Method and system for evaluating anti-overturning performance of single-column pier bridge

Abstract

The invention provides a single-column pier bridge anti-overturning performance evaluation method and system. The method comprises the steps that a corresponding initial overturning performance evaluation algorithm is constructed according to target bridge parameters; determining an anti-overturning performance influence factor of the reinforced single-column pier bridge in real time so as to construct a corresponding factor data set in real time, and determining a target weight corresponding to each factor in the factor data set; calculating a corresponding membership degree vector in real time, and determining a corresponding comprehensive fuzzy evaluation grade in real time according to the directivity of the membership degree vector; a target correction function matched with the comprehensive fuzzy evaluation grade is created in real time according to the comparison result of the anti-overturning coefficients of the single-column pier bridge before reinforcement and after reinforcement; and through the target correction function and the target weight, carrying out correction processing on the anti-overturning coefficient and the initial overturning performance evaluation algorithm of the reinforced single-column pier bridge so as to output an evaluation result. According to the invention, the anti-overturning performance evaluation can be accurately completed, and the working efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge performance evaluation, and in particular to a method and system for evaluating the anti-overturning performance of a single-pillar pier bridge. Background Art

[0002] With the advancement of science and technology and the rapid development of the times, my country has also achieved rapid development in the field of road transportation facilities. Among them, bridges, as an important component of the road network system, have been widely used, which has correspondingly improved the efficiency of road construction.

[0003] Among them, existing single-column pier bridges have been widely used in urban viaducts, interchange hubs and other highway interchange ramps due to their simple structure and convenient construction, to improve vehicle circulation efficiency and shorten mileage.

[0004] Furthermore, with the growth of traffic volume and the rising proportion of heavy-loaded vehicles, the defect of insufficient lateral anti-overturning stability of the structure of existing single-column pier bridges has become increasingly obvious. In addition, whether the existing anti-overturning capacity meets the design requirements depends on many factors such as the original bridge structure and the actual operating load. As a result, the existing single-column pier bridges still have certain safety hazards. Therefore, in view of the shortcomings of the existing technology, it is necessary to provide a method that can objectively and accurately evaluate the anti-overturning performance of single-column pier bridges. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a method and system for evaluating the anti-overturning performance of a single-column pier bridge, so as to provide a method that can objectively and accurately evaluate the anti-overturning performance of a single-column pier bridge.

[0006] The first aspect of the embodiment of the present invention proposes: A method for evaluating the anti-overturning performance of a single-pillar pier bridge, wherein the method comprises: Obtaining target bridge parameters of the reinforced single-column pier bridge, and constructing a corresponding initial overturning performance evaluation algorithm based on the target bridge parameters; In a special load test, the factors affecting the anti-overturning performance of the reinforced single-column pier bridge are determined in real time, so as to construct a corresponding factor data set in real time and determine the target weight corresponding to each factor in the factor data set; Based on a preset fuzzy comprehensive evaluation method, fuzzy and uncertain factors in the target bridge parameters are processed in real time, and a corresponding membership vector is calculated in real time, so as to determine a corresponding comprehensive fuzzy evaluation level in real time according to the directionality of the membership vector; According to the comparison results of the anti-overturning coefficient of the single-column pier bridge before and after reinforcement, a target correction function adapted to the comprehensive fuzzy evaluation level is created in real time, and the anti-overturning coefficient of the reinforced single-column pier bridge and the initial overturning performance evaluation algorithm are corrected by the target correction function and the target weight, so as to output the anti-overturning performance evaluation result of the reinforced single-column pier bridge in real time.

[0007] The beneficial effect of the present invention is that by real-time collection of the target bridge parameters of the reinforced single-column pier bridge, an initial overturning performance evaluation algorithm for subsequent evaluation can be preliminarily constructed. Based on this, in order to improve the accuracy of the subsequent evaluation, a data set of factors that need to be considered in the subsequent evaluation process will also be obtained at this time. Based on this, a target correction function adapted to the current initial overturning performance evaluation algorithm is generated in real time according to the current factor data set, and the current initial overturning performance evaluation algorithm is immediately corrected by the target correction function. Based on this, the anti-overturning performance evaluation result of the current single-column pier bridge can be finally output objectively and accurately, which eliminates the manual evaluation process and improves work efficiency.

[0008] Furthermore, the expression of the initial overturning performance evaluation algorithm is: C S =Z×k in, C S is the anti-overturning performance evaluation score of the single-column pier bridge that has completed the special load test for anti-overturning performance, Z is the fuzzy comprehensive evaluation result based on the special load test, and k is the standard anti-overturning coefficient calculated based on the actual measured value of the test.

