Bridge pile foundation stress nondestructive testing method and system

Abstract

The invention discloses a bridge pile foundation stress nondestructive testing method and system, the system comprises a sensor arrangement module, a data acquisition module, a data transmission module, a data processing module, a data analysis module, a result display and early warning module, a calibration module, a verification module and the like, sensors are various in type and high in precision, data acquisition multichannel synchronization is realized, and transmission is stable and reliable. Various technologies are used for data processing to construct a model, and a result is visually displayed and pre-warned. The system is further provided with an environment monitoring and structure health assessment module, comprehensive and accurate detection is guaranteed through an innovative formula and method, and efficient operation of the system is guaranteed through cooperative work of all modules. Through multi-module cooperation and innovative design, bridge pile foundation stress high-precision detection, environmental factor analysis and structure health assessment are achieved. Early warning can be carried out in time, bridge safety is guaranteed, a scientific basis is provided for maintenance management, and the reliability and safety of bridge operation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge pile foundation monitoring, and in particular to a bridge pile foundation stress nondestructive detection method and system. Background Art

[0002] As a key component of transportation infrastructure, bridges play a vital role in economic development and social life. Bridge pile foundations are an important foundation for supporting bridge superstructures, and their bearing capacity and structural stability are directly related to the safety and service life of bridges. However, during long-term use, bridge pile foundations will be affected by a variety of factors, causing changes in their stress state, which may in turn cause structural diseases and safety hazards.

[0003] There are mainly the following traditional methods for detecting stress in bridge pile foundations: First, the coring method. Although this method can directly obtain material information and stress conditions inside the pile foundation, it is destructive and will damage the pile foundation structure. In addition, the detection process is complex, costly, and inefficient, making it difficult to achieve large-scale detection and real-time monitoring. Second, the static load test method measures the bearing capacity and deformation characteristics of the pile foundation by applying a vertical load to the top of the pile, thereby indirectly evaluating its stress state. However, this method requires a large amount of equipment and manpower investment, has a long test cycle, and can only be tested at a specific time point, and cannot reflect the dynamic stress changes of the bridge during actual operation. Third, non-destructive testing methods such as the rebound method are mainly used to detect parameters such as the strength of concrete. The detection accuracy of the internal stress of the pile foundation is limited, and it is greatly affected by factors such as the surface condition and age of the concrete, making it difficult to accurately evaluate the actual stress condition of the pile foundation.

[0004] With the continuous development of bridge construction, the scale of bridges is getting larger and larger, the structure is getting more and more complex, and the requirements for pile foundation stress detection are getting higher and higher. The limitations of traditional detection methods are becoming increasingly prominent, and they cannot meet the needs of modern bridge safety monitoring and maintenance management. On the one hand, modern bridges need to monitor pile foundation stress in real time and continuously in order to promptly discover potential safety hazards and take corresponding maintenance measures to ensure the safe operation of the bridge. On the other hand, for large bridges and bridges at important transportation hubs, an efficient, accurate, and non-destructive detection method is needed to fully and detailed understand the stress state of the pile foundation without affecting the normal use of the bridge, and provide a scientific basis for bridge maintenance decisions.

[0005] In addition, the environmental conditions of bridges are complex and changeable, such as temperature changes, humidity changes, vehicle loads, wind loads, etc., which will affect the stress of pile foundations. Traditional detection methods often ignore the combined effects of these environmental factors, making it difficult to accurately analyze the real cause of pile foundation stress changes. Therefore, there is an urgent need for an innovative non-destructive detection method and system for bridge pile foundation stress that can overcome the shortcomings of traditional methods, achieve high-precision, real-time, and continuous monitoring of bridge pile foundation stress, and comprehensively consider the impact of environmental factors, providing comprehensive and reliable technical support for bridge safety assessment and maintenance management. Summary of the invention

[0006] The present invention proposes a bridge pile foundation stress nondestructive testing method and system to solve the problems mentioned in the above-mentioned prior art.

[0007] In order to achieve the above object, the present invention adopts the following technical solution: a bridge pile foundation stress nondestructive testing system, comprising:

[0008] The sensor arrangement module is used to arrange stress sensors at key locations of the bridge pile foundation. The key locations include the top, middle, and connection with the pedestal of the pile foundation. Sensor types include fiber grating sensors and piezoelectric sensors. The measurement accuracy of the fiber grating sensor is within ±0.1MPa, and the resolution is not less than 0.05MPa. The frequency response range of the piezoelectric sensor is 0.1Hz-10kHz, which can accurately sense the stress changes of the pile foundation under different working conditions. The sensor is fixed by a special mounting fixture. The mounting fixture should ensure that the sensor fits tightly to the surface of the pile foundation and does not damage the pile foundation structure. The installation position error of the sensor shall not exceed ±5mm.

[0009] For multiple sensors arranged at different key locations of the pile foundation, we can evaluate the uniformity of stress distribution using the following formula:

[0010]

[0011] Where H represents the stress distribution uniformity index, n is the number of sensors, S i is the stress value measured by the i-th sensor, It is the average value of stress values ​​measured by all sensors. The significance of this formula is that it can quantify the degree of dispersion of sensor measurement values ​​relative to the average value. The smaller the H value is, the more uniform the stress distribution is and the more reasonable the sensor layout is. When arranging sensors, the position of the sensors is adjusted so that the H value reaches a smaller ideal range, such as no more than 10%. It is set according to specific project requirements to ensure that the overall stress state of the pile foundation can be reflected more comprehensively and accurately.

