System and method for dynamically detecting cracks of prefabricated box girder

Abstract

The invention belongs to the technical field of prefabricated box girder crack detection, and particularly relates to a prefabricated box girder crack dynamic detection system and a prefabricated box girder crack dynamic detection method. The crack initiation position is efficiently identified from a single-source spectral image by utilizing spectral reflectivity difference, so that the crack detection efficiency is remarkably improved, and meanwhile, crack information and stress data are subjected to correlation analysis to determine a critical stress distribution state causing crack initiation, so that effective prediction of potential cracks is realized, and the accuracy of crack detection is improved. And meanwhile, after the crack is initiated, the crack propagation speed and the crack propagation direction are continuously monitored, so that the real-time tracking of the crack dynamic evolution process is realized, and targeted crack propagation response measures are taken by utilizing the risk orientation obtained by performing risk assessment in combination with a crack propagation monitoring result, so that the further propagation of the crack can be effectively prevented.

Description

Technical Field

[0001] The present invention belongs to the technical field of crack detection for precast box girders, and particularly relates to a dynamic crack detection system and method for precast box girders. Background Art

[0002] Precast box girders are a type of structural component widely used in bridge construction. By precasting concrete box girders in a factory or a specific area on site and then transporting and installing them at the bridge location, building bridges in this way not only improves the quality control level but also significantly shortens the on-site construction time and reduces the impact on the environment.

[0003] However, bridges are subjected to dynamic forces such as vehicle loads, wind loads, and earthquakes during long-term use, which are prone to cause fatigue damage. Cracks are usually the early manifestations of such damage. In particular, multiple joints formed by assembling precast box girders to form a bridge increase the risk of crack generation due to geometric discontinuity and stress concentration phenomena. Once cracks occur in the precast box girders, which are the main load-bearing structures of the bridge, their load-bearing capacity may be reduced, endangering the overall stability of the bridge. Therefore, crack detection of precast box girders is a key measure to ensure the safety and durability of bridges.

[0004] In the prior art, there are already some technical solutions for crack detection of precast box girders. For example, a steel box girder fatigue crack multi-source heterogeneous information fusion detection device and method proposed in a Chinese invention patent with the publication number CN119715765A can simultaneously carry out electromagnetic, eddy current thermography, and optical image quantitative detection and evaluation of fatigue cracks on the surface of a steel box girder in a specific area during one detection, completely reflecting the fatigue crack distribution of the scanning path, and realizing efficient and non-destructive detection and evaluation of fatigue cracks in the bridge steel box girder.

[0005] Although this solution demonstrates the advantages of detecting surface cracks of box girders by using the multi-source data fusion method through the fusion of electromagnetic two-dimensional images, infrared, and visible light imaging results, in order to ensure that data from different sources can accurately complement each other rather than produce misleading results, highly complex algorithms are required to support the fusion and analysis of multi-source heterogeneous data. This complexity not only increases the complexity of the system and the computational burden but also limits its real-time dynamic monitoring ability, making it more suitable for one-time or periodic static detection. For precast box girders, dynamic response monitoring under actual operating conditions is crucial. When the bridge is subjected to dynamic forces such as vehicle loads, wind loads, and earthquakes, it may cause crack propagation or the formation of new cracks. Relying solely on static detection cannot capture these dynamic changes, which may lead to the neglect of key problems and thus affect the overall safety and durability of the bridge.

[0006] In addition, this solution mainly focuses on crack detection while ignoring the stress conditions that cause cracks. Simply conducting crack detection without considering the stress factors that cause cracks not only makes it difficult to predict new cracks that may appear in the future, but also may lead to the formulated maintenance measures lacking pertinence, being unable to effectively prevent the further expansion of cracks, ultimately losing the opportunity to take preventive maintenance measures in advance, and increasing the risk of structural failure. Summary of the Invention

[0007] The present invention aims to overcome the deficiencies in the prior art and proposes a dynamic crack detection system and method for precast box girders. By using synchronous correlation detection of multispectral imaging and stress sensors within the detection area demarcated at the connection positions of precast box girders, dynamic and correlative detection of cracks from early initiation to expansion is achieved.

[0008] The object of the present invention can be achieved through the following technical solutions: In the first aspect of the present invention, a dynamic crack detection system for precast box girders is provided, including the following modules: Detection point layout module: Demarcate a detection area centered on the connection position of the precast box girder, and layout detection points through grid division. At the same time, configure stress sensors for each detection point.

[0009] Stress dynamic acquisition module: Dynamically acquire the stress data of each detection point during the operation of the precast box girder according to environmental fluctuations, and generate a stress distribution map under the time series by associating the position information of the detection points.

[0010] Crack initiation identification module: Select a specific wavelength band for distinguishing cracks based on the spectral reflectance difference, and use multispectral imaging to synchronously collect the spectral images of the detection area, and identify the crack initiation positions within the detection area from them.

[0011] Critical stress analysis module: Establish the correlation between the crack initiation positions and the stress distribution map, and predict the critical stress distribution state that causes crack initiation through statistical analysis.

[0012] Crack propagation monitoring module: Continuously monitor the crack propagation direction and crack propagation speed after crack initiation.

