Bridge structure safety evaluation method, device and equipment and storage medium

Abstract

This application discloses a method, apparatus, equipment, and storage medium for bridge structural safety assessment. The method includes: acquiring the actual load of the current bridge and inputting it into a preset bridge structural finite element model to obtain the actual tensile stress of the base plate; acquiring the standard tensile stress of the base plate and determining the current demand ratio based on the actual tensile stress of the base plate, wherein the standard tensile stress of the base plate is obtained by inputting the standard load of the current bridge into the preset bridge structural finite element model; determining the probability value that the current demand ratio exceeds the capacity spectrum based on the current demand ratio and the current bridge's capacity spectrum, wherein the capacity spectrum is obtained by fitting several sets of material simulation parameters and corresponding load proportion coefficients; comparing the probability value with a preset threshold and outputting the safety assessment result. This application, by introducing the actual load to construct the demand ratio for probability comparison with the capacity spectrum, can more realistically reflect the safety status of the bridge under actual load, improving the accuracy and reliability of the assessment results.

Description

Technical Field

[0001] This application relates to the field of safety assessment technology, and in particular to a method, apparatus, equipment and storage medium for assessing the safety of bridge structures. Background Technology

[0002] Prestressed concrete bridges are widely used in the construction of highways and high-standard national roads. These bridges are designed to have no tensile stress in the bridge deck concrete (tensile stress not exceeding 0) to reduce the risk of concrete cracking and ensure the durability and safety of the structure. During the bridge's service life, its safety status needs to be assessed to determine whether the structure meets operational requirements. Currently, engineering practice mainly relies on bridge design specifications and employs deterministic methods based on standard loads for safety assessment. This involves using finite element analysis and other methods to calculate the bridge structure's response under the standard loads specified in the specifications and comparing it with the limit values ​​to determine its safety.

[0003] However, the standard loads specified in the aforementioned deterministic assessment methods are representative values ​​based on statistical laws. In reality, bridges experience significant randomness and variability in loads such as vehicle loads, temperature variations, and wind loads. For example, the actual weight of passing vehicles may far exceed the standard vehicle weight, and actual temperature variations may exceed the specifications' expectations. Because the assessment uses standard loads rather than the actual loads borne by the bridge, the results cannot accurately reflect the structure's safety status under actual loads. This may lead to assessment conclusions that are overly risky or conservative, making it difficult to provide accurate information for bridge operation and maintenance decisions. Summary of the Invention

[0004] The main objective of this application is to provide a method, apparatus, equipment, and storage medium for bridge structure safety assessment, aiming to solve the technical problem that existing bridge safety assessment methods based on standard loads are difficult to reflect the safety status of bridge structures under actual loads, resulting in low reliability of assessment results.

[0005] To achieve the above objectives, this application proposes a method for assessing the safety of bridge structures, the method comprising: Obtain the actual load of the current bridge and input the actual load into the preset bridge structure finite element model to obtain the actual tensile stress of the bottom plate; Obtain the standard tensile stress of the base plate, and determine the current demand ratio based on the actual tensile stress of the base plate and the standard tensile stress of the base plate. The standard tensile stress of the base plate is obtained by inputting the standard load of the current bridge into the preset bridge structure finite element model. Based on the current demand ratio and the current bridge capacity spectrum, determine the probability value that the current demand ratio exceeds the capacity spectrum, wherein the capacity spectrum is obtained by fitting several sets of material simulation parameters and corresponding load proportion coefficients. The probability value is compared with a preset threshold, and the security assessment result is output.

[0006] In one embodiment, the step of obtaining the actual load of the current bridge and inputting the actual load into a preset bridge structure finite element model to obtain the actual tensile stress of the bottom plate includes: The actual vehicle load, actual temperature load, actual wind load, and actual settlement load corresponding to the current bridge are obtained and integrated to obtain the actual load. The actual load is input into the preset bridge structure finite element model and run to obtain the running results. The bridge structure parameters in the preset bridge structure finite element model are preset average values. Based on the running results, the maximum tensile stress value at the bottom plate position of the current bridge is extracted as the actual bottom plate tensile stress.

[0007] In one embodiment, before the step of determining the probability value of the current demand ratio exceeding the capacity spectrum based on the current demand ratio and the current bridge capacity spectrum, the method further includes: Obtain the material property parameters of the current bridge, and generate several material simulation parameters based on the material property parameters; Each of the material simulation parameters is input into the preset bridge structure finite element model, and a standard load is applied to the preset bridge structure finite element model. The load ratio coefficient corresponding to each of the material simulation parameters is determined by the proportional loading method. The load ratio coefficient is the ratio of the proportional load to the standard load when the tensile stress of the base plate reaches zero. The capacity spectrum is obtained by fitting the probability distribution of the load proportion coefficients corresponding to all the material simulation parameters.

[0008] In one embodiment, the step of obtaining the material property parameters of the current bridge and generating several material simulation parameters based on the material property parameters includes: Obtain the material information corresponding to the current bridge, and extract the material property parameters based on the material information. The material property parameters include at least the elastic modulus of concrete, the strength of concrete, and the strength of prestressed tendons. Based on the material property parameters, a combination of material parameters is generated using Monte Carlo simulation as the material simulation parameters.

[0009] In one embodiment, the step of determining the load proportion coefficient corresponding to each of the material simulation parameters by proportional loading includes: The standard load is applied to the preset bridge structure finite element model with the input material simulation parameters; The standard load is increased by a scaling factor to obtain the corresponding proportional load, and the corresponding tensile stress of the bottom plate in the preset bridge structure finite element model under the proportional load is obtained. The proportionality coefficient corresponding to the zero tensile stress in the base plate is determined as the load proportionality coefficient corresponding to the material simulation parameters.

