset temperature difference coefficient, the temperature difference threshold at the monitoring point is calculated. The actual temperature difference is compared with the temperature difference threshold. If the actual temperature difference is less than the temperature difference threshold, the grouting at the monitoring point is determined to be dense; otherwise, it is determined to be indense.

[0059] In this embodiment, the data processing device (1) performs a standardized calculation and judgment process for the concrete density state of the prestressed duct (6) of the truss tower after grouting during the construction period. This process is based on the conduction characteristics of concrete hydration heat and the fiber optic grating temperature sensing principle. It relies on the synchronous measured data of two sets of fiber optic grating temperature sensors (9) deployed at the same monitoring point to ensure that the judgment result accurately matches the actual grouting and filling state of the concrete in the duct.

[0060] The data processing equipment (1) first acquires the surface temperature of the steel strand (7) measured by the first fiber optic temperature sensor (9) installed on the surface of the steel strand (7) at the same monitoring point after grouting is completed, and the inner wall temperature of the pipe measured by the second fiber optic temperature sensor (9) installed on the inner wall of the prestressed pipe (6) of the truss tower. The surface temperature of the steel strand is obtained by processing the measured data of the four first fiber optic temperature sensors (9) evenly installed on a quarter circumference of the monitoring point. The wavelength change after grouting is collected by the sensors first. The temperature-wavelength change ratio of the sensor on the steel strand side, obtained through calibration before installation. This is converted into the corresponding temperature value, and the specific calculation formula is as follows:

[0061] In the formula, Let be the surface temperature of the steel strand at the j-th monitoring point. This refers to the change in wavelength caused by temperature after tensioning is completed. This represents the ratio of temperature to wavelength change of the sensor on the steel strand side.

[0062] The temperature of the inner wall of the pipeline is obtained by converting the measured data from the second fiber optic temperature sensor (9) deployed at the same monitoring point, and converting the wavelength change collected by the sensor after grouting is completed. The ratio of temperature to wavelength change of the sensor on the inner wall of the pipe, obtained through calibration before installation. This is converted into the corresponding temperature value, and the specific calculation formula is as follows:

[0063] In the formula, Let be the temperature of the inner wall of the pipe at the j-th monitoring point. This represents the change in wavelength after grouting is completed. This is the ratio of temperature to wavelength change of the sensor on the inner wall of the pipe.

[0064] Two sets of temperature data are collected and converted simultaneously to ensure the temporal consistency and spatial correspondence of the data, eliminating judgment bias caused by data acquisition time difference and location misalignment.

[0065] After acquiring and converting the temperature data, the data processing equipment (1) calculates the actual temperature difference between the surface temperature of the steel strand and the inner wall temperature of the pipe at the monitoring point. The actual temperature difference is taken as the absolute value of the two temperature differences to eliminate the influence of the temperature order on the calculation results. The specific calculation formula is as follows:

[0066] In the formula, The actual temperature difference at the j-th monitoring point is a value that can directly reflect the temperature conduction difference between the inner wall of the steel strand (7) and the prestressed pipe (6) of the truss tower within the same monitoring section of the pipe. The temperature conduction difference is directly determined by the density of the concrete poured in the middle. Let be the surface temperature of the steel strand at the j-th monitoring point. Let be the temperature of the inner wall of the pipe at the j-th monitoring point.

[0067] Subsequently, the data processing device (1) calculates the temperature difference threshold at the monitoring point based on the average surface temperature of the steel strand and the inner wall temperature of the pipe at that monitoring point, combined with a preset temperature difference coefficient. Temperature difference coefficient Based on the type of grouting material used in the project, the diameter of the prestressed duct (6) of the truss tower, and the ambient temperature at the site during grouting construction, the calculation is pre-set to fully match the actual working conditions of the current project. At the same time, since the area near the inner wall of the prestressed duct (6) of the truss tower is most prone to defects such as non-density and voids during grouting construction, the threshold calculation is based on the measured temperature of the inner wall of the duct as the core benchmark, combined with the temperature data of the steel strand side, to ensure that the judgment result can accurately capture the grouting defects at the inner wall of the duct. The specific calculation formula for the temperature difference threshold is as follows:

[0068] In the formula, The temperature difference threshold at the j-th monitoring point is dynamically calculated based on the actual operating conditions of different monitoring points, rather than using a fixed value. This effectively avoids judgment errors caused by differences in operating conditions at different monitoring locations and ensures the accuracy of density determination. The temperature difference coefficient, Let be the surface temperature of the steel strand at the j-th monitoring point. Let be the temperature of the inner wall of the pipe at the j-th monitoring point.