[0013] Risk assessment response module: Conduct itemized risk assessment according to the crack propagation speed and crack propagation direction, and output the risk indication. At the same time, dynamically adjust the stress distribution at the connection position of the precast box girder according to the response strategy matching the risk indication.

[0014] In the second aspect of the present invention, a dynamic crack detection method for precast box girders is proposed, including the following steps: S1: Demarcate a detection area centered on the connection position of the precast box girder, and layout detection points through grid division. At the same time, configure stress sensors for each detection point.

[0015] S2: During the operation of the precast box girder, stress data of each detection point are dynamically collected according to environmental fluctuations, and stress distribution maps under time series are generated by associating the position information of the detection points.

[0016] S3: Based on the spectral reflectance difference, specific bands for distinguishing cracks are selected, and spectral images of the detection area are synchronously collected using multi-spectral cameras to identify the crack initiation positions within the detection area.

[0017] S4: Establish the correlation between the crack initiation positions and the stress distribution maps, and predict the critical stress distribution state causing crack initiation through statistical analysis.

[0018] S5: Continuously monitor the crack propagation direction and crack propagation speed after crack initiation.

[0019] S6: Conduct sub-item risk assessments based on the crack propagation speed and crack propagation direction, and output risk pointers.

[0020] S7: Dynamically adjust the stress distribution at the connection position of the precast box girder according to the response strategy matching the risk pointer.

[0021] Combining all the above technical solutions, the positive effects of the present invention are as follows: 1. The present invention implements multi-point stress collection within the detection area at the connection position of the precast box girder, and synchronously collects spectral images. The crack initiation positions are efficiently identified from single-source spectral images using spectral reflectance differences, thus significantly improving the crack detection efficiency. At the same time, the crack information and stress data are correlated and analyzed to determine the critical stress distribution state causing crack initiation, realizing the effective prediction of potential cracks and providing a crucial opportunity for taking preventive maintenance measures.

[0022] 2. After crack initiation, the present invention realizes the real-time tracking of the dynamic evolution process of cracks by continuously monitoring the crack propagation speed and crack propagation direction, and takes targeted crack propagation response measures using the risk pointers obtained from the risk assessment combined with the crack propagation monitoring results. This not only improves the understanding and prediction ability of crack propagation behavior but also enables the timely and accurate implementation of maintenance and repair strategies, thereby effectively preventing further crack propagation. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention is further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to the following drawings without creative efforts.

[0024] Figure 1 It is a schematic diagram of the module connection of a precast box girder crack dynamic detection system provided in Embodiment 1 of the present invention.

[0025] Figure 2This is the operation flow chart for dynamically collecting stress data at each detection point according to environmental fluctuations during the operation of precast box girders in the present invention.

[0026] Figure 3 This is the step diagram of a method for dynamically detecting cracks in precast box girders provided in Embodiment 2 of the present invention. Specific embodiments

[0027] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0028] Embodiment 1

[0029] See Figure 1 As shown, the present invention provides a dynamic crack detection system for precast box girders, including a detection point layout module, a stress dynamic acquisition module connected to the detection point layout module, a crack initiation identification module connected to the stress dynamic acquisition module, a critical stress analysis module connected to the crack initiation identification module, a crack propagation monitoring module connected to the critical stress analysis module, and a risk assessment response module connected to the crack propagation monitoring module.

[0030] During the process of using precast box girders to build bridges, precast box girders usually need to be connected to piers, abutments, and other structural components such as cross beams and longitudinal beams. Due to their special connection methods, material compatibility, construction techniques, and other factors, these connection positions often become weak links in the structure and are prone to cracks and fissures. Therefore, the detection of cracks in precast box girders in the present invention mainly focuses on these connection positions.

[0031] The detection point layout module is used to demarcate a detection area centered on the connection position of the precast box girder, and layout detection points by grid division, and at the same time configure stress sensors for each detection point.

[0032] The specific implementation process of the above module is as follows: Identify each connection position according to the construction drawings of the precast box girder, and determine the symmetry axis of these positions, and extend a preset distance to both sides centered on the symmetry axis to form a detection area.

[0033] Preferably, the above connection positions include but are not limited to the connection points between the precast box girder and the pier, abutment, or other structural components.

[0034] It should be noted that the above method of extending a preset distance from the symmetric axis to both sides to form a detection area takes into account the stress diffusion effect that may occur in actual engineering. This method not only covers the parts directly bearing the load, but also includes the surrounding areas that may be indirectly affected, thus providing a more comprehensive monitoring perspective.

[0035] The determination of the above preset distance can be based on the material properties and connection methods at the connection position, because different materials have different mechanical properties and stress transfer characteristics. For example, the stress diffusion range of concrete is usually relatively wide, while the stress concentration phenomenon of steel is more obvious; different connection methods have different effects on the local stress distribution. For example, welded connections may result in obvious heat affected zones, thus expanding the potential crack propagation range. When specifically determining the preset distance, the common range of crack initiation can be analyzed based on the case data of similar projects as a reference, or it can also be determined according to the recommended detection area range in the bridge design specifications or relevant industry standards.

