Steel structure testing method for steel structure factory building

Abstract

The invention discloses a steel structure test method for a steel structure plant, which comprises the following steps: S1, obtaining basic parameters of a to-be-tested steel structure, and building a test system based on stress wave propagation characteristics, the test system meeting a preset precision requirement; and S2, transmitting a stress wave signal to the to-be-tested steel structure through the test system, and collecting signal data in a stress wave propagation process in real time by using a sensor array. The invention relates to the technical field of steel structure detection. According to the steel structure testing method for the steel structure factory building, the stress wave signals are transmitted, multi-channel signal data are collected in real time, and denoising processing and a time difference positioning algorithm are combined, so that the damage position can be accurately determined, detailed three-dimensional positioning coordinates are provided, it is guaranteed that the positioning precision meets the actual requirement, and the accuracy of the steel structure factory building is improved. The attenuation coefficient and the reflection signal are analyzed based on the propagation characteristic of the stress wave, a scientific judgment basis is provided for different types of damage, and damage evaluation is effectively supported.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of steel structure detection, more particularly, to a steel structure testing method for steel structure workshop. BACKGROUND

[0002] With the increasing application of steel structure workshop in the construction industry, the safety of steel structure has become a crucial problem. Steel structure will be affected by various factors such as load, environmental corrosion, etc. during long-term use, which may cause problems such as fatigue damage and crack propagation of the structure. Traditional steel structure detection methods mostly rely on manual inspection, surface flaw detection and other means, which are time-consuming and prone to missed detection, and cannot accurately determine the damage location and extent.

[0003] At present, non-destructive testing technology based on stress wave propagation characteristics is widely used because it can monitor the health status of the structure in real time. By using stress wave signals such as acoustic waves and ultrasonic waves, internal cracks, cavities, corrosion and other damage in materials can be effectively identified. In the prior art, some methods emit stress waves and collect signals for analysis, but these methods still have room for improvement in terms of positioning accuracy, signal processing capability, and system adaptability.

[0004] Therefore, there is an urgent need for a more efficient, accurate and easy-to-implement steel structure testing method to improve the accuracy of steel structure damage detection and provide more scientific data support for the maintenance and repair of steel structure workshop. SUMMARY

[0005] The purpose of the present application is to provide a steel structure testing method for steel structure workshop, which solves the problem that traditional steel structure detection methods mostly rely on manual inspection, surface flaw detection and other means, which are time-consuming and prone to missed detection, and cannot accurately determine the damage location and extent. In the prior art, some methods emit stress waves and collect signals for analysis, but these methods still have room for improvement in terms of positioning accuracy, signal processing capability, and system adaptability, which cannot meet the use requirements.

[0006] The present application achieves the above-mentioned purpose by the following technical solution: a steel structure testing method for steel structure workshop, comprising the following steps: S1, obtaining the basic parameters of the steel structure to be tested, and building a test system based on the stress wave propagation characteristics, which meets the preset accuracy requirements; S2, emitting stress wave signals to the steel structure to be tested through the test system, and collecting signal data in the stress wave propagation process in real time using a sensor array; S3, preprocessing the collected signal data, and extracting stress wave velocity, propagation path and attenuation characteristic parameters; S4. Based on the aforementioned characteristic parameters, the damage location of the steel structure is calculated and determined according to the signal reflection law and time difference positioning algorithm. S5 outputs the damage location results and corresponding characteristic parameter analysis report to complete the steel structure test.

[0007] Furthermore, obtaining the basic parameters of the steel structure to be tested in S1 includes: Collect the material type, cross-sectional dimensions, installation location coordinates, and design parameters of the steel structure to be tested; The cross-sectional dimensions at least include the parameters of length, width, and thickness.

[0008] Furthermore, the construction of the test system in S1 includes: A scale-adapted three-dimensional model is established based on the parameters of the steel structure to be tested, and stress wave emitting devices and sensor arrays are arranged on the surface of the steel structure according to a preset layout. The sensor array includes at least four stress wave receiving sensors; The distance between the transmitting device and the adjacent sensor is determined based on the steel structure dimensions and the stress wave propagation distance threshold.

