A method and system for evaluating overturning resistance performance of a single-column pier bridge

Abstract

The application provides a single-column pier bridge anti-overturning performance evaluation method and system, which comprises the following steps: constructing an initial overturning performance evaluation algorithm corresponding to target bridge parameters; determining the anti-overturning performance influencing factors of the reinforced single-column pier bridge in real time, constructing a corresponding factor dataset in real time, and determining the target weight corresponding to each factor in the factor dataset; calculating a corresponding membership vector in real time, and determining a comprehensive fuzzy evaluation grade according to the directivity of the membership vector; creating a target correction function adapted to the comprehensive fuzzy evaluation grade according to the comparison result of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, and correcting 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 to output an evaluation result. The application can accurately complete the anti-overturning performance evaluation and improve the work efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of bridge performance evaluation, in particular to a single-column pier bridge anti-overturning performance evaluation method and system. BACKGROUND

[0002] With the progress of science and technology and the rapid development of the times, China has also made rapid development in the field of highway transportation facilities, among which bridges, as an important part of the road network system, have been widely used, which has improved the construction efficiency of the road.

[0003] Among them, the existing single-column pier bridge has been widely used in urban viaducts and expressway interchanges for the purpose of improving the flow efficiency of vehicles and shortening the mileage due to its simple structure and convenient construction.

[0004] Further, with the increase of traffic volume and the increase of heavy vehicle proportion, the defect of insufficient lateral anti-overturning stability of the existing single-column pier bridge is increasingly obvious, and 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, so that the existing single-column pier bridge still has certain safety hazards, therefore, in view of the deficiencies of the prior art, it is necessary to provide a method for objectively and accurately evaluating the anti-overturning performance of the single-column pier bridge. SUMMARY

[0005] Therefore, the purpose of the present application is to provide a single-column pier bridge anti-overturning performance evaluation method and system to provide a method for objectively and accurately evaluating the anti-overturning performance of the single-column pier bridge.

[0006] The first aspect of the embodiment of the present application provides:

[0007] A single-column pier bridge anti-overturning performance evaluation method, wherein the method comprises:

[0008] Obtaining the target bridge parameters of the reinforced single-column pier bridge, and constructing the corresponding initial overturning performance evaluation algorithm according to the target bridge parameters;

[0009] In the special load test, the anti-overturning performance influencing factors of the reinforced single-column pier bridge are determined in real time, the corresponding factor data set is constructed in real time, and the target weight corresponding to each factor in the factor data set is determined;

[0010] Real-time processing of fuzzy and uncertain factors in the target bridge parameters based on a preset fuzzy comprehensive evaluation method, and real-time calculation of the corresponding membership degree vector to determine the corresponding comprehensive fuzzy evaluation grade in real time according to the directivity of the membership degree vector;

[0011] The target correction function adaptive to the comprehensive fuzzy evaluation level is created in real time according to the comparison result of the overturning resistance coefficients of the single-column pier bridge before reinforcement and after reinforcement, and the overturning resistance coefficient of the single-column pier bridge after reinforcement and the initial overturning performance evaluation algorithm are corrected through the target correction function and the target weight, so as to output the overturning performance evaluation result of the single-column pier bridge after reinforcement in real time.

[0012] The beneficial effects of the present application are: the initial overturning performance evaluation algorithm for subsequent evaluation can be initially constructed by real-time acquisition of the target bridge parameter of the single-column pier bridge after reinforcement. In order to improve the accuracy of subsequent evaluation, factor data set to be considered in the process of subsequent evaluation is also acquired at this time. Based on this, the target correction function adaptive 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 through the target correction function. Based on this, the overturning performance evaluation result of the current single-column pier bridge can be finally output objectively and accurately, which corresponds to the process of manual evaluation, and improves the work efficiency.

[0013] Further, the expression of the initial overturning performance evaluation algorithm is:

[0014] C S = Z x k

[0015] Among them, C S Z is the fuzzy comprehensive evaluation result based on the special load test, and k is the standard overturning resistance coefficient calculated based on the test measured value.

[0016] Further, the step of real-time processing the fuzzy and uncertain factors in the target bridge parameter based on the preset fuzzy comprehensive evaluation method and real-time calculating the corresponding membership degree vector to real-time determine the corresponding comprehensive fuzzy evaluation level according to the directivity of the membership degree vector comprises:

[0017] When the target bridge parameter is acquired in real time, the target bridge parameter is split into an evaluation set and a factor set, wherein the data contained in the evaluation set and the factor set correspond to each other;

[0018] The corresponding membership degree value is calculated in real time through the preset membership function according to the evaluation set and the factor set, and the membership degree value is converted into the corresponding membership degree matrix in real time;

[0019] The membership degree vector is generated according to the membership degree matrix, and the comprehensive fuzzy evaluation level is determined according to the membership degree vector.