[0012] Taking into account the shape and stress characteristics of the pile foundation, the following formula is used to calculate the optimal position when determining the layout position of the sensor in the middle of the pile foundation:

[0013]

[0014] Where L op is the distance from the optimal arrangement position of the sensor in the middle of the pile foundation to the top of the pile foundation, in meters (m), L is the total length of the pile foundation, in meters (m), and I is the moment of inertia of the pile foundation section about the neutral axis, in meters (m) 4 , A is the cross-sectional area of ​​the pile foundation, in square meters (m) 2 , σ m is the predicted maximum stress of the pile foundation under the design load, in Pascal Pa, α, β, γ, δ are coefficients related to the pile foundation material, structure and installation conditions. The principle of this formula is to arrange the sensor at a position that is more sensitive to stress changes and can representatively reflect the stress state in the middle according to the mechanical properties of the pile foundation. The L obtained by calculation op , the installation position of the sensor in the middle of the pile foundation can be determined more scientifically, improving the accuracy and effectiveness of the measurement;

[0015] In order to ensure that the sensor fits tightly to the pile surface through the mounting fixture and does not damage the pile structure, it is necessary to reasonably control the fastening force of the mounting fixture. The following formula can be used to evaluate the fastening force:

[0016] F a =μ×S c ×P t

[0017] where F a is the tightening force of the mounting fixture, μ is the friction coefficient between the fixture and the pile surface, S c is the effective contact area between the fixture and the pile foundation, P t It is the minimum contact pressure required for the sensor to work properly. Through this formula, the appropriate tightening force range can be calculated according to the type and working requirements of the sensor, as well as the material factors of the pile surface. In the actual installation process, by adjusting the fastening device of the fixture (such as the torque of the bolt), the tightening force is controlled within the calculated range, which can not only ensure the stable installation of the sensor, but also avoid excessive additional stress on the pile structure, including for fiber Bragg grating sensors, assuming μ = 0.3, assuming the contact area S between the fixture and the pile c =100cm 2 , assuming that the minimum contact pressure P required for the sensor to work properly t =0.5MPa, then the calculated tightening force F a= 1500N. During installation, the clamping force can be controlled within a reasonable range close to this value to ensure the reliability and accuracy of the sensor installation;

[0018] The data acquisition module is connected to the sensor to collect the pile foundation stress data monitored by the sensor in real time. It has a multi-channel synchronous acquisition function and can collect data from multiple sensors at the same time. The acquisition frequency is not less than 50Hz to ensure that the rapid changes in pile foundation stress can be captured. The data acquisition module has a signal conditioning function and can amplify and filter the signal output by the sensor to remove noise interference and improve signal quality. It uses a high-precision analog-to-digital conversion chip with an analog-to-digital conversion accuracy of not less than 16 bits to ensure the accuracy of data acquisition;

[0019] The data transmission module transmits the collected data to the data processing and analysis center via wired or wireless means. In the wired transmission mode, shielded twisted pair or optical fiber high-speed transmission cable is used to ensure the stability and reliability of data transmission, and the transmission rate is not less than 100Mbps. The wireless transmission mode uses Bluetooth, ZigBee or Wi-Fi technology, with automatic retransmission and error correction functions to ensure the integrity of data transmission, and the data packet loss rate does not exceed 1%. Supporting remote transmission, it can realize remote real-time monitoring of bridge site data;

[0020] The data processing and analysis center includes a data storage unit, a data analysis unit, and a model building unit. The data storage unit uses a large-capacity hard disk or solid-state hard disk, which can store at least 1 year of pile foundation stress monitoring data. The data storage format should be convenient for subsequent query and analysis. The data analysis unit uses digital signal processing technology and statistical analysis methods to perform real-time analysis and processing on the collected data. It can calculate the mean, variance, and peak statistical parameters of pile foundation stress, and perform spectrum analysis and wavelet analysis to extract characteristic information of stress data. The model building unit constructs a stress analysis model for bridge pile foundations based on machine learning algorithms and finite element analysis methods. Support vector machine (SVM) and artificial neural network (ANN) machine learning algorithms are used to learn and train a large amount of pile foundation stress data and corresponding working condition information, and establish a mapping relationship between stress and working conditions. At the same time, combined with the finite element analysis method, the structure of the bridge pile foundation is modeled and analyzed, the model parameters are optimized, and the accuracy and reliability of the model are improved. The prediction accuracy of the model is not less than 90% on the test set;

[0021] The result display and early warning module displays the results of data processing and analysis in the form of intuitive charts and curves. It includes the curve of pile foundation stress change over time and the stress distribution cloud map, so that users can intuitively understand the stress state of the pile foundation. It has an early warning function. When it is detected that the pile foundation stress exceeds the preset threshold, it will automatically issue an audible and visual alarm or SMS notification of early warning information. The early warning threshold can be set and adjusted according to the design specifications and actual operation of the bridge to ensure the accuracy and timeliness of the early warning;

[0022] The system calibration and verification module calibrates and verifies the sensor and the entire detection system regularly. The sensor is calibrated with a high-precision standard pressure source. The calibration cycle does not exceed 6 months. The measurement error of the sensor after calibration does not exceed ±0.05MPa. The accuracy and reliability of the detection results of this system are ensured by comparing and verifying with other mature detection methods or equipment. The error of the comparison verification is within the acceptable range, generally not exceeding ±5%.

[0023] The environmental monitoring module is used to monitor the environmental parameters around the bridge in real time, including temperature, humidity, wind speed, and vehicle load. The measurement accuracy of the temperature sensor is ±0.5°C, the measurement accuracy of the humidity sensor is ±3%RH, the measurement accuracy of the wind speed sensor is ±0.5m / s, and the measurement accuracy of the vehicle load sensor is ±5%. These environmental parameters have an important impact on the stress state of the bridge pile foundation. By monitoring the environmental parameters, the reasons for the changes in pile foundation stress can be better analyzed. This module associates the environmental data with the pile foundation stress data for storage and analysis, and uses the following formula to calculate the influence coefficient C of environmental factors on pile foundation stress. env :

[0024]

[0025] Where S i is the stress value measured by the i-th sensor, S0 is the reference stress value (stress value when there is no obvious environmental change), n is the number of sensors, and E j is the change of the jth environmental parameter, and m is the number of environmental parameters. Through this coefficient, the influence of environmental factors on pile foundation stress can be quantitatively evaluated, providing a more comprehensive basis for subsequent stress analysis and fault diagnosis.