[0009] Furthermore, the construction of the testing system also includes: The stress wave emission intensity, frequency parameters, and signal acquisition sensitivity of the sensor array of the calibrating device are assessed.

[0010] Furthermore, the transmitted stress wave signal in S2 includes: A pre-defined type of stress wave signal is directionally emitted toward the steel structure to be tested using a transmitting device; The transmission frequency range is adapted to the stress wave propagation characteristics of steel structures; The transmission frequency stability error is controlled within a preset threshold.

[0011] Furthermore, the signal data acquired in S2 includes: The sensor array acquires signals in a synchronous trigger mode, and the sampling rate and timestamp recording accuracy are set to meet the signal capture requirements; A clock synchronization protocol is used to ensure that the signal acquisition synchronization error between different sensors meets the requirements. Simultaneously record the amplitude and phase parameters of the signal received by each sensor; Continuously collect signal data for a preset duration to form a multi-channel stress wave signal dataset; Noise suppression processing is performed to ensure the signal-to-noise ratio.

[0012] Furthermore, the signal data preprocessing in S3 includes: A preset denoising algorithm is used to denoise the multi-channel signal data, and the amplitude distortion of the denoised signal is controlled within a preset range. The denoising algorithm includes a wavelet threshold denoising algorithm.

[0013] Furthermore, the extraction of feature parameters in S3 includes: Based on the denoised signal data, the average propagation velocity of stress waves in steel structures is calculated, and the signal amplitude attenuation law is analyzed to obtain the average attenuation coefficient. By combining the three-dimensional model, the propagation path of stress waves is traced through the signal propagation time difference and phase change, and the path nodes corresponding to abnormal reflection signals are marked to ensure that the path identification accuracy meets the preset standard.

[0014] Furthermore, determining the location of the damage in S4 includes: Set an attenuation coefficient threshold and determine the damage reflection signal based on phase abrupt changes; Extract the time when each sensor receives the damage reflection signal and calculate the time difference between the sensors; A time-difference positioning equation set was established based on sensor calibration coordinates and stress wave propagation laws. The equation set was solved using numerical methods, and the three-dimensional coordinates of the damage location were obtained by combining the stress wave propagation path constraints. The positioning accuracy met the preset requirements.

[0015] Furthermore, the analysis report output in S5 includes: The damage location coordinates are mapped to the three-dimensional model of the steel structure, and the damage type is determined by combining the attenuation coefficient and the duration of the reflected signal. The damage type includes at least microcracks, corrosion, and loosening of the connection. Generate a test report that includes steel structure foundation parameters, test system configuration and accuracy calibration records, characteristic parameter analysis results, damage location information, and damage assessment conclusions; If multiple damages are detected, the results are sorted and output according to a preset damage severity coefficient to provide a reference for steel structure maintenance.

[0016] The beneficial effects of this invention are as follows: 1. By transmitting stress wave signals and acquiring multi-channel signal data in real time, combined with noise reduction processing and time difference positioning algorithms, the damage location can be accurately determined and detailed three-dimensional positioning coordinates can be provided to ensure that the positioning accuracy meets the actual needs.

[0017] 2. In addition to locating damage during the testing process, it can also analyze the attenuation coefficient and reflection signal based on the propagation characteristics of stress waves, providing a scientific basis for judging different types of damage, such as cracks, corrosion, and loosening, and effectively supporting damage assessment.

[0018] 3. The testing system, by establishing a three-dimensional model that matches the parameters of the steel structure, can adapt to steel structure workshops of different sizes, materials and structural forms, and has strong versatility and flexibility.

[0019] 4. The collected signal data is preprocessed to generate damage location results and characteristic parameter analysis reports, which can not only effectively provide damage information, but also provide important reference for subsequent steel structure maintenance decisions, and has high practical value.