[0020] Further, the step of generating the membership vector according to the membership matrix and determining the comprehensive fuzzy evaluation grade according to the membership vector comprises:

[0021] When the membership matrix is acquired in real time, the membership matrix is normalized to output the mapping relationship between the evaluation set and the factor set in real time;

[0022] 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 grade according to the membership vector and the weight set.

[0023] Further, the step of determining the comprehensive fuzzy evaluation grade according to the membership vector and the weight set comprises:

[0024] When the membership vector is acquired in real time, the important factors and the secondary factors are divided in real time according to the size of the membership vector, and the weight value difference between the important factors and the secondary factors is determined in real time according to the effectiveness discrimination method of the maximum membership degree method;

[0025] If yes, the maximum membership degree method is modified through a preset modification algorithm, and the comprehensive fuzzy evaluation grade corresponding to each membership vector is determined in real time according to the modified maximum membership degree method.

[0026] Further, the expression of the effectiveness discrimination method of the maximum membership degree method is:

[0027]

[0028] Wherein, n is the number of evaluation vectors, γ is the second membership normalization value of the evaluation vector, β is the first membership planning value of the evaluation vector.

[0029] Further, the expression of the preset modification algorithm is:

[0030]

[0031] Wherein, D a is the distance between the evaluation value of the factor a and the average value, X ai is the score of the i th factor, is the arithmetic mean of the score of the i th factor.

[0032] The second aspect of the embodiment of the present application provides:

[0033] A system for evaluating the anti-overturning performance of a single-column pier bridge, wherein the system comprises:

[0034] An acquisition module configured to acquire target bridge parameters of the reinforced single-column pier bridge and construct an initial anti-overturning performance evaluation algorithm corresponding to the target bridge parameters;

[0035] A processing module configured to determine, in a special load test, factors influencing the anti-overturning performance of the reinforced single-column pier bridge, construct a factor dataset corresponding to the factors in real time, and determine target weights corresponding to the factors in the factor dataset respectively;

[0036] A calculation module configured to process fuzzy and uncertain factors in the target bridge parameters in real time based on a preset fuzzy comprehensive evaluation method, calculate a membership vector corresponding to the target bridge parameters in real time, and determine a comprehensive fuzzy evaluation grade corresponding to the membership vector based on the directionality of the membership vector;

[0037] A correction module configured to create a target correction function corresponding to the comprehensive fuzzy evaluation grade based on a comparison result of anti-overturning coefficients of the single-column pier bridge before and after reinforcement, and correct the anti-overturning coefficient of the reinforced single-column pier bridge and the initial anti-overturning performance evaluation algorithm based on the target correction function and the target weights, so as to output an anti-overturning performance evaluation result of the reinforced single-column pier bridge.

[0038] Further, the expression of the initial anti-overturning performance evaluation algorithm is:

[0039] C S = Z x k

[0040] wherein, C S is an anti-overturning performance evaluation score of the single-column pier bridge that has completed a special load test, Z is a fuzzy comprehensive evaluation result based on the special load test, and k is a standard anti-overturning coefficient calculated based on a test measured value.

[0041] Further, the calculation module is specifically configured to:

[0042] When the target bridge parameters are acquired in real time, the target bridge parameters are split into an evaluation set and a factor set, wherein the evaluation set and the factor set correspond to data contained therein;

[0043] A preset membership function is used to calculate a membership value corresponding to the evaluation set and the factor set in real time, and the membership value is converted into a membership matrix in real time;

[0044] generate the membership vector according to the membership matrix, and determine the comprehensive fuzzy evaluation grade according to the membership vector.

[0045] Further, the calculation module is specifically configured to:

[0046] when the membership matrix is acquired in real time, perform normalization calculation on the membership matrix to output the mapping relationship between the evaluation set and the factor set in real time;

[0047] fuse the mapping relationship and the membership matrix to generate the membership vector in real time, generate a corresponding weight set according to the target weight in real time, and determine the comprehensive fuzzy evaluation grade according to the membership vector and the weight set.

[0048] Further, the calculation module is specifically configured to:

[0049] when the membership vector is acquired in real time, divide important factors and secondary factors according to the size of the membership vector in real time, and determine whether the weight value difference between the important factors and the secondary factors is obvious according to the effectiveness discrimination method of the maximum membership degree method in real time.

