A method for analyzing test data of reinforced concrete integral bonding performance

Abstract

The present invention relates to the field of data analysis technology, and in particular to a method for analyzing reinforced concrete overall bonding performance test data. The method comprises: obtaining characteristic weight values ​​of each sub-curve in a first sub-curve set and characteristic weight values ​​of each sub-curve in a second sub-curve set, performing weighted fusion on each sub-curve in the sub-curve set according to the characteristic weight values ​​of each sub-curve in the first sub-curve set and the characteristic weight values ​​of each sub-curve in the second sub-curve set, obtaining a target bonding stress-slip curve, and obtaining bonding performance analysis results of a batch to be tested according to the target bonding stress-slip curve. The present invention can improve the accuracy and reliability of analyzing or evaluating the bonding performance of a batch of reinforced concrete to be tested.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a method for analyzing reinforced concrete overall bonding performance test data. Background Art

[0002] Since the bonding performance of prefabricated reinforced concrete is directly related to the safety and durability of the structure, many manufacturers currently obtain the bonding performance test data of reinforced concrete through implementation after producing reinforced concrete, and then evaluate the bonding performance of reinforced concrete by analyzing the obtained bonding performance test data, so as to ensure that the reinforced concrete put into use subsequently meets the bonding performance requirements and prevent the occurrence of engineering accidents. Therefore, it is very important to detect and analyze the bonding performance of prefabricated reinforced concrete.

[0003] ‌Since prefabricated reinforced concrete is a prefabricated reinforced concrete component produced in a factory, in order to reduce the detection time, some reinforced concrete are usually selected from all the reinforced concrete produced in the same batch for testing, and the bonding performance test data of each selected reinforced concrete is obtained, that is, the bonding stress-slip curve of each selected reinforced concrete is obtained, and then each obtained bonding stress-slip curve is analyzed separately, and then based on the results of the separate analysis, it is evaluated whether the bonding performance of the reinforced concrete produced in this batch meets the requirements. However, in the process of bonding performance testing, it may be disturbed by loading rate, equipment accuracy, and experimental environment, and these interferences will cause different bonding stress-slip curves or different regions. The importance or reference value of the bonding stress-slip curves is different, so when evaluating the bonding performance of the tested batch of reinforced concrete based on the results of a separate analysis of the bonding stress-slip curve, the evaluation results may be inaccurate or unreliable. Therefore, how to improve the accuracy of testing or evaluating the bonding performance of reinforced concrete is an urgent problem to be solved. Summary of the invention

[0004] In order to solve the above problems, the present invention provides a reinforced concrete overall bonding performance test data analysis method, the technical scheme adopted is as follows:

[0005] An embodiment of the present invention provides a method for analyzing reinforced concrete overall bonding performance test data, comprising the following steps:

[0006] In the batch to be tested, A reinforced concretes are selected as test samples, and the test samples are subjected to an adhesion performance test to obtain an adhesion stress-slip curve corresponding to the test samples, where A is greater than 1;

[0007] The adhesive stress-slip curve is divided to obtain a sub-curve set sequence; according to the coordinates of the data points on each sub-curve in the sub-curve set, a first importance degree characterization value of the sub-curve set is obtained, and the sub-curve set belongs to the sub-curve set sequence;

[0008] Obtaining, according to the first importance representation value, a feature weight value of each subcurve in the first subcurve set, the second subcurve set, and the first subcurve set;

[0009] Obtaining a second importance characterization value of each subcurve in the second subcurve set according to the curvature and the tangent slope corresponding to the data point on each subcurve in the second subcurve set, and obtaining a feature weight value of each subcurve in the second subcurve set according to the second importance characterization value;

[0010] According to the characteristic weight value of each sub-curve in the first sub-curve set and the characteristic weight value of each sub-curve in the second sub-curve set, each sub-curve in the sub-curve set is weightedly fused to obtain a target bonding stress-slip curve, and according to the target bonding stress-slip curve, the bonding performance analysis result of the batch to be tested is obtained.