[0020] 5. By using synchronous triggering mode and clock synchronization protocol, the synchronization of sensor array signals and data accuracy are guaranteed, which significantly improves the efficiency of steel structure testing and reduces manual intervention and errors. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Fig. 1 This is a flowchart illustrating the overall method of the present invention; Fig. 2 A flowchart illustrating the setup of the testing system for this invention; Fig. 3 This is a flowchart of the damage localization algorithm of the present invention. Detailed Implementation

[0022] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0023] Example 1: Please see Figs. 1-3 This invention provides a technical solution: a steel structure testing method for steel structure workshops, the method comprising: S1. Obtain the basic parameters of the steel structure to be tested in the steel structure workshop, and build a test system based on the stress wave propagation characteristics. The test system must meet the preset accuracy requirements. Among them, steel structure workshops are factory buildings with steel beams, steel columns, and other steel structural components as the main load-bearing structures, used for industrial production, warehousing, and other functions; the steel structure to be tested is the specific steel structural part of the steel structure workshop that needs to be tested and evaluated for its performance and condition, which may be a steel beam, steel column, or a structural node; basic parameters are the basic data information related to the steel structure to be tested, such as the dimensions, materials, connection methods, and environmental information of the steel structure, which provide the basis for subsequent testing and analysis; stress wave propagation characteristics are the characteristics exhibited by stress waves when propagating in steel structural materials, including wave velocity, propagation path, attenuation law, etc., and these characteristics are used to test steel structures using stress waves. Key theoretical foundations: The testing system is a complete device or system built to perform stress wave propagation characteristic testing on the steel structure under test. It includes equipment capable of emitting stress wave signals, sensors for acquiring signals, and software for data processing and analysis. Furthermore, the system needs to meet preset accuracy requirements to ensure the accuracy and reliability of the test results. These preset accuracy requirements are pre-set requirements for various performance indicators of the testing system based on the specific needs and standards of steel structure testing before the system is built. Examples include the accuracy of signal acquisition, the accuracy of data processing and analysis, and the accuracy of damage localization. Only by meeting these accuracy requirements can the testing system effectively complete the testing task. S2. Stress wave signals are emitted to the steel structure under test through the testing system, and signal data during the propagation of stress waves are collected in real time using a sensor array; Among them, stress wave signals are mechanical wave signals excited in the steel structure under test by specific equipment. This signal can propagate inside the steel structure, and when it encounters defects or boundaries inside the steel structure, it will undergo reflection, refraction, and other phenomena. By analyzing these signal changes, information about the internal structure of the steel structure can be obtained. The sensor array is an array structure composed of multiple sensors arranged in a certain way. In steel structure testing, the sensor array is used to collect signal data of stress waves in real time during propagation. Multiple sensors can collect signals from different positions and angles, improving the comprehensiveness and accuracy of signal acquisition, and providing rich information for subsequent data processing and analysis. S3. Preprocess the collected signal data to extract stress wave velocity, propagation path and attenuation characteristic parameters; Signal data preprocessing involves a series of processing operations on the acquired raw stress wave signal data. The aim is to remove noise interference and improve signal quality, enabling more accurate extraction of useful feature parameters. Stress wave velocity is the speed at which stress waves propagate within a steel structure. It is a crucial parameter for stress wave propagation characteristics. Different steel materials, structural forms, and stress states all affect the propagation speed. Measuring stress wave velocity allows us to understand the mechanical properties and internal state of the steel structure. The propagation path is the route taken by the stress wave within the steel structure. Understanding the propagation path is essential for analyzing the location of defects and structural characteristics within the steel structure. When stress waves encounter defects, reflection and refraction occur, altering the propagation path. Analyzing these changes allows us to infer the internal conditions of the steel structure. Attenuation characteristic parameters describe the gradual weakening of stress wave energy during propagation. Stress waves gradually lose energy due to internal friction and scattering within the material. Analyzing these attenuation characteristic parameters reveals the material uniformity and internal defect conditions of the steel structure, as defects alter the degree of stress wave attenuation. S4. Combining characteristic parameters, based on signal reflection patterns and time difference positioning algorithms, calculate and accurately determine the damage location of the steel structure; Among them, the signal reflection law is the law governing the reflection phenomenon of stress waves when they encounter defects or boundaries during propagation in steel structures. Different defect types (such as cracks, holes, etc.), defect sizes and shapes, and boundary conditions of the steel structure all affect the stress wave reflection law. For example, the amplitude, phase, and propagation direction of the reflected wave will change. By studying the signal reflection law, a correspondence between the reflected signal and the internal defects of the steel structure can be established. The time difference positioning algorithm is an algorithm that uses the time difference of signal propagation to determine the target location, i.e., the damage location in steel structure testing. By measuring the time difference of the stress wave from the emission point to different sensors in the sensor array, combined with the known stress wave velocity and the geometric information of the steel structure, the specific coordinates of the damage location in the steel structure can be calculated using specific mathematical models and calculation methods, thereby achieving precise positioning. S5. Output the damage location results and corresponding characteristic parameter analysis report to complete the steel structure test; The damage location result is the specific location information of internal damage in the steel structure determined through the above testing and analysis process. It is usually expressed in coordinate form, clearly indicating the location of the damage in the steel structure, providing an accurate basis for subsequent steel structure repair, reinforcement and other treatment measures. The characteristic parameter analysis report is a report that analyzes and summarizes in detail the stress wave velocity, propagation path and attenuation characteristic parameters extracted after preprocessing the collected signal data. The report will explain the relationship between these characteristic parameters and the performance of the steel structure and internal defects. By analyzing the changes in these characteristic parameters, the health status of the steel structure can be judged, such as whether there is damage and the degree of damage, providing a scientific basis for the quality assessment and safety monitoring of the steel structure.