[0026] The structural health assessment module conducts a comprehensive assessment of the structural health of the bridge pile foundation based on the pile foundation stress data and environmental monitoring data. The structural health assessment model is established by combining the analytic hierarchy process (AHP) and the fuzzy comprehensive evaluation method. First, the factor set U = {u1, u2, ..., u n}, where u1, u2, …, u nIncluding stress index, deformation index, and environmental factors. Then determine the evaluation set V = {v1, v2, ..., v m}, where v1, v2, …, v m Including health, sub-health, minor injury, and major injury. The fuzzy relationship matrix of the factor set to the evaluation set and the weight vector of the factor set are determined by expert scoring or historical data statistics. The comprehensive evaluation results of the health of the bridge pile foundation structure are obtained through fuzzy comprehensive evaluation calculation, and the structural health status of the bridge pile foundation is graded and assessed, providing a scientific basis for the maintenance and management of the bridge and timely discovering potential structural safety hazards.

[0027] Preferably, the sensor arrangement module also includes waterproof, moisture-proof and anti-corrosion treatment measures for the sensors, and the sensors are encapsulated with sealants and protective coating materials to ensure that the sensors can work stably for a long time in harsh bridge environments, with a service life of not less than 5 years.

[0028] Preferably, the data analysis unit of the data processing and analysis center supports two modes: real-time online analysis and offline analysis. Users can choose the appropriate analysis mode according to actual needs. Online analysis can monitor the stress changes of pile foundations in real time and detect abnormal conditions in time; offline analysis can conduct in-depth mining and analysis of historical data, providing a more comprehensive decision-making basis for bridge maintenance and management.

[0029] Preferably, the result display and warning module supports simultaneous access by multiple users and remote access, and users can view the stress detection results and warning information of the bridge pile foundation in real time through a web browser or mobile application. The system has a user authority management function, and different users have different operation permissions. For example, the administrator user has advanced permissions for system settings, data management, and user authority allocation, and ordinary users only have basic permissions for viewing data and receiving warning information.

[0030] Preferably, the system calibration and verification module has two functions: automatic calibration and manual calibration. When the system is started, the calibration test can be automatically performed. When the sensor data is found to be abnormal or accurate calibration is required, the user can manually start the calibration procedure. At the same time, the relevant data and records of the calibration and verification process should be automatically saved for subsequent query and tracing.

[0031] Preferably, a method for applying a bridge pile foundation stress nondestructive testing system comprises the following steps:

[0032] S1. Sensor layout: Use special mounting fixtures to install fiber Bragg grating sensors and piezoelectric sensor stress sensors at the top, middle and key locations of the bridge pile foundation and the connection with the pedestal. Ensure that the sensor fits tightly to the surface of the pile foundation and the installation position error does not exceed ±5mm. After the sensor is installed, perform initial parameter setting and calibration, and record the sensor number, installation location and initial value information;

[0033] S2, data acquisition, through the data acquisition module connected to the sensor, the pile foundation stress data monitored by the sensor is collected in real time at a collection frequency of not less than 50Hz. The data acquisition module amplifies the signal output by the sensor, filters the signal and processes it to remove noise interference, and uses a high-precision analog-to-digital conversion chip to convert the analog signal into a digital signal. The collected data is stored and cached in real time to prevent data loss;

[0034] S3. Data transmission: The collected data is transmitted to the data processing and analysis center via wired (shielded twisted pair or optical fiber) or wireless (Bluetooth, ZigBee or Wi-Fi). During the transmission process, data encryption and verification technology are used to ensure the security and integrity of the data. The stability and reliability of data transmission should be guaranteed, and the data packet loss rate should not exceed 1%;

[0035] S4. Data processing and analysis: In the data processing and analysis center, the transmitted data is stored and processed. Use digital signal processing technology and statistical analysis methods to calculate the mean, variance, and peak statistical parameters of pile foundation stress, and perform spectrum analysis and wavelet analysis to extract characteristic information of stress data. Construct a stress analysis model for bridge pile foundation based on machine learning algorithms (such as support vector machines, artificial neural networks) and finite element analysis methods. Input the collected stress data and corresponding working condition information into the model for training and learning, continuously optimize the model parameters, and improve the accuracy and reliability of the model. The prediction accuracy of the model is not less than 90% on the test set;

[0036] S5. Result display and early warning: the results of data processing and analysis are displayed in the form of intuitive charts (such as pile foundation stress change curve over time, stress distribution cloud map) and curves. When the pile foundation stress is detected to exceed the preset threshold, an audible and visual alarm or SMS notification of early warning information is automatically issued. The early warning threshold is reasonably set and adjusted according to the design specifications and actual operation of the bridge;

[0037] S6. System calibration and verification. Calibrate and verify the sensor and the entire detection system regularly (no more than 6 months). Use a high-precision standard pressure source to calibrate the sensor. After calibration, the measurement error of the sensor does not exceed ±0.05MPa. Ensure the accuracy and reliability of the test results by comparing and verifying with other mature detection methods or equipment. The error of the comparison verification is within the acceptable range, generally not exceeding ±5%. The relevant data and records of the calibration and verification process should be saved for subsequent query and traceability.

[0038] S7, environmental monitoring, collects environmental parameters around the bridge in real time through the environmental monitoring module, including temperature, humidity, wind speed, and vehicle load. Collect data at certain time intervals (such as every 5 minutes) and record them synchronously with the pile foundation stress data. According to the environmental monitoring data, the environmental impact coefficient at different times is calculated using the calculation formula for the influence coefficient of environmental factors on pile foundation stress. Analyze the changing trend of the environmental impact coefficient and its correlation with the change of pile foundation stress, and provide a reference for environmental factors for subsequent stress analysis.