[0011] Beneficial effects: The present invention first obtains the bonding stress-slip curve corresponding to the test sample, and divides the bonding stress-slip curve to obtain a sequence of sub-curve sets; then, according to the coordinates of the data points on each sub-curve in the sub-curve set, a first importance characterization value of the sub-curve set is obtained, and according to the first importance characterization value, characteristic weight values ​​of the first sub-curve set, the second sub-curve set and each sub-curve in the first sub-curve set are obtained; according to the curvature and tangent slope corresponding to the data points on each sub-curve in the second sub-curve set, a second importance characterization value of each sub-curve in the second sub-curve set is obtained, and according to the second importance characterization value, a characteristic weight value of each sub-curve in the second sub-curve set is obtained; finally, according to the characteristic weight value of each sub-curve in the first sub-curve set and the characteristic weight value of each sub-curve in the second sub-curve set, each sub-curve in the sub-curve set is weightedly fused to obtain a target bonding stress-slip curve, and according to the target bonding stress-slip curve, the bonding performance analysis result of the batch to be tested is obtained. The target bonding stress-slip curve obtained by weighted fusion according to the feature weight value in the present invention is more reliable, so the bonding performance of the batch of reinforced concrete to be tested can also be accurately and reliably analyzed or evaluated based on the target bonding stress-slip curve, that is, the accuracy and reliability of analyzing or evaluating the bonding performance of the batch of reinforced concrete to be tested can be improved based on the target bonding stress-slip curve. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0013] Figure 1 The present invention is a flow chart of a reinforced concrete overall bonding performance test data analysis method. DETAILED DESCRIPTION

[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the embodiments of the present invention.

[0015] Unless defined otherwise, 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 invention pertains.

[0016] This embodiment provides a reinforced concrete overall bonding performance test data analysis method, which is described in detail as follows:

[0017] like Figure 1 As shown, the reinforced concrete overall bonding performance test data analysis method comprises the following steps:

[0018] Step S001: Select A reinforced concretes as test samples in a batch to be tested, and perform an adhesion performance test on the test samples to obtain an adhesion stress-slip curve corresponding to the test samples.

[0019] This embodiment is mainly aimed at prefabricated reinforced concrete, that is, it mainly analyzes the bonding performance test data of prefabricated reinforced concrete. Since prefabricated reinforced concrete is a prefabricated reinforced concrete component produced in a factory, under normal circumstances, the factory generally produces it in batches, that is, only one type of reinforced concrete is produced in the same time period.

[0020] At present, in order to reduce the detection time and to ensure the bonding performance of the produced reinforced concrete, some reinforced concrete are usually selected from all the reinforced concrete produced in the same batch for testing, and the bonding performance test data of each selected reinforced concrete is obtained, that is, the bonding stress-slip curve of each selected reinforced concrete is obtained, and then each obtained bonding stress-slip curve is analyzed separately, and then based on the results of the separate analysis, it is evaluated whether the bonding performance of the reinforced concrete produced in this batch meets the requirements. However, in the process of bonding performance testing, it may be disturbed by loading rate, equipment accuracy, and experimental environment, and these interferences will lead to differences in the importance or reference value of different bonding stress-slip curves or bonding stress-slip curves in different regions. Therefore, in the process of bonding performance testing, the bonding stress-slip curve of each selected reinforced concrete is analyzed separately, and then the bonding stress-slip curve of each selected reinforced concrete is analyzed separately. When the bonding performance of the tested batch of reinforced concrete is evaluated based on the results of a separate analysis of the bonding stress-slip curve, inaccurate or unreliable evaluation results may occur. In order to make the evaluation results or test results more accurate and reliable, the present embodiment subsequently divides the obtained bonding stress-slip curve to obtain a sub-curve set sequence, and then analyzes the importance of each sub-curve in each sub-curve set in the sub-curve set sequence, obtains the characteristic weight value of each sub-curve in the sub-curve set based on the analysis result, and then performs weighted fusion on each sub-curve in the sub-curve set based on the obtained characteristic weight value to obtain a target bonding stress-slip curve. Finally, based on the obtained target bonding stress-slip curve, accurate and reliable detection or evaluation of the bonding performance of the tested batch can be achieved.