[0010] In one embodiment, the step of determining the probability value that the current demand ratio exceeds the capacity spectrum based on the current demand ratio and the current bridge capacity spectrum includes: Obtain the probability density function corresponding to the capability spectrum, wherein the probability density function has a mean parameter and a standard deviation parameter; Using the current demand ratio as the upper limit of integration, the probability density function is integrated over the interval from zero to the upper limit of integration to obtain the probability value.

[0011] In one embodiment, the step of comparing the probability value with a preset threshold and outputting a security assessment result includes: When the probability value is greater than the preset threshold, an unsafe bridge status signal is output. When the probability value is less than or equal to the preset threshold, a bridge safety status signal is output.

[0012] Furthermore, to achieve the above objectives, this application also proposes a bridge structural safety assessment device, the device comprising: The actual load acquisition module is used to acquire the actual load of the current bridge and input the actual load into the preset bridge structure finite element model to obtain the actual tensile stress of the bottom plate. The demand ratio calculation module is used to obtain the standard base plate tensile stress and determine the current demand ratio based on the actual base plate tensile stress and the standard base plate tensile stress. The standard base plate tensile stress is obtained by inputting the current standard load of the bridge into the preset bridge structure finite element model. The probability calculation module is used to determine the probability that the current demand ratio exceeds the current capacity spectrum based on the current demand ratio and the current capacity spectrum of the bridge. The capacity spectrum is obtained by fitting several sets of material simulation parameters and corresponding load proportion coefficients. The security assessment module is used to compare the probability value with a preset threshold and output a security assessment result.

[0013] In addition, to achieve the above objectives, this application also proposes a bridge structure safety assessment device, the device comprising: a memory, a processor, and a bridge structure safety assessment program stored in the memory and executable on the processor, the bridge structure safety assessment program being configured to implement the steps of the bridge structure safety assessment method described above.

[0014] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, storing a bridge structure safety assessment program, which, when executed by a processor, implements the steps of the bridge structure safety assessment method described above.

[0015] This application discloses a method for assessing the safety of a bridge structure. The method includes: obtaining the actual load of the current bridge and inputting the actual load into a preset finite element model of the bridge structure to obtain the actual tensile stress of the base plate; obtaining the standard tensile stress of the base plate and determining the current demand ratio based on the actual tensile stress and the standard tensile stress of the base plate, wherein the standard tensile stress of the base plate is obtained by inputting the standard load of the current bridge into the preset finite element model of the bridge structure; determining the probability value that the current demand ratio exceeds the capacity spectrum based on the current demand ratio and the current bridge's capacity spectrum, wherein the capacity spectrum is obtained by fitting several sets of material simulation parameters and corresponding load proportion coefficients; comparing the probability value with a preset threshold and outputting the safety assessment result.

[0016] This application calculates the actual tensile stress of the bridge slab based on the actual load obtained from actual monitoring and compares it with the standard tensile stress of the bridge slab under standard load, thus incorporating the actual state of the bridge into the safety assessment system and avoiding the bias caused by relying solely on standard load for assessment. Simultaneously, this application expresses the bridge's load-bearing capacity in the form of a capacity spectrum by constructing a capacity spectrum obtained from fitting material simulation parameters and calculating the probability value of actual demand exceeding this capacity spectrum, thereby transforming the traditional binary judgment into a continuous quantitative risk judgment. This more realistically reflects the safety status of the bridge under actual loads, helping to provide a more scientific and accurate risk basis for subsequent bridge operation and maintenance decisions. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the first embodiment of the bridge structure safety assessment method of this application; Figure 2 This is a flowchart illustrating the second embodiment of the bridge structure safety assessment method of this application; Figure 3 This is a flowchart illustrating the third embodiment of the bridge structure safety assessment method of this application; Figure 4 This is a schematic diagram of the modular structure of the bridge structural safety assessment device of this application; Figure 5 This is a structural schematic diagram of the bridge structural safety assessment equipment for this application.

[0020] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0021] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0022] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0023] This application provides a method for assessing the safety of bridge structures, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the bridge structure safety assessment method of this application. In this embodiment, the method includes: steps S10~S40: Step S10: Obtain the actual load of the current bridge and input the actual load into the preset bridge structure finite element model to obtain the actual tensile stress of the bottom plate.

[0024] It should be noted that the method in this embodiment can be applied to the operational safety assessment of fully prestressed concrete bridges, and is particularly suitable for fully prestressed concrete bridge structures on highways and high-standard national roads. The executing entity of this embodiment can be a computing electronic device with functions such as data processing, numerical calculation, and model calling, such as a server, workstation, or cloud computing platform. This embodiment and the following embodiments are described using a bridge structure safety assessment device (referred to as "the device") as an example.

[0025] It should be understood that actual loads can include actual vehicle loads, actual temperature loads, actual wind loads, and actual settlement loads. The equipment can acquire real-time data on these various loads borne by the bridge during its service life through a structural health monitoring system installed on the bridge.

[0026] It should also be noted that the device can pre-store preset finite element models of bridge structures. These preset finite element models are pre-set finite element models used to simulate the mechanical response of the current bridge structure under various loads.

[0027] It should be understood that after obtaining the actual load, the equipment can input the actual load into the preset bridge structure finite element model, run the finite element analysis, and extract the maximum tensile stress value at the bottom plate position from the running results as the actual bottom plate tensile stress.