[0069] Finally, the data processing device (1) compares the calculated actual temperature difference with the temperature difference threshold corresponding to the monitoring point to complete the final determination of the grout density. If the actual temperature difference at the monitoring point is less than the temperature difference threshold, it indicates that the concrete filling between the steel strand (7) and the inner wall of the pipe is full and the heat conduction is uniform and without abnormality. It is determined that the grout at the monitoring point is dense. If the actual temperature difference is greater than or equal to the temperature difference threshold, it indicates that there is a defect of void or non-dense concrete filling at the monitoring point, which leads to abnormal deviation in heat conduction. It is determined that the grout at the monitoring point is not dense. The specific axial and circumferential positions of the non-dense monitoring point are output simultaneously to provide accurate positioning guidance for on-site construction treatment. It can guide the construction personnel to carry out targeted vibration operations at the defect position through an external vibrator to make the grout in the pipe dense.

[0070] This judgment method relies on the synchronous measured data of two sets of fiber optic temperature sensors (9) deployed at the same monitoring point. It achieves accurate and full-coverage judgment of grout density through quantitative temperature difference comparison. It solves the problems of traditional manual inspection being unable to enter the closed pipeline, large dispersion of inspection results, and inability to achieve blind-spot-free inspection of the entire pipeline. It can identify concrete non-compact defects in a timely manner during the grouting construction stage of the construction period, guide precise rectification on site, effectively ensure the grouting construction quality of the prestressed pipeline (6) of the truss tower, and provide reliable support for the structural safety of the steel pipe-concrete-steel strand collaborative stress system.

[0071] Furthermore, the data processing device (1) monitors cracking of the grouting material during operation by performing the following steps: Acquire the temperature data of the second fiber optic temperature sensor (9) at the same monitoring point during the continuous monitoring time interval during the operation period, and calculate the temperature change rate; The stress change rate is calculated from the monitoring data of the fiber optic strain sensor (14) at the same monitoring point within the same time period. The temperature change rate is compared with a preset temperature change threshold, and the stress change rate is compared with a preset strain change threshold; If the temperature change rate is greater than the temperature change threshold and the stress change rate is greater than the strain change threshold, then it is determined that the grouting material at the monitoring point has cracked.

[0072] In this embodiment, the data processing device (1) establishes a real-time monitoring and judgment mechanism that links temperature and stress as dual indicators to address the potential cracking of the grouting material inside the prestressed pipe (6) of the prestressed steel pipe concrete truss tower during its operation. This mechanism relies on the monitoring data collected continuously and synchronously during the operation period, combined with the linkage characteristics of the temperature field change caused by the cracking of the grouting material and the stress redistribution of the steel strand (7), to achieve accurate identification and timely warning of cracking defects in the grouting material, and avoid the problem of single indicator monitoring being easily affected by environmental interference and misjudgment.

[0073] The data processing equipment (1) first acquires the real-time temperature data of the second fiber optic temperature sensor (9) installed on the inner wall of the prestressed duct (6) of the truss tower at the same monitoring point under the continuous monitoring time interval during the operation period, and calculates the temperature mutation rate of the monitoring point. The monitoring time interval Δt during the operation period can be preset according to the engineering operation and maintenance requirements, and the conventional value is 1h to ensure the real-time monitoring and data continuity; since the cracking of the grouting material usually starts from the inner wall of the prestressed duct (6) of the truss tower, the monitoring data of the second fiber optic temperature sensor (9) installed on the inner wall of the duct is used first, so that the abnormal temperature field change caused by the cracking can be captured in the first time. The specific calculation formula of the temperature mutation rate is:

[0074] In the formula, Let be the temperature abrupt change rate at the j-th monitoring point. The measured temperature of the pipe inner wall at the j-th monitoring point at the current monitoring time. This refers to the measured temperature of the pipe's inner wall at the same monitoring point at the previous monitoring time. This is a preset monitoring time interval. This calculation method can quantify the temperature change of the pipe's inner wall per unit time, accurately identifying temperature surges caused by cracks in the grouting material.

[0075] Simultaneously, the data processing device (1) acquires the stress change rate calculated from the data monitored by the fiber optic strain sensor (14) at the same monitoring point within the same monitoring time period. The fiber optic strain sensor (14) is integrated inside the steel strand (7) and can collect the strain data of the steel strand (7) in real time. After temperature compensation correction, the real-time stress value of the steel strand (7) at the corresponding monitoring time is calculated. When the grout cracks, the coordinated stress system of steel pipe-concrete-steel strand is destroyed, which will cause stress redistribution in the steel strand (7) and cause a sudden change in stress. This change can be accurately quantified by the stress change rate. The specific calculation formula for the stress change rate is:

[0076] In the formula, Let be the rate of change of stress at the i-th monitoring point. The measured stress value of the steel strand (7) at the i-th monitoring point at the current monitoring time. The value of the measured stress of the steel strand (7) at the same monitoring point at the previous monitoring time is t, where t is the time stamp of the monitoring time. This calculation method can quantitatively reflect the relative change in stress of the steel strand (7) and accurately capture the abnormal stress fluctuations caused by cracking of the grouting material.

