Bridge prestressed tendon system with intelligent monitoring and early warning functions and method

Abstract

The invention relates to the technical field of bridge engineering structure health monitoring, and discloses a bridge prestressed tendon system and method with intelligent monitoring and early warning functions, and the system comprises a prestress bearing subsystem, an intelligent sensing subsystem and a data acquisition and transmission subsystem. Wherein an intelligent ring of the intelligent sensing subsystem is coaxially clamped between a steel strand anchorage device and an anchoring steel plate and is connected to a stress path in series, and a sensor packaged in the intelligent sensing subsystem is used for outputting a physical signal reflecting the axial tension of a prestressed tendon along with the change of the intelligent ring; and the data acquisition and transmission subsystem receives the physical signal through the field signal transceiver station, calculates the prestress loss amount in combination with the environment temperature data, compares the prestress loss amount with a preset threshold value, and generates a graded early warning signal. Through the in-situ serial monitoring structure, direct quantitative sensing and real-time early warning of the stress state of the prestressed tendons are achieved, temperature interference is effectively eliminated, and the accuracy and timeliness of bridge structure safety monitoring are improved.

Description

Technical Field

[0001] This invention relates to the field of bridge engineering structural health monitoring technology, specifically to a bridge prestressed tendon system and method with intelligent monitoring and early warning functions. Background Technology

[0002] Currently, prestressed concrete structural systems are widely used in long-span bridge projects. The effective tension of the prestressing tendons directly determines the load-bearing capacity and durability of the bridge structure. After tensioning and anchoring are completed, the prestressing tendons are usually encapsulated in grouting material or concrete matrix inside the beam body, and their mechanical stress state is in a hidden and closed physical environment for a long time.

[0003] For monitoring applications of such prestressed systems, existing engineering practices mostly employ indirect estimation or periodic non-destructive testing methods. Common implementation methods include placing resistance strain gauges or fiber optic sensors on the surface of concrete members to assess the overall structural response by collecting deformation data of the concrete surface; or using magnetic flux detection equipment to scan specific areas of the beam to identify the cross-sectional losses of internal metal components; some solutions also incorporate acoustic emission devices to capture transient stress wave signals released at the moment of wire breakage or slippage.

[0004] However, existing technologies have limitations in practical applications. Surface-adhesive monitoring data is easily affected by concrete creep, shrinkage, and crack propagation, making it difficult to accurately invert the true axial tensile force of the internal prestressing tendons through external deformation. Detection methods based on magnetic flux or acoustic emission typically cannot achieve continuous tracking throughout the entire period, and cannot effectively capture the long-term slow decay trend of stress or sudden fatigue damage. In addition, conventional monitoring equipment lacks a temperature compensation mechanism for the microenvironment of the anchorage zone in outdoor environments. The thermal expansion and contraction effect caused by environmental temperature differences often couples with mechanical stress deformation, causing monitoring data drift and making it difficult for the system to establish a stable baseline state and achieve accurate quantitative classification and early warning.

[0005] Therefore, the present invention provides a bridge prestressed tendon system and method with intelligent monitoring and early warning functions to overcome the shortcomings of the prior art. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a bridge prestressed tendon system and method with intelligent monitoring and early warning functions. This solves the problem that existing bridge prestressed tendons are often hidden, making it impossible to directly, accurately, and in real-time quantify and proactively classify and warn of their true axial tensile force.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] In a first aspect, the present invention provides a bridge prestressing tendon system with intelligent monitoring and early warning functions, employing the following technical solution:

[0009] A bridge prestressed tendon system with intelligent monitoring and early warning functions includes a prestressed load-bearing subsystem, an intelligent sensing subsystem, and a data acquisition and transmission subsystem.

[0010] The prestressed load-bearing subsystem is used to form the monitored stress structure and generate stress physical quantities, including prestressed tendons inserted inside the beam end, the ends of which pass through anchoring steel plates set on the end face of the beam end and are mechanically locked by steel strand anchors.

[0011] The intelligent sensing subsystem is used to convert the physical quantity of force, including an intelligent ring coaxially clamped between the steel strand anchor and the anchoring steel plate and connected in series on the force path. The intelligent ring is encapsulated with a sensor, which is used to output a physical signal reflecting the physical quantity of force as the intelligent ring deforms.

[0012] The data acquisition and transmission subsystem is used to process the physical signals and issue early warnings. It includes a field signal transceiver station set outside the beam end. The field signal transceiver station is connected to the sensor through a signal transmission line. The field signal transceiver station calculates the prestress loss of the prestressed tendon based on the received physical signals and compares it with a preset threshold to generate a graded early warning signal.

[0013] By adopting the above technical solution, the use of a smart ring directly connected in series on the force path of the anchorage zone enables the sensor to form a physical coupling with the force-bearing structure, which can directly capture the real tension changes of the prestressing tendons. At the same time, the subsystem architecture design realizes the functional decoupling and coordination of the force-bearing structure, sensing unit and data processing unit, which not only ensures the mechanical integrity of the structure, but also realizes real-time, in-situ monitoring and automatic early warning of the prestressing state of the bridge, solving the problems of lagging and difficult quantification of traditional detection methods.

[0014] Preferably, the intelligent sensing subsystem further includes a ring steel pad disposed between the intelligent ring and the steel strand anchor, the ring steel pad being used to transmit the pressure of the steel strand anchor to the intelligent ring; the sensor encapsulated within the intelligent ring is a fiber optic grating sensor, a piezoelectric sensor, a resistance strain gauge, or a magnetic flux sensor.

[0015] By adopting the above technical solutions, the ring steel pad improves the stress distribution on the contact surface and prevents stress concentration from damaging the sensor; the elastic metal material ensures that the measurement has good linearity and repeatability, and various sensor types are suitable for different monitoring environments.

[0016] Preferably, the prestressed bearing subsystem further includes a corrugated pipe extending along the length of the prestressed tendon and sleeved on the outside of the prestressed tendon, and sealed concrete filling the gap on the back of the anchoring steel plate; the data acquisition and transmission subsystem further includes a protective cover covering the steel strand anchor, the ring steel pad, the smart ring and the end of the prestressed tendon, the protective cover being fixed to the surface of the anchoring steel plate or the beam end to form a closed cavity, and the signal transmission line extending to the outside through the protective cover.

[0017] By adopting the above technical solutions, a multi-layered physical protection system was constructed, which effectively isolated the anchoring system and sensing elements from external corrosive media, extended the service life of the monitoring system, and ensured the stability of long-term monitoring data.

[0018] Preferably, the field signal transceiver includes a collection and transmission box fixed to the bridge structure by a support frame. The collection and transmission box is connected to a solar panel for powering the system and an antenna for wireless communication. The collection and transmission box integrates a controller, and the signal transmission line is connected to the collection and transmission box to transmit the sensor signal.