[0036] Determine the effective coverage range of stress monitoring according to the technical specifications of the stress sensor.

[0037] In particular, the above-mentioned technical specification is the sensing range. The sensing range refers to the maximum spatial range within which the sensor can effectively and accurately measure stress changes. Determining the effective coverage range of stress monitoring according to the sensing range of the stress sensor can ensure that the sensor can provide stable and reliable stress data within its sensing range.

[0038] Divide the detection area into several equally spaced grids according to the effective coverage range of stress monitoring, and arrange a detection point at the center point of each grid.

[0039] In the above, the side length of each grid should not exceed the maximum value of the effective coverage range, so that the area range of each grid meets the effective coverage range of stress monitoring, which can avoid excessive overlap between adjacent sensors or the occurrence of monitoring blind spots, thus ensuring that the stress information in the entire detection area is comprehensively covered. In addition, arranging detection points at the center points of the grids can maximize the use of the sensing range of the sensor, while reducing data redundancy and improving monitoring efficiency.

[0040] The stress dynamic acquisition module is used to dynamically acquire the stress data of each detection point according to environmental fluctuations during the operation of the precast box girder, and generate a stress distribution map under the time series by associating the position information of the detection points.

[0041] In the ways that the above scheme can be realized, please refer to Figure 2As shown, dynamically collecting stress data at each detection point according to environmental fluctuations includes the following: During the operation of precast box girders, stress sensors are used to collect stress data at each detection point with an initial collection frequency, and at the same time, the environmental data at the connection positions is continuously monitored.

[0042] It should be noted that the initial collection frequency mentioned above is pre-set manually.

[0043] In an exemplary embodiment, the environmental data includes temperature, humidity, and vibration intensity.

[0044] It should be noted that it is crucial to monitor environmental data while collecting stress data at detection points in the precast box girder structure, because environmental factors such as temperature changes, humidity, and vibration intensity will all have a significant impact on the stress state of the material, thereby changing the stress distribution.

[0045] Specifically, temperature changes will cause the phenomenon of thermal expansion and contraction of materials. The materials expand under high-temperature conditions and contract under low-temperature conditions. This volume change will generate additional stress inside the structure, which is more obvious especially at the connection positions and areas with stronger constraints.

[0046] Humidity changes will affect the physical properties of materials. Especially in concrete structures, an increase in humidity may cause water intrusion, resulting in material expansion or contraction, further changing the stress distribution.

[0047] In addition, the vibration fluctuations caused by vehicle driving loads will generate transient stress changes inside the structure, especially at the joints where the stiffness changes greatly. These transient stress changes may lead to stress redistribution and affect the overall stress field.

[0048] Set a fixed time window, such as 1 hour, and calculate the environmental fluctuation amplitude between adjacent monitoring moments within each time window. The environmental fluctuation amplitude can be obtained by calculating the absolute value of the environmental item difference between adjacent monitoring moments and making a proportional calculation with the environmental data at the previous monitoring moment among adjacent monitoring moments, and comparing it with the preset allowable fluctuation amplitude. If the fluctuation amplitude of any environmental item exceeds its corresponding allowable fluctuation amplitude, record the time length exceeding the allowable fluctuation amplitude, and at the same time calculate the proportion of this time length in the entire time window, which is marked as the fluctuation maintenance ratio.

[0049] The allowable fluctuation range mentioned above refers to ensuring that the structure can withstand the stress changes brought about by environmental variations under normal working conditions, taking into account the differences in the sensitivity of different materials to environmental factors. For example, since concrete has a certain coefficient of thermal expansion and low tensile strength, making concrete structures particularly sensitive to temperature changes and vibration intensity, its allowable fluctuation range needs to be set according to material properties and relevant engineering design specifications. Exemplarily, for concrete structures, the allowable fluctuation range of temperature is set at 5%, the allowable fluctuation range of humidity is set at 10%, and the allowable fluctuation range of vibration intensity is set at 3%.

[0050] Compare the fluctuation maintenance ratio with the configured limit ratio. Exemplarily, the limit ratio is 0.1. If the limit ratio is reached, it indicates that the current environmental fluctuation is not sporadic but has a large persistence, which may have a significant impact on the structural stress state. At this time, fuse the fluctuation maintenance ratio with the initial acquisition frequency to calculate the new acquisition frequency, and then collect the stress data of each detection point at the new acquisition frequency within the next time window.

[0051] Specifically, fusing the fluctuation maintenance ratio with the initial acquisition frequency to calculate the new acquisition frequency can adopt the following calculation formula: , where represents the new acquisition frequency, represents the initial acquisition frequency, represents the fluctuation maintenance ratio, represents the limit ratio, represents the adjustment coefficient, which is used to control the sensitivity of the acquisition frequency adjustment. Usually, the value range is 1 to 3, and the specific value can be determined according to the actual engineering requirements.

[0052] In the above calculation formula of the new acquisition frequency represents the deviation term of the fluctuation maintenance ratio, which is used to quantify the degree of excess of the fluctuation maintenance ratio relative to the limit ratio.

[0053] The adjustment coefficient k is an empirical value used to control the sensitivity of the acquisition frequency adjustment. A larger k value will make the acquisition frequency more sensitive to changes in the fluctuation maintenance ratio, which is suitable for fine monitoring of high-risk areas.