[0077] After calculating the temperature mutation rate and stress change rate, the data processing device (1) compares the calculated temperature mutation rate with the preset temperature mutation threshold, and simultaneously compares the stress change rate with the preset strain mutation threshold. Both the temperature mutation threshold and the strain mutation threshold are calibrated and preset before sensor installation. The temperature mutation threshold... The standard value is 5℃ / h, strain mutation threshold. The standard value is 5%. Both thresholds can be adjusted according to the actual engineering parameters of the truss tower, the performance of the grouting material, and the on-site environmental conditions to ensure that the judgment criteria are consistent with the actual working conditions of the project.

[0078] The data processing equipment (1) completes the final judgment of grout cracking based on the comparison results of the two indicators. Only when the calculated temperature change rate is greater than the preset temperature change threshold and the stress change rate is greater than the preset strain change threshold at the same monitoring point and within the same monitoring period, is it determined that the grout at the monitoring point has cracked. This dual-indicator linkage judgment logic can effectively eliminate the abnormality of a single indicator caused by external factors such as sudden changes in ambient temperature and load fluctuations during the operation of wind turbines, greatly reduce the monitoring misjudgment rate, and ensure the accuracy of the cracking judgment result. When the grout is determined to have cracked, the data processing equipment (1) simultaneously outputs the specific location of the crack monitoring point, providing accurate guidance for the maintenance personnel's inspection work and taking timely measures to avoid further expansion of structural damage.

[0079] This monitoring method uses a dual-indicator linkage of the temperature change rate of the inner wall of the pipeline and the stress change rate of the steel strand to achieve real-time and accurate monitoring of grouting material cracking defects during the operation of the truss tower. It solves the problem that traditional monitoring methods cannot continuously and without blind spots monitor the long-term service status of grouting material in closed pipelines. It can identify and warn of cracking defects in a timely manner in the early stage, providing reliable data support for the operation and maintenance of the truss tower, and effectively ensuring the structural safety and stability of the prestressed steel tube concrete truss tower during long-term service.

[0080] Figure 5 The flowchart of a method for monitoring prestressed concrete density based on fiber Bragg gratings provided in this application embodiment includes the following steps: S1, a fiber optic strain sensor (14) is integrated inside the steel strand (7), and a first fiber optic temperature sensor (9) and a second fiber optic temperature sensor (9) are arranged on the surface of the steel strand (7) and the inner wall of the prestressed pipe (6) of the truss tower respectively.

[0081] In some embodiments, in the early stage of implementing the monitoring method, the sensor deployment step S1 is performed first. This step requires the integrated integration of fiber optic strain sensors (14) inside the steel strand (7) to form an integrated structure with the steel strand (7) that is synchronously stressed and deformed, ensuring that subsequent strain monitoring can truly reflect the stress state of the steel strand (7). At the same time, the first fiber optic temperature sensor (9) is uniformly arranged on the outer surface of the steel strand (7), and the second fiber optic temperature sensor (9) is arranged at the corresponding position on the inner wall of the prestressed duct (6) of the truss tower, ensuring that the positions of the two sets of temperature sensors on the same monitoring section correspond one-to-one, providing a consistent monitoring benchmark for subsequent temperature acquisition, temperature difference comparison, and density judgment. After all sensors are deployed, their positions are kept fixed to avoid displacement, loosening, or falling off during construction and monitoring, ensuring continuous and reliable monitoring data.

[0082] This deployment process establishes a multi-point monitoring layout covering strain and temperature, providing a stable hardware foundation for subsequent prestress calculation, density determination, and crack monitoring, thereby improving the accuracy and stability of the entire monitoring process.

[0083] S2, during the construction period, acquire the wavelength data of the fiber optic strain sensor (14) and each of the fiber optic temperature sensors (9).

[0084] In some embodiments, after the sensor deployment is completed, the construction period monitoring stage is entered, and step S2 is executed. During the entire process of grouting construction of the prestressed duct (6) of the truss tower and tensioning operation of the steel strand (7), the optical signals output by the fiber optic strain sensor (14), the first fiber optic temperature sensor (9), and the second fiber optic temperature sensor (9) are collected in real time by the demodulation device (2), and the optical signals are converted into corresponding wavelength data and transmitted synchronously to the data processing device (1). The data processing device (1) stably collects and stores the initial wavelength and real-time changing wavelength of each sensor during the construction period, and records the wavelength data generated by the fiber optic strain sensor (14) due to the combined effect of strain and temperature, as well as the wavelength data generated by the first fiber optic temperature sensor (9) and the second fiber optic temperature sensor (9) due to temperature changes, to ensure that the data at the same monitoring time and the same monitoring point are acquired synchronously, providing complete and accurate original data support for the subsequent calculation of prestress level and determination of concrete density during the construction period.