[0009] Furthermore, the step of processing the fuzzy and uncertain factors in the target bridge parameters in real time based on a preset fuzzy comprehensive evaluation method, and calculating the corresponding membership vector in real time, so as to determine the corresponding comprehensive fuzzy evaluation level in real time according to the directionality of the membership vector includes: When the target bridge parameters are acquired in real time, the target bridge parameters are correspondingly split into an evaluation set and a factor set, wherein the evaluation set corresponds to the data included in the factor set; Calculating corresponding membership values ​​in real time based on the evaluation set and the factor set through a preset membership function, and converting the membership values ​​into corresponding membership matrices in real time; The membership vector is generated according to the membership matrix, and the comprehensive fuzzy evaluation level is determined according to the membership vector.

[0010] Furthermore, the step of generating the membership vector according to the membership matrix and determining the comprehensive fuzzy evaluation level according to the membership vector includes: When the membership matrix is ​​obtained in real time, normalization calculation is performed on the membership matrix to output the mapping relationship between the evaluation set and the factor set in real time; The mapping relationship and the membership matrix are fused to generate the membership vector in real time, and a corresponding weight set is generated in real time according to the target weight, so as to determine the comprehensive fuzzy evaluation level according to the membership vector and the weight set.

[0011] Furthermore, the step of determining the comprehensive fuzzy evaluation level according to the membership vector and the weight set includes: When the membership vector is obtained in real time, the important factors and the secondary factors are divided in real time according to the size of the membership vector, and whether the difference in weight value between the important factor and the secondary factor is obvious is determined in real time according to the validity judgment method of the maximum membership method; If so, the maximum membership method is corrected by a preset correction algorithm, and the comprehensive fuzzy evaluation level corresponding to each membership vector is determined in real time according to the corrected maximum membership method.

[0012] Furthermore, the expression for determining the validity of the maximum membership method is:

[0013] in, n is the number of evaluation vectors, γ is the normalized value of the second membership degree of the judgment vector, β is the first membership planning value of the evaluation vector.

[0014] Furthermore, the expression of the preset correction algorithm is:

[0015] in, D a is the distance between the judgment value of factor a and the average value, X ai is the score of the i-th factor, is the arithmetic mean of the scores of the i-th factor.

[0016] The second aspect of the embodiment of the present invention proposes: A system for evaluating the anti-overturning performance of a single-pillar pier bridge, wherein the system comprises: an acquisition module, configured to acquire target bridge parameters of the reinforced single-column pier bridge and construct a corresponding initial overturning performance evaluation algorithm based on the target bridge parameters; A processing module is used to determine in real time, during a special load test, factors affecting the anti-overturning performance of the reinforced single-column pier bridge, so as to construct a corresponding factor data set in real time and determine target weights corresponding to the respective factors in the factor data set; a calculation module for processing fuzzy and uncertain factors in the target bridge parameters in real time based on a preset fuzzy comprehensive evaluation method, and calculating a corresponding membership vector in real time, so as to determine a corresponding comprehensive fuzzy evaluation level in real time according to the directionality of the membership vector; The correction module is used to create a target correction function that is adapted to the comprehensive fuzzy evaluation level in real time based on the comparison results of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, and to correct the anti-overturning coefficient of the reinforced single-column pier bridge and the initial overturning performance evaluation algorithm through the target correction function and the target weight, so as to output the anti-overturning performance evaluation results of the reinforced single-column pier bridge in real time.

[0017] Furthermore, the expression of the initial overturning performance evaluation algorithm is: C S =Z×k in, C S is the anti-overturning performance evaluation score of the single-column pier bridge that has completed the special load test for anti-overturning performance, Z is the fuzzy comprehensive evaluation result based on the special load test, and k is the standard anti-overturning coefficient calculated based on the actual measured value of the test.

[0018] Furthermore, the calculation module is specifically used to: When the target bridge parameters are acquired in real time, the target bridge parameters are correspondingly split into an evaluation set and a factor set, wherein the evaluation set corresponds to the data included in the factor set; Calculating corresponding membership values ​​in real time based on the evaluation set and the factor set through a preset membership function, and converting the membership values ​​into corresponding membership matrices in real time; The membership vector is generated according to the membership matrix, and the comprehensive fuzzy evaluation level is determined according to the membership vector.