[0028] Furthermore, to specifically illustrate the process of obtaining the actual load and calculating the actual tensile stress of the base plate, step S10 specifically includes: steps S101~S103: Step S101: Obtain and integrate the actual vehicle load, actual temperature load, actual wind load and actual settlement load corresponding to the current bridge to obtain the actual load.

[0029] It should be understood that the structural health monitoring system currently installed on bridges may include a dynamic weighing subsystem based on gravity sensors, temperature sensors embedded in key parts of the bridge, anemometers installed at the corresponding bridge site, and displacement sensors deployed at the piers.

[0030] In its implementation, the equipment uses a dynamic weighing subsystem to acquire the actual weight and wheelbase of vehicles currently traveling on the bridge, serving as the actual vehicle load; temperature sensors embedded in key parts of the bridge to acquire temperature distribution data at various locations, serving as the actual temperature load; anemometers at the bridge site to acquire current wind speed and direction data, serving as the actual wind load; and displacement sensors at the piers to acquire current pier settlement data, serving as the actual settlement load. The equipment can then sum these four types of loads to obtain the actual load.

[0031] Step S102: Input the actual load into the preset bridge structure finite element model and run it to obtain the running results. The bridge structure parameters in the preset bridge structure finite element model are preset average values.

[0032] It should be noted that the equipment pre-stores a preset finite element model of the bridge structure. This preset finite element model of the bridge structure can be a numerical analysis model established based on the current bridge design drawings, geometric dimensions, boundary conditions, and material property parameters, used to simulate the mechanical response of the bridge structure under various loads.

[0033] It should be understood that the preset bridge structure finite element model can include the current bridge's geometric dimensions (bridge length, bridge width, beam height, slab thickness, etc.), and can divide the current bridge into elements, that is, discretize the bridge into a large number of small elements. It can also set the current bridge's boundary conditions, including support constraints, pier connection methods, etc., as well as the current bridge's prestressed tendon arrangement (location, shape, tension force), etc.

[0034] It should also be noted that in the preset bridge structure finite element model, the material parameters of the bridge structure (such as the elastic modulus of concrete, concrete strength, prestressing tendon strength, etc.) can all be set to preset average values, which are determined based on the on-site measured data of the current bridge or the historical statistical data of bridges similar to the current bridge.

[0035] In a specific implementation, the device can input the aforementioned integrated actual load dataset into the preset bridge structure finite element model, call the preset bridge structure finite element model to run finite element analysis, and obtain the mechanical response results of the current bridge structure under actual load. The mechanical response results can include parameters such as stress, strain, and displacement of the current bridge at various parts.

[0036] Step S103: Extract the maximum tensile stress value of the current bridge at the bottom plate position based on the running results as the actual bottom plate tensile stress.

[0037] In practice, the equipment can locate all unit nodes in the current bridge's bottom plate area from the obtained operating results, read the tensile stress calculation value corresponding to each unit node, filter out the maximum value, and then use the maximum value as the actual tensile stress of the bottom plate.

[0038] Step S20: Obtain the standard base plate tensile stress, and determine the current demand ratio based on the actual base plate tensile stress and the standard base plate tensile stress. The standard base plate tensile stress is obtained by inputting the current standard load of the bridge into the preset bridge structure finite element model.

[0039] It should be noted that standard loads may include preset standard vehicle loads, standard temperature loads, standard wind loads, and standard settlement loads. These standard load types can be determined according to standard bridge design specifications and represent the expected level of normal operational loads for the bridge during the design phase.

[0040] Specifically, the device can acquire pre-stored standard load data and input the standard load data into the aforementioned preset bridge structure finite element model (the material properties are also taken as preset average values). Under the premise of keeping other parameters in the preset bridge structure finite element model unchanged except for the load, the device runs finite element analysis and then extracts the maximum tensile stress value at the current bridge bottom plate position from the running results as the standard bottom plate tensile stress.

[0041] Next, the equipment can calculate the ratio of the actual tensile stress of the base plate to the tensile stress of the standard base plate, and use this ratio as the current demand ratio. It can be represented as:

[0042] In the formula, This represents the actual tensile stress in the base plate. This represents the tensile stress of the standard base plate.

[0043] The current demand ratio reflects the degree of difference between the current actual load and the standard load in the design: when the current demand ratio is greater than 1, it means that the tensile stress generated by the actual load exceeds the tensile stress generated by the standard load, and the bridge is currently bearing a greater load demand than expected in the design.

[0044] Step S30: Based on the current demand ratio and the current bridge capacity spectrum, determine the probability value that the current demand ratio exceeds the capacity spectrum, wherein the capacity spectrum is obtained by fitting several sets of material simulation parameters and corresponding load proportion coefficients.

[0045] It should be understood that the capacity spectrum is a probability distribution function pre-built and stored in the device, which can be represented as a probability density curve. Its horizontal axis represents the ratio of the ultimate load that the bridge can withstand to the standard load (i.e., the load ratio coefficient), and the vertical axis represents the probability density of the occurrence of this ratio.

[0046] It should be noted that the capacity spectrum can be used to characterize the probability distribution characteristics of the current bridge's structural bearing capacity. It can be constructed based on the material uncertainty parameters of the bridge structure, reflecting the statistical law of the current bridge's bearing capacity under actual service conditions. Furthermore, the construction process of the capacity spectrum can be completed offline before the method in this embodiment is executed, or it can be generated in real time by the device during this step; this embodiment does not impose any restrictions on this.