[0085] This step, through full-cycle, synchronous wavelength data acquisition, ensures the integrity and timeliness of monitoring data during the construction period, and can truly reflect the actual changes in the stress on the steel strand (7) and the temperature field inside the pipeline during the construction process.

[0086] S3. Based on the wavelength data, the measured stress of the steel strand (7) is calculated by the strain wavelength change after temperature compensation, and the prestress level during the construction period is calculated by combining the theoretical friction loss.

[0087] In some embodiments, when performing step S3, the data processing device (1) first performs temperature compensation on the wavelength change of the fiber optic strain sensor (14) based on the construction period wavelength data obtained in step S2, and eliminates the influence of temperature factors measured by the first fiber optic temperature sensor (9) to obtain the strain wavelength change caused only by the deformation of the steel strand (7). Then, using the strain wavelength change, the elastic modulus of the steel strand (7), and the sensor calibration coefficient, the measured stress of the steel strand (7) is calculated. At the same time, the theoretical friction loss between the steel strand (7) and the inner wall of the prestressed duct (6) of the truss tower is calculated according to the specification requirements to obtain the theoretical stress value of the corresponding monitoring point. The measured stress and the theoretical stress corrected by the theoretical friction loss are weighted and averaged to finally determine the construction period prestress level of the monitoring point after tensioning.

[0088] This step eliminates environmental interference through temperature compensation, and combines measured data with theoretical calculations to make the prestress level results during the construction period more consistent with the actual project, thereby improving the accuracy and reliability of prestress monitoring.

[0089] S4. The density of concrete grouting during the construction period is judged based on the temperature difference between the surface of the steel strand and the inner wall of the pipe.

[0090] In some embodiments, step S4 relies on the wavelength data collected during the construction period to calculate the real-time temperatures of the surface of the steel strand (7) and the inner wall of the prestressed pipe (6) of the truss tower, and completes the determination of the concrete grouting density by comparing the temperature difference. The data processing device (1) first converts the wavelength data of the first fiber grating temperature sensor (9) and the second fiber grating temperature sensor (9) into the surface temperature of the steel strand and the inner wall temperature of the pipe at the corresponding monitoring points, and then calculates the actual temperature difference between the two sets of temperatures. The temperature difference threshold is calculated by combining the average temperature of the monitoring point with the preset temperature difference coefficient. The actual temperature difference is compared with the temperature difference threshold. If the actual temperature difference is less than the threshold, the grouting is determined to be dense. If the actual temperature difference is greater than or equal to the threshold, the grouting is determined to be not dense, thereby realizing the quantitative judgment of the grouting quality during the construction period.

[0091] This step utilizes the temperature conduction characteristics to achieve a non-invasive determination of the density within a closed pipe, which can accurately locate areas of looseness and provide a clear basis for on-site reinforcement construction.

[0092] S5. During operation, the cracking of concrete during operation is judged by combining the mutation rate of the temperature data of the inner wall of the pipeline and the mutation rate of the stress data of the steel strand (7).

[0093] In some embodiments, the operation monitoring phase is entered, and step S5 is executed. The data processing device (1) continuously collects the pipe inner wall temperature data of the second fiber optic temperature sensor (9) and the strain data of the steel strand (7) of the fiber optic strain sensor (14) during the operation period, and calculates the real-time stress data of the steel strand (7) based on the strain data.

[0094] The data processing device (1) first calculates the temperature mutation rate of the temperature data collected by the second fiber optic grating temperature sensor (9) at the same monitoring point under continuous monitoring time intervals. Specifically, it is the difference between the pipe inner wall temperature at the current monitoring time and the pipe inner wall temperature at the previous monitoring time divided by the monitoring time interval. At the same time, it calculates the stress change rate of the steel strand (7) stress data within the same time period, that is, the difference between the measured stress of the steel strand at the current monitoring time and the measured stress of the steel strand at the previous monitoring time divided by the measured stress of the steel strand at the previous monitoring time.

[0095] The calculated temperature mutation rate is compared with the preset temperature mutation threshold, and the stress change rate is compared with the preset strain mutation threshold. Only when the temperature mutation rate is greater than the temperature mutation threshold and the stress change rate is greater than the strain mutation threshold, the data processing device (1) determines that the concrete grout at the monitoring point has cracked, and outputs the specific location of the crack monitoring point simultaneously, providing accurate guidance for the maintenance personnel's inspection work.

[0096] This step uses a dual-indicator linkage of temperature mutation rate and stress change rate to effectively eliminate interference from environmental factors, enabling accurate and timely identification of grout cracking during operation and ensuring the safety and stability of the structure during long-term operation.

[0097] Furthermore, the calculation of the measured stress of the steel strand (7) based on the wavelength data through the strain wavelength change after temperature compensation, and the calculation of the prestress level during the construction period in conjunction with the theoretical friction loss, includes: Subtract the wavelength change measured by the fiber optic strain sensor (14) from the wavelength change caused by temperature measured by the first fiber optic temperature sensor (9) to obtain the wavelength change caused only by strain. The measured stress at the monitoring point is calculated based on the wavelength change caused solely by strain. The measured stress is weighted and averaged with the theoretical friction loss stress to obtain the prestress level at the monitoring point when tensioning is completed.