[0019] Furthermore, the calculation module is specifically used to: When the membership matrix is ​​obtained in real time, normalization calculation is performed on the membership matrix to output the mapping relationship between the evaluation set and the factor set in real time; The mapping relationship and the membership matrix are fused to generate the membership vector in real time, and a corresponding weight set is generated in real time according to the target weight, so as to determine the comprehensive fuzzy evaluation level according to the membership vector and the weight set.

[0020] Furthermore, the calculation module is specifically used to: When the membership vector is obtained in real time, the important factors and the secondary factors are divided in real time according to the size of the membership vector, and whether the difference in weight value between the important factor and the secondary factor is obvious is determined in real time according to the validity judgment method of the maximum membership method; If so, the maximum membership method is corrected by a preset correction algorithm, and the comprehensive fuzzy evaluation level corresponding to each membership vector is determined in real time according to the corrected maximum membership method.

[0021] Furthermore, the expression for determining the validity of the maximum membership method is:

[0022] in, n is the number of evaluation vectors, γ is the normalized value of the second membership degree of the judgment vector, β is the first membership planning value of the evaluation vector.

[0023] Furthermore, the expression of the preset correction algorithm is:

[0024] in, D a is the distance between the judgment value of factor a and the average value, X ai is the score of the i-th factor, is the arithmetic mean of the scores of the i-th factor.

[0025] The third aspect of the embodiment of the present invention proposes: A computer comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for evaluating the anti-overturning performance of a single-column pier bridge as described above is implemented.

[0026] The fourth aspect of the embodiments of the present invention proposes: A readable storage medium stores a computer program thereon, wherein when the program is executed by a processor, the method for evaluating the anti-overturning performance of a single-column pier bridge as described above is implemented.

[0027] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A flow chart of a method for evaluating the anti-overturning performance of a single-pillar pier bridge provided in accordance with the first embodiment of the present invention; Figure 2 This is a structural block diagram of a system for evaluating the anti-overturning performance of a single-pillar pier bridge provided in the third embodiment of the present invention.

[0029] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0030] To facilitate understanding of the present invention, the present invention will be described more fully below with reference to the accompanying drawings. The drawings illustrate several embodiments of the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the present invention.

[0031] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be an intermediate element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or there may be an intermediate element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0033] See also Figure 1 , shown is the anti-overturning performance evaluation method of a single-column pier bridge provided by the first embodiment of the present invention. The anti-overturning performance evaluation method of a single-column pier bridge provided by this embodiment can objectively and accurately evaluate the anti-overturning performance of the single-column pier bridge after reinforcement, thereby eliminating safety hazards.

[0034] Specifically, this embodiment provides: A method for evaluating the anti-overturning performance of a single-pillar pier bridge comprises the following steps: Step S10, obtaining target bridge parameters of the reinforced single-pillar pier bridge, and constructing a corresponding initial overturning performance evaluation algorithm based on the target bridge parameters; Step S20: in the special load test, determining in real time the factors affecting the anti-overturning performance of the reinforced single-column pier bridge, so as to construct a corresponding factor data set in real time, and determining the target weight corresponding to each factor in the factor data set; Step S30: processing the fuzzy and uncertain factors in the target bridge parameters in real time based on a preset fuzzy comprehensive evaluation method, and calculating the corresponding membership vector in real time, so as to determine the corresponding comprehensive fuzzy evaluation level in real time according to the directionality of the membership vector; Step S40: Based on the comparison results of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, a target correction function adapted to the comprehensive fuzzy evaluation level is created in real time, and the anti-overturning coefficient of the reinforced single-column pier bridge and the initial overturning performance evaluation algorithm are corrected by the target correction function and the target weight, so as to output the anti-overturning performance evaluation results of the reinforced single-column pier bridge in real time.

[0035] Second embodiment Furthermore, the expression of the initial overturning performance evaluation algorithm is: C S =Z×k in, C S is the anti-overturning performance evaluation score of the single-column pier bridge that has completed the special load test for anti-overturning performance, Z is the fuzzy comprehensive evaluation result based on the special load test, and k is the standard anti-overturning coefficient calculated based on the actual measured value of the test.

[0036] Furthermore, the step of processing the fuzzy and uncertain factors in the target bridge parameters in real time based on a preset fuzzy comprehensive evaluation method, and calculating the corresponding membership vector in real time, so as to determine the corresponding comprehensive fuzzy evaluation level in real time according to the directionality of the membership vector includes: When the target bridge parameters are acquired in real time, the target bridge parameters are correspondingly split into an evaluation set and a factor set, wherein the evaluation set corresponds to the data included in the factor set; Calculating corresponding membership values ​​in real time based on the evaluation set and the factor set through a preset membership function, and converting the membership values ​​into corresponding membership matrices in real time; The membership vector is generated according to the membership matrix, and the comprehensive fuzzy evaluation level is determined according to the membership vector.