[0019] By adopting the above technical solutions, the system achieves energy self-sufficiency and wireless data transmission, eliminating the need to lay complex long-distance cables on bridges, reducing installation and maintenance difficulties, and improving the system's adaptability to the field.

[0020] Secondly, this invention provides a method for bridge prestressing tendons with intelligent monitoring and early warning functions, employing the following technical solution:

[0021] A method for bridge prestressing tendons with intelligent monitoring and early warning functions includes the following steps:

[0022] After completing the system hardware installation and after the prestressed tensioning is stabilized, initial calibration is performed to establish a reference state including the initial reference value;

[0023] In operating mode, the controller controls the sensors to collect physical signals reflecting the force state and simultaneously acquires ambient temperature data.

[0024] The controller processes the collected physical signals and ambient temperature data to calculate the prestress loss of the prestressed tendons relative to the reference state.

[0025] The controller compares the calculated prestress loss with a preset safety threshold to determine the current health status.

[0026] The controller generates a corresponding status code based on the health status determination result, and performs hierarchical early warning and remote interaction.

[0027] By adopting the above technical solutions, a standardized full-process monitoring method was established, forming a closed-loop management system from installation and calibration to real-time monitoring and early warning feedback. In particular, the introduction of synchronous collection of ambient temperature data provides a data foundation for subsequent elimination of temperature interference and improves the accuracy of monitoring results in reflecting the true stress state of the structure.

[0028] Preferably, the process by which the controller completes the system hardware installation and performs initial calibration after the prestressed tension has stabilized, establishing a reference state including initial reference values, includes: confirming that the smart ring has been pressed onto the force path of the anchor plate and the steel strand anchor, and that the signal transmission line has been connected to the field signal transceiver; reading the original signal output by the sensor as the initial reference signal reading, and reading the current ambient temperature as the initial ambient temperature value; and writing the elastic modulus value of the smart ring body material, the effective cross-sectional area value for bearing pressure, and the sensitivity coefficient of the sensor into the controller's memory.

[0029] By adopting the above technical solution, the zero-point reference and physical parameters of the system were clarified, the influence of installation errors on subsequent calculations was eliminated, and reliable boundary conditions were provided for the accurate calculation of prestress loss.

[0030] Preferably, the process by which the controller controls the sensor to collect physical signals reflecting the stress state and simultaneously acquires ambient temperature data in the working mode includes: the controller sending an excitation signal to the sensor located inside the protective cover through a signal transmission line to acquire the current signal reading characterizing the intelligent toroidal transformer; the controller synchronously driving the environmental monitoring module to collect the current ambient temperature value of the beam end area; and combining and packaging the current signal reading, the current ambient temperature value, and the timestamp into an original data sequence.

[0031] By adopting the above technical solution, strict synchronization between mechanical and temperature signals in the time dimension is ensured, providing a high-quality data source for multi-source data fusion processing and preventing correction deviations caused by asynchronous data.

[0032] Preferably, the process by which the controller processes the collected physical signals and ambient temperature data to calculate the prestress loss of the prestressed tendon relative to the reference state includes: calculating the temperature difference between the current ambient temperature value and the initial ambient temperature value during initialization calibration; using the temperature difference in combination with the thermal expansion correction coefficient to calculate the spurious strain caused by temperature, and subtracting the spurious strain from the total strain measured by the sensor to obtain the true mechanical strain; multiplying the true mechanical strain by the elastic modulus value of the smart ring and the effective cross-sectional area value to obtain the prestress loss of the prestressed tendon.

[0033] By adopting the above technical solution, temperature compensation is achieved using pure numerical calculation logic, effectively eliminating non-stress deformation caused by thermal expansion and contraction, accurately extracting the real mechanical strain caused by substantial changes in structural stress, and thus calculating the accurate amount of prestress loss, solving the technical problem of false alarms caused by large temperature differences in outdoor environments.

[0034] Preferably, the process by which the controller compares the calculated prestress loss with a preset safety threshold to determine the current health status includes: determining whether the data stream from the sensor is continuous; if the data stream is interrupted, it is determined to be an integrity failure; calling blue, yellow, orange, and red warning thresholds set based on the initial prestress tension value, and comparing the value of the prestress loss with each of the above thresholds; if the value of the prestress loss is less than the blue warning threshold, it is determined to be a normal state; if the value of the prestress loss is greater than or equal to the blue warning threshold and less than the yellow warning threshold, a blue warning signal (Level IV) is generated; if the value of the prestress loss is greater than or equal to the yellow warning threshold and less than the orange warning threshold, a yellow warning signal (Level III) is generated; if the value of the prestress loss is greater than or equal to the orange warning threshold and less than the red warning threshold, an orange warning signal (Level II) is generated; if the value of the prestress loss is greater than or equal to the red warning threshold, a red warning signal (Level I) is generated.

[0035] By adopting the above technical solutions, a multi-level condition assessment model was constructed, which can not only identify the faults of the equipment itself, but also distinguish between the slow degradation of structural performance and sudden failure, thus realizing refined hierarchical control of bridge safety status.

[0036] Preferably, the process of the controller generating a corresponding status code based on the health status judgment result and performing graded early warning and remote interaction includes: sending the status code and the prestress loss amount to the remote monitoring terminal through the collection and transmission box and antenna; if the status code corresponds to a blue warning signal (Level IV) or a yellow warning signal (Level III), the remote monitoring terminal initiates a level II response procedure and adjusts the acquisition frequency of the on-site signal transceiver; if the status code corresponds to an orange warning signal (Level II), a red warning signal (Level I), or an integrity failure, the remote monitoring terminal triggers a level I response procedure, triggers an audible and visual alarm, and calls the structural analysis model to verify the bridge safety.

[0037] By adopting the above technical solutions, two-way interaction between the monitoring system and the remote management terminal is realized. It can not only report dangerous situations, but also dynamically adjust the monitoring strategy according to the risk level (such as encrypted data collection), and automatically trigger auxiliary decision analysis in critical moments, which greatly improves the response speed and intelligence level of bridge maintenance management.

[0038] This invention provides a bridge prestressed tendon system and method with intelligent monitoring and early warning functions. It has the following beneficial effects:

[0039] 1. This invention connects the intelligent ring in the intelligent sensing subsystem coaxially in series on the force path between the steel strand anchor and the anchoring steel plate, enabling the sensor to directly sense the axial tensile force of the prestressing tendon through physical deformation. This in-situ embedded structural design achieves direct quantitative monitoring of the hidden stress state inside the beam end, avoiding errors caused by indirect calculations and improving the authenticity and accuracy of the detection data.