[0098] In this embodiment, the data processing device (1) first completes the temperature compensation processing of the strain monitoring data, and subtracts the wavelength change measured by the fiber optic strain sensor (14) at the same time and the same monitoring point from the wavelength change caused by temperature measured by the first fiber optic temperature sensor (9), thus obtaining the wavelength change caused only by the tension deformation of the steel strand (7). In specific implementation, the initial wavelength of the fiber optic strain sensor (14) calibrated and recorded before the tensioning operation is retrieved first. And the wavelength change measured by the sensor after tensioning is completed. The measured value is the result of the combined effect of the structural strain of the steel strand (7) and the change in ambient temperature; the measured data of the four first fiber optic temperature sensors (9) evenly distributed in a quarter circumference of the monitoring point are retrieved simultaneously, and the wavelength change caused by temperature at the monitoring point is obtained after averaging. Data correction is achieved through temperature compensation calculation formula:

[0099] In the formula The wavelength change caused solely by strain. This represents the measured wavelength change acquired by the sensor after tensioning is complete. This represents the wavelength change caused by temperature after tensioning. This step completely eliminates the interference of ambient temperature changes on the fiber Bragg grating strain monitoring results, ensuring the accuracy of the basic data for subsequent stress calculations.

[0100] After temperature compensation is completed, the data processing device (1) calculates the measured stress value of the steel strand (7) at the corresponding monitoring point based on the wavelength change caused solely by strain. The calculation process is based on the factory calibration parameters of the fiber optic strain sensor (14) and the material mechanical properties of the steel strand (7). The specific calculation formula is as follows:

[0101] In the formula, Let E be the measured stress value of the steel strand (7) at the monitoring point, and let E be the elastic modulus of the steel strand (7). The wavelength change caused solely by strain. The coefficient is the strain constant coefficient of the steel strand. This coefficient is the factory calibration coefficient of the fiber optic strain sensor (14). Through this formula, the strain-related wavelength change can be directly converted into the actual stress value of the steel strand (7), which can intuitively reflect the tension stress state of the steel strand at the monitoring point.

[0102] Finally, the data processing device (1) performs a weighted average of the calculated measured stress value and the theoretical friction loss stress calculated according to the specification, and finally obtains the prestress level at the monitoring point when tensioning is completed. Among them, the calculation of theoretical friction loss strictly follows the relevant provisions of the "Code for Design of Concrete Structures" GB50010. First, the friction loss between the prestressed steel strand and the duct wall is calculated. The specific calculation formula is as follows:

[0103] In the formula The tension control stress is the value after deducting the friction loss at the anchor joint, k is the friction coefficient considering the local deviation per meter of duct length, and l is the arc length of the steel strand from the tensioning end to the monitoring point. The coefficient of friction between the prestressed steel strand and the duct wall. This is the sum of the angles between the tangents of each part of the curved duct from the tensioning end to the monitoring point of the prestressed steel strand. After calculating the theoretical stress value at the monitoring point based on friction loss, it is then averaged with the measured stress value using equal weights to obtain the final prestressing level during the construction period. The calculation formula is:

[0104] In the formula, i represents the i-th monitoring point. Let be the prestress level after tensioning at the i-th monitoring point, k be the friction coefficient considering local deviations per meter of duct length, and l be the arc length of the steel strand from the tensioning end to the monitoring point. The coefficient of friction between the prestressed steel strand and the duct wall. It is the sum of the angles between the tangents of each part of the curved duct from the tensioning end to the monitoring point of the prestressed steel strand. Let E be the strain constant coefficient of the steel strand, and E be the elastic modulus of the steel strand (7). Let represent the wavelength change at the i-th monitoring point caused solely by strain. This calculation method combines the theoretical friction loss law specified in the standard with the actual measured data from on-site tensioning. It can effectively avoid the problems of neglecting on-site construction deviations in single theoretical calculations and the random errors in single measured data, thus obtaining prestress level calculation results that are more in line with the actual engineering situation.

[0105] This step eliminates the interference of ambient temperature on the monitoring results through temperature compensation. It combines theoretical calculations based on current standards with on-site measured data to complete the quantitative calculation of the prestress level, realizing accurate monitoring of the prestress of the steel strand tensioning during the construction period. This provides reliable data support for the quality control of prestressing tensioning construction, can promptly identify problems of insufficient prestressing tensioning, guide on-site supplementary tensioning operations, and ensure the quality of prestressing application and structural safety of the prestressed steel tube concrete truss tower.

