Real-time monitoring and early warning method for anti-sliding performance of steel structure node

Abstract

The invention relates to the technical field of structure health monitoring, and discloses a steel structure node anti-slip performance real-time monitoring and early warning method, which comprises the following steps: applying a pressure-sensitive acoustic impedance matching coating containing a pressure-sensitive microstructure unit and inert acoustic beacon particles on a friction surface of a steel structure node; the method comprises the following steps: deploying a phased array ultrasonic transducer array, and generating a reference pre-tightening force distribution topological graph through a full-matrix data acquisition and synthetic aperture focusing technology; in a subsequent monitoring period, the process is repeated to generate a real-time pre-tightening force distribution topological graph; and finally, generating a pre-tightening force change difference graph by comparing the reference with the real-time topological graph, extracting quantitative characteristic indexes such as a maximum change value and a significant change region area from the pre-tightening force change difference graph, and comparing the quantitative characteristic indexes with a preset threshold value to realize multi-level early warning. According to the invention, visual, quantitative and automatic remote monitoring of pre-tightening force distribution can be realized, and the system has the advantages of high monitoring precision, strong anti-interference capability and good reliability.

Description

Technical Field

[0001] This invention relates to the field of structural health monitoring technology, specifically a method for real-time monitoring and early warning of the anti-slip performance of steel structure nodes. Background Technology

[0002] In large steel structures such as high-rise buildings, bridges, offshore platforms, and heavy industrial plants, high-strength bolted connections are crucial for ensuring the overall safety and stability of the structure. Their load-bearing capacity, especially their anti-slip performance, largely depends on the inter-plate friction generated by the preload applied to the bolts. However, during the structure's service life, due to the combined effects of dynamic loads, vibration, temperature cycling, and material creep, the bolt preload inevitably loosens. Once this loosening accumulates to a certain extent, it will severely weaken the load-bearing capacity of the connection and may even lead to catastrophic structural accidents. Therefore, long-term and effective monitoring of the preload status of critical connections is of paramount importance for preventing structural failure and ensuring personnel safety.

[0003] Currently, bolt preload detection technologies mainly focus on control during the installation phase and random inspections during service. While traditional torque and rotation methods are widely used during installation, their accuracy is easily affected by the friction coefficient between the bolt and the plate, and they cannot be used for condition monitoring during service. To achieve long-term monitoring, some sensor-based technologies have emerged, such as smart bolts using built-in strain gauges or installing force-measuring washers. Although these methods can provide direct readings of preload, they are costly, and sensor implantation may alter the original mechanical properties of the bolt connection. Furthermore, the durability and stability of the sensors themselves and their leads face challenges in harsh service environments, limiting their large-scale application.

[0004] Ultrasonic testing technology, due to its non-destructive and sensitive characteristics, is considered a more promising monitoring method. Traditional ultrasonic methods primarily calculate bolt elongation by measuring the time variation of ultrasonic waves propagating axially within the bolt shank, and then inferring its average preload. However, this single-point, average stress-based measurement technique has inherent limitations. It cannot reveal the actual distribution of preload on the frictional contact surface of the joint, and the uniformity of this distribution is crucial in determining the joint's anti-slip capability. Furthermore, the propagation speed of ultrasonic waves in steel is extremely sensitive to temperature; daily fluctuations in ambient temperature introduce significant measurement errors, severely impacting the reliability of monitoring results. Simultaneously, environmental loads such as wind and traffic loads experienced by the structure during actual service generate continuous vibration noise, which can overlap with weak ultrasonic echo signals, further reducing the signal-to-noise ratio and monitoring accuracy. Finally, the long-term stability of the acoustic coupling between the ultrasonic transducer and the tested structure is also a significant challenge in ensuring data consistency and reliability.

[0005] In summary, existing technologies still have many shortcomings in achieving accurate, reliable, distributed, and highly environmentally adaptable automated long-term monitoring of preload in steel structure nodes. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a method for real-time monitoring and early warning of the anti-slip performance of steel structure nodes. This method solves the problem that existing technologies, when conducting long-term automated monitoring of the preload distribution on the friction surface of steel structure nodes, cannot simultaneously overcome environmental temperature drift and vibration noise interference, thus making it difficult to achieve accurate, reliable, and visualized monitoring.