[0021] Based on the above analysis, it can be known that in this embodiment, any batch of reinforced concrete produced by any factory is first recorded as a batch to be tested, and the type of all reinforced concrete in the batch to be tested is the same; then A reinforced concretes are arbitrarily selected from the batch to be tested as test samples, and the test samples are mainly used for bonding performance experiments; and in specific applications, the implementer needs to set the value of A according to the actual situation or the total number of reinforced concrete in the batch to be tested. For example, in this embodiment, the value of A is set to the integer value after the total number is multiplied by 0.1%, and the total number at this time refers to the total number of reinforced concrete in the batch to be tested.

[0022] After all the test samples are obtained, the adhesion performance test is then performed on all the test samples to obtain the adhesion stress-slip curve corresponding to each test sample, and the test or experimental method and test conditions or experimental conditions of each test sample are consistent during the test; in addition, in this embodiment, the process of obtaining the adhesion stress-slip curve corresponding to the test sample is as follows:

[0023] First, the preset slip interval is obtained, and the maximum value in the preset slip interval is recorded as the preset maximum slip, and the unit of the slip is millimeter; in addition, under normal circumstances, the minimum value in the preset slip interval is 0; then the preset slip interval is evenly divided, and the slip corresponding to each segmentation position is recorded as the target slip, and the maximum value and the minimum value in the preset slip interval are also recorded as the target slip; for example, if the preset slip interval is [0,10], the preset slip interval can be evenly divided into 10 equal parts, and the slip corresponding to the segmentation position is 0, 1, 2, 3, etc. in the preset slip interval.

[0024] In addition, the slip amount is also called the slip length, and the slip length refers to the distance of sliding between the steel bar and the concrete in the center pull-out test. The size of the sliding length can reflect the degree of bonding between the steel bar and the concrete. Generally, the smaller the slip length, the stronger the bond between the steel bar and the concrete. In specific applications, the implementer needs to set the maximum slip amount in the preset slip amount range according to the actual situation of the experiment, that is, the diameter of the steel bar, etc., that is, the preset maximum slip amount. For example, if the length of the steel bar is 20 mm, then the preset maximum slip amount can be set to 20 mm, that is, the experimental cutoff condition is set to 20 mm.

[0025] After obtaining the preset slip range and the target slip, it is necessary to construct a mapping space, in which the horizontal coordinate of the mapping space is the slip and the vertical coordinate is the bonding stress, and the mapping space is mainly used to map the data recorded in the subsequent experimental process.

[0026] After the mapping space is constructed, for ease of understanding, this embodiment will take the acquisition of the bonding stress-slip curve of any test sample B as an example for description, specifically: a center pull-out experiment is performed on the test sample B, and each time the relative slip between the steel bars and the concrete in the test sample B reaches the target slip, the bonding stress is recorded once, and the experiment is stopped until the relative slip between the steel bars and the concrete in the test sample B reaches the preset maximum slip, and the mapping vector sequence corresponding to the test sample B is obtained, and the ath mapping vector in the mapping vector sequence is composed of the ath target slip in the preset slip interval and the bonding stress recorded when the relative slip between the steel bars and the concrete in the test sample B reaches the ath target slip. ; Then, each mapping vector in the mapping vector sequence corresponding to the test sample B is mapped to the mapping space to obtain the data points corresponding to each mapping vector, and they are all recorded as the data points corresponding to the test sample B, and then all the data points corresponding to the test sample B are connected in order from small to large in the order of the horizontal coordinate value, and the connected curve is recorded as the bonding stress-slip curve corresponding to the test sample B, and the number of data points on the bonding stress-slip curve is the same as the number of target slip amounts in the preset slip amount interval; that is, the center pull-out experimental device is to clamp the exposed steel bar end through the testing machine to apply pressure until the steel bar is pulled out or yields, and then measure the pull-out force at the loading end of the steel bar and the relative slip amount between the steel bar and the concrete to determine the corresponding bonding stress-slip relationship curve

[0027] Therefore, according to the above process, the bonding stress-slip curve corresponding to each test sample can be obtained; in this embodiment, the horizontal coordinate spans corresponding to all bonding stress-slip curves are consistent with the preset slip range, and the horizontal coordinate span corresponding to the bonding stress-slip curve refers to the horizontal coordinate distance between the initial point to the last point on the corresponding bonding stress-slip curve, and the bonding stress-slip curves corresponding to all test samples are located in the same mapping space.