[0050] If yes, the maximum membership degree method is modified through a preset modification algorithm, and the comprehensive fuzzy evaluation grade corresponding to each membership vector is determined in real time according to the modified maximum membership degree method.

[0051] Further, the expression of the effectiveness discrimination method of the maximum membership degree method is:

[0052]

[0053] wherein, n is the number of evaluation vectors, γ is the second membership degree normalized value of the evaluation vector, β is the first membership degree planning value of the evaluation vector.

[0054] Further, the expression of the preset modification algorithm is:

[0055]

[0056] wherein, D a is the distance between the evaluation value of the factor a and the average value, X ai is the score of the i-th factor, is the arithmetic mean of the score of the i-th factor.

[0057] The third aspect of the embodiments of the present application provides a method for evaluating overturning resistance performance of a single-column pier bridge.

[0058] A computer comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for evaluating overturning resistance performance of a single-column pier bridge as described above when executing the computer program.

[0059] The fourth aspect of the embodiments of the present application provides a computer program product comprising a computer program for evaluating overturning resistance performance of a single-column pier bridge.

[0060] A readable storage medium having a computer program stored thereon, wherein the program is executable by a processor to implement the method for evaluating overturning resistance performance of a single-column pier bridge as described above.

[0061] Additional aspects and advantages of the present application will be made apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 A flow chart of the method for evaluating overturning resistance performance of a single-column pier bridge provided by the first embodiment of the present application;

[0063] Figure 2 A structural block diagram of the system for evaluating overturning resistance performance of a single-column pier bridge provided by the third embodiment of the present application.

[0064] The following detailed description will further describe the present application with reference to the above-mentioned drawings. DETAILED DESCRIPTION

[0065] In order to facilitate the understanding of the present application, the present application will be described more fully below with reference to the accompanying drawings. The drawings show several embodiments of the present application. However, the present application can be realized in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present application more thorough and comprehensive.

[0066] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can be a middle element. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or there can be a middle element. The terms "vertical", "horizontal", "left", "right", and similar expressions used herein are for illustrative purposes only.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description herein is for describing particular embodiments only and is not intended to be limiting of the application. The use herein of the terms "and / or" includes a set of one or more associated listed items.

[0068] Referring to Figure 1 , a single-column pier bridge anti-overturning performance evaluation method provided by the first embodiment of the application is shown. The single-column pier bridge anti-overturning performance evaluation method provided by the embodiment can objectively and accurately evaluate the anti-overturning performance of the reinforced single-column pier bridge, thereby eliminating the safety hazard.

[0069] Specifically, the embodiment provides:

[0070] A single-column pier bridge anti-overturning performance evaluation method, specifically comprising the following steps:

[0071] Step S10, obtaining a target bridge parameter of the reinforced single-column pier bridge, and constructing a corresponding initial overturning performance evaluation algorithm according to the target bridge parameter;

[0072] Step S20, in a special load test, determining in real time an anti-overturning performance influencing factor of the reinforced single-column pier bridge, constructing in real time a corresponding factor data set, and determining a target weight corresponding to each factor in the factor data set;

[0073] Step S30, processing in real time fuzzy and uncertain factors in the target bridge parameter based on a preset fuzzy comprehensive evaluation method, and calculating in real time a corresponding membership degree vector, so as to determine in real time a comprehensive fuzzy evaluation grade according to the directivity of the membership degree vector;

[0074] Step S40, creating in real time a target correction function adapted to the comprehensive fuzzy evaluation grade according to a comparison result of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, and correcting 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 in real time an anti-overturning performance evaluation result of the reinforced single-column pier bridge.

[0075] Second embodiment

[0076] Further, the expression of the initial overturning performance evaluation algorithm is:

[0077] C S = Z x k

[0078] wherein, CS For the completed anti-overturning performance special load test of single column pier bridge, the anti-overturning performance evaluation score is Z, the fuzzy comprehensive evaluation result based on the special load test is k, and the specification anti-overturning coefficient calculated based on the test measured value is k.

[0079] Further, the step of real-time processing the fuzzy and uncertain factors in the target bridge parameters based on the preset fuzzy comprehensive evaluation method and real-time calculating the corresponding membership degree vector to determine the corresponding comprehensive fuzzy evaluation grade according to the directivity of the membership degree vector comprises:

[0080] 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 data contained in the evaluation set and the factor set correspond;

[0081] The corresponding membership degree value is calculated in real time through a preset membership function according to the evaluation set and the factor set, and the membership degree value is converted into a corresponding membership degree matrix in real time;

[0082] The membership degree vector is generated according to the membership degree matrix, and the comprehensive fuzzy evaluation grade is determined according to the membership degree vector.