[0039] S8. Structural health assessment: Based on pile foundation stress data and environmental monitoring data, the structural health assessment model is used to conduct structural health assessment of bridge pile foundations. First, determine the factor set and evaluation set that affect the health of the pile foundation structure, and determine the fuzzy relationship matrix of the factor set to the evaluation set and the weight vector of the factor set through expert scoring or historical data. Then, the comprehensive evaluation results of the health of the bridge pile foundation structure are obtained through fuzzy comprehensive evaluation calculations, and the structural health status of the bridge pile foundation is graded according to the evaluation results. According to the evaluation results, formulate corresponding maintenance and management strategies, and arrange further inspection and maintenance measures in a timely manner for pile foundations that are in a sub-healthy or slightly damaged state to ensure the structural safety of the bridge.

[0040] Preferably, in the sensor arrangement step, the sensors are treated with waterproofing, moisture-proofing and anti-corrosion treatment, and are encapsulated with sealants and protective coating materials to ensure that the sensors can work stably for a long time in harsh bridge environments and have a service life of not less than 5 years.

[0041] Preferably, in the data processing and analysis steps, two modes are supported: real-time online analysis and offline analysis. Online analysis monitors the stress changes of pile foundations in real time and detects abnormal conditions in a timely manner; offline analysis conducts in-depth mining and analysis of historical data to provide a more comprehensive decision-making basis for bridge maintenance and management.

[0042] Preferably, in the result display and warning step, multiple users are supported to access simultaneously and remotely. Users can view the stress detection results and warning information of the bridge pile foundation in real time through a web browser or mobile application. The system sets a user authority management function, and different users have different operation authorities.

[0043] Preferably, in the system calibration and verification steps, there are two functions: automatic calibration and manual calibration. The system automatically performs calibration detection when it starts up. When the sensor data is found to be abnormal or accurate calibration is required, the user can manually start the calibration procedure. The relevant data and records of the calibration and verification process should be automatically saved for subsequent query and traceability.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] The present invention uses a high-precision sensor arrangement module to accurately install fiber grating sensors and piezoelectric sensors at key locations of pile foundations. Its precise measurement accuracy and frequency response range can accurately sense the stress changes of pile foundations under different working conditions, with minimal error and high resolution. Special installation fixtures ensure that the sensors fit tightly without damaging the pile foundation, and the installation position error is strictly controlled, laying the foundation for accurate detection.

[0046] The innovative data processing and analysis center, combined with digital signal processing technology and machine learning algorithms, can not only analyze and calculate various statistical parameters of stress in real time and perform spectrum and wavelet analysis, but also build accurate and reliable stress analysis models. The model has a high prediction accuracy and can effectively analyze the relationship between stress and working conditions, providing a scientific basis for evaluating the status of pile foundations.

[0047] The result display and warning module displays the results with intuitive charts and curves, allowing users to intuitively understand the stress state of the pile foundation. When the stress exceeds the threshold, a warning is given in a timely manner, and the threshold can be flexibly set according to actual conditions, ensuring the timeliness and accuracy of bridge safety monitoring.

[0048] The system calibration and verification module regularly calibrates sensors and systems, using high-precision standard pressure sources and comparative verification to ensure the accuracy and reliability of test results, with errors controlled within a very small range.

[0049] The newly added environmental monitoring module monitors a variety of environmental parameters in real time, and calculates the influence coefficient of environmental factors on pile foundation stress through innovative formulas, providing data support for comprehensive analysis of the causes of stress changes and helping to more accurately assess the status of pile foundations. The structural health assessment module uses advanced evaluation methods to comprehensively consider stress and environmental data to assess and grade the health of pile foundation structures, providing a scientific basis for bridge maintenance and management, and can promptly detect potential safety hazards and take corresponding measures to ensure the safety, stability and long-term operation of bridges. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A schematic block diagram of a sensor arrangement module of a bridge pile foundation stress nondestructive testing system proposed by the present invention;

[0051] Figure 2This is an overall schematic block diagram of a bridge pile foundation stress nondestructive testing system proposed by the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise" and "counterclockwise" indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0054] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, and it can be the internal connection of two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0055] Reference Figure 1-2 :A bridge pile foundation stress nondestructive testing system, comprising:

[0056] The sensor arrangement module is used to arrange stress sensors at key locations of the bridge pile foundation. The key locations include the top, middle, and connection with the pedestal of the pile foundation. Sensor types include fiber grating sensors and piezoelectric sensors. The measurement accuracy of the fiber grating sensor is within ±0.1MPa, and the resolution is not less than 0.05MPa. The frequency response range of the piezoelectric sensor is 0.1Hz-10kHz, which can accurately sense the stress changes of the pile foundation under different working conditions. The sensor is fixed by a special mounting fixture. The mounting fixture should ensure that the sensor fits tightly to the surface of the pile foundation and does not damage the pile foundation structure. The installation position error of the sensor shall not exceed ±5mm.

[0057] For multiple sensors arranged at different key locations of the pile foundation, we can evaluate the uniformity of stress distribution using the following formula:

[0058]

[0059] Where H represents the stress distribution uniformity index, n is the number of sensors, S i is the stress value measured by the i-th sensor, It is the average value of stress values ​​measured by all sensors. The significance of this formula is that it can quantify the degree of dispersion of sensor measurement values ​​relative to the average value. The smaller the H value is, the more uniform the stress distribution is and the more reasonable the sensor layout is. When arranging sensors, the position of the sensors is adjusted so that the H value reaches a smaller ideal range, such as no more than 10%. It is set according to specific project requirements to ensure that the overall stress state of the pile foundation can be reflected more comprehensively and accurately.