[0106] Furthermore, the method of determining the density of concrete grouting during construction based on the temperature difference between the surface of the steel strand and the inner wall of the pipe includes: Based on the wavelength change measured by the first fiber grating temperature sensor (9) and the second fiber grating temperature sensor (9), the surface temperature of the steel strand and the inner wall temperature of the pipe are calculated respectively. Calculate the actual temperature difference between the surface temperature of the steel strand and the inner wall temperature of the pipe; Based on the average surface temperature of the steel strand and the inner wall temperature of the pipe, and a preset temperature difference coefficient, the temperature difference threshold at the monitoring point is calculated. The actual temperature difference is compared with the temperature difference threshold. If the actual temperature difference is less than the temperature difference threshold, the grouting at the monitoring point is determined to be dense; otherwise, it is determined to be indense.

[0107] In this embodiment, this step is the core implementation link for judging the construction quality of concrete grouting of the prestressed duct (6) of the truss tower during the construction period. The data processing equipment (1) based on the wavelength data of two sets of fiber optic temperature sensors (9) at the same monitoring point and at the same time after the grouting is completed in step S2, completes the quantification and accurate judgment of the grouting density through standardized temperature conversion, temperature difference calculation and threshold comparison process. The specific implementation process is as follows.

[0108] The data processing device (1) first calculates the surface temperature of the steel strand and the inner wall temperature of the pipe at the corresponding monitoring points based on the wavelength changes measured by the first fiber grating temperature sensor (9) and the second fiber grating temperature sensor (9). The surface temperature of the steel strand is calculated from the measured data of the first fiber grating temperature sensor (9) installed on the surface of the steel strand (7). Four sensors are evenly distributed along the circumference of the steel strand (7) in the same monitoring section, with each sensor having a quarter circumference. The wavelength changes caused by temperature after grouting are collected by the four sensors. Averaging is performed to eliminate monitoring bias caused by uneven circumferential temperature distribution in the steel strand. This is then combined with the temperature-wavelength change ratio of the steel strand side, which was calibrated before sensor installation. The temperature conversion is completed using the following formula:

[0109] In the formula, Let be the surface temperature of the steel strand at the j-th monitoring point. This refers to the change in wavelength caused by temperature after tensioning is completed. The ratio of temperature to wavelength change of the sensor on the steel strand side is used. The temperature of the inner wall of the pipe is calculated from the measured data of the second fiber optic temperature sensor (9), which is installed on the inner wall of the prestressed pipe (6) of the truss tower and corresponds to the monitoring point of the first fiber optic temperature sensor (9). The wavelength change caused by temperature after grouting is collected by the sensor is retrieved. Combined with the temperature-wavelength change ratio of the inner wall of the pipe calibrated before installation The temperature conversion is completed using the following formula:

[0110] In the formula, Let be the temperature of the inner wall of the pipe at the j-th monitoring point. This represents the change in wavelength after grouting is completed. This represents the ratio of temperature to wavelength change from the sensor on the inner wall of the pipe. The two sets of temperature data are calculated using synchronously acquired data from the same moment to ensure temporal consistency and spatial correspondence, avoiding judgment errors caused by data time differences and location misalignments.

[0111] After converting the surface temperature of the steel strand to the inner wall temperature of the pipe, the data processing equipment (1) calculates the actual temperature difference between the surface temperature of the steel strand and the inner wall temperature of the pipe at the monitoring point. The actual temperature difference is taken as the absolute value of the two temperature differences to eliminate the influence of the temperature order on the calculation results, and to ensure that the temperature conduction difference between the two sides can be accurately quantified regardless of whether the temperature is higher on the steel strand side or the inner wall side of the pipe. The specific calculation formula is as follows:

[0112] In the formula, The actual temperature difference at the j-th monitoring point is a value that can directly reflect the temperature conduction difference between the inner wall of the steel strand (7) and the prestressed pipe (6) of the truss tower within the same monitoring section of the pipe. The temperature conduction difference is directly determined by the density of the concrete poured in the middle. Let be the surface temperature of the steel strand at the j-th monitoring point. Let be the temperature of the inner wall of the pipe at the j-th monitoring point.

[0113] During the hydration process of concrete grout, heat of hydration is released. When the concrete in the pipe is fully and densely filled, the heat conduction between the steel strand (7) and the inner wall of the pipe is uniform and stable, and the temperature difference between the two is small. When there are defects such as non-dense or hollow, the air medium at the defect will hinder the heat conduction, resulting in a significant abnormal temperature deviation on both sides. This actual temperature difference can directly reflect the filling state of the concrete in the pipe.