[0040] 2. This invention utilizes a controller within the data acquisition and transmission subsystem to execute temperature compensation and tiered early warning logic. By synchronously acquiring ambient temperature data and using a thermal expansion correction coefficient to eliminate spurious strain, combined with a comparison of prestress loss and multi-level safety thresholds, it achieves refined assessment of the structural health status. This not only solves the problem of environmental temperature difference interfering with monitoring results but also enables automated trend analysis and tiered early warning for different levels of safety risks, transforming post-event remediation into pre-event prevention, thereby improving the safety and intelligence level of bridge operation.

[0041] 3. This invention employs a highly integrated structural design. The intelligent ring is embedded as part of the anchoring component and, together with the protective cover, forms a closed cavity to protect the core element. The field signal transceiver is powered by solar panels and uses wireless communication. This design does not affect the original prestressed construction process, avoids complex on-site wiring, reduces construction interference and maintenance costs, and ensures long-term stable operation of the system in harsh outdoor environments. Attached Figure Description

[0042] Figure 1 This is a schematic diagram of the overall structure of a bridge prestressed tendon system with intelligent monitoring and early warning functions according to an embodiment of the present invention;

[0043] Figure 2 This is a schematic diagram of the arrangement of the intelligent monitoring ring on the prestressing tendon according to an embodiment of the present invention;

[0044] Figure 3 This is a flowchart of the intelligent monitoring method for prestressed tendons according to an embodiment of the present invention;

[0045] Figure 4 This is a simulation curve of the prestressed tendon's full life cycle stress monitoring according to an embodiment of the present invention.

[0046] Among them, 1. Beam end; 2. Prestressed tendon; 3. Corrugated pipe; 4. Anchor steel plate; 5. Enclosed concrete; 6. Ring steel pad; 7. Steel strand anchor; 10. Smart ring; 11. Sensor; 12. Signal transmission line; 20. Field signal transceiver; 21. Collection and transmission box; 22. Solar panel; 23. Antenna; 24. Protective cover; 25. Support frame. Detailed Implementation

[0047] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] See attached document Figure 1 This invention provides a bridge prestressed tendon system with intelligent monitoring and early warning functions. The system is structurally divided into a prestressed load-bearing subsystem, an intelligent sensing subsystem, and a data acquisition and transmission subsystem. Physically, the system relies on the beam end 1 of the bridge structure. By embedding sensing elements into the traditional prestressed structure and using an external processing terminal, it achieves digital monitoring of the entire lifecycle of the prestressed structure.

[0049] In the specific layout of the system, beam end 1 constitutes the concrete foundation of the bridge's main body, serving as the area for prestressing application and anchorage. Prestressing tendons 2, as the core load-bearing components, are inserted into beam end 1 along the bridge's axial direction. To ensure effective bonding between the prestressing tendons 2 and the concrete beam and to prevent corrosion, corrugated pipes 3 are fitted over the prestressing tendons 2, extending along their length. The annular gap formed between the inner wall of the corrugated pipe 3 and the outer wall of the prestressing tendon 2 is filled with dense cement mortar. This structural form establishes the physical basis of the monitoring system: the monitored object is encased within multiple layers of media.

[0050] The system has a field signal transceiver 20 installed outside or near the beam end 1. This field signal transceiver 20 is the data collection and relay hub for the entire monitoring system on site. The field signal transceiver 20 is fixedly installed on the bridge cap beam, maintenance passage, or slope location via a support frame 25. The support frame 25 is a metal pole or bracket structure, ensuring that the field signal transceiver 20 can stand stably in the outdoor environment, resist wind loads, and maintain stable communication posture.

[0051] In terms of system connectivity, the sensing units arranged on the prestressing tendons 2 extend to the outside of the beam end 1 via physical lines and are ultimately connected to the field signal transceiver station 20. The field signal transceiver station 20 is responsible for receiving physical quantity signals from inside the prestressing tendons 2 and converting them into digital signals for processing or forwarding. This overall architecture physically connects the prestressing tendons 2, which were originally in a closed black box state, with the external visual monitoring network, allowing managers to obtain internal stress information without damaging the concrete structure of the beam end 1.

[0052] See attached document Figure 2 The intelligent bridge prestressing tendon system provided by this invention constructs a hierarchical force transmission and physical protection structure in the anchorage area of ​​beam end 1. The anchoring steel plate 4, as the main bearing base, is stably set at the end face of beam end 1. It has a through hole in its center for the prestressing tendon 2 to pass through, and the bearing surface of the anchoring steel plate 4 is perpendicular to the axial centerline of the prestressing tendon 2, providing a flat and highly rigid reference plane for the subsequent installation of anchoring components.

[0053] On the outer side of the anchoring steel plate 4, a smart ring 10, a ring steel pad 6, and a steel strand anchor 7 are coaxially installed in sequence. The smart ring 10 is directly fitted onto the outer circumference of the prestressing tendon 2, with one end face tightly against the outer surface of the anchoring steel plate 4. The ring steel pad 6 is positioned between the other end face of the smart ring 10 and the steel strand anchor 7, serving as a rigid force transmission medium. The steel strand anchor 7 tightly engages and locks the tensioning end of the prestressing tendon 2 through an internal clamping mechanism. This arrangement forms a tightly pressed sandwich-like mechanical structure, ensuring the coaxiality and contact density of each component in the direction of force application.

[0054] Based on the above structural layout, this system establishes a clear prestress transfer path. When the prestressing tendon 2 is in tension, the axial tensile force generated by its retraction tendency first acts on the steel strand anchor 7; the steel strand anchor 7 converts this tensile force into compressive force and applies it vertically to the ring steel pad 6; the ring steel pad 6 evenly diffuses the compressive force and transfers it to the intelligent ring 10; finally, the intelligent ring 10 transfers the compressive force to the anchoring steel plate 4 and is borne by the beam end 1. In this process, the intelligent ring 10 is connected in series on the main stress link, and the mechanical pressure it bears has a direct and definite physical mapping relationship with the internal tensile force of the prestressing tendon 2, thereby eliminating measurement errors caused by bypass diversion or indirect calculation.

[0055] To ensure the durability of the monitoring components and core load-bearing parts, a protective cover 24 is installed over the exposed ends of the steel strand anchor 7, the ring steel pad 6, the smart ring 10, and the prestressing tendons 2. The bottom edge of the protective cover 24 is fixed to the surface of the anchoring steel plate 4 or the beam end 1 by a seal or mechanical connector, thereby forming a physically enclosed independent cavity at the beam end 1. This protective cover 24 completely isolates the aforementioned key metal load-bearing components and precision electronic sensing components from the external atmospheric environment, effectively blocking the erosion paths of rainwater, salt spray, and industrial dust. In addition, sealing concrete 5 fills the gaps on the back of the anchoring steel plate 4 or the area around the corrugated pipe 3 port to permanently seal the structural gaps in the anchoring area. Together with the protective cover 24, this forms a double-sealed protection system for the prestressed anchoring end, ensuring the structural integrity of the prestressing tendons 2 throughout their entire life cycle.