[0047] Understandably, the device can acquire a pre-stored capacity spectrum of the current bridge, expressed as a probability density function. Then, using the determined current demand ratio as an upper limit for integration, the probability density function corresponding to the capacity spectrum is integrated over the interval from zero to this upper limit, yielding an integral result as a probability value. This probability value represents the probability that, under the current actual load demand, the actual load-bearing capacity of the current bridge is less than the actual demand, i.e., the probability that the demand exceeds the capacity.

[0048] Step S40: Compare the probability value with a preset threshold and output the security assessment result.

[0049] It should be noted that the preset threshold can be set in advance based on factors such as the current importance level of the bridge and the owner's safety management requirements. For example, if the current bridge is an important bridge on a highway, the preset threshold can be set to a lower value (such as 5%) to maintain a higher safety margin.

[0050] Specifically, the device compares the calculated probability value with a preset threshold. When the probability value is greater than the preset threshold, it indicates that the bridge is at risk beyond acceptable limits under the current actual load, and the device outputs a bridge unsafe state signal. When the probability value is less than or equal to the preset threshold, it indicates that the current safety risk of the bridge is within acceptable limits, and the device outputs a bridge safe state signal.

[0051] It should also be noted that the output signal can take various forms, including but not limited to: displaying assessment results on the monitoring interface, generating a security assessment report, triggering early warning indicator lights, and sending alert messages to maintenance personnel. The output signal can also include the aforementioned probability values, thereby providing maintenance personnel with continuous quantitative risk indicators.

[0052] This embodiment incorporates the actual operating status of the bridge into the evaluation system by acquiring the actual load and calculating the actual tensile stress of the foundation slab, thus avoiding the evaluation bias caused by relying solely on standard loads in traditional methods. By introducing the demand ratio as the current demand ratio, the difference between the actual load and the standard load is quantified into a dimensionless index, facilitating probabilistic comparison with the capacity spectrum. By constructing a capacity spectrum fitted by material uncertainty parameters, the bridge's bearing capacity is expressed as a probability distribution, fully considering the natural variability of material properties. By calculating the probability value of the demand ratio exceeding the capacity spectrum and comparing this probability value with a preset threshold to output the evaluation result, the traditional binary safety judgment is transformed into a continuous risk quantification index. This overcomes the shortcomings of traditional deterministic evaluation methods that ignore the randomness of loads and material variability, improving the reliability of the safety evaluation results for fully prestressed concrete bridges.

[0053] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 , Figure 2 This is a flowchart illustrating the second embodiment of the bridge structure safety assessment method of this application.

[0054] In this embodiment, to specifically illustrate how to fit and construct a capacity spectrum from several sets of material simulation parameters and corresponding load scaling factors, before step S30, the following steps are included: S01~S04: Step S01: Obtain the material property parameters of the current bridge, and generate several material simulation parameters based on the material property parameters.

[0055] It should be noted that the material property parameters are used to describe the mechanical performance characteristics of key materials in the bridge structure. The equipment can extract the above material property parameters based on the material information corresponding to the current bridge. This material information can come from on-site measured data or historical statistical data, such as bridge design documents and construction records.

[0056] It should be understood that the equipment extracts material property parameters based on the acquired material information. These material property parameters may include at least the elastic modulus of concrete, concrete strength, and prestressing tendon strength. These various material property parameters do not necessarily have single fixed values, but rather represent their natural variability in the form of a probability distribution; for example, they can be assumed to follow a normal distribution.

[0057] For example, the elastic modulus of concrete can be assumed to follow a normal distribution, with its mean being the design value or the measured mean, and its standard deviation being determined based on the dispersion of the measured data; the strength of concrete can also be assumed to follow a normal distribution; the strength of prestressed tendons can also be described using a similar probability distribution.

[0058] It should also be noted that the material simulation parameters can include different types of material property parameters. The equipment can simulate and generate corresponding simulation parameters based on different types of material property parameters, and then combine the various simulation parameters to obtain the material simulation parameters.

[0059] Furthermore, to illustrate in detail how to generate several material simulation parameters based on material property parameters, step S01 also includes: steps S011~S012: Step S011: Obtain the material information corresponding to the current bridge, and extract the material property parameters based on the material information. The material property parameters include at least the elastic modulus of concrete, the strength of concrete, and the strength of prestressed tendons.

[0060] It should be noted that the equipment can read basic information such as concrete grade and prestressed tendon specifications from bridge design documents, and combine it with on-site measured data (such as concrete strength measured by rebound method and elastic modulus measured by core specimens) to determine the mean and standard deviation of each material property parameter.

[0061] For example, the elastic modulus of concrete can be expressed as E~N ( Concrete strength can be expressed as ~N( The strength of prestressed tendons can be expressed as f. ~N( ).

[0062] Step S012: Based on the material property parameters, generate a combination of material parameters as the material simulation parameters using Monte Carlo simulation.

[0063] It should be understood that the equipment can use the Monte Carlo simulation method to randomly sample materials based on the probability distribution of each material property parameter to obtain material simulation parameters.

[0064] Specifically, each sampling can independently extract a value from each probability distribution, and then combine the extracted values ​​of concrete elastic modulus, concrete strength, and prestressed tendon strength into a set of material parameter combinations. The equipment repeats the above sampling process to generate several sets (e.g., one hundred sets) of material parameter combinations as material simulation parameters.

[0065] Step S02: Input the simulation parameters of each material into the preset bridge structure finite element model, and apply standard loads to the preset bridge structure finite element model.