[0114] The data processing device (1) calculates the temperature difference threshold at the monitoring point based on the average surface temperature of the steel strand and the inner wall temperature of the pipe at that monitoring point, combined with a preset temperature difference coefficient. Temperature difference coefficient Based on the thermal conductivity of the grouting material used in the project, the pipe diameter of the prestressed duct (6) of the truss tower, and the pre-set ambient temperature during grouting construction, the actual working conditions of the project are fully met. At the same time, since the area near the inner wall of the duct is the most prone to defects such as non-compactness and voids during the grouting construction of the prestressed duct (6) of the truss tower, the threshold calculation combines the dual reference temperatures of the inner wall of the duct and the steel strand side, rather than using a fixed threshold uniform throughout the duct. It can be dynamically adjusted for the actual temperature field of different monitoring points, effectively avoiding the judgment error caused by the difference in working conditions at different monitoring locations. The specific calculation formula for the temperature difference threshold is as follows:

[0115] In the formula, The temperature difference threshold at the j-th monitoring point is dynamically calculated based on the actual operating conditions of different monitoring points, rather than using a fixed value. This effectively avoids judgment errors caused by differences in operating conditions at different monitoring locations and ensures the accuracy of density determination. The temperature difference coefficient, Let be the surface temperature of the steel strand at the j-th monitoring point. Let be the temperature of the inner wall of the pipe at the j-th monitoring point.

[0116] The data processing device (1) compares the calculated actual temperature difference with the temperature difference threshold corresponding to the monitoring point one by one to complete the final determination of the grout density. If the actual temperature difference of the monitoring point is less than the temperature difference threshold, it indicates that the concrete filling between the steel strand (7) and the inner wall of the prestressed pipe (6) of the truss tower is full, the hydration heat conduction is uniform and there is no abnormality, and the grouting at the monitoring point is determined to be dense; if the actual temperature difference of the monitoring point is greater than or equal to the temperature difference threshold, it indicates that there is a defect of void or non-dense concrete filling at the monitoring point, which leads to the obstruction of heat conduction and abnormal temperature difference, and the grouting at the monitoring point is determined to be non-dense. When it is determined that there is a non-dense area, the data processing device (1) simultaneously outputs the specific axial position and circumferential orientation of the non-dense monitoring point, providing accurate positioning guidance for on-site construction and guiding construction personnel to carry out targeted vibration operations on the defect location through external vibrators to ensure that the grouting material in the pipe is filled densely.

[0117] This step uses the synchronous measured data of two sets of fiber optic grating temperature sensors (9) deployed at the same monitoring point to realize the quantification and blind-zone-free determination of the concrete grouting density in the closed pipeline. It solves the pain points of traditional manual detection methods that cannot enter the closed pipeline, have large dispersion of detection results, and cannot achieve full coverage detection of the entire pipeline. It can identify concrete non-compact defects in a timely manner during the grouting construction stage of the construction period, guide precise rectification on site, effectively ensure the grouting construction quality of the prestressed pipeline (6) of the truss tower, and provide reliable data support for the long-term structural safety of the steel pipe-concrete-steel strand collaborative stress system.

[0118] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0119] The above are merely specific embodiments of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A prestressed concrete density monitoring system based on fiber Bragg gratings, characterized in that, The system is applied to prestressed steel-concrete composite truss towers, which include a tower cylinder (5) and a truss tower composed of prestressed ducts (6). Steel strands (7) are embedded within the prestressed ducts (6). The monitoring system includes: A fiber optic strain sensor (14) is integrated inside the steel strand (7) to monitor the strain of the steel strand (7); Multiple first fiber optic temperature sensors (9) are arranged on the circumferential surface of the steel strand (7) along the length direction of the steel strand (7) to monitor the temperature of the surface of the steel strand (7); Multiple second fiber grating temperature sensors (9) are arranged on the inner wall of the prestressed duct (6) of the truss tower, and their positions correspond to those of the first fiber grating temperature sensor (9). The data processing device (1) acquires the wavelength data of the fiber optic strain sensor (14), the first fiber optic temperature sensor (9), and the second fiber optic temperature sensor (9) through the demodulation device (2), and calculates the density state of the concrete in the prestressed duct (6) of the truss tower and the prestress level of the steel strand (7) based on the wavelength data.

2. The prestressing and concrete density monitoring system based on fiber Bragg grating according to claim 1, characterized in that, The fiber optic strain sensor (14) and a steel strand protective layer (15) are combined to form a special steel strand, which is twisted together with other ordinary steel strands to form the steel strand (7), and the special steel strand is located at the center of the steel strand (7).

3. The prestressing and concrete density monitoring system based on fiber Bragg grating according to claim 1, characterized in that, Four of the first fiber optic temperature sensors (9) are evenly arranged in the circumferential direction at the same monitoring point of the steel strand (7), that is, one is arranged in every quarter circumference.

4. The prestressing and concrete density monitoring system based on fiber Bragg grating according to claim 1, characterized in that, The second fiber optic temperature sensor (9) is pre-fixed on a thin steel plate (10) by a clamp (11). The thin steel plate (10) extends into the prestressed pipe (6) of the truss tower and is fixed by welding both ends of the thin steel plate (10) to the inner wall of the prestressed pipe (6) of the truss tower.