[0060] Taking into account the shape and stress characteristics of the pile foundation, the following formula is used to calculate the optimal position when determining the layout position of the sensor in the middle of the pile foundation:

[0061]

[0062] Where L op is the distance from the optimal arrangement position of the sensor in the middle of the pile foundation to the top of the pile foundation, in meters (m), L is the total length of the pile foundation, in meters (m), and I is the moment of inertia of the pile foundation section about the neutral axis, in meters (m) 4 , A is the cross-sectional area of ​​the pile foundation, in square meters (m) 2 , σ m It is the predicted maximum stress value of the pile foundation under the design load, in Pascal Pa, α, β, γ, δ are coefficients related to the pile foundation material, structure and installation conditions;

[0063] In order to ensure that the sensor fits tightly to the pile surface through the mounting fixture and does not damage the pile structure, it is necessary to reasonably control the fastening force of the mounting fixture. The following formula can be used to evaluate the fastening force:

[0064] F a =μ×S c ×P t

[0065] Among them, F a is the tightening force of the mounting fixture, μ is the friction coefficient between the fixture and the pile surface, S c is the effective contact area between the fixture and the pile foundation, P t It is the minimum contact pressure required for the sensor to work properly. Through this formula, the appropriate tightening force range can be calculated according to the type and working requirements of the sensor, as well as the material factors of the pile surface. In the actual installation process, by adjusting the fastening device of the fixture (such as the torque of the bolt), the tightening force is controlled within the calculated range, which can not only ensure the stable installation of the sensor, but also avoid excessive additional stress on the pile structure, including for fiber Bragg grating sensors, assuming μ = 0.3, assuming the contact area S between the fixture and the pile c =100cm 2 , assuming that the minimum contact pressure P required for the sensor to work properly t =0.5MPa, then the calculated tightening force F a = 1500N. During installation, the clamping force can be controlled within a reasonable range close to this value to ensure the reliability and accuracy of the sensor installation;

[0066] The data acquisition module is connected to the sensor to collect the pile foundation stress data monitored by the sensor in real time. It has a multi-channel synchronous acquisition function and can collect data from multiple sensors at the same time. The acquisition frequency is not less than 50Hz to ensure that the rapid changes in pile foundation stress can be captured. The data acquisition module has a signal conditioning function and can amplify and filter the signal output by the sensor to remove noise interference and improve signal quality. It uses a high-precision analog-to-digital conversion chip with an analog-to-digital conversion accuracy of not less than 16 bits to ensure the accuracy of data acquisition;

[0067] The data transmission module transmits the collected data to the data processing and analysis center via wired or wireless means. In the wired transmission mode, shielded twisted pair or optical fiber high-speed transmission cable is used to ensure the stability and reliability of data transmission, and the transmission rate is not less than 100Mbps. The wireless transmission mode uses Bluetooth, ZigBee or Wi-Fi technology, with automatic retransmission and error correction functions to ensure the integrity of data transmission, and the data packet loss rate does not exceed 1%. Supporting remote transmission, it can realize remote real-time monitoring of bridge site data;

[0068] The data processing and analysis center includes a data storage unit, a data analysis unit, and a model building unit. The data storage unit uses a large-capacity hard disk or solid-state hard disk, which can store at least 1 year of pile foundation stress monitoring data. The data storage format should be convenient for subsequent query and analysis. The data analysis unit uses digital signal processing technology and statistical analysis methods to perform real-time analysis and processing on the collected data. It can calculate the mean, variance, and peak statistical parameters of pile foundation stress, and perform spectrum analysis and wavelet analysis to extract characteristic information of stress data. The model building unit constructs a stress analysis model for bridge pile foundations based on machine learning algorithms and finite element analysis methods. Support vector machine (SVM) and artificial neural network (ANN) machine learning algorithms are used to learn and train a large amount of pile foundation stress data and corresponding working condition information, and establish a mapping relationship between stress and working conditions. At the same time, combined with the finite element analysis method, the structure of the bridge pile foundation is modeled and analyzed, the model parameters are optimized, and the accuracy and reliability of the model are improved. The prediction accuracy of the model is not less than 90% on the test set;

[0069] The result display and early warning module displays the results of data processing and analysis in the form of intuitive charts and curves. It includes the curve of pile foundation stress change over time and the stress distribution cloud map, so that users can intuitively understand the stress state of the pile foundation. It has an early warning function. When it is detected that the pile foundation stress exceeds the preset threshold, it will automatically issue an audible and visual alarm or SMS notification of early warning information. The early warning threshold can be set and adjusted according to the design specifications and actual operation of the bridge to ensure the accuracy and timeliness of the early warning;

[0070] The system calibration and verification module calibrates and verifies the sensor and the entire detection system regularly. The sensor is calibrated with a high-precision standard pressure source. The calibration cycle does not exceed 6 months. The measurement error of the sensor after calibration does not exceed ±0.05MPa. The accuracy and reliability of the detection results of this system are ensured by comparing and verifying with other mature detection methods or equipment. The error of the comparison verification is within the acceptable range, generally not exceeding ±5%.

[0071] The environmental monitoring module is used to monitor the environmental parameters around the bridge in real time, including temperature, humidity, wind speed, and vehicle load. The measurement accuracy of the temperature sensor is ±0.5°C, the measurement accuracy of the humidity sensor is ±3%RH, the measurement accuracy of the wind speed sensor is ±0.5m / s, and the measurement accuracy of the vehicle load sensor is ±5%. These environmental parameters have an important impact on the stress state of the bridge pile foundation. By monitoring the environmental parameters, the reasons for the changes in pile foundation stress can be better analyzed. This module associates the environmental data with the pile foundation stress data for storage and analysis, and uses the following formula to calculate the influence coefficient C of environmental factors on pile foundation stress. env :

[0072]

[0073] Where S i is the stress value measured by the i-th sensor, S0 is the reference stress value (stress value when there is no obvious environmental change), n is the number of sensors, and E j is the change of the jth environmental parameter, and m is the number of environmental parameters. Through this coefficient, the influence of environmental factors on pile foundation stress can be quantitatively evaluated, providing a more comprehensive basis for subsequent stress analysis and fault diagnosis.