[0056] See attached document Figure 2 In this embodiment of the invention, the sensor 11, serving as the sensing core, is encapsulated and integrated within the main structure of the smart ring 10. The smart ring 10 is made of a high-strength metal material with elastic deformation capability, and its interior has a pre-set cavity or groove for accommodating the sensor 11. The sensor 11 is fixed within the cavity by epoxy resin bonding or mechanical locking, forming an integrated strain sensing unit with the smart ring 10. When the smart ring 10 is subjected to axial compressive force from the steel strand anchor 7 and the anchoring steel plate 4, its minute elastic deformation is directly transmitted to the sensor 11, which then generates a corresponding physical signal change. In this embodiment, the sensor 11 is selected from one or a combination of fiber optic grating sensors, piezoelectric sensors, resistance strain gauges, or magnetic flux sensors to adapt to different monitoring accuracy and environmental durability requirements.

[0057] To transmit the analog signals collected by sensor 11 to external processing equipment, one end of signal transmission line 12 is physically connected to sensor 11 located inside smart ring 10. Signal transmission line 12 extends from the side wall or non-load-bearing surface of smart ring 10, and this exit point is equipped with a sealing sleeve or waterproof connector to prevent external moisture from entering the smart ring 10 along cable gaps and corroding sensor 11. When multiple monitoring points are distributed axially along prestressed tendons 2, the signals from each sensor 11 are collected in series or parallel via signal transmission line 12, forming a distributed sensor network.

[0058] After leaving the smart ring 10, the signal transmission line 12 is arranged within the enclosed cavity formed by the protective cover 24. To enable signal interaction with external systems, the protective cover 24 has dedicated cable entry holes on its side walls or top, where waterproof, sealed headers or dedicated through-wall connectors are installed. The signal transmission line 12 extends through the waterproof sealing structure to the outside of the protective cover 24 and is laid along the concrete surface of the beam end 1. During installation, the signal transmission line 12 is run through pre-embedded PVC pipes or metal cable trays to provide mechanical protection against construction damage or rodent bites.

[0059] The signal transmission line 12, extending to the outside of beam end 1, is ultimately connected to the input interface of the field signal transceiver 20. When using fiber Bragg grating sensors, the signal transmission line 12 is an armored optical cable, connected to the optical demodulation module of the field signal transceiver 20 via fusion splicing; when using electrical sensors, the signal transmission line 12 is a multi-core shielded cable, connected to the analog-to-digital conversion module of the field signal transceiver 20. Through the above physical connection path, a complete signal transmission link is constructed from the stress point at the anchorage end of the prestressed tendon 2 to the external data processing terminal, enabling the output of stress state data shielded inside the protective cover 24.

[0060] See attached document Figure 1 The intelligent bridge prestressed tendon system provided by this invention has a field signal transceiver 20 installed at a maintenance-accessible location near the beam end 1 or pier. This field signal transceiver 20 is fixedly installed on the concrete structure surface of the bridge via a support frame 25. The support frame 25 is constructed from corrosion-resistant metal profiles welded or bolted together, providing stable mechanical support for the entire acquisition terminal. The collection and transmission box 21 is installed on the support frame 25 and adopts an industrial-grade waterproof and dustproof enclosure structure. Its box door is equipped with sealing strips and anti-theft locks to house and protect the internal precision electronic components from external environmental corrosion.

[0061] The core circuit board and controller of the monitoring device are integrated inside the collection and transmission box 21. The aforementioned signal transmission line 12 extending to the outside passes through the inlet hole at the bottom of the collection and transmission box 21 and connects to the internal signal conditioning module. When the sensor 11 is a fiber optic grating type, a fiber optic demodulator is configured inside the collection and transmission box 21; when the sensor 11 is an electrical type, a multi-channel data acquisition card is configured inside the box. The controller is electrically connected to the signal conditioning module and consists of a microprocessor, memory, and embedded operating system, responsible for executing timed wake-up, data reading, analog-to-digital conversion, local storage, and preliminary logic operation instructions.

[0062] To address the power supply challenges in outdoor bridge environments, the on-site signal transceiver 20 is equipped with an independent solar-powered system. Solar panels 22 are mounted on the top or side of the support frame 25 using adjustable brackets, ensuring that the receiving surface receives sufficient solar radiation. The output of the solar panels 22 is connected to a charging controller and battery pack located inside the collection and transmission box 21. This power management unit is responsible for converting solar energy into electrical energy for storage and providing a stable DC operating voltage for the controller, sensor 11, and wireless communication module, ensuring continuous system operation even on cloudy days or at night.

[0063] For data communication, antenna 23 is vertically mounted on top of the collection and transmission box 21 or at a high point on the support frame 25, and is connected to the wireless communication module inside the box via an RF cable. The wireless communication module supports 4G, 5G, or NB-IoT narrowband Internet of Things communication protocols. The controller packages the processed prestressed tendon 2 status data or early warning signals and transmits them to the wireless network via antenna 23 through the wireless communication module, ultimately transmitting them to a remote server or monitoring terminal, thus realizing remote wireless uploading of on-site monitoring data.

[0064] Referring to the force monitoring principle in this embodiment of the invention, its core lies in utilizing Hooke's law in elasticity and the structural force transmission mechanism to transform the internal tension of the prestressing tendon 2, which is difficult to measure directly, into the geometric deformation of the intelligent ring 10, which is easy to measure. The intelligent ring 10 is installed at the anchoring end of the prestressing tendon 2 and is physically located in the critical force transmission path. Specifically, after the prestressing tendon 2 has undergone tensioning and is locked by the steel strand anchor 7, the axial tensile force maintained inside the prestressing tendon 2 will be transmitted and output through the end face of the steel strand anchor 7. The intelligent ring 10, as a high-rigidity pressure-bearing component, is tightly clamped between the steel strand anchor 7 and the anchoring steel plate 4, or directly replaces the traditional anchor pad. In this structural layout, the axial tensile force of the prestressing tendon 2 is converted into axial pressure acting on the annular end face of the intelligent ring 10 without loss. Since the main body of the smart ring 10 is made of an alloy material with stable elastic modulus and high yield strength, and its design working range is strictly limited to the elastic deformation range of the material, there is a strict linear correspondence between the magnitude of the axial pressure acting on it and the amount of axial elastic compression deformation generated by the smart ring 10 body.