[0066] It should be noted that the device can input the aforementioned sets of material simulation parameters one by one into the preset bridge structure finite element model. Specifically, for each set of material simulation parameters, the device can assign the concrete elastic modulus, concrete strength, and prestressing tendon strength in that set to the corresponding material property fields of the preset bridge structure finite element model.

[0067] After assigning material parameters, the equipment can apply standard loads to the preset bridge structure finite element model. These standard loads may include standard vehicle loads, standard temperature loads, standard wind loads, and standard settlement loads as determined by bridge design specifications.

[0068] Step S03: Determine the load ratio coefficient corresponding to each of the material simulation parameters by means of proportional loading. The load ratio coefficient is the ratio of the proportional load to the standard load when the tensile stress of the base plate reaches zero.

[0069] It should be understood that proportional loading involves multiplying the standard load by a gradually increasing scaling factor, and using the amplified load as the load applied to the finite element model.

[0070] Furthermore, to illustrate in detail how to determine the load proportion factor, step S03 also includes: steps S031~S033: Step S031: Apply the standard load to the preset bridge structure finite element model that has been input with the material simulation parameters.

[0071] Step S032: Increase the standard load by a scaling factor to obtain the corresponding scaling load, and obtain the corresponding tensile stress of the bottom plate in the preset bridge structure finite element model under the scaling load.

[0072] It should be noted that the equipment can apply standard loads to the finite element model with assigned material simulation parameters as the initial loading state.

[0073] Next, the device can be set with an initial scaling factor (e.g.) =1.0), multiply the standard load by this scaling factor to obtain the proportional load, and then apply the proportional load to the preset bridge structure finite element model, run the finite element analysis, calculate and record the tensile stress of the bottom plate under the current load (proportional load).

[0074] Subsequently, the device follows a preset step size (e.g. (=0.05) Gradually increase the scaling factor, repeat the above calculation process, and record the tensile stress of the base plate corresponding to each scaling factor.

[0075] Step S033: Determine the proportional coefficient corresponding to the zero tensile stress of the base plate as the load proportional coefficient corresponding to the material simulation parameters.

[0076] It should be understood that the equipment can continuously monitor the change in tensile stress in the base plate as the scaling factor increases. When the tensile stress in the base plate gradually increases from a negative value (compressive stress) and first reaches zero, the equipment records the scaling factor at this time as the load scaling factor corresponding to that set of material simulation parameters.

[0077] Understandably, this load ratio factor is the critical load multiple corresponding to the transition of the current bridge from a safe state (base plate under compression) to an ultimate state (base plate tensile stress is zero) under the current set of material simulation parameters. In other words, it is how many times the maximum load that the current bridge can withstand is greater than the standard load under the current set of material simulation parameters.

[0078] In practice, the device can repeatedly execute steps S031 to S033 on all the previously generated sets of material simulation parameters to obtain the load ratio coefficients corresponding to each set of material simulation parameters.

[0079] Step S04: Perform probability distribution fitting on the load proportion coefficients corresponding to all the material simulation parameters to obtain the capacity spectrum.

[0080] It should be understood that the equipment can collect the load proportioning coefficients corresponding to all sets of material simulation parameters, forming a data sequence. For example, for N sets of material simulation parameters, the corresponding load proportioning coefficient can be x=[ , ,..., ].

[0081] Next, the device can fit a normal distribution to the data sequence to determine its mean parameter μ and standard deviation parameter σ, thus obtaining the probability density function. This probability density function is the capability spectrum, expressed as:

[0082] In the formula, Let be a random variable, representing the ratio of the current ultimate load of the bridge to the standard load. The mean value obtained from the fitting reflects the average level of the current bridge's load-bearing capacity (expressed as a multiple of the standard load). The standard deviation obtained from the fitting represents the degree of uncertainty in the current load-bearing capacity of the bridge.

[0083] It should be noted that this capacity spectrum is used to characterize the probability distribution of the ultimate bearing capacity (expressed as a multiple of the standard load) of a bridge under the current structural characteristics, thus providing an input basis for subsequent probability assessment.

[0084] Finally, the device can store the fitted capability spectrum in its local storage or cloud storage for use in subsequent steps.

[0085] This embodiment obtains material property parameters and generates multiple sets of material simulation parameters using Monte Carlo simulation. This fully considers the impact of the natural variability of material properties on the bridge's load-bearing capacity, avoiding the evaluation bias caused by treating material parameters as fixed values ​​in traditional deterministic methods. Furthermore, this embodiment determines the ultimate load proportion coefficient corresponding to each material simulation parameter group by using a proportional loading method, and obtains a capacity spectrum by fitting a probability distribution to all coefficients. This expands the bridge's load-bearing capacity from a single numerical value to a complete probability distribution form, providing a foundation for subsequent safety assessments based on probability theory.

[0086] Based on the first and second embodiments of this application, in the third embodiment of this application, the content that is the same as or similar to the first and second embodiments described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 , Figure 3 This is a flowchart illustrating the third embodiment of the bridge structure safety assessment method of this application.

[0087] In this embodiment, to specifically illustrate how to calculate the probability value of the current demand ratio exceeding the capability spectrum through integration, step S30 further includes: steps S301~S302: Step S301: Obtain the probability density function corresponding to the capability spectrum, wherein the probability density function has a mean parameter and a standard deviation parameter.

[0088] It should be understood that the device can read a pre-built and stored capability spectrum from local storage or cloud storage. This capability spectrum is represented in the form of a probability density function, i.e., as follows:

[0089] Specifically, the device can read the mean parameter corresponding to the probability density function. and standard deviation parameter The specific value.