[0083] Further, the step of generating the membership degree vector according to the membership degree matrix and determining the comprehensive fuzzy evaluation grade according to the membership degree vector comprises:

[0084] When the membership degree matrix is acquired in real time, the membership degree matrix is normalized to output the mapping relationship between the evaluation set and the factor set in real time;

[0085] The mapping relationship and the membership degree matrix are fused to generate the membership degree vector in real time, and a corresponding weight set is generated according to the target weight in real time, so as to determine the comprehensive fuzzy evaluation grade according to the membership degree vector and the weight set.

[0086] Further, the step of determining the comprehensive fuzzy evaluation grade according to the membership degree vector and the weight set comprises:

[0087] When the membership degree vector is acquired in real time, the important factors and the secondary factors are divided according to the size of the membership degree vector in real time, and the weight value difference between the important factors and the secondary factors is determined according to the effectiveness discrimination method of the maximum membership degree method in real time;

[0088] If yes, the maximum membership degree method is modified by a preset modification algorithm, and a comprehensive fuzzy evaluation grade corresponding to each membership degree vector is determined in real time according to the modified maximum membership degree method.

[0089] Further, the expression of the validity discrimination method of the maximum membership degree method is:

[0090]

[0091] wherein, n is the number of evaluation vectors, γ is the normalized value of the second membership degree of the evaluation vector, β is the planning value of the first membership degree of the evaluation vector.

[0092] Further, the expression of the preset modification algorithm is:

[0093]

[0094] wherein, D a is the distance between the evaluation value of the factor a and the average value, X ai is the score of the ith factor, is the arithmetic mean of the score of the ith factor.

[0095] The method for evaluating the anti-overturning performance of a single-column pier bridge after reinforcement provided by the embodiment of the application comprises the following steps:

[0096] Step S1: determining the basic parameters of the bridge structure according to the actual structure of the reinforced single-column pier bridge, and constructing a calculation formula of the anti-overturning performance evaluation score of the reinforced single-column pier bridge.

[0097] Specifically,

[0098] This step needs to determine the data of the special load test and the basic parameters of the bridge structure and materials, and construct a calculation formula of the anti-overturning performance evaluation score of the reinforced single-column pier bridge based on the special load test, and the specific expression is:

[0099]

[0100] wherein: C S is the anti-overturning performance evaluation score of the reinforced single-column pier bridge that has completed the anti-overturning performance special load test; 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 measured value of the test.

[0101] Step S2: determining the anti-overturning performance influencing factors of the reinforced single-column pier bridge based on the special load test, constructing a factor set, and determining the weight of each factor in the factor set.

[0102] Specifically,

[0103] The factors influencing the anti-overturning performance of the reinforced single-column pier bridge in the special load test are divided into four categories, namely, the original structure test response, the newly added reinforcement structure test response, the operation load condition, and the operation and maintenance measures.

[0104] Step S3: Using the fuzzy comprehensive evaluation method, process the fuzzy and uncertain information, calculate the membership degree vector, and determine the comprehensive fuzzy evaluation level according to the membership degree directionality.

[0105] Specifically,

[0106] The evaluation set V and the factor set U are established respectively, the membership degree value is obtained by applying the membership function calculation to the evaluation set V of each factor, and then the membership degree matrix R is converted. After normalizing the membership degree matrix R, the relationship R0 from V to U is obtained.

[0107] The weight set K is established to assign corresponding weights to different elements, and the comprehensive fuzzy evaluation B is obtained, and B=K×R. According to the effectiveness discrimination method of the maximum membership degree method, it is determined whether the weight values between important factors and secondary factors are significantly different. If they are significantly different, the maximum membership degree method needs to be modified, otherwise it does not need to be modified.

[0108] The specific expression of the effectiveness discrimination method of the maximum membership degree method is:

[0109]

[0110] In the formula, n is the number of evaluation vectors, γ is the normalized value of the second membership degree of the evaluation vector, and β is the planning value of the first membership degree of the evaluation vector.

[0111] 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 low efficient; 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 modified, and the modification formula is as follows:

[0112]

[0113] 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, The arithmetic mean of the score of the i-th factor is obtained.

[0114] Step S4: According to the comparison of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, a correction function corresponding to different evaluation levels is designed, the anti-overturning stability coefficient is calculated by using the formula in the existing specification, the anti-overturning coefficient in the specification is corrected by using the corresponding correction function, and the anti-overturning performance evaluation result is output.