[0028] Step S002, divide the adhesion stress-slip curve to obtain a sequence of sub-curve sets; obtain a coincidence degree characterization value of the sub-curve set according to the coordinates of the data points on each sub-curve in the sub-curve set, and the sub-curve set belongs to the sequence of sub-curve sets; obtain the characteristic weight values ​​of the first sub-curve set, the second sub-curve set and each sub-curve in the first sub-curve set according to the first importance characterization value; obtain the second importance characterization value of each sub-curve in the second sub-curve set according to the curvature and tangent slope corresponding to the data points on each sub-curve in the second sub-curve set, and obtain the characteristic weight value of each sub-curve in the second sub-curve set according to the second importance characterization value.

[0029] Since the adhesion performance test may be interfered by loading rate, equipment accuracy, and experimental environment, and these interferences may cause differences in the importance or reference value of different adhesion stress-slip curves or adhesion stress-slip curves in different regions, and this difference may also cause inaccurate or unreliable evaluation results when evaluating the adhesion performance of the tested batch of reinforced concrete. In order to solve the above problems and to accurately and reliably detect or evaluate the adhesion performance of the tested batch, this embodiment is mainly achieved by weighted fusion of adhesion stress-slip curves. Before weighted fusion, all adhesion stress-slip curves need to be divided to obtain a sub-curve set sequence, and then the importance of each sub-curve in each sub-curve set in the sub-curve set sequence is analyzed, and then the characteristic weight value of each sub-curve in the sub-curve set is determined based on the analysis result. Therefore, based on the above analysis, it can be seen that the adhesion stress-slip curve needs to be divided to obtain a sub-curve set sequence in this embodiment, that is, the specific process of obtaining the sub-curve set sequence is as follows:

[0030] First, the preset division length is obtained, and in specific applications, the implementer needs to set the preset division length according to the actual situation. It is known that the horizontal axis spans corresponding to all bonding stress-slip curves are consistent with the preset slip range. If the present embodiment requires dividing the preset division length into 10 equal parts, that is, dividing each bonding stress-slip curve into 10 equal parts, then the preset division length is the ratio of the length of the preset slip range to 10.

[0031] Then, the adhesion stress-slip curve is divided by using a preset division length to obtain a sub-curve sequence corresponding to each adhesion stress-slip curve; and for ease of understanding, this embodiment takes the sub-curve sequence corresponding to any adhesion stress-slip curve V as an example for description, that is, the specific acquisition process of the sub-curve sequence corresponding to the adhesion stress-slip curve V is: the adhesion stress-slip curve V is divided by using a preset division length, and the sequence constructed by each segment of the divided curve is recorded as the sub-curve sequence corresponding to the adhesion stress-slip curve V, and the horizontal coordinate value of the data point on the b-th sub-curve in the sub-curve sequence is greater than the horizontal coordinate value of the data point on the b-1th sub-curve and less than the horizontal coordinate value of the data point on the b+1th sub-curve.

[0032] Therefore, through the above process, the sub-curve sequence corresponding to each adhesion stress-slip curve can be obtained, and then the sub-curves in the sub-curve sequence corresponding to each adhesion stress-slip curve are marked respectively to obtain the first marking value of each sub-curve. In this embodiment, the first marking value of the b-th sub-curve in each sub-curve sequence is b, that is, in different sub-curve sequences, the first marking values ​​of sub-curves at the same position are consistent.