[0037] Furthermore, the step of generating the membership vector according to the membership matrix and determining the comprehensive fuzzy evaluation level according to the membership vector includes: When the membership matrix is ​​obtained in real time, normalization calculation is performed on the membership matrix to output the mapping relationship between the evaluation set and the factor set in real time; The mapping relationship and the membership matrix are fused to generate the membership vector in real time, and a corresponding weight set is generated in real time according to the target weight, so as to determine the comprehensive fuzzy evaluation level according to the membership vector and the weight set.

[0038] Furthermore, the step of determining the comprehensive fuzzy evaluation level according to the membership vector and the weight set includes: When the membership vector is obtained in real time, the important factors and the secondary factors are divided in real time according to the size of the membership vector, and whether the difference in weight value between the important factor and the secondary factor is obvious is determined in real time according to the validity judgment method of the maximum membership method; If so, the maximum membership method is corrected by a preset correction algorithm, and the comprehensive fuzzy evaluation level corresponding to each membership vector is determined in real time according to the corrected maximum membership method.

[0039] Furthermore, the expression for determining the validity of the maximum membership method is:

[0040] in, n is the number of evaluation vectors, γ is the normalized value of the second membership degree of the judgment vector, β is the first membership planning value of the evaluation vector.

[0041] Furthermore, the expression of the preset correction algorithm is:

[0042] in, D a is the distance between the judgment value of factor a and the average value, X ai is the score of the i-th factor, is the arithmetic mean of the scores of the i-th factor.

[0043] The embodiment of the present application provides a method for evaluating the anti-overturning performance of a reinforced single-pillar pier bridge, comprising the following steps: Step S1: Based on the actual on-site structure of the reinforced single-pillar pier bridge, the basic parameters of the bridge structure are determined, and a calculation formula for the anti-overturning performance evaluation score of the single-pillar pier reinforced bridge is constructed.

[0044] Specifically: This step requires determining the data from the special load test and the basic parameters of the bridge structure and materials, and constructing a calculation formula for the anti-overturning performance evaluation score of the single-pillar pier reinforced bridge based on the special load test. The specific expression is:

[0045] Where: C S is the anti-overturning performance evaluation score of the single-column pier reinforced bridge that has completed the special anti-overturning performance load test; Z is the fuzzy comprehensive evaluation result based on the special load test; k is the standard anti-overturning coefficient calculated based on the actual measured value of the test.

[0046] Step S2: Determine the factors affecting the anti-overturning performance of the reinforced single-column pier bridge based on the special load test, construct a factor set, and determine the weight of each factor in the factor set.

[0047] Specifically: The factors influencing the anti-overturning performance of reinforced single-pillar bridges in special load tests were divided into four categories: the test response of the original structure, the test response of the newly reinforced structure, operational load conditions, and operational maintenance measures. The indicators included in each category were determined in turn, and the corresponding influence weights of each factor were calculated.

[0048] Step S3: Using the fuzzy comprehensive evaluation method, process the fuzzy and uncertain information, calculate the membership vector, and determine the comprehensive fuzzy evaluation level according to the directionality of the membership.

[0049] Specifically: The evaluation set V and factor set U are established respectively, and the corresponding membership value is obtained by applying the membership function to the evaluation set V of each factor, and then converted into the membership matrix R. After normalizing the membership matrix R, the relationship R0 from V to U is obtained.

[0050] By establishing a weight set K and assigning corresponding weights to different elements, we can obtain a comprehensive fuzzy evaluation B, where B = K × R. According to the effectiveness judgment method of the maximum membership method, we determine whether the weight values ​​of important factors and minor factors differ significantly. If the difference is significant, the maximum membership method needs to be revised; otherwise, it is not necessary.

[0051] The validity judgment method of the maximum membership method is specifically expressed as follows:

[0052] Where n is the number of evaluation vectors, γ is the normalized value of the second membership of the evaluation vector, and β is the planned value of the first membership of the evaluation vector.