[0054] A smaller k value will make the adjustment smoother, which is suitable for general monitoring scenarios.

[0055] In the formula This part is the core adjustment logic: when the fluctuation maintenance ratio is less than or equal to the limit ratio, the adjustment factor is 1, indicating that the acquisition frequency remains unchanged.

[0056] When the fluctuation maintenance ratio is greater than the limit ratio, the adjustment factor is greater than 1, indicating that the acquisition frequency needs to be increased.

[0057] The size of the adjustment factor is proportional to the degree of excess of the fluctuation maintenance ratio, ensuring that the adjustment range of the acquisition frequency matches the fluctuation intensity.

[0058] The new acquisition frequency is the initial frequency multiplied by This ensures that the adjustment of the acquisition frequency is based on the actual change of the fluctuation maintenance ratio and is restricted by the adjustment coefficient, avoiding excessive or insufficient adjustment amplitude.

[0059] In a specific example of the calculation, assume that the initial acquisition frequency is 1 Hz (acquired once per second), the fluctuation maintenance ratio is 0.2, the limit ratio is 0.1, and the adjustment coefficient is set to 2. Then the new acquisition frequency is calculated as .

[0060] Therefore, the new acquisition frequency is 2 Hz, that is, acquired 2 times per second.

[0061] In subsequent time windows, if the fluctuation amplitude of all environmental items does not exceed the allowable fluctuation amplitude, or even if it exceeds the allowable fluctuation amplitude but the fluctuation maintenance ratio fails to reach the limit ratio, the acquisition frequency automatically returns to the initial acquisition frequency for stress data acquisition in the subsequent time windows.

[0062] The present invention can dynamically adjust the acquisition frequency of stress data according to changes in environmental parameters such as temperature, humidity, and vibration intensity. This method ensures that data is not over-acquired when the environmental conditions are relatively stable, thereby reducing the system load, extending the service life of the sensor, and saving storage space and energy consumption. When detecting abnormal environmental fluctuations, the monitoring frequency can be quickly increased, which means that the change trend of the structural health status can be captured more accurately at an early stage, achieving the optimal utilization of resources.

[0063] In another achievable manner of the above solution, generating a stress distribution map under a time series by associating the position information of the detection points is implemented as follows: Establish a three-dimensional coordinate system at the connection position of the precast box girder, and thus locate the spatial coordinates of each detection point.

[0064] Use a three-dimensional visualization tool to construct a three-dimensional model of the connection position of the precast box girder, and map the stress data collected in real time at each detection point to its corresponding spatial coordinates on the three-dimensional model to generate a stress distribution map under a time series.

[0065] Specifically, when establishing a three-dimensional coordinate system at the connection position of the precast box girder, it is usually necessary to combine the geometric characteristics of the actual engineering structure and the detection requirements. The specific steps are as follows: Set the origin of the three-dimensional coordinate system at a key reference point at the connection position, such as the geometric center of the connection area, a certain fixed marking point, or a physical feature point that is easy to locate.

[0066] Define the axis directions: X-axis: Usually extends along the length direction of the precast box girder.

[0067] Y - axis: perpendicular to the X - axis, usually extending along the transverse width direction of the precast box girder.

[0068] Z - axis: perpendicular to the X - Y plane, usually extending along the height direction of the precast box girder.

[0069] The directions of the coordinate axes should be consistent with the geometric definitions in the engineering design drawings, and the convenience of actual construction and monitoring should be considered.

[0070] Determine the unit scale: According to the actual size of the precast box girder and the requirements of detection accuracy, determine the unit scale (such as meters or millimeters) of the three - dimensional coordinate system to ensure the accuracy and consistency of spatial coordinates.

[0071] By establishing a three - dimensional coordinate system, the spatial coordinates of each detection point can be uniquely determined, so as to accurately map these spatial coordinates in the constructed three - dimensional model. This method ensures that the stress data of each detection point corresponds one - to - one with its actual physical position, improving the accuracy and reliability of data correlation.

[0072] It should be added that since the detection points are usually discretely distributed, in order to generate a continuous stress distribution map, stress interpolation calculation needs to be carried out for the areas where stress sensors are not arranged.

[0073] The crack initiation identification module is used to select a specific band for distinguishing cracks based on the spectral reflectance difference, and use multi - spectral imaging to synchronously collect the spectral images of the detection area, and identify the crack initiation positions in the detection area from them.

[0074] The specific content of the above - mentioned module is as follows: collect historical crack samples for spectral tests, and thus screen out specific bands with significant reflectance changes between the crack area and the non - crack area by analyzing the spectral reflectance differences of the samples.

[0075] It should be noted that the present invention uses spectral imaging to detect cracks. With its high resolution, this technology can identify subtle changes on the material surface at the micron or even nanometer scale. Its core principle is that cracks change the microscopic structure of the material surface, resulting in significant reflectance differences between the crack area and the non - crack area. Although relying only on the single - dimensional detection method of spectral analysis, this method can identify the reflectance changes caused by cracks by comparing the spectral reflectances of different regions, so as to accurately locate the crack positions. In addition, compared with multi - dimensional detection methods, single - dimensional spectral analysis does not require complex fusion calculations, simplifies the data processing process, and improves the detection efficiency. Due to its simplicity and high efficiency, it can be applied to dynamic crack detection to detect early cracks in a timely manner.