[0065] The sensor 11, integrated and packaged within the smart ring 10, achieves micron-level tight coupling with the ring substrate, enabling the sensor 11 to synchronously and lag-free detect minute geometric deformations of the smart ring 10. When the smart ring 10 experiences axial compressive strain due to pressure from the steel strand anchor 7, the structure of the sensitive element inside the sensor 11 deforms accordingly, leading to changes in the characteristics of its output physical signal. For example, when a fiber optic grating sensor is used as the sensor 11, axial compression causes the grating pitch to shorten, resulting in a shift of the center wavelength of the reflected light towards shorter wavelengths; if a resistance strain gauge is used, this manifests as a change in resistance value. The monitoring device captures these minute changes in physical signals relative to the initial state through a high-precision demodulation circuit, thereby deducing the real-time strain state of the smart ring 10 at the current moment.

[0066] Based on the geometric dimensions and material physical properties of the smart ring 10, which are pre-calibrated or precisely measured in the laboratory, the controller can convert the strain data collected by the monitoring device into corresponding stress values ​​and total axial pressure. Since the smart ring 10 and the prestressing tendon 2 are connected in series in terms of mechanical force, according to Newton's third law and static equilibrium conditions, the total axial pressure borne by the smart ring 10 is numerically equal to the current effective prestress of the prestressing tendon 2. By continuously monitoring this pressure value over time, the system can monitor the tension of the prestressing tendon 2 and its relaxation over time in real time. To quantify the above physical conversion process, this system calculates and converts the core data based on the constitutive equations of mechanics of materials, following the following fundamental physical formulas:

[0067] ;

[0068] in, This represents the current axial tensile force of prestressing tendon 2; The elastic modulus of the material representing the body of the smart ring 10; The effective cross-sectional area of ​​the smart ring 10 used to withstand pressure; This represents the axial strain value measured by sensor 11 and corrected for necessary temperature compensation. Through this core formula, the system accurately maps changes in microscopic sensing signals to structural stress parameters at the macroscopic level, thereby achieving precise quantitative monitoring of the stress state of prestressed structures in a concealed state.

[0069] To accurately quantify the stress state evolution of prestressing tendons 2 during operation, especially to identify the degree of effective prestress loss or sudden stress impact, the controller does not only focus on the absolute force value at a single moment, but also emphasizes calculating the prestress loss relative to the initial locked state. After the system is installed and undergoes system initialization and calibration, the controller establishes a baseline state. Based on this, by comparing real-time acquired data with baseline data, the prestress loss index reflecting the structural health trend is calculated using the principles of mechanics of materials. This prestress loss not only visually reflects the current change in the tightness of prestressing tendons 2, but also serves as a direct numerical basis for triggering subsequent graded early warning mechanisms.

[0070] The core physical formula used in this invention to calculate the prestress loss of prestressing tendon 2 is as follows:

[0071] ;

[0072] in, This represents the amount of prestress loss of prestressing tendon 2 relative to the initial moment. The sign of this value directly reflects the direction of stress change. A positive value usually means prestress loss, while an abnormally negative value will mean local overload of the structure. The elastic modulus of the material that makes up the smart ring 10 is determined by the properties of the metal material used to manufacture the smart ring 10 and is precisely measured before leaving the factory. The effective cross-sectional area of ​​the smart ring 10 for bearing axial pressure is represented by the geometric design dimensions of the smart ring 10. This represents the current monitoring time by sensor 11. The measured real-time axial strain value of the smart ring 10; This represents the initial reference axial strain value of the smart ring 10 recorded during the system initialization phase. This value is typically obtained after prestressing tensioning is completed and anchoring is stable. Through this calculation formula, the controller can convert the microscopic strain changes output by the sensor 11 into macroscopic mechanical indicators, thereby achieving quantitative monitoring of the entire life cycle of the prestressed structure.

[0073] See attached document Figure 3 This invention provides a prestressed tendon intelligent monitoring method based on the above system, wherein step S1, system installation and initialization calibration, may specifically include:

[0074] During the prestressing tensioning stage of the bridge, construction personnel need to coaxially mount the smart ring 10 onto the end of the prestressing tendon 2, ensuring it is accurately positioned between the steel strand anchor 7 and the anchoring steel plate 4 or the ring steel pad 6, guaranteeing that the force transmission path passes perpendicularly through the annular end face of the smart ring 10. With the completion of the prestressing tensioning operation and the mechanical locking of the steel strand anchor 7, the tension inside the prestressing tendon 2 acts on the smart ring 10, placing it in a load-bearing working state. At this time, the signal transmission line 12 led from the smart ring 10 passes through the protective cover 24 and connects to the collection and transmission box 21 of the field signal transceiver station 20. After the hardware connection is completed, technicians configure the controller via a handheld terminal or remote command, binding the unique hardware identification code of the sensor 11 encapsulated within each smart ring 10 to its specific physical installation location in the bridge structure, thereby establishing a digital spatial mapping database of monitoring points.

[0075] After confirming stable electrical connections and unobstructed signal paths, the controller executes the initialization calibration procedure. The system immediately activates sensor 11 and reads its output raw physical signal value. This signal value represents the initial stress level of the prestressed tendon 2 after tensioning and locking, and its stable state, i.e., the physical starting point of the effective prestress. The controller marks the signal value collected at this specific moment as the initial reference value and stores it in non-volatile memory, serving as the zero-point reference data for calculating prestress loss in all subsequent monitoring cycles. Simultaneously, the system initialization process also includes writing the inherent physical property parameters of the smart ring 10 into the controller's computing unit. These physical property parameters strictly include the elastic modulus of the smart ring 10's material, the effective cross-sectional area for bearing pressure, and the factory sensitivity coefficient of sensor 11. Based on these preset parameters, the controller constructs a low-level data conversion model, completing the algorithm configuration from microscopic sensor signals to macroscopic mechanical physical quantities. At this point, the system enters standby monitoring mode.

[0076] See attached document Figure 3 The specific steps of data acquisition and transmission in step S2 may include:

[0077] Once the system enters the formal operation phase, the controller inside the collection and transmission box 21 of the field signal transceiver station 20 defaults to a low-power sleep mode to adapt to the energy-constrained environment powered by the solar panels 22. The real-time clock module integrated inside the controller keeps time according to a preset sampling period, which is usually set to once every six hours or other fixed time intervals depending on the bridge maintenance requirements. When the predetermined sampling time is reached, or when the controller receives a forced wake-up command from the remote monitoring terminal via the antenna 23, the controller automatically switches to the working mode and outputs excitation signals to all connected sensor channels.

[0078] The controller sends query commands or optical signals to the sensors 11 installed in the smart ring 10 on the prestressed tendon 2 via signal transmission line 12. The sensors 11 sense the current physical state of the prestressed tendon 2 and convert the sensed strain, magnetic flux, or vibration frequency information into electrical or optical wavelength signals, feeding them back to the collection and transmission box 21. To ensure the accuracy of the collected data and eliminate transient noise interference, the controller performs multiple consecutive high-frequency samples on the same sensor 11 within a single wake-up cycle and takes the arithmetic mean as the valid monitoring data at that time point.