[0074] The structural health assessment module conducts a comprehensive assessment of the structural health of the bridge pile foundation based on the pile foundation stress data and environmental monitoring data. The structural health assessment model is established by combining the analytic hierarchy process (AHP) and the fuzzy comprehensive evaluation method. First, the factor set U = {u1, u2, ..., u n}, where u1, u2, …, u n Including stress index, deformation index, and environmental factors. Then determine the evaluation set V = {v1, v2, ..., v m}, where v1, v2, …, v m Including health, sub-health, minor injury, and serious injury. The fuzzy relationship matrix of the factor set to the evaluation set and the weight vector of the factor set are determined by expert scoring or historical data statistics. The comprehensive evaluation results of the health of the bridge pile foundation structure are obtained through fuzzy comprehensive evaluation calculation. According to the comprehensive evaluation results, the structural health status of the bridge pile foundation is graded and evaluated, providing a scientific basis for the maintenance and management of the bridge and timely discovering potential structural safety hazards.

[0075] In the present invention, the sensor arrangement module also includes waterproof, moisture-proof and anti-corrosion treatment measures for the sensor, and the sensor is encapsulated with sealant and protective coating materials to ensure that the sensor can work stably for a long time in a harsh bridge environment, and the service life is not less than 5 years.

[0076] In the present invention, the data analysis unit of the data processing and analysis center supports two modes: real-time online analysis and offline analysis. Users can select the appropriate analysis mode according to actual needs. Online analysis can monitor the stress changes of pile foundations in real time and detect abnormal conditions in time; offline analysis can deeply mine and analyze historical data, providing a more comprehensive decision-making basis for bridge maintenance and management.

[0077] In the present invention, the result display and warning module supports simultaneous access by multiple users and remote access, and users can view the stress detection results and warning information of the bridge pile foundation in real time through a web browser or a mobile application. The system has a user authority management function, and different users have different operation authorities. For example, the administrator user has advanced authorities for system settings, data management, and user authority allocation, and ordinary users only have basic authorities for viewing data and receiving warning information.

[0078] In the present invention, the system calibration and verification module has two functions: automatic calibration and manual calibration. When the system is started, the calibration test can be automatically performed. When the sensor data is found to be abnormal or accurate calibration is required, the user can manually start the calibration procedure. At the same time, the relevant data and records of the calibration and verification process should be automatically saved for subsequent query and tracing.

[0079] In the present invention, a method for applying a bridge pile foundation stress nondestructive testing system comprises the following steps:

[0080] S1. Sensor layout: Use special mounting fixtures to install fiber Bragg grating sensors and piezoelectric sensor stress sensors at the top, middle and key locations of the bridge pile foundation and the connection with the pedestal. Ensure that the sensor fits tightly to the surface of the pile foundation and the installation position error does not exceed ±5mm. After the sensor is installed, perform initial parameter setting and calibration, and record the sensor number, installation location and initial value information;

[0081] S2, data acquisition, through the data acquisition module connected to the sensor, the pile foundation stress data monitored by the sensor is collected in real time at a collection frequency of not less than 50Hz. The data acquisition module amplifies the signal output by the sensor, filters the signal and processes it to remove noise interference, and uses a high-precision analog-to-digital conversion chip to convert the analog signal into a digital signal. The collected data is stored and cached in real time to prevent data loss;

[0082] S3. Data transmission: The collected data is transmitted to the data processing and analysis center via wired (shielded twisted pair or optical fiber) or wireless (Bluetooth, ZigBee or Wi-Fi). During the transmission process, data encryption and verification technology are used to ensure the security and integrity of the data. The stability and reliability of data transmission should be guaranteed, and the data packet loss rate should not exceed 1%;

[0083] S4. Data processing and analysis: In the data processing and analysis center, the transmitted data is stored and processed. Use digital signal processing technology and statistical analysis methods to calculate the mean, variance, and peak statistical parameters of pile foundation stress, and perform spectrum analysis and wavelet analysis to extract characteristic information of stress data. Construct a stress analysis model for bridge pile foundation based on machine learning algorithms (such as support vector machines, artificial neural networks) and finite element analysis methods. Input the collected stress data and corresponding working condition information into the model for training and learning, continuously optimize the model parameters, and improve the accuracy and reliability of the model. The prediction accuracy of the model is not less than 90% on the test set;

[0084] S5. Result display and early warning: the results of data processing and analysis are displayed in the form of intuitive charts (such as pile foundation stress change curve over time, stress distribution cloud map) and curves. When the pile foundation stress is detected to exceed the preset threshold, an audible and visual alarm or SMS notification of early warning information is automatically issued. The early warning threshold is reasonably set and adjusted according to the design specifications and actual operation of the bridge;

[0085] S6. System calibration and verification. Calibrate and verify the sensor and the entire detection system regularly (no more than 6 months). Use a high-precision standard pressure source to calibrate the sensor. After calibration, the measurement error of the sensor does not exceed ±0.05MPa. Ensure the accuracy and reliability of the test results by comparing and verifying with other mature detection methods or equipment. The error of the comparison verification is within the acceptable range, generally not exceeding ±5%. The relevant data and records of the calibration and verification process should be saved for subsequent query and traceability.

[0086] S7, environmental monitoring, collects environmental parameters around the bridge in real time through the environmental monitoring module, including temperature, humidity, wind speed, and vehicle load. Collect data at certain time intervals (such as every 5 minutes) and record them synchronously with the pile foundation stress data. According to the environmental monitoring data, the environmental impact coefficient at different times is calculated using the calculation formula for the influence coefficient of environmental factors on pile foundation stress. Analyze the changing trend of the environmental impact coefficient and its correlation with the change of pile foundation stress, and provide a reference for environmental factors for subsequent stress analysis.