[0076] During the spectral imaging process, the spectral images collected cover multiple bands. The reflectivity of the crack region and the non-crack region varies at different wavelengths. To more quickly and significantly utilize the reflectivity difference between the crack region and the non-crack region to identify cracks, specific bands need to be selected for presentation. Therefore, through statistical analysis of a large amount of historical sample data, it is possible to identify which bands have the most significant reflectivity changes to distinguish the crack region from the non-crack region. For example, in the near-infrared or mid-infrared bands, the changes in the internal structure of the material may be more obvious, making these bands particularly suitable for distinguishing the crack region from the non-crack region.

[0077] While collecting stress data, a multispectral imaging device is used to simultaneously capture the detection area to obtain the spectral image of the area at the previously selected specific band.

[0078] The above-mentioned simultaneous acquisition of spectral images while collecting stress data ensures the correlation between the structural stress state and surface cracks.

[0079] Interference removal is performed on the collected spectral images.

[0080] It should be understood that considering that spectral images are vulnerable to various external factors such as light changes, noise, and dust, in order to ensure the accuracy and reliability of subsequent analysis results, a series of interference removal steps must be performed on the spectral images before analysis. These steps include but are not limited to light correction, noise filtering, and correction of other environmental impacts.

[0081] The spectral images after interference removal processing are converted into grayscale images, and the texture features of each pixel point are extracted from the generated grayscale images. Then, they are compared with the set texture feature thresholds. If the texture feature of a certain pixel point does not meet the corresponding threshold after the spectral image collected at a certain moment is converted into a grayscale image, then it is compared whether the texture feature of this pixel point still does not meet the corresponding threshold after the spectral image collected at the next moment is converted into a grayscale image. If it continuously does not meet the corresponding threshold, then this pixel point is marked as the crack initiation location, and the time when the texture feature was first found not to meet the corresponding threshold is recorded as the crack initiation time.

[0082] It should be explained that cracks are discontinuities on the surface or inside of materials, which usually lead to changes in the texture of the surface structure, mainly manifested as: the gray value of the crack region may be different from that of the surrounding normal region, especially in the specific band after spectral reflectivity screening.

[0083] It is also manifested as: the spatial relationship between local pixel points in the crack region (such as the gray correlation of neighboring pixels) will change significantly.

[0084] It continues to be manifested as: cracks will break the original texture periodicity of the material surface, resulting in more complex texture features.

[0085] Therefore, there are obvious differences in texture characteristics between cracked and non-cracked areas, which provides a basis for crack identification.

[0086] Converting the spectral image into a grayscale image before crack identification simplifies the data analysis process and makes it easier to apply image processing technology to extract texture features.

[0087] The texture features mentioned above can quantitatively describe the texture characteristics of each pixel and its neighborhood in the image. Exemplarily, the texture features may be a gray level co-occurrence matrix GLCM and a local binary pattern LBP.

[0088] What needs to be further explained is that by analyzing a large amount of historical data, a texture feature threshold can be determined to distinguish between crack areas and normal areas. By comparing multiple consecutive time series images to confirm whether the texture feature of a certain pixel point is continuously higher than the threshold, the influence of accidental noise can be effectively eliminated to ensure the reliability of the recognition results.

[0089] The critical stress analysis module is used to establish the correlation between the crack initiation position and the stress distribution spectrum, and predict the critical stress distribution that causes crack initiation through statistical analysis.

[0090] The specific implementation content of the above module is as follows: extract the crack initiation time and the crack initiation position at several previous time points and the stress data of other detection points from the stress distribution map under the time series to calculate the stress concentration.

[0091] It should be understood that stress concentration reflects the difference between local stress and the average stress in the surrounding area. Specifically, the stress at the crack initiation location can be compared with the stress average of the detection points around the location to obtain the stress concentration. The greater the stress concentration, the higher the local stress at the crack initiation location, which implies that the location is more likely to crack due to the higher local stress. This is because high stress concentration is usually caused by geometric discontinuities or material defects in the structure, which make the local area a weak point of stress concentration, thereby increasing the risk of crack initiation.

[0092] The mean and standard deviation of the stress concentration at each time point before the stress initiation time are calculated, and the significance judgment condition is defined using the mean and standard deviation. The judgment condition can be expressed as: ,in represents the stress concentration at the time of crack initiation, represents the mean, represents the standard deviation, Indicates the setting coefficient, which can be set according to the requirements, for example, the value is 2.

[0093] Compare the stress concentration at the crack initiation moment with the significance determination condition defined above. If it meets the significance judgment condition, consider the stress concentration at the stress initiation time as the critical stress distribution state that causes crack initiation.

[0094] When determining the critical stress distribution state of crack initiation in the present invention, it does not directly use the stress concentration at the stress initiation time as the critical stress distribution state. Instead, it adopts a quantitative statistical analysis method, combines data at multiple time points for comparative analysis, can more comprehensively evaluate the change trend of stress concentration, and thus reduces the possibility of misjudgment.