[0007] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of this invention provides a method for real-time monitoring and early warning of the anti-slip performance of steel structure nodes, the method comprising: A pressure-sensitive acoustic impedance matching coating is applied to the friction surface of the steel structure node; When the steel structure node is in an initial pre-tightened state, ultrasonic waves are emitted to the friction surface and a first echo signal is received by an ultrasonic transducer arranged outside the steel structure node. The first echo signal is processed to generate and store a reference pre-tightening force distribution topology map. The ultrasonic transducer periodically emits ultrasonic waves to the friction surface and receives a second echo signal, and processes the second echo signal to generate a real-time preload distribution topology map; The real-time preload distribution topology map is compared with the stored baseline preload distribution topology map to identify preload changes; Based on the comparison results, an early warning signal is output when the preload change exceeds a preset threshold.

[0008] In one specific embodiment, the preparation step of the pressure-sensitive acoustic impedance matching coating includes: uniformly doping a pressure-sensitive microstructure unit and inert acoustic beacon particles into a substrate material. The acoustic impedance of the pressure-sensitive microstructure unit increases with increasing normal pressure, while the acoustic properties of the inert acoustic beacon particles are pressure-insensitive and remain stable.

[0009] This method utilizes the principle of acoustic impedance mismatch for imaging. Ultrasonic waves are formed at acoustic impedances of... and When propagation occurs at the interface between two media, its energy reflection coefficient Determined by the following formula: ; In this method, Acoustic impedance of steel , The equivalent acoustic impedance of the pressure-sensitive acoustic impedance matching coating .

[0010] In the low preload region much smaller ,lead to Approaching 1, the echo signal is strong; in the high preload region, the pressure-sensitive microstructure unit is compacted, resulting in... near , When the value approaches zero, the echo signal is weak. Therefore, the intensity of the echo signal directly reflects the degree of matching of the interface acoustic impedance, and thus characterizes the distribution of the preload.

[0011] In one specific embodiment, the step of processing the first echo signal to generate the reference preload distribution topology map includes adaptive calibration and environmental noise removal processing of the first echo signal, followed by image reconstruction. Preferably, the adaptive calibration processing involves emitting a calibration beam to the inert acoustic beacon particles at a predetermined location, calculating the sound speed drift caused by changes in ambient temperature based on the flight time variation of its echo signal, and performing time-domain compensation on the first echo signal.

[0012] If the speed of sound in the initial calibration state is The measured round-trip flight time of the calibration sound beam is During real-time monitoring, the measured flight time was: The speed of sound after real-time calibration The calculation is as follows: ; Preferably, the environmental noise removal process involves passively monitoring the structural response signal caused by environmental vibration during the intervals between ultrasonic wave transmissions, establishing an environmental noise fingerprint database, and using the environmental noise fingerprint database to filter the first echo signal.

[0013] In both the processing of the first echo signal and the processing of the second echo signal, synthetic aperture focusing technology is employed. Coherent addition operations are performed on the corresponding echo signals to reconstruct the acoustic reflection intensity at each point on the friction stirrer, thereby generating a topology map. For each point on the friction stirrer... Intensity values ​​in its topological map It can be calculated using the following formula: ; in, This represents the total number of transducer array elements. For the first Each element is launched, after the first... The calibrated echo signal received by each array element This represents the time delay corresponding to the transmission path.

[0014] In one specific embodiment, the step of comparing the real-time preload distribution topology map with the reference preload distribution topology map is as follows: For each spatial coordinate point on the friction surface, obtain the intensity value of the corresponding pixel in the real-time preload distribution topology map. and the intensity value of the corresponding pixel in the reference preload distribution topology map. ; Calculate the absolute value of the difference between the two strength values, and use it as a difference strength characterizing the magnitude of the preload variation. The calculation formula is as follows: ; Furthermore, the difference intensity calculated from all spatial coordinate points is combined into a new two-dimensional image, which is a preload variation difference diagram.

[0015] Preferably, the step of outputting a warning signal is achieved by extracting at least one quantitative feature index from the preload variation difference map and determining whether the quantitative feature index exceeds its corresponding warning threshold.

[0016] Preferably, the quantification feature index includes: the maximum pixel intensity change value in the preload variation map. And the pixel intensity change value exceeds a preset attention threshold. area The calculation method is as follows: ; ; in, Indicates the location The change in intensity at that location. Indicates all possible Find the maximum value among the coordinate points. Indicates to and Perform double integration. This defines the conditions for the integration region; only when the intensity change... Exceeding a certain threshold Only when this condition is met will it be included in the area calculation.