[0024] It should be noted that, during use, acquiring basic parameters and building a testing system that meets the preset accuracy requirements provides an accurate foundation for subsequent testing, ensuring reliable test results. Emitting stress wave signals and using a sensor array to collect data in real time comprehensively captures stress wave propagation information, reflecting the steel structure's condition from multiple dimensions. Preprocessing the signal data and extracting key feature parameters removes interference, accurately grasps the stress wave propagation characteristics, and provides an effective basis for damage location. Combining feature parameters with signal reflection patterns and time-difference positioning algorithms, the damage location is determined with high accuracy, quickly identifying potential steel structure hazards. Damage location results and analysis reports are output, providing both a visual presentation of the damage and in-depth analysis of the steel structure's performance. This provides scientific support for subsequent maintenance and reinforcement decisions, helping to ensure the safe and stable operation of steel structure workshops and reduce safety risks and maintenance costs.

[0025] In one embodiment, the basic parameters of the steel structure to be tested in the steel structure workshop are obtained, and a testing system based on stress wave propagation characteristics is built, including: Obtain the material type, cross-sectional dimensions, installation location coordinates, and design working condition parameters of the steel structure to be tested, and establish a 1:1 scale 3D model of the steel structure with a model coordinate error not exceeding ±0.3mm; The cross-sectional dimensions include: length ,width ,thickness Measurement accuracy ±0.1mm; Based on a 3D model, stress wave emitting devices and sensor arrays are arranged in a uniform grid layout on the surface of a steel structure. The sensor array consists of... indivual The stress wave receiving sensor consists of [components], and the distance between the transmitting device and adjacent sensors is [details]. satisfy The spacing is determined based on the steel structure dimensions and the stress wave propagation distance threshold. Determined, that is ; The stress wave emission intensity of the calibrated transmitter is rated. The frequency parameters and the signal acquisition sensitivity of the sensor array, after calibration, must meet the following requirements: Stress wave signal transmission frequency error , Sensor signal acquisition time synchronization accuracy , Signal amplitude measurement error ; Set the overall positioning accuracy threshold of the test system Through multiple standard test block calibration experiments, it was verified that the final damage location error meets the threshold requirement, thus meeting the needs of detecting minor defects in steel structures.

[0026] This design allows for the acquisition of key basic parameters of the steel structure under test and the creation of a 1:1 3D model, ensuring model accuracy. The transmitting device and sensor array are arranged on the steel structure surface using a uniform grid, with appropriately determined spacing. The parameters of the transmitting device and sensor array are rigorously calibrated, and a comprehensive positioning accuracy threshold is set and verified through calibration experiments. The accurate 3D model provides a solid foundation for subsequent analysis. The rational layout of the devices and arrays enables comprehensive capture of stress wave information. Rigorous calibration ensures stable performance and meets accuracy standards for the testing system, enabling precise adaptation to the detection of minute defects in steel structures. This lays a solid foundation for accurate analysis of damage location and type, improving the reliability of test results.