[0115] Specifically,

[0116] The anti-overturning state of the single-column pier bridge is divided into five levels (good, better, medium, worse, and dangerous), and according to the comparison of the anti-overturning coefficients of the single-column pier bridge before and after reinforcement, a correction function corresponding to different evaluation levels is designed, and the evaluation level is determined according to the multi-level comprehensive fuzzy evaluation result. According to the specification formula, the anti-overturning coefficient k of the single-column pier bridge is calculated. The anti-overturning performance evaluation result is output by using the correction function corresponding to the evaluation level to correct the anti-overturning coefficient in the specification.

[0117] The anti-overturning state of the reinforced single-column pier bridge is divided into five evaluation levels: good, better, medium, worse, and dangerous. In order to more scientifically reflect the anti-overturning performance of the bridge under different evaluation levels and provide quantitative basis for subsequent bridge maintenance and reinforcement, the present application defines a correction function Z corresponding to the above five levels in combination with the multi-level comprehensive fuzzy evaluation result. i The correction function is used to adjust the anti-overturning coefficient in the specification, so as to more accurately reflect the actual anti-overturning capacity of the bridge. The present application combines the existing "Highway Bridge Bearing Capacity Detection and Evaluation Regulations" (JTGTJ21-2011) and "Highway Bridge Technical Condition Evaluation Standard" (JTG / TH21-2011) to correct the function as shown in Table 1.

[0118] Table 1 Correction function table based on special load test

[0119]

[0120] Wherein: 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.

[0121] For evaluating the anti-overturning performance of the single-column pier reinforced bridge, according to the corresponding situation, the comprehensive fuzzy evaluation result is calculated and the bridge evaluation level is located, and the anti-overturning coefficient in the specification is corrected. The actual anti-overturning performance of the bridge can be accurately judged. It has great significance for the reinforcement design, construction and maintenance decision of the single-column pier bridge.

[0122] To further illustrate the application examples of the method of the present application, a full process for evaluating the post-strengthening overturning resistance capacity of a single-column pier bridge is supplemented, which specifically includes the following steps:

[0123] 1) Project overview:

[0124] The first link of a single-column pier urban ramp bridge in Wuhan City was built in 2010, and the bridge has a span of 3x25m. Double bearings are provided at 1# and 4# piers, and the type is GPZ-II 3.0 pot-type rubber bearing. The remaining two piers are provided with single bearings, and the type is GPZ-II 7.0 pot-type rubber bearing. The main girder is an equal-height single-box single-room box girder, with a girder height of 1.6m, a top plate width of 8.5m, a wing flange cantilever length of 2m, and a bottom plate width of 4.5m. The thickness of the top plate of the mid-span box girder is 24cm, the thickness of the bottom plate is 22cm, the thickness of the web plate is 45cm, the thickness of the end diaphragm is 1.2m, and the thickness of the middle diaphragm is 1.8m. C50 ordinary reinforced concrete is used. A 0.5m crash barrier is provided on both sides of the bridge deck, and the bridge deck pavement is 6cm of concrete layer + 9cm of asphalt concrete. The bridge piers are circular column piers, 1# and 4# piers use 1.1m x 1.1m double-column piers, and the remaining piers use 1.3m x 1.3m single-column piers, which are made of C30 reinforced concrete. The vehicle load level is highway-I level.

[0125] In December 2020, the 3# single-column pier of the bridge was subjected to anti-overturning reinforcement and reconstruction, and the reconstruction method was to wrap the pier body with a steel pipe and connect a steel cap beam, and 200mm thick micro-expanding concrete was poured between the steel pipe and the original pier column. The newly added steel cap beam is 5.4m long, 2.0m wide, and 1.2m high, and two GBZJ500x500x80 type plate-type rubber bearings with a spacing of 3.5m are newly added on the top of the cap beam.

[0126] Special load test scheme:

[0127] Loading vehicle: a three-axle load vehicle with a total weight of 350kN is used for staged loading.

[0128] Loading position: based on the bridge component cross section, material properties, boundary conditions, design load level and other parameters given in the as-built drawings, and referring to relevant specifications, the "MIDAS / Civil" finite element software is used for modeling analysis.

[0129] 3) Determine the factors affecting the anti-overturning performance of the reinforced single-column pier bridge based on the special load test, construct the factor set, and determine the weight of each factor in the factor set. In this case, the factor weight is calculated by the analytic hierarchy process, and the specific steps are as follows:

[0130] After constructing the analytic hierarchy model, the root method is used to calculate the weight value of the judgment matrix, and the weight vector is checked for consistency before outputting the final comprehensive weight index value. The final comprehensive weight index value of the second layer index is shown in Table 2.