5. The prestressing and concrete density monitoring system based on fiber Bragg grating according to claim 1, characterized in that, The data processing device (1) calculates the prestress level of the steel strand (7) during the construction period by performing the following steps: The measured wavelength change of the fiber optic strain sensor (14) at the end of the tensioning process is obtained; Acquire the wavelength change of the first fiber optic grating temperature sensor (9) at the same monitoring point at the same time due to temperature; By subtracting the wavelength change caused by temperature from the measured wavelength change, the wavelength change caused solely by strain is obtained. The measured stress value of the steel strand (7) was calculated based on the wavelength change caused solely by strain. The measured stress value is weighted and averaged with the theoretical stress value calculated based on the theoretical friction loss formula to obtain the prestress level at the monitoring point when tensioning is completed.

6. The prestressing and concrete density monitoring system based on fiber Bragg grating according to claim 1, characterized in that, The data processing device (1) determines the grouting density during the construction period by performing the following steps: After grouting is completed, the surface temperature of the steel strand and the inner wall temperature of the pipe are obtained by the first fiber grating temperature sensor (9) and the second fiber grating temperature sensor (9) at the same monitoring point. Calculate the actual temperature difference between the surface temperature of the steel strand and the inner wall temperature of the pipe; Based on the average surface temperature of the steel strand and the inner wall temperature of the pipe, and a preset temperature difference coefficient, the temperature difference threshold at the monitoring point is calculated. The actual temperature difference is compared with the temperature difference threshold. If the actual temperature difference is less than the temperature difference threshold, the grouting at the monitoring point is determined to be dense; otherwise, it is determined to be indense.

7. The prestressing and concrete density monitoring system based on fiber Bragg grating according to claim 1, characterized in that, The data processing device (1) monitors cracking of grouting material during operation by performing the following steps: Acquire the temperature data of the second fiber optic temperature sensor (9) at the same monitoring point during the continuous monitoring time interval during the operation period, and calculate the temperature change rate; The stress change rate is calculated from the monitoring data of the fiber optic strain sensor (14) at the same monitoring point within the same time period. The temperature change rate is compared with a preset temperature change threshold, and the stress change rate is compared with a preset strain change threshold; If the temperature change rate is greater than the temperature change threshold and the stress change rate is greater than the strain change threshold, then it is determined that the grouting material at the monitoring point has cracked.

8. A method for monitoring prestress and concrete density based on fiber Bragg gratings, characterized in that, The fiber Bragg grating-based prestressing and concrete density monitoring system applied to any one of claims 1-7 comprises: A fiber optic strain sensor (14) is integrated inside the steel strand (7), and a first fiber optic temperature sensor (9) and a second fiber optic temperature sensor (9) are arranged on the surface of the steel strand (7) and the inner wall of the prestressed pipe (6) of the truss tower. During the construction period, wavelength data of the fiber optic strain sensor (14) and each of the fiber optic temperature sensors (9) are acquired; Based on the wavelength data, the measured stress of the steel strand (7) is calculated by the strain wavelength change after temperature compensation, and the prestress level during the construction period is calculated in combination with the theoretical friction loss. The density of concrete grouting during the construction period is determined by the temperature difference between the surface of the steel strand and the inner wall of the pipe. During operation, the cracking of concrete during operation is judged by combining the mutation rate of the temperature data of the inner wall of the pipeline and the mutation rate of the stress data of the steel strand (7).

9. The method according to claim 8, characterized in that, The calculation of the measured stress of the steel strand (7) based on the wavelength data and the strain wavelength change after temperature compensation, and the calculation of the prestress level during the construction period in conjunction with theoretical friction loss, includes: Subtract the wavelength change measured by the fiber optic strain sensor (14) from the wavelength change caused by temperature measured by the first fiber optic temperature sensor (9) to obtain the wavelength change caused only by strain. The measured stress at the monitoring point is calculated based on the wavelength change caused solely by strain. The measured stress is weighted and averaged with the theoretical friction loss stress to obtain the prestress level at the monitoring point when tensioning is completed.

10. The method according to claim 8, characterized in that, The method of determining the concrete grouting density during construction based on the temperature difference between the surface of the steel strand and the inner wall of the pipe includes: Based on the wavelength change measured by the first fiber grating temperature sensor (9) and the second fiber grating temperature sensor (9), the surface temperature of the steel strand and the inner wall temperature of the pipe are calculated respectively. Calculate the actual temperature difference between the surface temperature of the steel strand and the inner wall temperature of the pipe; Based on the average surface temperature of the steel strand and the inner wall temperature of the pipe, and a preset temperature difference coefficient, the temperature difference threshold at the monitoring point is calculated. The actual temperature difference is compared with the temperature difference threshold. If the actual temperature difference is less than the temperature difference threshold, the grouting at the monitoring point is determined to be dense; otherwise, it is determined to be indense.

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