[0017] In one specific embodiment, the ultrasonic transducer is a phased array ultrasonic transducer array, and the step of emitting ultrasonic waves is to electronically control the array elements in the array to be excited sequentially, thereby achieving rapid scanning of the entire friction surface.

[0018] This invention provides a method for real-time monitoring and early warning of the anti-slip performance of steel structure nodes. It has the following beneficial effects: 1. This invention converts the invisible pressure field into an acoustic impedance field that can be detected by ultrasonic waves by setting a pressure-sensitive acoustic impedance matching coating on the friction surface, and combines synthetic aperture focusing technology to invert and reconstruct the echo signal to generate an intuitive preload distribution topology map. Compared with traditional single-point or average value measurement methods, this invention can identify the uneven distribution of preload and local relaxation areas, and provides more comprehensive node status information.

[0019] 2. By setting inert acoustic beacon particles that are insensitive to pressure in the coating, this invention can calibrate the sound velocity drift caused by temperature changes in real time, eliminating thermal measurement errors. At the same time, by passively listening and establishing an environmental noise fingerprint database, vibration interference caused by wind load and traffic load can be effectively removed from the original echo signal, ensuring the data reliability of the monitoring system under complex field conditions.

[0020] 3. This invention generates a preload variation difference map by performing pixel-by-pixel difference calculation between the real-time preload distribution topology map and the baseline topology map, which intuitively presents the area and magnitude of preload attenuation. Furthermore, by extracting quantitative feature indicators such as the maximum intensity change value and the area of ​​significant change region in the difference map and comparing them with preset thresholds, a multi-level early warning judgment from concern to danger is realized, providing accurate data support for structural maintenance decisions. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the overall method flow of the present invention; Figure 2 This is a schematic diagram illustrating the process of establishing and applying the environmental noise fingerprint database according to the present invention; Figure 3 This is a schematic diagram illustrating the adaptive acoustic path calibration principle of the present invention; Figure 4 This is a schematic diagram of the periodic real-time monitoring process of the present invention; Figure 5 This is a schematic diagram of the difference analysis and multi-level early warning process of the present invention. Detailed Implementation

[0022] 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.

[0023] See attached document Figure 1This invention provides a method for real-time monitoring and early warning of the anti-slip performance of steel structure nodes. In one specific embodiment, the method may include the following steps: First, during node assembly, a pre-prepared pressure-sensitive acoustic impedance matching coating is applied to the friction surface of the steel structure node. After the node is assembled according to design requirements, a phased array ultrasonic transducer array is arranged on the steel plate surface outside the node, and the transducer array is electrically connected to a data processing terminal.

[0024] When the initial preload is applied to the steel structure node and it is in an initial healthy state, a baseline state establishment procedure is executed. The procedure includes emitting ultrasonic waves to the friction surface through the phased array ultrasonic transducer array and receiving the first echo signal.

[0025] The first echo signal is processed to generate and store a reference preload distribution topology map. The processing includes environmental noise removal, adaptive acoustic path calibration, and image reconstruction. During the intervals between ultrasonic wave transmissions, environmental vibration signals are passively monitored to establish an environmental noise fingerprint database, which is then used to filter the first echo signal.

[0026] Simultaneously, a calibration sound beam is emitted towards inert acoustic beacon particles at predetermined locations within the coating, and the real-time sound velocity is calculated based on the change in the echo's flight time. If the sound velocity in the initial calibration state is... The measured round-trip flight time of the calibration sound beam is During real-time monitoring, the measured flight time was: and using the calculated Time-domain correction is performed on the first echo signal.

[0027] Synthetic aperture focusing technology is used to reconstruct the image from the first echo signal after the above processing. For any point on the friction surface... And calculate the intensity value in the topological map. .

[0028] After establishing the baseline state, the system enters the periodic real-time monitoring phase. The data acquisition and signal processing steps in the baseline state establishment process are repeated according to a preset time period. Specifically, ultrasonic waves are emitted through the phased array ultrasonic transducer array, and a second echo signal is received. Similarly, environmental noise is removed from the second echo signal, adaptive acoustic path calibration is performed, and synthetic aperture focusing image reconstruction is conducted to generate a real-time preload distribution topology map. .