[0090] Step S302: Using the current demand ratio as the upper limit of integration, perform integration calculation on the probability density function within the interval from zero to the upper limit of integration to obtain the probability value.

[0091] It should be noted that the physical meaning of integral calculation is to obtain the random variable from the probability density function of the capability spectrum. The probability that the bridge's load-bearing capacity is less than or equal to a certain threshold (i.e., the ratio of current demand). This probability is the probability that the bridge's current load-bearing capacity is insufficient to meet the current actual load demand.

[0092] In practical implementation, the device can obtain the current demand ratio calculated above. , will The value serves as the upper limit of integration for the probability density function of the ability spectrum. The integral is performed over the interval [0, y], and the integration formula is as follows:

[0093] In the formula, the lower limit of integration is 0, indicating that the load proportion coefficient is a non-negative real number; the upper limit of integration... The ratio of current demand, the integral result This is the probability value we are looking for.

[0094] In practical implementation, the device can approximate the integral using numerical integration methods (such as the adaptive Simpson integral or the Gauss-Legendal integral), or it can directly obtain the integral result by looking up a table or calling a function library using the cumulative distribution function of the normal distribution. The calculated probability value is then output to facilitate further safety assessments.

[0095] Furthermore, in order to conduct a safety assessment of the current bridge based on probability values, step S40 specifically includes: steps S401~S402: Step S401: When the probability value is greater than the preset threshold, output a bridge unsafe state signal.

[0096] Step S402: When the probability value is less than or equal to the preset threshold, output the bridge safety status signal.

[0097] What should be understood is that probability values It has a clear physical meaning: The closer the value is to 0, the lower the probability that the current load-bearing capacity of the bridge is less than the current demand, and the higher the probability that the bridge is in a safe state. The closer the value is to 1, the higher the probability that the current load-bearing capacity of the bridge is less than the current demand, and the higher the probability that the bridge is in an unsafe state.

[0098] It should be noted that the preset threshold is a dividing line used to determine the safety status of a bridge. This threshold can be preset based on factors such as the bridge's importance level, relevant regulatory requirements, and the owner's safety management strategy. For example, for a fully prestressed concrete bridge on a highway, the preset threshold can be set to 5%; for bridges of lower importance, the preset threshold can be appropriately relaxed; for extra-large or particularly important bridges, the preset threshold can be set to a more stringent value (such as 1% or 2%).

[0099] In the specific implementation, the device obtains a pre-stored preset threshold. The probability values ​​obtained from the above calculations Compare with the preset threshold.

[0100] When the device determines the probability value Greater than the preset threshold When this occurs, it indicates that the probability of the bridge's load-bearing capacity being insufficient under the current actual load exceeds the acceptable risk level, and the bridge is currently in an unsafe state. At this time, the equipment can generate and output a bridge unsafe state signal.

[0101] The bridge's unsafe condition signal can take various forms, including but not limited to: displaying a red warning icon on the equipment's visual interface, generating and pushing safety warning notifications, triggering audible and visual alarm devices such as buzzers or warning lights, and sending warning SMS messages or application push messages to the terminal devices of bridge maintenance personnel. Upon receiving the signal, maintenance personnel can take corresponding measures such as load restrictions, traffic control, on-site inspections, and reinforcement and repair.

[0102] When the device determines the probability value Less than or equal to the preset threshold When the bridge is in a safe state, it indicates that the probability of insufficient load-bearing capacity under the current actual load is within an acceptable risk level. At this time, the equipment can generate and output a bridge safety status signal.

[0103] The bridge's safety status signal can take various forms, including but not limited to: displaying a green normal indicator on the equipment's visual interface, generating routine status reports, and recording safety assessment results to a log file. Upon receiving this signal, maintenance personnel can maintain normal operation and continue monitoring.

[0104] In addition, the device can also calculate the probability values. The data is displayed in real-time as numerical values ​​on a visual interface, allowing operations and maintenance personnel to intuitively understand the current quantifiable level of risk. For example, the device can simultaneously display the current probability value on the visual interface. Preset threshold And the comparison between the two, so that maintenance personnel can grasp the safety margin.

[0105] Furthermore, the device can also be set to an evaluation cycle, such as performing a complete evaluation process once per hour, day, or week, i.e., steps S10 to S40 above, thereby obtaining the probability value corresponding to each evaluation cycle and forming a probability value time series.

[0106] Specifically, after each evaluation is completed, the device can store the current period's timestamp and the calculated probability value as a record in the historical evaluation database.

[0107] As the number of evaluations increases, the device can accumulate a time series of probability values:

[0108] in, For the evaluation period, For the corresponding evaluation period The probability value.

[0109] Next, the device can perform trend analysis on the above probability value time series to determine the direction and rate of change of the probability values.

[0110] It should be understood that the device can employ various trend analysis methods. For example, the device can calculate the slope of the linear fit of the probability value time series: when the slope is positive, it indicates that the probability value is trending upward and the bridge safety condition is deteriorating; when the slope is negative, it indicates that the probability value is trending downward and the bridge safety condition is improving; when the slope is close to zero, it indicates that the probability value remains stable.

[0111] In addition, the device can calculate a moving average of the probability values ​​to eliminate short-term fluctuations and extract long-term trends. It can also compare the current probability value with historical probability values ​​for the same period to identify abnormal changes.

[0112] Simultaneously, the equipment can also acquire the composition of the actual load in each evaluation cycle, that is, determine the specific values ​​of the actual vehicle load, actual temperature load, actual wind load, and actual settlement load in each evaluation cycle. Then, in the process of calculating the current demand ratio in step S20, the contribution ratio of each type of load to the tensile stress of the base plate is determined through sensitivity analysis or load separation method.