[0053] Definition of L: When L ≥ 1, the maximum membership degree method is very effective; when 0.5 ≤ L < 1, the maximum membership degree method is generally effective; when 0 < L < 0.5, the maximum membership degree method is very inefficient; when L = 0, the maximum membership degree method is invalid. When the effectiveness of the maximum membership degree is less than 0.5, it should be corrected, and the correction formula is as follows:

[0054] In the formula: D a is the distance between the evaluation value of factor a and the average value, X ai is the score of the i-th factor, is the arithmetic mean of the scores of the i-th factor. After correcting to meet the requirements through the above method, determine the comprehensive fuzzy evaluation level according to the membership degree vector.

[0055] Step S4: According to the comparison of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, design the correction functions corresponding to different evaluation levels, use the formula in the current specification to calculate the anti-overturning stability coefficient, and use the corresponding correction function to correct the specification anti-overturning coefficient, and output the anti-overturning performance evaluation result.

[0056] Specifically: In this embodiment, the anti-overturning state of the above single-column pier reinforced bridge is divided into five levels (good, better, medium, poor, dangerous), and according to the comparison of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, design the correction functions corresponding to different evaluation levels, and determine the evaluation level according to the multi-level comprehensive fuzzy evaluation results. According to the specification formula, calculate the anti-overturning coefficient k of the single-column pier bridge. Use the correction function corresponding to the evaluation level to correct the specification anti-overturning coefficient, and output the anti-overturning performance evaluation result.

[0057] The present invention divides the anti-overturning state of the reinforced single-column pier bridge into five evaluation levels of "good, better, medium, poor, dangerous". In order to more scientifically reflect the anti-overturning performance of the bridge under different evaluation levels and provide a quantitative basis for subsequent bridge maintenance and reinforcement, the present invention combines the multi-level comprehensive fuzzy evaluation results and defines the correction function Z<00!00016>. The correction function is used to adjust the specification anti-overturning coefficient, so as to more accurately reflect the actual anti-overturning ability of the bridge. The present invention combines the existing "Code for Inspection and Evaluation of Bearing Capacity of Highway Bridges" (JTGT J21-2011) and "Standard for Evaluation of Technical Condition of Highway Bridges" (JTG / T H21-2011). The specific correction functions are shown in Table 1 below.

[0058] Table 1 Correction function table based on special load test

[0059] Among them: k1 is the anti-overturning stability coefficient of the single-column pier bridge before reinforcement, and k2 is the theoretical value of the anti-overturning stability coefficient of the single-column pier bridge after reinforcement.

[0060] To assess the anti-overturning performance of single-pillar pier reinforced bridges, a comprehensive fuzzy assessment is calculated based on the specific situation, and the bridge's assessment grade is determined. This allows for corrections to the standard anti-overturning coefficient. This allows for an accurate assessment of the bridge's actual anti-overturning performance. This is of great significance for decision-making in the design, construction, and maintenance of single-pillar pier bridge reinforcements.

[0061] To further illustrate an application example of the method proposed in the present invention, a full process for evaluating the anti-overturning bearing capacity of a reinforced single-pillar pier bridge proposed in this application is now added, which specifically includes the following steps: 1) Project Overview: The first section of a single-pillar urban ramp bridge in Wuhan was constructed in 2010. The bridge spans 3 x 25 meters. Piers 1 and 4 are equipped with double GPZ-II 3.0 pot-type rubber bearings, while the remaining two piers are equipped with single GPZ-II 7.0 pot-type rubber bearings. The main girder is a single-chamber box girder with a uniform height of 1.6 meters, a top plate width of 8.5 meters, a flange cantilever length of 2 meters, and a bottom plate width of 4.5 meters. The top of the box girder at mid-span is 24 cm thick, the bottom plate is 22 cm thick, the web is 45 cm thick, the end diaphragms are 1.2 m thick, and the center diaphragms are 1.8 m thick. C50 reinforced concrete is used. 0.5 m thick crash barriers are installed on both sides of the bridge deck, and the deck pavement consists of a 6 cm concrete layer and a 9 cm asphalt concrete layer. The bridge piers are circular columnar. Piers 1 and 4 are double column piers measuring 1.1m x 1.1m, while the others are single column piers measuring 1.3m x 1.3m. They are constructed of C30 reinforced concrete. The vehicle load rating is Highway-I.

[0062] In December 2020, the bridge's single-column pier #3 underwent anti-overturning reinforcement. The pier was encased in steel pipes and connected to a steel cap beam. 200mm thick, slightly expansive concrete was poured between the steel pipes and the original pier. The new steel cap beam is 5.4m long, 2.0m wide, and 1.2m high. Two GBZJ500×500×80 plate rubber bearings, spaced 3.5m apart, were added to the top of the cap beam.