[0029] Obtain the intensity value of the corresponding pixel in the real-time preload distribution topology map. and the intensity value of the corresponding pixel in the reference preload distribution topology map. ; After generating a real-time preload distribution topology map, it is compared with the stored baseline preload distribution topology map to identify preload changes. This comparison step involves performing pixel-by-pixel differential operations to generate a preload change difference map. .

[0030] Subsequently, quantitative feature indicators are extracted from the preload variation difference map for use in subsequent early warning determination. These quantitative feature indicators include the maximum pixel intensity change value. Area of ​​significant change .

[0031] Finally, based on the quantitative characteristic indicators and preset warning thresholds, a warning is determined. If one or more indicators exceed their corresponding thresholds, the system outputs a warning signal to the monitoring center.

[0032] The pressure-sensitive acoustic impedance matching coating is the physical basis for realizing the method of the present invention. It is applied to the friction surface of the steel structure node to convert the mechanical pressure field into an acoustic impedance distribution field that can be detected by ultrasonic waves. In a specific embodiment, the coating is constructed and prepared as follows.

[0033] The coating consists of three basic components: a matrix material, pressure-sensitive microstructure units, and inert acoustic beacon particles.

[0034] The matrix material is a liquid or paste-like curable polymer or resin. In one specific embodiment, a two-component epoxy resin is selected as the matrix material. After curing, the epoxy resin exhibits strong adhesion to the steel substrate, abrasion resistance, and chemical stability. The cured matrix material itself has a fixed acoustic impedance value that is mismatched with the acoustic impedance of the steel, and its acoustic properties remain stable within the expected operating temperature and pressure range.

[0035] The pressure-sensitive microstructure unit is a micron-sized particle uniformly dispersed in a matrix material. In one specific embodiment, the unit is a hollow glass microsphere with a particle size ranging from 10 to 100 micrometers and a wall thickness of 1 to 5 micrometers. Under no pressure or low pressure, the hollow glass microsphere maintains its complete spherical structure, with its interior being gas or a vacuum, resulting in extremely low acoustic impedance. When ultrasonic waves propagate to the interface between the coating and the steel, due to the presence of a large number of such low-impedance microspheres in the coating, the equivalent acoustic impedance of the coating is much lower than that of the steel, thus generating strong interface reflection.

[0036] When the coating is subjected to normal high pressure applied by bolt preload, its spherical shell irreversibly breaks when the pressure exceeds the compressive strength threshold of the hollow glass microspheres. The broken microsphere fragments mix with the matrix material, eliminating the original hollow structure. This results in a significant increase in the local equivalent density and elastic modulus of the coating in the pressure zone, and its equivalent acoustic impedance increases accordingly, approaching the acoustic impedance of steel, thereby significantly reducing the ultrasonic wave reflection coefficient at this interface.

[0037] The inert acoustic beacon particles are another type of micron-sized particles sparsely and uniformly dispersed in the matrix material. In one specific embodiment, zirconia ceramic microspheres with a particle size ranging from 150 to 300 micrometers are selected as the beacon particles. These zirconia microspheres possess high hardness and compressive strength, ensuring they do not deform or break under the maximum preload of the nodes. Simultaneously, their acoustic impedance differs significantly from that of the cured matrix material, making them a stable, highly reflective acoustic scatterer. These particles are spatially fixed within the coating, serving as reference points for subsequent acoustic path calibration.

[0038] The preparation and application process of the coating includes the following steps: First, the matrix material, the pressure-sensitive microstructure unit, and the inert acoustic beacon microparticles are mixed according to a predetermined mass ratio. For example, the ratio of epoxy resin, hollow glass microspheres, and zirconia microspheres by mass is 100:20:5. The mixture is stirred at a low speed using a mechanical stirrer until all microparticles are uniformly dispersed in the resin, forming a coating mixture.

[0039] Secondly, before assembling the steel structure nodes, the target friction surfaces are surface-treated, such as by sandblasting and cleaning, to ensure the adhesion of the coating.

[0040] Subsequently, the coating mixture is applied evenly to the treated friction surface by spraying or brushing, controlling the wet film thickness to ensure that the dry film thickness after curing is between 200 and 500 micrometers.