[0087] S8. Structural health assessment: Based on pile foundation stress data and environmental monitoring data, the structural health assessment model is used to conduct structural health assessment of bridge pile foundations. First, determine the factor set and evaluation set that affect the health of the pile foundation structure, and determine the fuzzy relationship matrix of the factor set to the evaluation set and the weight vector of the factor set through expert scoring or historical data. Then, the comprehensive evaluation results of the health of the bridge pile foundation structure are obtained through fuzzy comprehensive evaluation calculations, and the structural health status of the bridge pile foundation is graded according to the evaluation results. According to the evaluation results, formulate corresponding maintenance and management strategies, and arrange further inspection and maintenance measures in a timely manner for pile foundations that are in a sub-healthy or slightly damaged state to ensure the structural safety of the bridge.

[0088] In the present invention, in the sensor arrangement step, the sensor is treated with waterproofing, moisture-proofing and anti-corrosion, and the sensor is encapsulated with sealant and protective coating materials to ensure that the sensor can work stably for a long time in a harsh bridge environment and the service life is not less than 5 years.

[0089] In the present invention, in the data processing and analysis steps, two modes are supported: real-time online analysis and offline analysis. Online analysis monitors the stress changes of pile foundations in real time and finds abnormal conditions in time; offline analysis conducts in-depth mining and analysis of historical data to provide a more comprehensive decision-making basis for bridge maintenance and management.

[0090] In the present invention, in the result display and early warning step, multiple users are supported to access simultaneously and remotely. Users can view the stress detection results and early warning information of the bridge pile foundation in real time through a web browser or a mobile application. The system sets a user authority management function, and different users have different operation authorities.

[0091] In the present invention, in the system calibration and verification steps, there are two functions: automatic calibration and manual calibration. The system automatically performs calibration detection when it starts up. When the sensor data is found to be abnormal or accurate calibration is required, the user can manually start the calibration procedure. The relevant data and records of the calibration and verification process should be automatically saved for subsequent query and tracing.

[0092] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can replace or change the technical solution and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A bridge pile foundation stress nondestructive testing system, characterized in that: include: A sensor arrangement module is used to arrange stress sensors at key positions of the bridge pile foundation, including the top, middle and connection with the pile foundation. Sensor types include fiber grating sensors and piezoelectric sensors. The sensors are fixed by mounting fixtures. For sensors arranged at different key positions of the pile foundation, the uniformity of stress distribution is evaluated by the following formula: Where H represents the stress distribution uniformity index, n is the number of sensors, S i is the stress value measured by the i-th sensor, is the average value of stress values ​​measured by all sensors; When determining the placement of the sensor in the middle of the pile foundation, the following formula is used to calculate the optimal position: Where L op is the distance from the optimal arrangement position of the sensor in the middle of the pile foundation to the top of the pile foundation, in meters (m), L is the total length of the pile foundation, in meters (m), and I is the moment of inertia of the pile foundation section about the neutral axis, in meters (m) 4 , A is the cross-sectional area of ​​the pile foundation, in square meters (m) 2 , σ m It is the predicted maximum stress value of the pile foundation under the design load, in Pascal Pa, α, β, γ, δ are coefficients related to the pile foundation material, structure and installation conditions; In order to ensure that the sensor fits tightly to the pile surface through the mounting fixture and does not cause damage to the pile structure, the following formula is used to evaluate the tightening force: F a =μ×S c ×P t Among them, F a is the tightening force of the mounting fixture, μ is the friction coefficient between the fixture and the pile surface, S c is the effective contact area between the fixture and the pile foundation, P t It is the minimum contact pressure required for the sensor to work properly; The data acquisition module is connected to the sensor to collect the pile foundation stress data monitored by the sensor in real time; Data transmission module, which transmits the collected data to the data processing and analysis center via wired or wireless means; The data processing and analysis center includes a data storage unit, a data analysis unit and a model building unit. The data storage unit uses a large-capacity hard disk or solid-state hard disk. The data analysis unit uses digital signal processing technology and statistical analysis methods to perform real-time analysis and processing on the collected data. The model building unit builds a stress analysis model of the bridge pile foundation based on machine learning algorithms and finite element analysis methods. It uses support vector machine SVM and artificial neural network ANN machine learning algorithms to learn and train the pile foundation stress data and corresponding working condition information, establish a mapping relationship between stress and working conditions, and combine finite element analysis methods to model and analyze the structure of the bridge pile foundation and optimize model parameters. The result display and early warning module displays the results of data processing and analysis in the form of intuitive charts and curves, including the pile foundation stress change curve over time and the stress distribution cloud map. When the pile foundation stress is detected to exceed the preset threshold, an audible and visual alarm or SMS notification of early warning information is automatically issued. The early warning threshold is set and adjusted according to the design specifications and actual operation of the bridge; System calibration and verification module, calibrates and verifies the sensor and the entire detection system. The sensor is calibrated using a standard pressure source. The calibration cycle does not exceed 6 months. After calibration, the measurement error of the sensor does not exceed ±0.05MPa. The environmental monitoring module is used to monitor the environmental parameters around the bridge in real time, including temperature, humidity, wind speed, and vehicle load. The measurement accuracy of the temperature sensor is ±0.5°C, the measurement accuracy of the humidity sensor is ±3%RH, the measurement accuracy of the wind speed sensor is ±0.5m / s, and the measurement accuracy of the vehicle load sensor is ±5%. The environmental data is associated with the pile foundation stress data for storage and analysis, and the influence coefficient C of environmental factors on pile foundation stress is calculated using the following formula env : Where S i is the stress value measured by the i-th sensor, S0 is the reference stress value, n is the number of sensors, E j is the change of the jth environmental parameter, and m is the number of environmental parameters; The structural health assessment module conducts a comprehensive assessment of the structural health status of the bridge pile foundation based on the pile foundation stress data and environmental monitoring data, and establishes a structural health assessment model by combining the hierarchical analysis method (AHP) and the fuzzy comprehensive evaluation method.