[0079] During the synchronous period of collecting stress data from the intelligent ring 10, the auxiliary environmental monitoring module integrated into the field signal transceiver station 20 or near the intelligent ring 10 is simultaneously activated. This module is responsible for collecting the ambient temperature and humidity data of the beam end 1 area at the current moment. Since both the prestressed tendon 2 and the intelligent ring 10 are made of metal, their physical deformation is significantly affected by thermal expansion and contraction. Therefore, synchronously collecting ambient temperature data is crucial for subsequently eliminating the interference of temperature on tensile force calculation. The controller packages and encodes the collected raw stress data, ambient temperature data, ambient humidity data, and the current timestamp, and temporarily stores them in local memory, awaiting entry into the next step of the data processing flow.

[0080] See attached document Figure 3 The specific steps of feature extraction and data preprocessing in step S3 may include:

[0081] The controller first unpacks the received raw data packet, extracting a digital sequence containing the original sensing values ​​from sensor 11, the ambient temperature value, and a timestamp. The controller's internal processor then calls a preset digital filtering algorithm, such as a moving average filter or a Kalman filter, to smooth the raw sensing value sequence, eliminating random noise pulses caused by electromagnetic interference or transient circuit fluctuations. During this process, the controller checks the integrity of the data sequence. If all data is found to be zero or exceeds the physical range of sensor 11, an anomaly flag is generated; otherwise, the filtered, valid data is input to the physical quantity conversion module.

[0082] Subsequently, the controller performs crucial temperature compensation calculations to eliminate the impact of thermal expansion and contraction on measurement accuracy. Due to the metallic properties of the prestressing tendon 2 and the smart ring 10, changes in ambient temperature cause non-stressed volumetric deformation, which is recorded as spurious stress changes by the sensor 11. The controller reads the current ambient temperature value and retrieves the initial ambient temperature value recorded during the system initialization phase from the memory, calculating the temperature difference between the two. Using preset material thermal expansion coefficients and temperature sensitivity coefficients, the controller calculates the spurious strain component caused by temperature changes and subtracts it from the total strain measured by the sensor 11, thereby separating the true mechanical strain caused only by external loads or prestress loss.

[0083] After obtaining the temperature-corrected true mechanical strain, the controller, combining the effective cross-sectional parameters of the smart ring 10 and the material's elastic modulus, calculates the current actual tensile force value of the prestressing tendon 2. To assess the evolution of the prestress state, the controller performs a difference calculation between this current actual tensile force value and the initial reference value recorded in step S1 to obtain the prestress loss. This prestress loss is a core indicator for judging the structural health status. The calculation of the prestress loss follows the physical relationship formula:

[0084] ;

[0085] in, This indicates the prestress loss of prestressing tendon 2, in Newtons. This represents the elastic modulus of the material of the smart ring 10, expressed in megapascals (MPA). This indicates the effective cross-sectional area of ​​the smart ring 10 for bearing loads, in square millimeters; This represents the sensitivity coefficient of sensor 11, which is used to convert the sensed signal into a strain value; This indicates the current reading of the sensor 11 signal after acquisition and filtering; This represents the initial reference signal reading of sensor 11 recorded during system initialization; It represents the comprehensive thermal expansion correction coefficient, used to characterize the temperature response characteristics of materials and sensors; This indicates the ambient temperature value collected at the current moment; This represents the initial ambient temperature recorded during system initialization. The prestress loss calculated using this formula accurately reflects the stress change of prestressing tendon 2 relative to the initial locked state, eliminating environmental interference and providing reliable data support for subsequent failure assessment.

[0086] See attached document Figure 3 The specific steps of the health status intelligent judgment process, S4, may include:

[0087] The controller first executes a logical judgment procedure for the physical integrity of the prestressed tendon 2. The controller reads the preprocessed data sequence status flags from step S3. If the data stream of the sensor 11 corresponding to a specific smart ring 10 exhibits an unnatural, sudden interruption, a signal amplitude drop to zero, or an open circuit state, and this state cannot be automatically recovered within multiple consecutive sampling periods, the controller determines that the prestressed tendon 2 at that monitoring point has suffered a physical fracture or significant structural damage. This judgment logic is based on the physical characteristic that fiber optic grating sensors or electrical sensors will be damaged due to excessive physical stretching or have their circuits severed at the moment of carrier fracture. Once a fracture state is confirmed, the controller immediately generates the highest priority integrity failure status code.

[0088] Assuming the signal from sensor 11 is continuous and valid, the controller enters the stress state quantification and evaluation stage. The controller retrieves preset multi-level safety threshold parameters from its memory. These parameters represent the limits of tension increment (or loss) calculated based on the initial prestressing tension value at a set ratio. These thresholds include a blue warning threshold (Level IV), a yellow warning threshold (Level III), an orange warning threshold (Level II), and a red warning threshold (Level I), with the red warning threshold (Level I) being the most severe. For example, the blue warning threshold is set to 3% of the initial prestressing tension value, the yellow warning threshold to 5%, the orange warning threshold to 10%, and the red warning threshold to 15%. The controller then compares the prestressing loss value calculated in step S3 with each of the aforementioned threshold levels.

[0089] The controller compares the prestress loss value calculated in step S3 with the above threshold values ​​step by step.

[0090] If the prestress loss calculated by the controller is less than the blue warning threshold, the controller determines that prestressing tendon 2 is in normal working condition. If the prestress loss is greater than or equal to the blue warning threshold and less than the yellow warning threshold, a blue warning signal (Level IV) is generated; if the value is greater than or equal to the yellow warning threshold and less than the orange warning threshold, a yellow warning signal (Level III) is generated; if the value is greater than or equal to the orange warning threshold and less than the red warning threshold, an orange warning signal (Level II) is generated, indicating a serious risk of stress relaxation or slippage; if the prestress loss is greater than or equal to the red warning threshold, the controller determines that the effective prestress of prestressing tendon 2 is severely insufficient, facing the risk of structural failure, and generates a red warning signal (Level I).

[0091] In addition, the controller executes a time-series-based trend prediction algorithm. The controller retrieves historical prestress loss data for the smart ring 10 within a set time window and calculates the stress change rate slope using the least squares method. The controller compares this stress change rate slope with a preset slip rate threshold. Even if the current prestress loss value has not yet triggered the first warning threshold, if the stress change rate slope indicates that the stress is continuously decreasing at a rate exceeding the allowable range, the controller also generates a trend anomaly warning signal to identify a slow slippage failure that may occur in the anchor 7. All judgment results and generated status codes are written to the controller's transmission buffer.