[0041] Finally, the coated steel plate is cured under specified environmental conditions until the coating is completely hardened, forming the final functional interface.

[0042] The monitoring system is used to emit ultrasonic waves, collect echo signals, and perform data processing. In one specific embodiment, its hardware configuration and deployment are as follows.

[0043] The monitoring system includes a phased array ultrasonic transducer array, a data acquisition and control unit, and a data processing terminal.

[0044] The phased array ultrasonic transducer array is the front-end component for ultrasonic wave transmission and reception. In one specific embodiment, a two-dimensional area array transducer is selected, which contains 256 independent array elements arranged in a 16x16 matrix. Each array element is made of piezoelectric composite material and has an independent electrode lead-out. The center operating frequency of the array is 5MHz, and the element spacing is 2mm. The transducer array is tightly bonded to the outer surface of the steel structure node under test by an acoustic coupling agent (e.g., ultrasonic coupling gel) and fixed with magnetic clamps to maintain a stable acoustic coupling state during long-term monitoring.

[0045] The data acquisition and control unit is a multi-channel ultrasonic signal transceiver. Internally, it includes a multi-channel pulse generator / receiver, an analog-to-digital converter array, and a control logic module. The multi-channel pulse generator / receiver has 256 parallel channels, each connected to an element in the phased array ultrasonic transducer array via a multi-core shielded cable. The pulse generator generates high-voltage pulses to excite the array element to emit ultrasonic waves, and the receiver amplifies the weak echo voltage signal received by the array element with low noise.

[0046] The analog-to-digital converter array is connected to the output of the receiver and is responsible for converting the amplified analog echo signal into a digital signal. In one specific embodiment, the sampling frequency of each channel is 60 MSPS (millions of samples per second), and the quantization precision is 16 bits. The control logic module is implemented by a field-programmable gate array (FPGA), which is responsible for precisely controlling the trigger time delay and trigger sequence of each pulse generation channel to execute scanning strategies such as Full Matrix Capture (FMC) and synchronously manage the data acquisition and buffering of all analog-to-digital conversion channels.

[0047] The data processing terminal is an industrial computer or embedded controller, connected to the data acquisition and control unit via a high-speed data interface (e.g., PCI Express or 10 Gigabit Ethernet). It is responsible for receiving the raw full-matrix echo data uploaded by the data acquisition and control unit. The data processing terminal runs a pre-set software program to perform all the computational tasks described in subsequent steps of this invention, including signal processing, image reconstruction, difference comparison, and early warning determination, and is also responsible for data storage and display of monitoring results.

[0048] See attached document Figure 2 In the initial stage of establishing the baseline state, in order to eliminate the interference of environmental vibration on the ultrasonic echo signal, this method first establishes an environmental noise fingerprint database.

[0049] The establishment of the environmental noise fingerprint database is achieved by switching the data acquisition and control unit to passive listening mode during the intermittent period of active ultrasonic wave transmission. In this mode, all elements of the phased array ultrasonic transducer array are used only as high-sensitivity acoustic sensors to continuously receive the weak structural response signals caused by environmental vibrations generated by wind loads, traffic loads, or the operation of the equipment itself in the steel structure nodes.

[0050] The data acquisition and control unit continuously acquires multiple independent background noise signal samples with a preset time length (e.g., 100 milliseconds) as the window. Each acquired time-domain noise signal is processed by the data processing terminal to extract features and generate a fingerprint vector that characterizes the current noise properties.

[0051] In one specific embodiment, the feature extraction step includes: First, the collected time-domain noise signal samples are subjected to Fast Fourier Transform (FFT) to obtain their corresponding spectrum; Secondly, the power spectral density (PSD) of the spectrum is calculated to characterize the distribution characteristics of noise energy at different frequencies; Then, the autocorrelation function of the time-domain noise signal sample is calculated to characterize the correlation structure of the noise over time; Finally, the calculated power spectral density curve, autocorrelation function curve, and other statistical features (such as the root mean square value of the signal and kurtosis factor) are combined into a high-dimensional fingerprint vector.