2. The bridge pile foundation stress nondestructive testing system according to claim 1 is characterized in that: The sensor arrangement module also includes waterproof, moisture-proof and anti-corrosion treatment measures for the sensor, and the sensor is encapsulated with sealant and protective coating materials, with a service life of not less than 5 years.

3. The bridge pile foundation stress nondestructive testing system according to claim 1 is characterized in that: The data analysis unit of the data processing and analysis center supports two modes: real-time online analysis and offline analysis. Users can choose the appropriate analysis mode according to actual needs. Online analysis can monitor the stress changes of pile foundations in real time, and offline analysis can conduct in-depth mining and analysis of historical data, providing a more comprehensive decision-making basis for bridge maintenance and management.

4. The bridge pile foundation stress nondestructive testing system according to claim 1 is characterized in that: The result display and warning module supports simultaneous access by multiple users and remote access. Users can view the stress detection results and warning information of bridge pile foundations in real time through web browsers or mobile applications. Different users have different operation permissions, among which administrator users have advanced permissions for system settings, data management and user permission allocation, and ordinary users only have basic permissions for viewing data and receiving warning information.

5. The bridge pile foundation stress nondestructive testing system according to claim 1 is characterized in that: The system calibration and verification module has two functions: automatic calibration and manual calibration. It automatically performs calibration detection when the system is started. When the sensor data is found to be abnormal or precise calibration is required, the user manually starts the calibration program, and the relevant data and records of the calibration and verification process are automatically saved.

6. A bridge pile foundation stress nondestructive testing method, used for applying the bridge pile foundation stress nondestructive testing system according to any one of claims 1 to 5, characterized in that: The following steps are involved: S1. Sensor arrangement: Use special mounting fixtures to install fiber Bragg grating sensors and piezoelectric sensor stress sensors at the top, middle and key locations of the bridge pile foundation and the connection with the pedestal. Ensure that the sensor fits tightly to the surface of the pile foundation and the installation position error does not exceed ±5mm. After the sensor is installed, perform initial parameter setting and calibration, and record the sensor number, installation location and initial value information. S2, data acquisition, through the data acquisition module connected to the sensor, the pile foundation stress data monitored by the sensor is collected in real time at a collection frequency of not less than 50Hz. The data acquisition module amplifies the signal output by the sensor, filters the signal and processes it to remove noise interference, and uses a high-precision analog-to-digital conversion chip to convert the analog signal into a digital signal. The collected data is stored and cached in real time to prevent data loss; S3, data transmission, the collected data is transmitted to the data processing and analysis center via shielded twisted pair or optical fiber or Bluetooth or ZigBee or Wi-Fi, and data encryption and verification technology is used during the transmission process; S4. Data processing and analysis: In the data processing and analysis center, the transmitted data is stored and processed. Digital signal processing technology and statistical analysis methods are used to calculate the mean, variance, and peak statistical parameters of pile foundation stress, and spectrum analysis and wavelet analysis are performed to extract the characteristic information of stress data. Based on machine learning algorithms and finite element analysis methods, a stress analysis model of bridge pile foundation is constructed. The collected stress data and corresponding working condition information are input into the model for training and learning, and the model parameters are optimized to improve the accuracy and reliability of the model. The prediction accuracy of the model is not less than 90% on the test set. S5. Result display and early warning: the results of data processing and analysis are displayed in the form of a pile foundation stress variation curve or a stress distribution cloud map. When the pile foundation stress is detected to exceed the preset threshold, an audible and visual alarm or SMS notification of early warning information is automatically issued. The early warning threshold is reasonably set and adjusted according to the design specifications and actual operation of the bridge; S6. System calibration and verification: the sensor and the entire detection system shall be calibrated and verified every 6 months. The sensor shall be calibrated with a high-precision standard pressure source. The measurement error of the sensor after calibration shall not exceed ±0.05MPa, and the error of comparative verification shall not exceed ±5%; S7, environmental monitoring, collecting environmental parameters around the bridge in real time through the environmental monitoring module, including temperature, humidity, wind speed, and vehicle load, collecting data at intervals of 5 minutes, and synchronously recording with the pile foundation stress data, calculating the environmental impact coefficient at different times based on the environmental monitoring data using the calculation formula for the influence coefficient of environmental factors on pile foundation stress, analyzing the change trend of the environmental impact coefficient and its correlation with the change of pile foundation stress, and providing a reference basis for environmental factors for subsequent stress analysis; S8. Structural health assessment. Based on pile foundation stress data and environmental monitoring data, the structural health assessment model is used to perform structural health assessment of bridge pile foundations. First, the factor set and evaluation set that affect the health of the pile foundation structure are determined. The fuzzy relationship matrix of the factor set to the evaluation set and the weight vector of the factor set are determined through expert scoring or historical data. Then, the comprehensive evaluation results of the health of the bridge pile foundation structure are obtained through fuzzy comprehensive evaluation calculations. According to the evaluation results, the structural health status of the bridge pile foundation is graded and assessed, and corresponding maintenance and management strategies are formulated based on the assessment results.

7. The bridge pile foundation stress nondestructive testing method according to claim 6, characterized in that: In the structural health assessment step, the factor set U = {u1, u2, ..., u n }, where u1, u2, …, u n Including stress index, deformation index, environmental factors, determine the evaluation set V = {υ1,υ2,…,υ m }, where υ1, υ2,…, υ m Representing health, sub-health, slight injury and severe injury data, the fuzzy relationship matrix of the factor set to the evaluation set and the weight vector of the factor set are determined by expert scoring or historical data statistics, and the comprehensive evaluation result of the health of the bridge pile foundation structure is obtained through fuzzy comprehensive evaluation calculation.

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