[0033] Therefore, the first label value of each subcurve in each subcurve sequence is obtained through the above process. Then, in this embodiment, all subcurves with the same first label value are divided into the same set, and all are recorded as a subcurve set, that is, subcurves at the same position in different subcurve sequences are divided into the same set, and then the first label value of the subcurve in the subcurve set is used as the characteristic label value of the corresponding subcurve set; and the first label value of the subcurve in each subcurve set is the same, and the subcurves in the subcurve set are from different subcurve sequences; then, all the obtained subcurve sets are sorted in the order of the characteristic label value from small to large, and the sorted sequence is recorded as the subcurve set sequence.

[0034] Therefore, this embodiment obtains a subcurve set sequence through the above process. After obtaining the subcurve set sequence, this embodiment obtains the first importance characterization value of the subcurve set according to the coordinates of the data points on each subcurve in the subcurve set. The first importance characterization value is an important indicator for subsequently obtaining the feature weight value of the subcurve. In addition, for ease of understanding, this embodiment takes the process of obtaining the first importance characterization value of any subcurve set C in the subcurve set sequence as an example for description, that is, the process of obtaining the first importance characterization value of the subcurve set C is:

[0035] First, the total number of data points on each subcurve in the subcurve set C is obtained, and they are all recorded as the characteristic representation values ​​corresponding to the corresponding subcurves; then the cumulative sum of the characteristic representation values ​​corresponding to each subcurve in the subcurve set C is obtained, and recorded as the comprehensive representation value corresponding to the subcurve set C; then, according to the data points on the subcurves in the subcurve set C, the first quantity representation value and the second quantity representation value corresponding to the subcurve set C are obtained; then, the ratio of the first quantity representation value to the comprehensive representation value corresponding to the subcurve set C is obtained, and recorded as the first ratio, and the ratio of the second quantity representation value to the comprehensive representation value corresponding to the subcurve set C is obtained, and recorded as the second ratio; then, the first ratio and the second ratio are weightedly summed, and the result of the weighted summation is recorded as the overlap degree of the subcurve set C, and then the overlap degree of the subcurve set C is used as the first importance degree representation value of the subcurve set C.

[0036] In this embodiment, the specific expression for obtaining the overlap degree of the sub-curve set C is:

[0037]

[0038] in, is the overlap degree of the sub-curve set C, a1 is the first weight factor, a2 is the second weight factor, N0 is the comprehensive characterization value, N1 is the first quantity characterization value corresponding to the sub-curve set C, and N2 is the second quantity characterization value corresponding to the sub-curve set C; and in this embodiment, the first weight factor and the second weight factor are set to 0.3 and 0.7, respectively.

[0039] And when the values ​​of N1 and N2 are larger, The larger the value of or the larger the first importance representation value of the sub-curve set C, The larger the value of or the first importance representation value of the subcurve set C is, the higher the overlap between the subcurves in the subcurve set C is. When the overlap is high, it means that the subcurves in the subcurve set C are less disturbed. Then, when the subcurves in the subcurve set C are subsequently merged, the subcurves can be given the same weight. On the contrary, when the values ​​of N1 and N2 are smaller, The smaller the value of or the smaller the first importance representation value of the subcurve set C, The smaller the value of or the first importance representation value of the subcurve set C is, the lower the overlap between the subcurves in the subcurve set C is. When the overlap is lower, it indicates that the subcurves in the subcurve set C are more interfered with. In this case, further analysis of the subcurves in the subcurve set C is required to determine the weights used for fusion.

[0040] In addition, in this embodiment, the method for obtaining the first quantity characterization value and the second quantity characterization value corresponding to the sub-curve set C is:

[0041] On all subcurves in the subcurve set C, all sets constructed by all data points with the same horizontal coordinate value are recorded as the sets to be analyzed corresponding to the subcurve set C, and then all the sets to be analyzed corresponding to the subcurve set C are sorted in ascending order of the horizontal coordinates, and the sorted sequence is recorded as the set sequence to be analyzed corresponding to the subcurve set C, and the d-th set to be analyzed in the set sequence to be analyzed is composed of the d-th data points on all subcurves in the subcurve set C; then, the target label value of each set to be analyzed in the set sequence to be analyzed is obtained, and in this embodiment, the target label value of the d-th set to be analyzed in the set sequence to be analyzed is recorded as d.