[0052] The data processing terminal stores multiple fingerprint vectors obtained through continuous acquisition and calculation, forming an environmental noise fingerprint database that can characterize the environmental noise characteristics under different times and operating conditions. In subsequent ultrasonic data processing, when a mixed signal containing real echoes and environmental noise (such as the first echo signal or the second echo signal) is received, the data processing terminal retrieves the noise fingerprint closest to the current acquisition time from the environmental noise fingerprint database, and uses an adaptive filtering algorithm to estimate and subtract the noise component from the mixed signal, thereby achieving accurate filtering of the echo signal.

[0053] In one specific embodiment, the adaptive filtering algorithm is a Least Mean Squares (LMS) adaptive filtering algorithm. The acquired mixed signal is used as the main input, and the corresponding noise sample retrieved from the noise fingerprint database is used as the reference input. The filter weights are iteratively updated using the LMS algorithm, so that the filter output can best approximate the noise component in the mixed signal. Finally, the mixed signal is subtracted from the filter output to obtain a clean echo signal.

[0054] See attached document Figure 3Before reconstructing the image from the echo signal, this method performs an adaptive acoustic path calibration to eliminate the measurement error caused by the drift of ultrasonic propagation speed (sound velocity) in steel due to changes in ambient temperature.

[0055] The calibration process utilizes inert acoustic beacon particles, pre-dispersed in a pressure-sensitive acoustic impedance matching coating and with fixed spatial positions, as acoustic reference points. In one specific embodiment, during the initial system deployment phase, a single calibration scan precisely determines and stores the three-dimensional spatial coordinates of at least one or more beacon particles.

[0056] Before each data acquisition (whether generating a baseline topology map or a real-time topology map), the data processing terminal controls the phased array ultrasonic transducer array to enter calibration mode. In this mode, the system selects a beacon particle with calibrated coordinates as the target. Based on the spatial coordinates of the target beacon particle, the data processing terminal calculates the precise time delay required for each element in the array to emit a pulse, ensuring that the ultrasonic waves emitted by all elements are superimposed in phase at the position of the target beacon particle, thereby forming a high-energy focused sound beam.

[0057] The focused acoustic beam propagates to the target beacon particles and is reflected by them. The echo signal is received by all elements of the phased array ultrasonic transducer array. The data acquisition and control unit records the round-trip time of flight (TOF) from the moment of transmission to the moment the strongest target echo is received, denoted as . The data processing terminal will measure the flight time. Compared to the initial calibration conditions (e.g., at a known temperature) The reference flight time of the stored beacon particles (measured below) The comparisons were made, and the calibrated speed of sound under the current environment was calculated. : ; Calculated calibrated sound velocity It is used as a key parameter in the subsequent synthetic aperture focusing image reconstruction step. Specifically, it is substituted into the formula for calculating the total propagation delay to accurately compensate for the time of signal superposition path at each pixel, thereby ensuring that the geometric accuracy and focusing quality of the reconstructed image remain stable even under temperature variations, providing an accurate data basis for subsequent difference comparisons.

[0058] After establishing the environmental noise fingerprint database and adaptively calibrating the acoustic path, this method performs image reconstruction on the processed first echo signal to generate a full matrix data acquisition (FMC) scan strategy. In a specific embodiment, the data acquisition and control unit first executes a full matrix data acquisition (FMC) scan strategy. This strategy electronically controls each element in the phased array ultrasonic transducer array to be independently excited to emit ultrasonic waves in sequence. After each emission, all elements in the array synchronously receive the reflected echo signal, thereby obtaining a full matrix raw echo dataset containing information on all transmission and reception combined paths.

[0059] The original echo dataset, after undergoing the aforementioned environmental noise removal and adaptive acoustic path calibration processes, yields a calibrated and filtered first echo signal matrix. ,in For the index of the transmitting array element, To receive the array element index, For time.

[0060] The data processing terminal uses Synthetic Aperture Focusing Technique (SAFT) to process the first echo signal matrix in order to reconstruct the spatial coordinates of each point on the friction surface. The corresponding acoustic reflection intensity is used to generate a topology map.

[0061] Furthermore, the difference intensity calculated from all spatial coordinate points is combined into a new two-dimensional image, which is a preload variation difference diagram.

[0062] By performing the above coherent superposition operation on all pixels within a predetermined area of ​​the friction surface, a two-dimensional image is finally generated. Each pixel intensity value of the two-dimensional image corresponds to the acoustic reflection intensity at a specific location on the friction surface, and the magnitude of this intensity value is inversely proportional to the magnitude of the preload at that location. The two-dimensional image is then defined and stored as a reference preload distribution topology map.