[0092] See attached document Figure 3 The specific steps of S5, graded early warning and remote interaction, may include:

[0093] The controller first packages the health status judgment result status code generated in step S4, the prestress loss value calculated in step S3, and the filtered raw sensor data into a data frame conforming to the transmission protocol. This data frame contains a unique device identifier, timestamp, geographic location coordinates, and checksum. The controller drives the collection and transmission box 21 located within the field signal transceiver station 20 via a hardware interface. The collection and transmission box 21 activates its integrated wireless communication module, modulates the data frame into a radio frequency signal, and transmits it through antenna 23 to a mobile communication network or dedicated data transmission link, ultimately transmitting it to a remote monitoring terminal deployed at the management center.

[0094] After receiving the data frame, the remote monitoring terminal decrypts and verifies the data packet, and writes it to the associated historical database. If the parsed status code indicates that the prestressed tendon 2 is in normal working condition, the remote monitoring terminal only updates the record in the background log of the visualization interface and refreshes the current tension value point on the corresponding digital model or two-dimensional trend chart, without triggering an active prompt signal, and maintains the normal monitoring mode.

[0095] If the parsed status code corresponds to a blue warning signal (Level IV), a yellow warning signal (Level III), or a trend anomaly warning signal, the remote monitoring terminal immediately initiates a Level II response procedure. The server marks the corresponding bridge node in yellow on the geographic information system map of the main monitoring interface and displays a floating window containing the specific station number, beam segment location, and stress loss percentage. Simultaneously, the remote monitoring terminal automatically generates an electronic maintenance work order containing comparative analysis of historical data from the past week and sends it to the designated bridge maintenance engineer's terminal via the communication gateway. In this state, the remote monitoring terminal sends a reverse control command to the controller, adjusting the sampling frequency of the monitoring point from the default low-frequency mode to a high-frequency dense sampling mode to capture subsequent stress evolution details.

[0096] If the parsed status code corresponds to an orange warning signal (Level II), a red warning signal (Level I), or an integrity failure status code, the remote monitoring terminal triggers the highest-level Level I response procedure. The audible and visual alarm in the monitoring center is physically activated, emitting a continuous warning sound and flashing red light. The server automatically calls the bridge structure finite element analysis module, inputs the spatial location parameters of the failed prestressed tendon 2, and quickly verifies the remaining bearing capacity and safety factor of the bridge section based on the current load conditions. The system simultaneously pushes an emergency accident report to the emergency command system of the bridge management department and automatically drafts emergency response plans suggesting traffic flow restrictions or bridge closure for management personnel to make decisions, until on-site verification is completed.

[0097] To further verify the effectiveness and accuracy of the bridge prestressed tendon system with intelligent monitoring and early warning functions of the present invention, a specific application embodiment is provided below. This embodiment selects a precast box girder (number XL-2025-03) of a super-large highway bridge under construction as the pilot object, and combines it with the attached... Figure 4 Please provide a detailed explanation.

[0098] See attached document Figure 4 In this embodiment, the smart ring 10 is made of custom-made 40CrNiMoA alloy steel, with an effective cross-sectional area A of 4850 square millimeters designed to withstand pressure. Precisely calibrated in the laboratory, the elastic modulus E of this material is 206000 MPa. The sensor 11 is a fiber optic grating sensor with a sensitivity coefficient... Calibrated at 1.2 pm / με, with a comprehensive thermal expansion correction factor. The initial temperature was set at 11.5 με / ℃. The system underwent initial calibration on day 0 after prestressing tensioning and anchoring stabilization, at which time the initial ambient temperature was recorded. The temperature is set to 15.0℃, and the initial prestress loss is set to zero (corresponding to...). Figure 4 The starting coordinate of the black solid line curve is 0).

[0099] See attached document Figure 4 The gray dashed curve, representing the uncompensated original loss calculation value, shows the original stress data collected by the system during the first 120 days of operation. It can be seen that the curve exhibits severe sawtooth fluctuations with large amplitude. This is because beam end 1 and smart ring 10 are located in an outdoor environment, affected by diurnal temperature differences and seasonal temperature changes (simulating the transition from autumn to winter), causing significant thermal expansion and contraction of the materials. For example, around day 60, the ambient temperature Tt decreases, causing a wavelength drift in the output of sensor 11. If the system directly judges based on this raw data, it will misjudge that the prestressed tendon 2 has experienced significant stress fluctuations, leading to frequent false alarms.

[0100] To obtain the true stress state, the controller performs temperature compensation and prestress loss calculation based on the core algorithm of this invention. (See attached diagram.) Figure 4 The black solid line curve, representing the compensated actual prestress loss, is drawn using the formula... The processed results show that, after removing temperature interference, the black solid line exhibits a smooth upward trend, accurately reflecting the natural stress relaxation phenomenon (i.e., creep leading to cumulative loss) that occurs in prestressed tendon 2 over time. On day 100, although the low ambient temperature caused fluctuations in the original data (dashed line), the compensated real data (solid line) indicates that the effective prestress loss at this time is still within the first warning threshold. Figure 4 Below the dashed line (indicated by the midpoint), the structure is in a safe state.

[0101] See attached document Figure 4 At day 120 on the timeline, the system detected a sudden force anomaly. In the simulation, technicians fine-tuned the anchor nut at this moment, artificially creating a slight anchor slippage fault and releasing approximately 50 kN of tension. Figure 4 As shown, the black solid line shows a vertical upward jump at day 120. The controller captures this change in real time and calculates the prestress loss at this point. The number of cases increased suddenly, and the total effective prestress loss exceeded the first warning threshold.

[0102] The specific numerical calculations are as follows: After slippage occurs on day 120, the strain change measured by the sensor, after temperature correction and benchmark comparison, corresponds to the strain loss difference value. Substitute the values ​​into the formula to calculate the tensile loss: kN. This value accurately reflects the superposition of natural relaxation loss (approximately 70 kN) and sudden slip loss (50 kN).

[0103] For comparison, if traditional periodic manual inspections (usually quarterly) are used, inspectors are highly likely to find normal data on the 90th day, only to discover the problem on the 180th day. During this 90-day period, the bridge structure will operate in a defective state with excessive prestress loss (above the threshold). In contrast, the system of this invention... Figure 4 As shown, the fault occurred on the curve on the 120th day and triggered an early warning, enabling immediate detection and maintenance, effectively avoiding the risk of minor thread slippage evolving into serious structural failure.

Claims

1. A bridge prestressed tendon system with intelligent monitoring and early warning functions, characterized in that, include: The prestressed load-bearing subsystem, which is used to form the monitored load-bearing structure and generate load-bearing physical quantities, includes prestressed tendons (2) inserted inside the beam end (1), the ends of which pass through anchoring steel plates (4) set on the end face of the beam end (1) and are mechanically locked by steel strand anchors (7). The intelligent sensing subsystem, which is used to convert the physical quantity of the force, includes an intelligent ring (10) coaxially clamped between the steel strand anchor (7) and the anchoring steel plate (4) and connected in series on the force path. The intelligent ring (10) contains a sensor (11), which is used to output a physical signal reflecting the physical quantity of the force as the intelligent ring (10) deforms. The data acquisition and transmission subsystem, which is used to process the physical signals and issue early warnings, includes a field signal transceiver (20) set outside the beam end (1). The field signal transceiver (20) is connected to the sensor (11) through a signal transmission line (12). The field signal transceiver (20) calculates the prestress loss of the prestressed tendon (2) based on the received physical signals and compares it with a preset threshold to generate a graded early warning signal.