[0027] In one embodiment, a stress wave signal is emitted to the steel structure under test through a testing system, and signal data during the propagation of the stress wave is acquired in real time using a sensor array, including: A continuous sinusoidal stress wave signal is directionally emitted towards the steel structure under test using a transmitting device, with the transmission frequency range set to [specify frequency range]. Transmission frequency stability error , The actual transmission frequency at any given time is adapted to the stress wave propagation characteristics of steel structures. The sensor array acquires signals in a synchronous trigger mode, with a sampling rate of [missing information]. timestamp recording precision A clock synchronization protocol is used to ensure the synchronization error of signal acquisition between different sensors. Simultaneously, the amplitude of the signal received by each sensor is recorded. and phase ,in, , ; Continuous data collection for a preset duration The signal data forms The channel stress wave signal dataset undergoes noise suppression processing to ensure a high signal-to-noise ratio. ,

[0028] in, For effective signal power, This represents noise power.

[0029] This design allows the transmitting device to directionally emit stable, continuous sinusoidal stress wave signals within a specific frequency range. The sensor array acquires data in a synchronous trigger mode, ensuring sampling rate, timestamp accuracy, and acquisition synchronization error, while recording amplitude and phase. Continuous acquisition of signals for a certain duration forms a dataset, and noise suppression processing ensures a high signal-to-noise ratio. This design adapts to the characteristics of steel structures, enabling precise signal transmission and acquisition, and obtaining high-quality signal data. Continuous acquisition and noise suppression prevent signal loss and interference, ensuring data integrity and accuracy. This provides reliable data support for subsequent accurate extraction of feature parameters, improving the accuracy of test analysis.

[0030] In one embodiment, the acquired signal data is preprocessed to extract stress wave velocity, propagation path, and attenuation characteristic parameters, including: Wavelet thresholding denoising algorithm was used to process multi-channel signal data, selecting the db4 wavelet basis, setting the decomposition level to 3 levels, and setting the threshold... ,in, The standard deviation of noise. The number of signal sampling points. Amplitude distortion of the denoised signal: ;

[0031] Based on the denoised signal data, the rising edge trigger time of the direct signal is extracted. ,in Based on the launch device start time Using this as a reference, calculate the direct propagation time of the signal: ,

[0032] Combined with the launch device and the Linear distance of each sensor Measurement error According to the formula: ,

[0033] Calculate the average propagation velocity of stress waves in steel structures. ,in Measurement error Wave velocity calculation error ; Analyze the signal amplitude attenuation law and select the signal amplitude at the transmitting end. and distance from the transmitter Signal amplitude at ,in, Measurement error According to the formula: ,

[0034] Calculate the average attenuation coefficient Attenuation coefficient calculation error ; By combining a 3D model of the steel structure, the propagation path of stress waves is traced through signal propagation time difference and phase change, and path nodes corresponding to abnormal reflection signals are marked. The path identification accuracy is: .

[0035] This design employs a wavelet threshold denoising algorithm to process multi-channel signal data, controlling the amplitude distortion of the denoised signal. Based on the denoised signal, it extracts the trigger time of the rising edge of the direct signal, calculates the propagation time and average wave velocity, and controls the error. It analyzes the amplitude attenuation law to calculate the average attenuation coefficient and error. Combined with the model, it traces the propagation path and marks abnormal nodes, ensuring accurate path identification and effectively removing noise while reducing signal distortion. Accurate calculation of wave velocity and attenuation coefficient provides key parameters for damage assessment. Precise tracing of the propagation path enables timely detection of internal anomalies in the steel structure, helping to accurately determine the location and type of damage and improve testing accuracy.

[0036] In one embodiment, by combining characteristic parameters and based on signal reflection patterns and time-difference positioning algorithms, the damage location of the steel structure is calculated and accurately determined, including: Set attenuation coefficient threshold (Based on the steel structure material, such as Q235 steel) When detected And phase abrupt change When the signal is identified as a damage reflection signal, the signal recognition accuracy is: ; Extracting damage reflection signals at the first The receiving time of each sensor Calculate the time difference with the first sensor. Time difference measurement accuracy ; Let the first sensor in the sensor array be... The calibration coordinates of each sensor are Among them, the installation coordinate calibration error all The coordinates of the damage location are , Based on the relationship between stress wave propagation distance, wave velocity, and time, a set of time-difference positioning equations is established: ,