[0063] See attached document Figure 4 After generating and storing the baseline preload distribution topology map, this method enters a periodic real-time monitoring phase to continuously track changes in the preload state of nodes.

[0064] In one specific embodiment, the data processing terminal automatically triggers a real-time monitoring process according to a preset time period (e.g., every hour). Within each monitoring period, the system first repeatedly executes the environmental perception and adaptive calibration steps described in Part Three. Specifically, during the intervals between actively emitting ultrasonic waves, the environmental noise fingerprint database is updated; and a calibration sound beam is emitted towards inert acoustic beacon particles at a predetermined location to calculate the calibration sound velocity in the current environment. .

[0065] In a preferred embodiment, the monitoring period is dynamically adjustable. For example, if no warning is triggered for several consecutive monitoring periods, the system can automatically extend the monitoring period (e.g., adjust it to once every four hours); when a level one or level two warning is triggered, the system automatically shortens the monitoring period (e.g., adjust it to once every ten minutes) to more intensively track changes in node status.

[0066] Subsequently, the data acquisition and control unit executes the same full-matrix data acquisition and scanning strategy as when the reference state was established, emitting ultrasonic waves to the friction surface through the phased array ultrasonic transducer array and receiving the second echo signal.

[0067] The second echo signal undergoes the same processing procedure as the first echo signal: first, adaptive filtering is performed using the updated environmental noise fingerprint database, and then the calculated calibration velocity is used... Time-domain compensation is performed to obtain a calibrated and filtered second echo signal matrix. .

[0068] The data processing terminal uses the same synthetic aperture focusing technology to reconstruct the image of the second echo signal matrix, generating a real-time preload distribution topology map. Intensity values ​​in its topological map It can be calculated using the following formula: ; in, This represents the total number of transducer array elements. For the first Each element is launched, after the first... The calibrated echo signal received by each array element This represents the time delay corresponding to the transmission path.

[0069] See attached document Figure 5 After generating a real-time preload distribution topology map, this method performs a difference analysis between it and a stored baseline preload distribution topology map to quantify preload changes and make early warning judgments. In one specific embodiment, the data processing terminal first executes an algorithm for generating a preload change difference map. The algorithm targets each spatial coordinate point on the friction surface. From the real-time preload distribution topology diagram and reference preload distribution topology diagram In the process, the intensity value of the corresponding pixel is obtained; then, the absolute value of the difference between the two intensity values ​​is calculated, and the calculation result is used as the coordinate point. Diagram showing the difference in preload variation The new pixel intensity value. Its calculation formula is: ; By performing the above operations on all pixels within the imaging area, a complete preload variation difference map is finally generated. The intensity value of each pixel in the difference map directly represents the magnitude of the change in preload at the corresponding physical location since its initial state. After generating the preload variation difference map, the data processing terminal then extracts its features to calculate two key feature indicators used for quantitative evaluation.

[0070] The first metric is the maximum pixel intensity change value. This represents the magnitude of preload relaxation at the point on the entire friction surface. It is calculated by iterating through all pixels in the preload variation map and finding the maximum intensity. ; in, Indicates the location The change in intensity at that location. Indicates all possible Find the maximum value among the coordinate points.

[0071] The second indicator is the area of ​​the region of significant change. This characterizes the region where preload significantly loosens. It is calculated by first setting a threshold value to define what constitutes a significant change. Then, the pixel intensity values ​​in the preload variation difference graph that exceed the attention threshold are statistically analyzed. The second indicator is the area of ​​the region of significant change. This characterizes the region where preload significantly loosens. It is calculated by first setting a threshold value to define what constitutes a significant change. Then, the pixel intensity values ​​in the preload variation difference graph that exceed the attention threshold are statistically analyzed. The total area covered by all pixels: ; in, Indicates to and Perform double integration. This defines the conditions for the integration region; only when the intensity change... Exceeding a certain threshold Only when this condition is met will it be included in the area calculation.

[0072] Finally, the data processing terminal calculates two quantitative characteristic indicators and preset multi-level early warning thresholds ( The system executes the warning determination logic. In one specific embodiment, the determination logic is as follows: If... If so, it is determined to be a Level 3 warning (danger); If the conditions for a Level III warning are not met, but are met or If so, it is determined to be a Level 2 warning. If the conditions for a Level II early warning are not met, but are met If so, it is classified as a Level 1 warning (attention). If none of the above conditions are met, it will be determined that there is no warning.