2. A bridge prestressed tendon system with intelligent monitoring and early warning functions according to claim 1, characterized in that, The intelligent sensing subsystem also includes a ring steel pad (6) disposed between the intelligent ring (10) and the steel strand anchor (7), the ring steel pad (6) being used to transmit the pressure of the steel strand anchor (7) to the intelligent ring (10). The sensor (11) encapsulated within the smart ring (10) is a fiber optic grating sensor, a piezoelectric sensor, a resistance strain gauge, or a magnetic flux sensor.

3. A bridge prestressed tendon system with intelligent monitoring and early warning functions according to claim 2, characterized in that, The prestressed bearing subsystem also includes a corrugated pipe (3) extending along the length of the prestressed tendon (2) and sleeved on the outside of the prestressed tendon (2), and a sealed concrete (5) filling the gap on the back of the anchoring steel plate (4). The data acquisition and transmission subsystem also includes a protective cover (24) covering the outside of the steel strand anchor (7), the ring steel pad (6), the smart ring (10) and the end of the prestressed tendon (2). The protective cover (24) is fixed to the surface of the anchoring steel plate (4) or the beam end (1) to form a closed cavity. The signal transmission line (12) extends to the outside through the protective cover (24).

4. A bridge prestressed tendon system with intelligent monitoring and early warning functions according to claim 1, characterized in that, The field signal transceiver (20) includes a collection and transmission box (21) fixed to the bridge structure by a support frame (25), the collection and transmission box (21) being connected to a solar panel (22) for powering the system and an antenna (23) for wireless communication. The collection and transmission box (21) integrates a controller, and the signal transmission line (12) is connected to the collection and transmission box (21) to transmit the signal of the sensor (11).

5. A method for bridge prestressing tendons with intelligent monitoring and early warning functions, characterized in that, A bridge prestressing tendon system with intelligent monitoring and early warning function according to any one of claims 1 to 4 includes the following steps: After completing the system hardware installation and after the prestressed tensioning is stabilized, initial calibration is performed to establish a reference state including the initial reference value; In the working mode, the controller controls the sensor (11) to collect physical signals reflecting the force state and simultaneously acquires ambient temperature data; The controller processes the collected physical signals and ambient temperature data to calculate the prestress loss of the prestressed tendon (2) relative to the reference state. The controller compares the calculated prestress loss with a preset safety threshold to determine the current health status. The controller generates a corresponding status code based on the health status determination result, and performs hierarchical early warning and remote interaction.

6. A method for bridge prestressing tendons with intelligent monitoring and early warning functions according to claim 5, characterized in that, The process by which the controller completes the system hardware installation and performs initialization calibration after the prestressed tension has stabilized, establishing a reference state including initial reference values, includes: It is confirmed that the smart ring (10) has been pressed onto the force path of the anchoring steel plate (4) and the steel strand anchor (7), and that the signal transmission line (12) has been connected to the field signal transceiver station (20). Read the original signal output by the sensor (11) as the initial reference signal reading, and read the current ambient temperature as the initial ambient temperature value; The elastic modulus value of the body material of the smart ring (10), the effective cross-sectional area value for bearing pressure, and the sensitivity coefficient of the sensor (11) are written into the memory of the controller.

7. A method for bridge prestressing tendons with intelligent monitoring and early warning functions according to claim 5, characterized in that, The process by which the controller controls the sensor (11) to collect physical signals reflecting the force state in the working mode and simultaneously acquires ambient temperature data includes: The controller sends an excitation signal to the sensor (11) located inside the protective cover (24) via the signal transmission line (12) to obtain the current signal reading characterizing the deformation of the smart ring (10); The controller synchronously drives the environmental monitoring module to collect the current ambient temperature value of the beam end (1) area; The current signal reading, the current ambient temperature value, and the timestamp are combined and packaged into a raw data sequence.

8. A method for bridge prestressing tendons with intelligent monitoring and early warning functions according to claim 5, characterized in that, The process by which the controller processes the collected physical signals and ambient temperature data to calculate the prestress loss of the prestressed tendon (2) relative to the reference state includes: Calculate the temperature difference between the current ambient temperature value and the initial ambient temperature value during initialization calibration; The spurious strain caused by temperature is calculated by using the temperature difference combined with the thermal expansion correction coefficient, and the spurious strain is subtracted from the total strain measured by the sensor (11) to obtain the true mechanical strain; The actual mechanical strain is multiplied by the elastic modulus of the smart ring (10) and the effective cross-sectional area, and the prestress loss of the prestressed tendon (2) is calculated based on the reference state.

9. A method for bridge prestressing tendons with intelligent monitoring and early warning functions according to claim 5, characterized in that, The process by which the controller compares the calculated prestress loss with a preset safety threshold to determine the current health status includes: Determine whether the data stream of the sensor (11) is continuous; if the data stream is interrupted, it is determined that the integrity has failed. The blue, yellow, orange, and red warning thresholds set based on the initial prestressing tension value are invoked, and the value of the prestress loss is compared with the above-mentioned thresholds at each level. If the value of the prestress loss is less than the blue warning threshold, it is determined to be a normal state; If the value of the prestress loss is greater than or equal to the blue warning threshold and less than the yellow warning threshold, a blue warning signal is generated. If the value of the prestress loss is greater than or equal to the yellow warning threshold and less than the orange warning threshold, a yellow warning signal is generated. If the value of the prestress loss is greater than or equal to the orange warning threshold and less than the red warning threshold, an orange warning signal is generated. If the value of the prestress loss is greater than or equal to the red warning threshold, a red warning signal is generated.

10. A method for bridge prestressing tendons with intelligent monitoring and early warning functions according to claim 5, characterized in that, The process by which the controller generates a corresponding status code based on the health status assessment result and performs tiered early warning and remote interaction includes: The status code and the prestress loss amount are sent to the remote monitoring terminal through the collection and transmission box (21) and antenna (23); If the status code corresponds to a blue warning signal or a yellow warning signal, the remote monitoring terminal initiates a secondary response procedure to adjust the acquisition frequency of the field signal transceiver (20); If the status code corresponds to an orange warning signal, a red warning signal, or an integrity failure, the remote monitoring terminal triggers a level one response procedure, triggers an audible and visual alarm, and calls the structural analysis model to verify the bridge's safety.

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