[0113] For example, the device can input the actual vehicle load into a preset bridge structure finite element model (with other loads set to zero) and calculate the tensile stress of the base plate under the action of the actual vehicle load alone. Similarly, calculate the tensile stress of the base plate under the actual temperature load acting alone. Tensile stress in the base plate under actual wind load alone Tensile stress in the base plate under actual settlement load alone The contribution ratio of each type of load can be expressed as the sum of the tensile stress on the base plate generated by each load and the actual tensile stress on the base plate. The ratio of .

[0114] Finally, the device can perform correlation analysis on the trend and rate of change of the aforementioned probability values, combined with the contribution ratio of various loads to the tensile stress of the base plate, to generate targeted predictive prompts.

[0115] For example, when the device identifies a continuous upward trend in the probability value and the rate of change exceeds a preset threshold, the device can generate an early warning message indicating "continuous increase in bridge safety risk," and can further pinpoint the main driving factors of the risk increase by combining load contribution ratio analysis. If the actual vehicle load accounts for the largest proportion and shows an increasing trend, the equipment can generate a prompt message that "it is recommended to pay attention to the management of overloaded vehicles". If the contribution of actual temperature load increases significantly, the equipment can generate a prompt message that "it is recommended to pay attention to the impact of extreme temperature weather", and can combine meteorological forecast data to predict the potential impact of future temperature changes on the safety status of the bridge. If the contribution of the actual settlement load continues to increase, the equipment can generate a prompt message that "it is recommended to check the settlement of the bridge pier foundation". If the contribution of actual wind load increases abnormally, the equipment can generate a "warning message suggesting attention to strong winds" message.

[0116] In practice, when generating bridge unsafe state signals / bridge safe state signals in each assessment cycle, the device's visualization interface can also simultaneously display the aforementioned predictive prompts, thus providing a time window for maintenance personnel to take preventive measures in advance.

[0117] This embodiment transforms bridge safety assessment from a traditional deterministic binary judgment to a continuous quantitative assessment based on probability theory by integrating the probability density function of the capacity spectrum with the demand ratio as the upper limit of integration. This outputs accurate risk probability values, providing a more scientific quantitative basis for bridge operation and maintenance decisions. Furthermore, by comparing the probability values ​​with preset thresholds and outputting corresponding status signals, this embodiment achieves automatic judgment and tiered early warning of safety assessment results, improving the intelligence level and response efficiency of bridge safety management.

[0118] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the bridge structure safety assessment method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0119] In addition, this application also provides a bridge structural safety assessment device, such as... Figure 4 As shown, Figure 4 This is a schematic diagram of the modular structure of the bridge structural safety assessment device of this application. (The remaining text appears to be a fragment and doesn't translate directly.) Figure 4 It is known that the device includes: The actual load acquisition module 401 is used to acquire the actual load of the current bridge and input the actual load into the preset bridge structure finite element model to obtain the actual tensile stress of the bottom plate. The demand ratio calculation module 402 is used to obtain the standard base plate tensile stress and determine the current demand ratio based on the actual base plate tensile stress and the standard base plate tensile stress. The standard base plate tensile stress is obtained by inputting the current standard load of the bridge into the preset bridge structure finite element model. The probability calculation module 403 is used to determine the probability value that the current demand ratio exceeds the capacity spectrum based on the current demand ratio and the current bridge capacity spectrum, wherein the capacity spectrum is obtained by fitting several sets of material simulation parameters and corresponding load proportion coefficients. The security determination module 404 is used to compare the probability value with a preset threshold and output a security assessment result.

[0120] This embodiment's device incorporates the actual bridge's current operational status into the evaluation system by acquiring the actual load and calculating the actual tensile stress of the foundation slab, avoiding the evaluation bias caused by relying solely on standard loads in traditional methods. By introducing the demand ratio as the current demand ratio, the difference between the actual load and the standard load is quantified into a dimensionless index, facilitating probabilistic comparison with the capacity spectrum. By constructing a capacity spectrum fitted by material uncertainty parameters, the bridge's bearing capacity is expressed as a probability distribution, fully considering the natural variability of material properties. By calculating the probability value of the demand ratio exceeding the capacity spectrum and comparing this probability value with a preset threshold to output the evaluation result, the traditional binary safety judgment is transformed into a continuous risk quantification index. This overcomes the shortcomings of traditional deterministic evaluation methods that ignore load randomness and material variability, improving the reliability of safety evaluation results for fully prestressed concrete bridges.

[0121] This application also provides a bridge structure safety assessment device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the bridge structure safety assessment method in the above embodiment 1.

[0122] The following is for reference. Figure 5 , Figure 5This is a schematic diagram of the bridge structural safety assessment device of this application. The bridge structural safety assessment device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, personal digital assistants (PDAs), tablet computers (PADs), portable media players (PMPs), etc., as well as fixed terminals such as digital TVs, desktop computers, etc. Figure 5 The bridge structural safety assessment device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0123] like Figure 5 As shown, the bridge structure safety assessment device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the bridge structure safety assessment device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the bridge structural safety assessment equipment to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows a bridge structural safety assessment equipment with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0124] The bridge structural safety assessment equipment provided in this application, employing the bridge structural safety assessment method described in the above embodiments, can solve the technical problems of bridge structural safety assessment. Compared with the prior art, the beneficial effects of the bridge structural safety assessment equipment provided in this application are the same as those of the bridge structural safety assessment method provided in the above embodiments, and other technical features of this bridge structural safety assessment equipment are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0125] This application also provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the bridge structure safety assessment method in the above embodiments.