[0042] Next, the feature set in the sequence of sets to be analyzed is obtained. The specific method of obtaining the feature set is as follows: for the dth set to be analyzed in the sequence of sets to be analyzed, if it is determined that the vertical coordinate values ​​of all data points in the dth set to be analyzed are the same, then the dth set to be analyzed is recorded as the feature set.

[0043] Therefore, all feature sets in the sequence of sets to be analyzed can be obtained through the above process; then, in the sequence of sets to be analyzed, each sequence constructed by feature sets with continuous target mark values ​​is obtained, and they are all recorded as the feature set sequence corresponding to the sub-curve set C; for example, if there are 5 feature sets, and in these 5 feature sets, the target mark value of the first feature set is 1, the target mark value of the second feature set is 2, the target mark value of the third feature set is 4, the target mark value of the fourth feature set is 7, and the target mark value of the fifth feature set is 8, then there are two feature set sequences corresponding to the sub-curve set C at this time, namely the sequence formed by the first feature set and the second feature set and the sequence formed by the fourth feature set and the fifth feature set.

[0044] Then, the number of feature sets in each feature set sequence is obtained, and recorded as the first index value of the corresponding feature set sequence; then, the first index value set is obtained, and the first index value set is composed of the first index values ​​of all feature set sequences corresponding to the subcurve set C, and the maximum value in the first index value set is used as the first quantity representation value corresponding to the subcurve set C; then, in all feature set sequences corresponding to the subcurve set C, the number of feature set sequences whose first index values ​​are greater than the preset index threshold is counted, and recorded as the second quantity representation value, and the first quantity representation value and the second quantity representation value can both reflect the overlap of the subcurves in the subcurve set C; in addition, in specific applications, the implementer needs to set the preset index threshold according to the actual situation, such as setting the preset index threshold to 3 in this embodiment.

[0045] Therefore, this embodiment can obtain the first importance characterization value of each sub-curve set through the above process. After obtaining the first importance characterization value of the sub-curve set, the feature weight value of each data point on the first sub-curve set, the second sub-curve set, and each sub-curve in the first sub-curve set is obtained. The specific acquisition process is:

[0046] For the subcurve set C in the subcurve set sequence, it is determined whether the first importance representation value of the subcurve set C is greater than the preset first threshold value. If so, it is determined that the overlap degree of the subcurves in the subcurve set C is high or the interference degree is low, and the subcurve set C at this time is recorded as the first subcurve set. Otherwise, it is determined that the overlap degree of the subcurves in the subcurve set C is low or the interference degree is large, then the subcurve set C at this time is recorded as the second subcurve set; and in specific applications, the implementer needs to set the preset first threshold value according to actual conditions, such as setting the preset first threshold value to 0.6 in this embodiment.

[0047] Therefore, the first sub-curve set and the second sub-curve set in the sub-curve set sequence can be obtained through the above process; and based on the above description, it can be known that when the overlap degree of the sub-curve sets is high, then when the sub-curves in the sub-curve set are subsequently merged, the same weight can be given to these sub-curves; therefore, in this embodiment, the process of obtaining the characteristic weight value of each sub-curve in the first sub-curve set is: for any first sub-curve set, the reciprocal of the total number of sub-curves in the first sub-curve set is used as the characteristic weight value of each sub-curve in the first sub-curve set.

[0048] Therefore, the feature weight value of each subcurve in each first subcurve set can be obtained through the above process. After obtaining the feature weight value of each subcurve in the first subcurve set, the second subcurve set needs to be further analyzed to determine the second importance characterization value of each subcurve in the second subcurve set. Subsequently, the feature weight value of each subcurve in the second subcurve set is determined based on the obtained second importance characterization value. Therefore, the second importance characterization value of each subcurve in the second subcurve set will be first obtained in this embodiment. In addition, for ease of understanding, the second importance characterization value of the i-th subcurve in any second subcurve set F will be used as an example to describe the acquisition process. That is, the acquisition process of the second importance characterization value of the i-th subcurve in the second subcurve set F is:

[0049] First, the curvature of each data point on the ith sub-curve is obtained, and the mean curvature of all data points on the ith sub-curve is taken as the mean curvature corresponding to the ith sub-curve, and the inverse of the mean curvature corresponding to the ith sub-curve is recorded as the smoothness characterization value of the ith sub-curve, the smoothness characterization value of the ith sub-curve can reflect the interference degree of the ith sub-curve, and the larger the smoothness characterization value of the ith sub-curve is, the smaller the interference degree of the ith sub-curve is, and vice versa, the greater the interference degree of the ith sub-curve is; the curvature of the rth data point on the ith sub-curve refers to the curvature of the curve formed by the r-1th data point, the rth data point and the r+1th data point on the ith sub-curve, wherein the value of r is neither 1 nor M0, and M0 is the total number of data points on the ith sub-curve; in addition, when obtaining the mean curvature corresponding to the ith sub-curve, the first data point and the last data point on the ith sub-curve are not involved.

[0050] After obtaining the smoothness representation value of the i-th sub-curve, the present embodiment then obtains the sequence of data points to be analyzed corresponding to each sub-curve in the second sub-curve set F and the slope representation value corresponding to each data point in the sequence of data points to be analyzed, and the sequence of data points to be analyzed corresponding to the sub-curve refers to the sequence formed by all the data points remaining after removing the first data point and the last data point on the corresponding sub-curve; then, according to the slope representation value corresponding to each data point in the sequence of data points to be analyzed corresponding to each sub-curve in the second sub-curve set F, the fluctuation amplitude representation value corresponding to each sub-curve in the second sub-curve set F is obtained, and the i-th sub-curve in the second sub-curve set F corresponds to The fluctuation amplitude characterization value refers to the cumulative sum of the slope characterization values ​​corresponding to all data points in the sequence of data points to be analyzed corresponding to the i-th sub-curve; then the mean of the fluctuation amplitude characterization values ​​corresponding to all sub-curves in the second sub-curve set F is obtained, and recorded as the characteristic mean; then the normalized value of the absolute value of the difference between the fluctuation amplitude characterization value corresponding to the i-th sub-curve and the characteristic mean is obtained, and recorded as the fluctuation difference characterization value corresponding to the i-th sub-curve; the fluctuation difference characterization value of the i-th sub-curve can also reflect the degree of interference of the i-th sub-curve, and the smaller the fluctuation difference characterization value of the i-th sub-curve, the smaller the degree of interference of the i-th sub-curve, and vice versa, the greater the degree of interference of the i-th sub-curve.

[0051] Then, the reciprocal of the smoothness representation value and the fluctuation difference representation value of the ith sub-curve is weightedly summed, and the result of the weighted summation is used as the second importance representation value of the ith sub-curve; and the specific expression for obtaining the second importance representation value of the ith sub-curve is:

[0052]

[0053] in, is the second importance representation value of the i-th sub-curve, a3 is the third weight factor, a4 is the fourth weight factor, is the smoothness representation value of the ith sub-curve, is the fluctuation difference representation value of the ith sub-curve, , , is the curvature of the rth data point on the ith subcurve, norm() is the normalization function, is the fluctuation amplitude representation value corresponding to the i-th sub-curve, is the characteristic mean; in addition, in this embodiment, the values ​​of a3 and a4 are 0.6 and 0.4 respectively.

[0054] And when and The larger the value of The larger the value of The larger the value of , the less interference the ith sub-curve has. Then, when the sub-curves in the sub-curve set F are subsequently merged, a larger weight needs to be given to the ith sub-curve. and The smaller the value of The larger the value of The smaller the value of , the more interference the ith sub-curve has. Therefore, when the sub-curves in the sub-curve set F are subsequently merged, a smaller weight needs to be given to the ith sub-curve.