[0037] in, The time difference is the initial time of stress wave emission. ; Solve the system of equations using the least squares method and construct the objective function: ,

[0038] Using the gradient descent method, find Minimum value corresponding to By combining the stress wave propagation path constraint (the path must be within the steel structure entity), the three-dimensional coordinates of the damage location are obtained, and the positioning accuracy error is: ,in, , refers to the measured coordinate value in the X-axis direction of the three-dimensional coordinate system, which is collected by the sensor array of the test system to characterize the location of damage to the steel structure, and the unit is millimeters (mm). , refers to the actual coordinate value of the location of the damage to the steel structure in the X-axis direction in the three-dimensional coordinate system, in millimeters (mm). , refers to the measured coordinate value in the Y-axis direction of the three-dimensional coordinate system, which is collected by the sensor array of the test system to characterize the location of damage to the steel structure, and the unit is millimeters (mm). , refers to the actual coordinate value of the location of the damage to the steel structure in the Y-axis direction in the three-dimensional coordinate system, in millimeters (mm). , refers to the measured coordinate value in the Z-axis direction of the three-dimensional coordinate system, which is collected by the sensor array of the test system to characterize the location of damage to the steel structure, and the unit is millimeters (mm). , refers to the actual coordinate value of the steel structure's damage location in the Z-axis direction of the three-dimensional coordinate system, in millimeters (mm); it meets the preset comprehensive positioning accuracy requirements of the testing system.

[0039] This design sets attenuation coefficient thresholds and phase change conditions to determine damage reflection signals and ensure signal recognition accuracy; it extracts the reception time of damage reflection signals to calculate the time difference; it establishes a time difference positioning equation set based on sensor calibration coordinates and stress wave relationships; it uses the least squares method to solve the equations and combines them with propagation path constraints to obtain the three-dimensional coordinates of the damage location, controlling positioning accuracy errors, accurately identifying damage signals, and providing a reliable basis for positioning; through precise calculation and reasonable algorithm solutions, combined with path constraints, it can accurately determine the damage location, meet preset accuracy requirements, provide accurate location information for steel structure maintenance, and ensure the safety of steel structures.

[0040] In one embodiment, the damage location results and corresponding characteristic parameter analysis report are output to complete the steel structure test, including: Damage location coordinates Mapped to the 3D model of the steel structure, based on the attenuation coefficient and duration of reflected signal Determine the type of damage: when and At that time, it was determined to be a minor crack; when and At that time, it was determined to be corrosion; when and When the connection is deemed loose, the accuracy of damage type identification is as follows: ; Generate a test report, including steel structure foundation parameters, test system configuration and accuracy calibration records, characteristic parameter analysis results, and damage location coordinates. The solution process and damage assessment conclusions; Among them, the accuracy calibration record includes calibration data such as transmission frequency and synchronization accuracy; Feature parameter analysis results include The calculation process and Error explanation; If multiple injuries are detected, they are classified according to the severity coefficient: ,

[0041] Sort the output. The larger the value, the higher the priority, providing a reference for steel structure maintenance. The report must clearly indicate whether the test results meet the preset accuracy requirements.

[0042] This design maps the coordinates of the damage location to a 3D model, determines the damage type based on the attenuation coefficient and the duration of the reflected signal, and ensures accurate identification. It generates a test report containing multiple aspects; it sorts and outputs multiple damages according to their severity coefficients, intuitively presenting the damage location and accurately determining the damage type, facilitating targeted treatment; the detailed test report provides a comprehensive basis for assessing the condition of the steel structure; and the sorting and outputting of multiple damages allows for prioritizing the treatment of severe damage, providing a scientific and reasonable reference for steel structure maintenance, and improving maintenance efficiency and quality.

[0043] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0044] The above embodiments provide a detailed description of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for testing steel structures in steel structure workshops, characterized in that, Includes the following steps: S1. Obtain the basic parameters of the steel structure to be tested, and build a test system based on the stress wave propagation characteristics. The test system meets the preset accuracy requirements. S2. The test system emits stress wave signals to the steel structure under test and uses a sensor array to collect signal data in real time during the propagation of the stress wave. S3. Preprocess the collected signal data to extract stress wave velocity, propagation path and attenuation characteristic parameters; S4. Based on the aforementioned characteristic parameters, the damage location of the steel structure is calculated and determined according to the signal reflection law and time difference positioning algorithm. S5 outputs the damage location results and corresponding characteristic parameter analysis report to complete the steel structure test.