[0063] Special load test plan: Loading vehicle: Use a three-axle truck with a total vehicle weight of 350kN for graded loading.

[0064] Loading location: Based on the parameters such as the bridge component cross-section, material properties, boundary conditions, and design load levels given in the as-built drawings, and referring to relevant specifications, the "MIDAS / Civil" finite element software was used for modeling and analysis.

[0065] 3) Determine the factors influencing the anti-overturning performance of reinforced single-pillar bridges based on special load tests, construct a factor set, and determine the weights of each factor in the factor set. In this case, the analytic hierarchy process (AHP) was used to calculate the factor weights. The specific steps are as follows: After constructing the hierarchical analysis model, the root method was used to calculate the weight values ​​of the judgment matrix factors. After the consistency of the weight vector was verified, the final comprehensive weight index value was output. The final comprehensive weight index values ​​of the second-level indicators are shown in Table 2.

[0066] Table 2 Final comprehensive weight index values

[0067] The final comprehensive weight index value of the third-level indicators can be obtained in the same way and will not be repeated here.

[0068] 4) Use the fuzzy comprehensive evaluation method to process fuzzy and uncertain information, calculate the membership vector, and determine the comprehensive fuzzy evaluation level based on the directionality of the membership. The specific steps are as follows: According to the existing database, the evaluation level of each factor is determined. Based on the determined bridge evaluation indicators, the evaluation vector of each underlying indicator is determined.

[0069] Assign the indicator factor weights to the membership vector, that is, substitute , thus we can get the third-level evaluation index. Combining all the third-level evaluation indexes, we can get the secondary index membership matrix. By allocating factor weights in the same way, we can get the comprehensive fuzzy evaluation membership vector B A1 The result is shown in the following formula:

[0070] Correction of assessment results: Using the above method, we can determine the membership vector of the comprehensive fuzzy assessment of the reinforced single-pillar bridge: {0.547, 0.109, 0.280, 0.048, 0.016}. Based on the maximum membership correction principle, the effectiveness index value is calculated, resulting in L = 0.707. Based on the calculated effectiveness index value, we know that 0.5 ≤ L = 0.707 < 1, so no correction is required. The comprehensive fuzzy assessment membership values ​​of the reinforced single-pillar bridge based on bridge inspection show that the first level is 0.547, the second level is 0.109, the third level is 0.280, the fourth level is 0.048, and the fifth level is 0.016. Based on the maximum membership principle, the comprehensive fuzzy assessment result for this bridge is "good" (first level 0.547).

[0071] 5) Calculation of the final evaluation value of anti-overturning performance. The specific steps are as follows: This step requires verification of support reaction and calculation of anti-overturning stability coefficient.

[0072] The formulas in the Code for Design of Highway Reinforced Concrete and Prestressed Concrete Bridges and Culverts (JTG 3362-2018) were used to verify the support reaction and calculate the anti-overturning stability coefficient. The results are shown in Tables 3 and 4.

[0073] Table 3 Measured support reaction force verification table

[0074] Table 4 Calculation results of the anti-overturning coefficient under the most unfavorable eccentric load condition

[0075] It can be seen that the stability coefficient finally calculated by the above method is 6.01, which is significantly higher than the limit of 2.5 specified in the specification, thus meeting the requirements for the anti-overturning coefficient verification.

[0076] In addition, based on the function corresponding to the comprehensive fuzzy evaluation results in the correction function table, the correction value Z = 1. Combined with the previous calculation, the anti-overturning coefficient k1 of the reinforced single-pillar pier bridge is 6.01. The anti-overturning performance evaluation result of the single-pillar pier reinforced bridge can be calculated as follows:

[0077] The final assessment value of the bridge's anti-overturning performance is 6.01, indicating that the reinforced single-pillar bridge has good overall anti-overturning performance, and that both the original and newly reinforced structures performed well during the test.

[0078] See also Figure 2 , the third embodiment of the present invention provides: A system for evaluating the anti-overturning performance of a single-pillar pier bridge, wherein the system comprises: an acquisition module, configured to acquire target bridge parameters of the reinforced single-column pier bridge and construct a corresponding initial overturning performance evaluation algorithm based on the target bridge parameters; A processing module is used to determine in real time, during a special load test, factors affecting the anti-overturning performance of the reinforced single-column pier bridge, so as to construct a corresponding factor data set in real time and determine target weights corresponding to the respective factors in the factor data set; a calculation module for processing fuzzy and uncertain factors in the target bridge parameters in real time based on a preset fuzzy comprehensive evaluation method, and calculating a corresponding membership vector in real time, so as to determine a corresponding comprehensive fuzzy evaluation level in real time according to the directionality of the membership vector; The correction module is used to create a target correction function that is adapted to the comprehensive fuzzy evaluation level in real time based on the comparison results of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, and to correct the anti-overturning coefficient of the reinforced single-column pier bridge and the initial overturning performance evaluation algorithm through the target correction function and the target weight, so as to output the anti-overturning performance evaluation results of the reinforced single-column pier bridge in real time.