[0095] The above method of using the mean and standard deviation to define the significance determination condition is a statistical method, aiming to provide a determination condition for whether the stress concentration significantly changes during the period from before crack initiation to crack initiation, and can more accurately identify whether it is the stress concentration that causes crack initiation. This method not only improves the accuracy of judging the cause of crack initiation, but also makes the conclusion about the cause of crack initiation more scientific and persuasive.

[0096] In the improved implementation of the above scheme, if it does not meet the significance judgment condition, it indicates that the stress concentration has not changed significantly during the period from before crack initiation to crack initiation. In this case, the crack initiation may be caused by other factors such as the accumulation of material fatigue damage, rather than stress concentration, and such cases are not within the scope of research of the present invention.

[0097] The present invention analyzes the stress distribution state at several time points before the crack initiation moment to determine the critical stress distribution state. This method can identify in advance the key stress characteristics that may induce crack initiation. Based on these characteristics, targeted preventive measures can be implemented at the connection positions of the same material and similar structures, so as to effectively intervene before the crack actually forms and prevent the further expansion of structural damage.

[0098] The crack propagation monitoring module is used to continuously monitor the crack propagation direction and crack propagation speed after crack initiation.

[0099] The specific monitoring content is as follows: During the crack propagation process, collect the position coordinates of the crack tip and the crack length at preset time intervals.

[0100] In the above, crack propagation monitoring can continue to use spectral analysis or acoustic emission monitoring.

[0101] Obtain the direction vector of crack propagation according to the continuously collected crack tip positions. This vector indicates the main propagation direction of the crack from one time point to the next time point, and thus determine the crack propagation direction.

[0102] Use the crack length between adjacent time points to determine the crack propagation speed.

[0103] The risk assessment response module is used to conduct itemized risk assessment based on the crack propagation speed and crack propagation direction, output a risk indication, and dynamically adjust the stress distribution at the connection position of the precast box girder according to the response strategy matched with the risk indication.

[0104] Preferably, conduct itemized risk assessment based on the crack propagation speed and crack propagation direction, and output the risk indication as follows: while continuously monitoring the crack propagation, collect the stress distribution data of the detection area and determine the principal stress direction therefrom.

[0105] It should be noted that the principal stress direction can be determined by the eigenvalue decomposition of the stress tensor. The principal stress direction is the main stress direction in the stress concentration area of the structure, and cracks usually tend to propagate along the principal stress direction.

[0106] Compare the continuously monitored crack propagation direction with the principal stress direction to obtain the crack propagation deviation angle.

[0107] Specifically, the calculation of the crack propagation deviation angle can be obtained through the calculation formula, where represents the crack propagation deviation angle, , respectively represent the crack propagation direction and the principal stress direction vector.

[0108] It should be understood that the crack propagation speed reflects the dynamic characteristics of crack development. A higher crack propagation speed usually means that the crack may rapidly expand to a degree that endangers the structural safety. The crack propagation deviation angle indicates whether the crack propagation path meets the expectation. If the crack propagation direction deviates from the principal stress direction, this may indicate the existence of complex stress distribution or other potential problems.

[0109] Set the safety thresholds for the crack propagation speed and the crack propagation deviation angle based on the material properties of the connection position of the precast box girder.

[0110] Compare the continuously monitored crack propagation speed and crack propagation deviation angle with the corresponding safety thresholds. If any item exceeds the corresponding safety threshold, output this item as the risk indication.

[0111] The setting of the above safety thresholds is based on the material mechanics properties and can be extracted from the usage instructions of the corresponding materials. These thresholds provide a quantitative standard for the crack propagation speed and deviation angle, and are used to judge whether the crack propagation exceeds the safe range.

[0112] By independently evaluating the crack propagation speed and deviation angle respectively, it is possible to clearly distinguish which factor has led to the increased risk. This method avoids the situation where a comprehensive index may mask the deviation of a single factor, thus more accurately identifying the main risk sources. After clarifying the risk direction, corresponding maintenance measures can be taken according to the specific situation to improve the maintenance efficiency and effect.

[0113] Further preferably, the stress distribution at the connection position of the precast box girder is dynamically adjusted according to the response strategy matched with the risk direction as follows: when the risk direction is the crack propagation speed, the response strategy is to execute stress release measures.

[0114] It should be explained that when there is a risk in the crack propagation speed, by reducing the stress acting on the structure, the stress concentration phenomenon at the crack tip is alleviated, thereby slowing down the crack propagation speed. Exemplary measures are: drilling holes near the crack tip, changing the stress distribution path, and reducing the stress concentration coefficient.

[0115] When the risk direction is the crack propagation direction, the response strategy is to link external support devices to apply reverse stress to the crack propagation direction.

[0116] It should be explained that when there is a risk in the crack propagation direction, by applying reverse stress to the crack propagation direction, the crack is guided to propagate in a safer direction.

[0117] Exemplary measures are: setting external support devices around the crack and adjusting the crack propagation path by applying reverse stress.

[0118] When the risk direction includes both the crack propagation speed and the crack propagation direction, the response strategy is to take structural reinforcement measures.