[0073] After the judgment is completed, the system will output information such as the warning level, the corresponding quantitative characteristic index value, and the preload change difference diagram to the monitoring center.

Claims

1. A method for real-time monitoring and early warning of anti-slippage performance of a steel structure joint, characterized in that, The method comprises the following steps: a pressure-sensitive acoustic impedance matching coating is arranged on the friction surface of the steel structure joint; when the steel structure joint is in the initial pre-tightening state, an ultrasonic transducer arranged outside the steel structure joint emits ultrasonic waves to the friction surface and receives first echo signals, and the first echo signals are processed to generate and store a baseline pre-tightening force distribution topology map; periodically, the ultrasonic transducer emits ultrasonic waves to the friction surface and receives second echo signals, and the second echo signals are processed to generate a real-time pre-tightening force distribution topology map; the real-time pre-tightening force distribution topology map is compared with the stored baseline pre-tightening force distribution topology map to identify pre-tightening force changes; based on the comparison result of the real-time pre-tightening force distribution topology map and the stored baseline pre-tightening force distribution topology map, a pre-warning signal is output when the pre-tightening force changes exceed a preset threshold.

2. The method according to claim 1, characterized in that, The preparation steps of the pressure-sensitive acoustic impedance matching coating comprise: pressure-sensitive microstructure units and inert acoustic beacon microparticles are uniformly doped in a base material; wherein the acoustic impedance of the pressure-sensitive microstructure units increases with the increase of the normal pressure, and the acoustic characteristics of the inert acoustic beacon microparticles are not sensitive to pressure and remain stable.

3. The method of claim 1, wherein the method comprises: The step of processing the first echo signals to generate the baseline pre-tightening force distribution topology map comprises adaptive calibration and environmental noise removal processing of the first echo signals, and then image reconstruction.

4. The method according to claim 3, characterized in that, The adaptive calibration processing step comprises emitting a calibration acoustic beam to the inert acoustic beacon microparticles at a predetermined position, calculating the acoustic velocity drift caused by environmental temperature changes according to the time-of-flight changes of the calibration acoustic beam echo signals, and performing time domain compensation on the first echo signals.

5. The method of claim 3, wherein the method further comprises: The environmental noise removal processing step comprises passively monitoring the structural response signals caused by environmental vibration during the intermittent period of emitting ultrasonic waves, establishing an environmental noise fingerprint library, and filtering the first echo signals using the environmental noise fingerprint library.

6. The method of claim 1, wherein the method comprises: Both the processing of the first echo signals and the processing of the second echo signals use synthetic aperture focusing technology to perform coherent superposition operation on the corresponding echo signals, reconstruct the acoustic reflection intensity corresponding to each point on the friction surface, and generate the real-time pre-tightening force distribution topology map and the stored baseline pre-tightening force distribution topology map.

7. The method of claim 1, wherein the method comprises: The step of comparing the real-time pre-tightening force distribution topology map with the baseline pre-tightening force distribution topology map comprises: for each spatial coordinate point on the friction surface, obtaining the intensity value of the corresponding pixel in the real-time pre-tightening force distribution topology map and the intensity value of the corresponding pixel in the baseline pre-tightening force distribution topology map; calculating the absolute value of the difference between the two intensity values as a difference intensity representing the pre-tightening force change amplitude; combining the difference intensities calculated for all spatial coordinate points into a new two-dimensional image, which is a pre-tightening force change difference map.

8. The method according to claim 7, characterized in that, The step of outputting the pre-warning signal is realized by extracting at least one quantitative feature index from the pre-tightening force change difference map and judging whether the quantitative feature index exceeds its corresponding pre-warning threshold.

9. The method according to claim 8, characterized in that, The quantification feature index comprises: a maximum pixel intensity change value in the pre-tightening force change difference map, and an area of a region in which the pixel intensity change value exceeds a preset attention threshold.

10. The method of claim 1, wherein the method comprises: The ultrasonic transducer is a phased array ultrasonic transducer array, and the step of emitting ultrasonic waves is achieved by sequentially exciting array elements in the array in an electronic manner for rapid scanning of the entire friction surface.

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