[0126] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0127] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described bridge structure safety assessment method, and is capable of solving the technical problems of the bridge structure safety assessment method. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the bridge structure safety assessment method provided in the above embodiments, and will not be repeated here.

[0128] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other elements in the process, method, article, or system that includes that element.

[0129] The above embodiment numbers are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. They are only some embodiments of this application and do not limit the scope of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included within the protection scope of this application.

Claims

1. A method for assessing the safety of a bridge structure, characterized by, The method includes: Obtain the actual load of the current bridge and input the actual load into the preset bridge structure finite element model to obtain the actual tensile stress of the bottom plate; Obtain the standard tensile stress of the base plate, and determine the current demand ratio based on the actual tensile stress of the base plate and the standard tensile stress of the base plate. The standard tensile stress of the base plate is obtained by inputting the standard load of the current bridge into the preset bridge structure finite element model. Based on the current demand ratio and the current bridge capacity spectrum, determine the probability value that the current demand ratio exceeds the capacity spectrum, wherein the capacity spectrum is obtained by fitting several sets of material simulation parameters and corresponding load proportion coefficients. The probability value is compared with a preset threshold, and the security assessment result is output.

2. The method of claim 1, wherein, The step of obtaining the actual load of the current bridge and inputting the actual load into a preset bridge structure finite element model to obtain the actual tensile stress of the bottom plate includes: The actual vehicle load, actual temperature load, actual wind load, and actual settlement load corresponding to the current bridge are obtained and integrated to obtain the actual load. The actual load is input into the preset bridge structure finite element model and run to obtain the running results. The bridge structure parameters in the preset bridge structure finite element model are preset average values. Based on the running results, the maximum tensile stress value at the bottom plate position of the current bridge is extracted as the actual bottom plate tensile stress.

3. The method as described in claim 1, characterized in that, Before the step of determining the probability value of the current demand ratio exceeding the capacity spectrum based on the current demand ratio and the current bridge capacity spectrum, the method further includes: Obtain the material property parameters of the current bridge, and generate several material simulation parameters based on the material property parameters; Each of the material simulation parameters is input into the preset bridge structure finite element model, and a standard load is applied to the preset bridge structure finite element model. The load proportion coefficient corresponding to each of the material simulation parameters is determined by the proportional loading method. The load proportion coefficient is the ratio of the proportional load to the standard load when the tensile stress of the base plate reaches zero. The capacity spectrum is obtained by fitting the probability distribution of the load proportion coefficients corresponding to all the material simulation parameters.

4. The method as described in claim 3, characterized in that, The step of obtaining the material property parameters of the current bridge and generating several material simulation parameters based on the material property parameters includes: Obtain the material information corresponding to the current bridge, and extract the material property parameters based on the material information. The material property parameters include at least the elastic modulus of concrete, the strength of concrete, and the strength of prestressed tendons. Based on the material property parameters, a combination of material parameters is generated using Monte Carlo simulation as the material simulation parameters.

5. The method as described in claim 3, characterized in that, The step of determining the load proportion coefficient corresponding to each of the material simulation parameters by proportional loading includes: The standard load is applied to the preset bridge structure finite element model with the input material simulation parameters; The standard load is increased by a scaling factor to obtain the corresponding proportional load, and the corresponding tensile stress of the bottom plate in the preset bridge structure finite element model under the proportional load is obtained. The proportionality coefficient corresponding to the zero tensile stress in the base plate is determined as the load proportionality coefficient corresponding to the material simulation parameters.

6. The method as described in claim 1, characterized in that, The step of determining the probability value that the current demand ratio exceeds the capacity spectrum based on the current demand ratio and the current bridge capacity spectrum includes: Obtain the probability density function corresponding to the capability spectrum, wherein the probability density function has a mean parameter and a standard deviation parameter; Using the current demand ratio as the upper limit of integration, the probability density function is integrated over the interval from zero to the upper limit of integration to obtain the probability value.

7. The method as described in claim 1, characterized in that, The step of comparing the probability value with a preset threshold and outputting a security assessment result includes: When the probability value is greater than the preset threshold, an unsafe bridge status signal is output. When the probability value is less than or equal to the preset threshold, a bridge safety status signal is output.

8. A bridge structural safety assessment device, characterized in that, The device includes: The actual load acquisition module is used to acquire the actual load of the current bridge and input the actual load into the preset bridge structure finite element model to obtain the actual tensile stress of the bottom plate. The demand ratio calculation module is used to obtain the standard base plate tensile stress and determine the current demand ratio based on the actual base plate tensile stress and the standard base plate tensile stress. The standard base plate tensile stress is obtained by inputting the current standard load of the bridge into the preset bridge structure finite element model. The probability calculation module is used to determine the probability that the current demand ratio exceeds the current capacity spectrum based on the current demand ratio and the current capacity spectrum of the bridge. The capacity spectrum is obtained by fitting several sets of material simulation parameters and corresponding load proportion coefficients. The security assessment module is used to compare the probability value with a preset threshold and output a security assessment result.

9. A bridge structural safety assessment device, characterized in that, The device includes: a memory, a processor, and a bridge structure safety assessment program stored in the memory and executable on the processor, wherein the bridge structure safety assessment program, when executed by the processor, implements the bridge structure safety assessment method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that, The storage medium stores a bridge structure safety assessment program, which, when executed by a processor, implements the bridge structure safety assessment method as described in any one of claims 1 to 7.

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