2. The steel structure testing method for steel structure workshops according to claim 1, characterized in that, The basic parameters for obtaining the steel structure to be tested in S1 include: Collect the material type, cross-sectional dimensions, installation location coordinates, and design parameters of the steel structure to be tested; The cross-sectional dimensions at least include the parameters of length, width, and thickness.

3. The steel structure testing method for steel structure workshops according to claim 2, characterized in that, The test system built in S1 includes: A scale-adapted three-dimensional model is established based on the parameters of the steel structure to be tested, and stress wave emitting devices and sensor arrays are arranged on the surface of the steel structure according to a preset layout. The sensor array includes at least four stress wave receiving sensors; The distance between the transmitting device and the adjacent sensor is determined based on the steel structure dimensions and the stress wave propagation distance threshold.

4. The steel structure testing method for steel structure workshops according to claim 3, characterized in that, The construction of the testing system also includes: The stress wave emission intensity, frequency parameters, and signal acquisition sensitivity of the sensor array of the calibrating device are assessed.

5. The steel structure testing method for steel structure workshops according to claim 1, characterized in that, The transmitted stress wave signal in S2 includes: A pre-defined type of stress wave signal is directionally emitted toward the steel structure to be tested using a transmitting device; The transmission frequency range is adapted to the stress wave propagation characteristics of steel structures; The transmission frequency stability error is controlled within a preset threshold.

6. The steel structure testing method for steel structure workshops according to claim 5, characterized in that, The signal data collected in S2 includes: The sensor array acquires signals in a synchronous trigger mode, and the sampling rate and timestamp recording accuracy are set to meet the signal capture requirements; A clock synchronization protocol is used to ensure that the signal acquisition synchronization error between different sensors meets the requirements. Simultaneously record the amplitude and phase parameters of the signal received by each sensor; Continuously collect signal data for a preset duration to form a multi-channel stress wave signal dataset; Noise suppression processing is performed to ensure the signal-to-noise ratio.

7. The steel structure testing method for steel structure workshops according to claim 1, characterized in that, The signal data preprocessing in S3 includes: A preset denoising algorithm is used to denoise the multi-channel signal data, and the amplitude distortion of the denoised signal is controlled within a preset range. The denoising algorithm includes a wavelet threshold denoising algorithm.

8. The steel structure testing method for steel structure workshops according to claim 7, characterized in that, The feature parameters extracted in S3 include: Based on the denoised signal data, the average propagation velocity of stress waves in steel structures is calculated, and the signal amplitude attenuation law is analyzed to obtain the average attenuation coefficient. By combining the three-dimensional model, the propagation path of stress waves is traced through the signal propagation time difference and phase change, and the path nodes corresponding to abnormal reflection signals are marked to ensure that the path identification accuracy meets the preset standard.

9. The steel structure testing method for steel structure workshops according to claim 1, characterized in that, Determining the location of damage in step S4 includes: Set an attenuation coefficient threshold and determine the damage reflection signal based on phase abrupt changes; Extract the time when each sensor receives the damage reflection signal and calculate the time difference between the sensors; A time-difference positioning equation set was established based on sensor calibration coordinates and stress wave propagation laws. The equation set was solved using numerical methods, and the three-dimensional coordinates of the damage location were obtained by combining the stress wave propagation path constraints. The positioning accuracy met the preset requirements.

10. The steel structure testing method for steel structure workshops according to claim 1, characterized in that, The output analysis report in S5 includes: The damage location coordinates are mapped to the three-dimensional model of the steel structure, and the damage type is determined by combining the attenuation coefficient and the duration of the reflected signal. The damage type includes at least microcracks, corrosion, and loosening of the connection. Generate a test report that includes steel structure foundation parameters, test system configuration and accuracy calibration records, characteristic parameter analysis results, damage location information, and damage assessment conclusions; If multiple damages are detected, the results are sorted and output according to a preset damage severity coefficient to provide a reference for steel structure maintenance.

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