[0119] It should be explained that when there are risks in both the crack propagation speed and the crack propagation direction, it indicates that the current structure faces a high failure risk in a local area. A single stress release measure or reverse stress application method may not be able to comprehensively and effectively inhibit the crack propagation. In this case, more comprehensive structural reinforcement measures need to be taken to enhance the stiffness and load-bearing capacity of the overall structure and prevent the crack from further expanding.

[0120] Exemplary measures are: adding stiffeners or reinforcement plates in the crack and its surrounding areas to enhance the local strength and stiffness.

[0121] After the crack initiation, the present invention realizes the real-time tracking of the dynamic evolution process of the crack by continuously monitoring the crack propagation speed and the crack propagation direction, and takes targeted crack propagation response measures by using the risk direction obtained from the risk assessment combined with the crack propagation monitoring results. This not only improves the understanding and prediction ability of the crack propagation behavior, but also can timely and accurately implement maintenance and repair strategies, thereby effectively preventing the crack from further expanding.

[0122] Example 2

[0123] Refer to Figure 3 As shown, the present invention provides a method for dynamically detecting cracks in precast box girders, including the following steps: S1: Define a detection area centered on the connection position of the precast box girder, and arrange detection points, and configure stress sensors for each detection point.

[0124] S2: During the operation of the precast box girder, dynamically collect the stress data of each detection point according to environmental fluctuations, and generate a stress distribution map in the time series by associating the position information of the detection points.

[0125] S3: Select a specific band for distinguishing cracks based on the spectral reflectance difference, and synchronously collect the spectral images of the detection area by using multi-spectral cameras to identify the crack initiation positions in the detection area.

[0126] S4: Establish the correlation between the crack initiation positions and the stress distribution map, and predict the critical stress distribution state causing crack initiation through statistical analysis.

[0127] S5: Continuously monitor the crack propagation direction and crack propagation speed after crack initiation.

[0128] S6: Conduct sub-item risk assessment according to the crack propagation speed and crack propagation direction, and output the risk indication.

[0129] S7: Dynamically adjust the stress distribution at the connection position of the precast box girder according to the response strategy matching the risk indication.

[0130] The above formulas are all dimensionless and take their numerical values for calculation. The formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0131] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0132] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0133] In addition, in each embodiment of the present application, each functional module can be integrated into a processing module, can exist separately physically for each module, or two or more modules can be integrated into one module.

[0134] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present application, and all of them should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0135] Finally, the above description is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A dynamic detection system for cracks in precast box girders, characterized in that, Includes the following modules: Inspection point layout module: The inspection area is delineated with the connection position of the prefabricated box girder as the center, and the inspection points are arranged through grid division, and stress sensors are configured for each inspection point; Stress dynamic collection module: During the operation of prefabricated box girders, the stress data of each detection point is dynamically collected according to environmental fluctuations, and the stress distribution map under the time series is generated by correlating the detection point position information; Crack initiation identification module: Based on the difference in spectral reflectance, a specific band for distinguishing cracks is selected and a spectral image of the detection area is synchronously collected using multi-spectral camera to identify the crack initiation position in the detection area; Critical stress analysis module: establishes the correlation between the crack initiation position and the stress distribution spectrum, and predicts the critical stress distribution state that causes crack initiation through statistical analysis; Crack propagation monitoring module, which continuously monitors the crack propagation direction and crack propagation speed after crack initiation; The risk assessment response module performs sub-item risk assessment based on the crack propagation speed and crack propagation direction, and outputs the risk orientation. At the same time, it dynamically adjusts the stress distribution at the connection position of the prefabricated box girder according to the response strategy matching the risk orientation.

2. The dynamic crack detection system for precast box girders according to claim 1, wherein: The detection point layout module is implemented as follows: According to the construction drawings of the prefabricated box beam, the connection positions are identified, and the symmetry axes of these positions are determined. The detection area is formed by extending the preset distance to both sides with the symmetry axis as the center; Determine the effective coverage of stress monitoring based on the technical specifications of the stress sensor; The detection area is divided into several equally spaced grids according to the effective coverage of stress monitoring, and a detection point is arranged at the center point of each grid.

3. A precast box girder crack dynamic detection system according to claim 1, characterized in that: The stress data of each detection point are dynamically collected according to environmental fluctuations during the operation of the prefabricated box girder as follows: During the operation of prefabricated box girders, stress sensors are used to collect stress data at each detection point at the initial acquisition frequency, while continuously monitoring environmental data at the connection location; A fixed time window is set, and the environmental fluctuation amplitudes at adjacent monitoring moments are calculated in each time window, and then compared with the preset allowable fluctuation amplitude. If the fluctuation amplitude of any environmental item exceeds its corresponding allowable fluctuation amplitude, the length of time exceeding the allowable fluctuation amplitude is recorded, and the proportion of this time length in the entire time window is calculated, which is marked as the fluctuation maintenance ratio. The fluctuation maintenance ratio is compared with the configured limit ratio. If the limit ratio is reached, the fluctuation maintenance ratio is integrated with the initial acquisition frequency to calculate a new acquisition frequency, and then the stress data of each detection point is collected according to the new acquisition frequency in the next time window; In the subsequent time window, if the fluctuation amplitude of all environmental items does not exceed the allowable fluctuation amplitude, or even if it exceeds the allowable fluctuation amplitude but the fluctuation maintenance ratio fails to reach the limited ratio, the initial acquisition frequency will be automatically restored to the subsequent time window for stress data acquisition.