[0131] Table 2 Final comprehensive weight index value

[0132]

[0133] The final comprehensive weight index value of the third layer index can be obtained in the same way, which will not be described here.

[0134] 4) Fuzzy comprehensive evaluation method is used to process fuzzy and uncertain information, calculate membership vectors, and determine the comprehensive fuzzy evaluation level according to the membership direction. The specific steps are as follows:

[0135] According to the existing database, the evaluation level of each factor is determined. Based on the determined bridge evaluation index, the evaluation vector of each bottom layer index is determined.

[0136] The index factor weight is distributed to the membership vector, that is, , so that the third layer evaluation index can be obtained. By integrating all the third layer evaluation indexes, the secondary index membership matrix can be obtained. By distributing the factor weight in the same way, the comprehensive fuzzy evaluation membership vector B A1 can be obtained. The result is as follows:

[0137]

[0138] Evaluation result correction:

[0139] Through the above method, the current reinforced single column pier bridge comprehensive fuzzy evaluation membership vector is obtained as {0.547, 0.109, 0.280, 0.048, 0.016}. According to the correction principle of the maximum membership degree, the effectiveness index value L=0.707 is calculated. According to the calculated effectiveness index value, it can be seen that 0.5≤L=0.707<1, and no correction is needed. From the reinforced single column pier bridge comprehensive fuzzy evaluation membership value based on bridge detection, it can be seen 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. According to the maximum membership principle, the comprehensive fuzzy evaluation result of the bridge is "good" (first level 0.547).

[0140] 5) The final evaluation value of the anti-overturning performance is calculated as follows:

[0141] This step needs to perform support reaction calculation and calculate the anti-overturning stability coefficient.

[0142] The formula in the specification "Design Code for Highway Reinforced Concrete and Prestressed Concrete Bridges and Culverts" (JTG 3362-2018) is used to calculate the support reaction and calculate the anti-overturning stability coefficient. The results are shown in Tables 3 and 4.

[0143] Table 3 measured support reaction checking table

[0144]

[0145] Table 4 the most unfavorable partial load working condition anti-overturning coefficient checking result

[0146]

[0147] From it, the stability coefficient finally calculated by the above-mentioned mode is 6.01, which is obviously higher than the limit value of 2.5 specified in the specification, thereby meeting the anti-overturning coefficient checking requirement.

[0148] In addition, according to the function corresponding to the comprehensive fuzzy evaluation result in the correction function table, the correction value Z = 1 can be calculated. Combined with the anti-overturning coefficient k1 of the reinforced single-column pier bridge calculated in the foregoing, the anti-overturning performance evaluation result of the single-column pier reinforced bridge can be calculated, and the specific expression is:

[0149]

[0150] According to the above formula, the final evaluation value of the anti-overturning performance of the bridge is 6.01. This shows that the overall anti-overturning performance of the reinforced single-column pier bridge is good, and the original structure and the newly added reinforced structure show a good working state in the test process.

[0151] Please refer to Figure 2 The third embodiment of the present application provides:

[0152] An anti-overturning performance evaluation system of a single-column pier bridge, wherein the system comprises:

[0153] An acquisition module is configured to acquire target bridge parameters of a reinforced single-column pier bridge, and construct an initial overturning performance evaluation algorithm corresponding to the target bridge parameters;

[0154] A processing module is configured to determine, in a special load test, an anti-overturning performance influencing factor of the reinforced single-column pier bridge in real time, to construct a corresponding factor dataset in real time, and determine a target weight corresponding to each factor in the factor dataset;

[0155] A calculation module is configured to process fuzzy and uncertain factors in the target bridge parameters in real time based on a preset fuzzy comprehensive evaluation method, and calculate a corresponding membership degree vector in real time, to determine a corresponding comprehensive fuzzy evaluation grade in real time according to the directivity of the membership degree vector;

[0156] The correction module is configured to create a target correction function adaptive to the comprehensive fuzzy evaluation grade according to a comparison result of the overturning resistance coefficients of the single-column pier bridge before reinforcement and after reinforcement, and correct the overturning resistance coefficient of the single-column pier bridge after reinforcement and the initial overturning performance evaluation algorithm by using the target correction function and the target weight, so as to output the overturning performance evaluation result of the single-column pier bridge after reinforcement in real time.

[0157] Further, the expression of the initial overturning performance evaluation algorithm is as follows:

[0158] C S = Z x k

[0159] wherein, C S Z is a fuzzy comprehensive evaluation result based on the special load test, and k is a standard overturning resistance coefficient calculated based on the test measured value.