[0079] Furthermore, the expression of the initial overturning performance evaluation algorithm is: C S =Z×k in, C S is the anti-overturning performance evaluation score of the single-column pier bridge that has completed the special load test for anti-overturning performance, Z is the fuzzy comprehensive evaluation result based on the special load test, and k is the standard anti-overturning coefficient calculated based on the actual measured value of the test.

[0080] Furthermore, the calculation module is specifically used to: When the target bridge parameters are acquired in real time, the target bridge parameters are correspondingly split into an evaluation set and a factor set, wherein the evaluation set corresponds to the data included in the factor set; Calculating corresponding membership values ​​in real time based on the evaluation set and the factor set through a preset membership function, and converting the membership values ​​into corresponding membership matrices in real time; The membership vector is generated according to the membership matrix, and the comprehensive fuzzy evaluation level is determined according to the membership vector.

[0081] Furthermore, the calculation module is specifically used to: When the membership matrix is ​​obtained in real time, normalization calculation is performed on the membership matrix to output the mapping relationship between the evaluation set and the factor set in real time; The mapping relationship and the membership matrix are fused to generate the membership vector in real time, and a corresponding weight set is generated in real time according to the target weight, so as to determine the comprehensive fuzzy evaluation level according to the membership vector and the weight set.

[0082] Furthermore, the calculation module is specifically used to: When the membership vector is obtained in real time, the important factors and the secondary factors are divided in real time according to the size of the membership vector, and whether the difference in weight value between the important factor and the secondary factor is obvious is determined in real time according to the validity judgment method of the maximum membership method; If so, the maximum membership method is corrected by a preset correction algorithm, and the comprehensive fuzzy evaluation level corresponding to each membership vector is determined in real time according to the corrected maximum membership method.

[0083] Furthermore, the expression for determining the validity of the maximum membership method is:

[0084] in, n is the number of evaluation vectors, γ is the normalized value of the second membership degree of the judgment vector, β is the first membership planning value of the evaluation vector.

[0085] Furthermore, the expression of the preset correction algorithm is:

[0086] in, D a is the distance between the judgment value of factor a and the average value, X ai is the score of the i-th factor, is the arithmetic mean of the scores of the i-th factor.

[0087] A fourth embodiment of the present invention provides a computer, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the method for evaluating the anti-overturning performance of a single-column pier bridge as described above is implemented.

[0088] A fifth embodiment of the present invention provides a readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the method for evaluating the anti-overturning performance of a single-column pier bridge as described above is implemented.

[0089] In summary, the anti-overturning performance evaluation method and system for a single-column pier bridge provided by the above embodiments of the present invention can objectively and accurately evaluate the anti-overturning performance of a reinforced single-column pier bridge, thereby eliminating potential safety hazards.

[0090] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0091] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0092] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.

[0093] It should be understood that various components of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof may be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0094] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0095] The above-described embodiments merely illustrate several embodiments of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make various modifications and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A method for evaluating the anti-overturning performance of a single-pillar pier bridge, characterized in that: The method comprises: Obtaining target bridge parameters of the reinforced single-column pier bridge, and constructing a corresponding initial overturning performance evaluation algorithm based on the target bridge parameters; In a special load test, the factors affecting the anti-overturning performance of the reinforced single-column pier bridge are determined in real time, so as to construct a corresponding factor data set in real time and determine the target weight corresponding to each factor in the factor data set; Based on a preset fuzzy comprehensive evaluation method, fuzzy and uncertain factors in the target bridge parameters are processed in real time, and a corresponding membership vector is calculated in real time, so as to determine a corresponding comprehensive fuzzy evaluation level in real time according to the directionality of the membership vector; According to the comparison results of the anti-overturning coefficient of the single-column pier bridge before and after reinforcement, a target correction function adapted to the comprehensive fuzzy evaluation level is created in real time, and the anti-overturning coefficient of the reinforced single-column pier bridge and the initial overturning performance evaluation algorithm are corrected by the target correction function and the target weight, so as to output the anti-overturning performance evaluation result of the reinforced single-column pier bridge in real time.