4. A precast box girder crack dynamic detection system according to claim 1, characterized in that: The generation of stress distribution map under time series by associating detection point position information is implemented as follows: Establish a three-dimensional coordinate system at the connection position of the prefabricated box beam, thereby locating the spatial coordinates of each detection point; Use a 3D visualization tool to construct a 3D model of the connection position of precast box girders, and map the stress data collected in real time at each detection point and its corresponding spatial coordinates onto the 3D model to generate a stress distribution map under a time series.

5. The dynamic crack detection system for precast box girders according to claim 1, wherein: The content included in the crack initiation recognition module is as follows: Collect historical crack samples for spectral tests, and thus screen out specific bands with significant changes in reflectance between the crack area and the non-crack area by analyzing the spectral reflectance differences of the samples; While collecting stress data, use a multispectral imaging device to synchronously photograph the detection area to obtain the spectral image of this area under the previously selected specific band; Remove interference from the collected spectral images; Convert the spectral image after interference removal processing into a grayscale image, extract the texture features of each pixel point on the generated grayscale image, and then compare with the set texture feature threshold. If the texture feature of a certain pixel point exceeds the corresponding threshold after the spectral image collected at a certain moment is converted into a grayscale image, then compare whether the texture feature of this pixel point still exceeds the corresponding threshold after the spectral image collected at the next moment is converted into a grayscale image. If it continuously exceeds the corresponding threshold, mark this pixel point as the crack initiation position, and record the time when the texture feature first exceeds the corresponding threshold as the crack initiation time.

6. The dynamic detection system for cracks in precast box girders according to claim 5, wherein: The implementation process of the critical stress analysis module is as follows: Extract the stress data of the crack initiation position and several other detection points at the crack initiation moment and the previous several time points from the stress distribution map under the time series for stress concentration calculation; Calculate the mean and standard deviation of the stress concentration at each time point before the stress initiation time, and define the significance determination condition using the mean and standard deviation; Compare the stress concentration at the crack initiation moment with the above-defined significance determination condition. If it meets the significance judgment condition, regard the stress concentration at the stress initiation time as the critical stress distribution state causing crack initiation.

7. The dynamic crack detection system for precast box girders according to claim 1, characterized in that: The content included in the crack propagation monitoring module is as follows: During the crack propagation process, collect the position coordinates of the crack tip and the crack length at preset time intervals; Obtain the direction vector of crack propagation according to the continuously collected crack tip positions, and thus determine the crack propagation direction; Use the crack lengths between adjacent time points to determine the crack propagation speed.

8. A precast box girder crack dynamic detection system according to claim 1, characterized in that: Conduct sub-item risk assessment according to the crack propagation speed and crack propagation direction, and output the risk indication as follows: While continuously monitoring the crack propagation, collect the stress distribution data of the detection area and determine the principal stress direction from it; Compare the continuously monitored crack propagation direction with the principal stress direction to obtain the crack propagation deviation angle; Set safety thresholds for the crack propagation speed and crack propagation deviation angle based on the material properties of the connection position of the precast box girder; Compare the continuously monitored crack propagation speed and crack propagation deviation angle with the corresponding safety thresholds. If any item exceeds the corresponding safety threshold, output this item as the risk indication.

9. The dynamic crack detection system for precast box girders according to claim 8, wherein: Dynamically adjust the stress distribution of the connection position of the precast box girder according to the response strategy matched by the risk indication as follows: When the risk indication is the crack propagation speed, the response strategy is to execute stress release measures; When the risk direction is the crack extension direction, the response strategy is to link the external support equipment to apply reverse stress to the crack extension direction; When the risk direction includes both crack growth rate and crack growth direction, the response strategy is to take structural reinforcement measures.

10. A method for dynamically detecting cracks in precast box girders, characterized in that: The steps include: S1: The inspection area is delineated with the connection position of the prefabricated box girder as the center, and the inspection points are arranged through grid division, and a stress sensor is configured for each inspection point; S2: During the operation of the prefabricated box girder, the stress data of each detection point is dynamically collected according to the environmental fluctuations, and the stress distribution map under the time series is generated by correlating the detection point position information; S3: Based on the difference in spectral reflectance, a specific waveband for distinguishing cracks is selected and a spectral image of the inspection area is synchronously collected using a multi-spectral camera to identify the crack initiation position in the inspection area; S4: Establish the correlation between the crack initiation position and the stress distribution map, and predict the critical stress distribution state that causes crack initiation through statistical analysis; S5: Continuously monitor the crack propagation direction and crack propagation speed after crack initiation; S6: Perform sub-item risk assessment based on crack propagation speed and crack propagation direction, and output risk orientation; S7: Dynamically adjust the stress distribution at the connection position of the precast box girder according to the risk-oriented matching response strategy.

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