[0160] Further, the calculation module is specifically configured to:

[0161] When the target bridge parameter is acquired in real time, the target bridge parameter is split into an evaluation set and a factor set, wherein the data contained in the evaluation set and the factor set correspond to each other.

[0162] The membership degree value corresponding to the evaluation set and the factor set is calculated in real time by using a preset membership function, and the membership degree value is converted into a corresponding membership degree matrix in real time.

[0163] The membership degree vector is generated according to the membership degree matrix, and the comprehensive fuzzy evaluation grade is determined according to the membership degree vector.

[0164] Further, the calculation module is specifically configured to:

[0165] When the membership degree matrix is acquired in real time, the membership degree matrix is normalized to output the mapping relationship between the evaluation set and the factor set in real time.

[0166] The mapping relationship and the membership degree matrix are fused to generate the membership degree vector in real time, and a corresponding weight set is generated according to the target weight, so as to determine the comprehensive fuzzy evaluation grade according to the membership degree vector and the weight set.

[0167] Further, the calculation module is specifically configured to:

[0168] When the membership vectors are acquired in real time, the important factors and the secondary factors are divided in real time according to the size of the membership vectors, and whether the weight value difference between the important factors and the secondary factors is obvious is determined in real time according to the validity discrimination method of the maximum membership degree method.

[0169] If yes, the maximum membership degree method is modified through a preset modification algorithm, and the comprehensive fuzzy evaluation grade corresponding to each membership vector is determined in real time according to the modified maximum membership degree method.

[0170] Further, the expression of the validity discrimination method of the maximum membership degree method is:

[0171]

[0172] Among them, n is the number of evaluation vectors, γ is the second membership degree normalized value of the evaluation vector, β is the first membership degree planning value of the evaluation vector.

[0173] Further, the expression of the preset modification algorithm is:

[0174]

[0175] Among them, D a is the distance between the evaluation value of the factor a and the average value, X ai is the score of the i th factor, is the arithmetic mean of the score of the i th factor.

[0176] The fourth embodiment of the present application provides a computer, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the single-column pier bridge anti-overturning performance evaluation method as described above when executing the computer program.

[0177] The fifth embodiment of the present application provides a readable storage medium, which stores a computer program, wherein the program is executed by a processor to implement the single-column pier bridge anti-overturning performance evaluation method as described above.

[0178] In summary, the single-column pier bridge anti-overturning performance evaluation method and system provided by the above embodiments of the present application can objectively and accurately evaluate the anti-overturning performance of the reinforced single-column pier bridge, thereby eliminating the safety hazards.

[0179] It should be noted that the above-mentioned various modules can be functional modules or program modules, which can be implemented by software or hardware. For the modules implemented by hardware, the above-mentioned various modules can be located in the same processor; or the above-mentioned various modules can also be located in different processors in any combination.

[0180] The logic and / or steps represented in the flowcharts and / or otherwise described herein, for example, can be considered as a list of executable instructions for implementing logic functions, and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor- based system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions, or a combination of the above. For the purposes of this specification, a "computer-readable medium" can be any apparatus that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

[0181] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection (electronic) having one or more wires, a portable computer diskette (magnetic), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium can even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, for example, by optically scanning the paper or other suitable medium, then electronically converted into a form that is suitable for use in a computer storage medium.

[0182] It should be understood that parts of the present application can be realized by hardware, software, firmware or a combination thereof. In the above-described embodiments, a plurality of steps or methods can be realized by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if realized by hardware, and as in another embodiment, any one or a combination of the following technologies known in the art can be used: discrete logic circuitry having logic gates for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), etc.

[0183] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0184] The above-described embodiments only express several implementation manners of the present application, which are described in a more specific and detailed manner, but cannot be understood as a limitation on the scope of the present application. It should be noted that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present application, which are all within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A method for evaluating overturning resistance performance of a single-column-pier bridge, characterized by, The method comprises: acquiring the target bridge parameter of the reinforced single-column pier bridge, and constructing the corresponding initial overturning performance evaluation algorithm according to the target bridge parameter; in the special load test, the anti-overturning performance influencing factors of the reinforced single-column pier bridge are determined in real time, the corresponding factor dataset is constructed in real time, and the target weight corresponding to each factor in the factor dataset is determined; the fuzzy and uncertain factors in the target bridge parameter are processed in real time based on the preset fuzzy comprehensive evaluation method, the corresponding membership degree vector is calculated in real time, and the corresponding comprehensive fuzzy evaluation grade is determined in real time according to the directivity of the membership degree vector; the target correction function adaptive to 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 and after reinforcement, and the anti-overturning coefficient of the reinforced single-column pier bridge and the initial overturning performance evaluation algorithm are corrected and processed through 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; the expression of the initial overturning performance evaluation algorithm is: C S Z=k wherein, C S is the overturning resistance performance evaluation score of the single-column pier bridge that has completed the special load test, Z is the fuzzy comprehensive evaluation result based on the special load test, and k is the specification overturning resistance coefficient calculated based on the measured value.