2. The method for evaluating the anti-overturning performance of a single-pillar pier bridge according to claim 1 is characterized in that: The expression of the initial overturning performance evaluation algorithm is: C S =Z×k in, C S is the anti-overturning performance evaluation score of the single-column pier bridge that has completed the special load test for anti-overturning performance, Z is the fuzzy comprehensive evaluation result based on the special load test, and k is the standard anti-overturning coefficient calculated based on the actual measured value of the test.

3. The method for evaluating the anti-overturning performance of a single-pillar pier bridge according to claim 1 is characterized in that: The steps of processing the fuzzy and uncertain factors in the target bridge parameters in real time based on the preset fuzzy comprehensive evaluation method, and calculating the corresponding membership vector in real time, and determining the corresponding comprehensive fuzzy evaluation level in real time according to the directionality of the membership vector include: When the target bridge parameters are acquired in real time, the target bridge parameters are correspondingly split into an evaluation set and a factor set, wherein the evaluation set corresponds to the data included in the factor set; Calculating corresponding membership values ​​in real time based on the evaluation set and the factor set through a preset membership function, and converting the membership values ​​into corresponding membership matrices in real time; The membership vector is generated according to the membership matrix, and the comprehensive fuzzy evaluation level is determined according to the membership vector.

4. The method for evaluating the anti-overturning performance of a single-pillar pier bridge according to claim 3 is characterized in that: The steps of generating the membership vector according to the membership matrix and determining the comprehensive fuzzy evaluation level according to the membership vector include: When the membership matrix is ​​obtained in real time, normalization calculation is performed on the membership matrix to output the mapping relationship between the evaluation set and the factor set in real time; The mapping relationship and the membership matrix are fused to generate the membership vector in real time, and a corresponding weight set is generated in real time according to the target weight, so as to determine the comprehensive fuzzy evaluation level according to the membership vector and the weight set.

5. The method for evaluating the anti-overturning performance of a single-pillar pier bridge according to claim 4 is characterized in that: The step of determining the comprehensive fuzzy evaluation level according to the membership vector and the weight set includes: When the membership vector is obtained in real time, the important factors and the secondary factors are divided in real time according to the size of the membership vector, and whether the difference in weight value between the important factor and the secondary factor is obvious is determined in real time according to the validity judgment method of the maximum membership method; If so, the maximum membership method is corrected by a preset correction algorithm, and the comprehensive fuzzy evaluation level corresponding to each membership vector is determined in real time according to the corrected maximum membership method.

6. The method for evaluating the anti-overturning performance of a single-pillar pier bridge according to claim 5, characterized in that: The expression of the validity judgment method of the maximum membership method is: in, n is the number of evaluation vectors, γ is the normalized value of the second membership degree of the judgment vector, β is the first membership planning value of the evaluation vector.

7. The method for evaluating the anti-overturning performance of a single-pillar pier bridge according to claim 6, characterized in that: The expression of the preset correction algorithm is: in, D a is the distance between the judgment value of factor a and the average value, X ai is the score of the i-th factor, is the arithmetic mean of the scores of the i-th factor.

8. A system for evaluating the anti-overturning performance of a single-pillar pier bridge, characterized in that: The system comprises: an acquisition module, configured to acquire target bridge parameters of the reinforced single-column pier bridge and construct a corresponding initial overturning performance evaluation algorithm based on the target bridge parameters; A processing module is used to determine in real time, during a special load test, factors affecting the anti-overturning performance of the reinforced single-column pier bridge, so as to construct a corresponding factor data set in real time and determine target weights corresponding to the respective factors in the factor data set; a calculation module for processing fuzzy and uncertain factors in the target bridge parameters in real time based on a preset fuzzy comprehensive evaluation method, and calculating a corresponding membership vector in real time, so as to determine a corresponding comprehensive fuzzy evaluation level in real time according to the directionality of the membership vector; The correction module is used to create a target correction function that is adapted to the comprehensive fuzzy evaluation level in real time based on the comparison results of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, and to correct the anti-overturning coefficient of the reinforced single-column pier bridge and the initial overturning performance evaluation algorithm through the target correction function and the target weight, so as to output the anti-overturning performance evaluation results of the reinforced single-column pier bridge in real time.

9. A computer comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for evaluating the anti-overturning performance of a single-column pier bridge according to any one of claims 1 to 7 is implemented.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for evaluating the anti-overturning performance of a single-column pier bridge as described in any one of claims 1 to 7 is implemented.

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