2. The method of claim 1, wherein: the step of processing the fuzzy and uncertain factors in the target bridge parameter in real time based on the preset fuzzy comprehensive evaluation method, and calculating the corresponding membership degree vector in real time, and determining the corresponding comprehensive fuzzy evaluation grade in real time according to the directivity of the membership degree vector comprises: when the target bridge parameter is acquired in real time, the target bridge parameter is split into an evaluation set and a factor set, wherein the data contained in the evaluation set and the factor set correspond to each other; the membership degree value is calculated in real time according to the evaluation set and the factor set through a preset membership function, and the membership degree value is converted into a corresponding membership degree matrix in real time; the membership degree vector is generated according to the membership degree matrix, and the comprehensive fuzzy evaluation grade is determined according to the membership degree vector.

3. The method of claim 2, wherein: the step of generating the membership degree vector according to the membership degree matrix, and determining the comprehensive fuzzy evaluation grade according to the membership degree vector comprises: when the membership degree matrix is acquired in real time, the membership degree matrix is normalized to output the mapping relationship between the evaluation set and the factor set in real time; the mapping relationship and the membership degree matrix are fused to generate the membership degree 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 grade according to the membership degree vector and the weight set.

4. The method of claim 3, wherein: the step of determining the comprehensive fuzzy evaluation grade according to the membership degree vector and the weight set comprises: when the membership degree vector is acquired in real time, the important factors and the secondary factors are divided according to the size of the membership degree vector in real time, and the weight value difference between the important factors and the secondary factors is determined according to the effectiveness discrimination method of the maximum membership degree method in real time. If yes, the maximum membership degree method is modified by a preset modification algorithm, and a comprehensive fuzzy evaluation grade corresponding to each membership degree vector is determined in real time according to the modified maximum membership degree method.

5. The method of claim 4, wherein: The expression of the effectiveness discrimination method of the maximum membership degree method is: wherein, n is the number of evaluation vectors, The expression of the preset modification algorithm is: is the second membership degree normalized value of the evaluation vector, β is the first membership degree planning value of the evaluation vector.

6. The method of claim 5, wherein: The system comprises: wherein, D a is the distance of the evaluation value of the factor a from 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.

7. A system for evaluating the overturning resistance of a single-column pier bridge, characterized in that, An acquisition module is configured to acquire a target bridge parameter of the reinforced single-column pier bridge, and construct an initial overturning performance evaluation algorithm corresponding to the target bridge parameter; A processing module is configured to determine, in a special load test, an anti-overturning performance influencing factor of the reinforced single-column pier bridge in real time, construct a corresponding factor data set in real time, and determine a target weight corresponding to each factor in the factor data set; A calculation module is configured to process fuzzy and uncertain factors in the target bridge parameter in real time based on a preset fuzzy comprehensive evaluation method, calculate a corresponding membership degree vector in real time, and determine a corresponding comprehensive fuzzy evaluation grade according to a directivity of the membership degree vector; A modification module is configured to create a target modification function adapted to the comprehensive fuzzy evaluation grade according to a comparison result of anti-overturning coefficients of the single-column pier bridge before and after reinforcement, and modify the anti-overturning coefficient of the reinforced single-column pier bridge and the initial overturning performance evaluation algorithm by using the target modification function and the target weight, so as to output an anti-overturning performance evaluation result of the reinforced single-column pier bridge in real time; The expression of the initial overturning performance evaluation algorithm is: Z = Z x k C S The processor executes the computer program to implement the single-column pier bridge anti-overturning performance evaluation method in any one of claims 1 to 6. wherein, C S is the overturning resistance performance evaluation score of the single-column pier bridge that has completed the special load test, Z is the fuzzy comprehensive evaluation result based on the special load test, and k is the specification overturning resistance coefficient calculated based on the measured value.

8. A computer comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, The program is executed by the processor to implement the single-column pier bridge anti-overturning performance evaluation method in any one of claims 1 to 6.

9. A readable storage medium, having stored thereon a computer program, characterized in that, ​

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