[0055] In this embodiment, the method for obtaining the slope characterization value corresponding to each data point in the sequence of data points to be analyzed is:

[0056] For the jth data point in the sequence of data points to be analyzed corresponding to the ith subcurve in any second subcurve set F: on the ith subcurve, obtain the data point located on the left and adjacent to the jth data point, and record it as the left adjacent data point of the jth data point, obtain the data point located on the right and adjacent to the jth data point, and record it as the right adjacent data point of the jth data point; then obtain the absolute value of the difference between the tangent slope of the jth data point and the tangent slope of the left adjacent data point, and record it as the first slope difference, obtain the absolute value of the difference between the tangent slope of the jth data point and the tangent slope of the right adjacent data point, and record it as the second slope difference; then obtain the absolute value of the difference between the tangent slope of the left adjacent data point and the tangent slope of the right adjacent data point, and record it as the third slope difference; finally, select a maximum value between the first slope difference and the second slope difference, and record the absolute value of the difference between the selected maximum value and the third slope difference as the slope representation value of the jth data point.

[0057] Therefore, this embodiment can obtain the second importance characterization value of each subcurve in the second subcurve set through the above process, and after obtaining the second importance characterization value, the characteristic weight value of each subcurve in the second subcurve set is obtained according to the second importance characterization value, specifically: for the second subcurve set F, the cumulative sum of the second importance characterization values ​​of all subcurves in the second subcurve set F is obtained, and recorded as the comprehensive importance of the second subcurve set F, and then the ratio of the second importance characterization value of each subcurve in the second subcurve set F to the comprehensive importance is obtained, and recorded as the characteristic weight value of the corresponding subcurve.

[0058] Therefore, this embodiment can obtain the characteristic weight value of each subcurve in the first subcurve set in the subcurve set sequence and the characteristic weight value of each subcurve in the second subcurve set through the above process, that is, the characteristic weight value of each subcurve in each subcurve set in the subcurve set sequence is obtained through the above process.

[0059] Step S003, based on the characteristic weight value of each sub-curve in the first sub-curve set and the characteristic weight value of each sub-curve in the second sub-curve set, weighted fusion is performed on each sub-curve in the sub-curve set to obtain a target bonding stress-slip curve, and based on the target bonding stress-slip curve, the bonding performance analysis result of the batch to be tested is obtained.

[0060] After obtaining the characteristic weight value, this embodiment performs weighted fusion on each sub-curve in the sub-curve set to obtain the target adhesion stress-slip curve. That is, the method for obtaining the target adhesion stress-slip curve is:

[0061] First, a weighted data point set corresponding to the first sub-curve set and a weighted data point set corresponding to the second sub-curve set are obtained; then a new set constructed by the weighted data point sets corresponding to all the first sub-curve sets and the weighted data point sets corresponding to all the second sub-curve sets is recorded as a target data point set; then, the data points in the target data point set are connected in ascending order of the horizontal coordinate value, and the connected curve is recorded as a target adhesion stress-slip curve.

[0062] In this embodiment, the method for obtaining the weighted data point set corresponding to the sub-curve set includes:

[0063] For any subcurve set G: in the subcurve set G, the sets constructed by all data points with the same horizontal coordinate value are recorded as the to-be-weighted sets corresponding to the subcurve set G, and the weighted values ​​of each data point in the to-be-weighted set are obtained; and the weighted values ​​of the data points are obtained as follows: if the g-th data point in any to-be-weighted set belongs to the subcurve g0 in the subcurve set G, then the characteristic weight value of the subcurve g0 is used as the weighted value of the g-th data point.

[0064] Then, according to the weighted value of each data point in the set to be weighted, the weighted data points of the set to be weighted are obtained, and then the set constructed by all the weighted data points of the set to be weighted corresponding to the sub-curve set G is recorded as the weighted data point set corresponding to the sub-curve set G.

[0065] In addition, the method for obtaining the weighted data points corresponding to any to-be-weighted set G0 corresponding to the sub-curve set G is as follows: first, the weighted ordinate value sequence corresponding to the to-be-weighted set G0 is obtained, and then the cumulative sum of the weighted ordinate value sequence is used as the target ordinate value corresponding to the to-be-weighted set G0, and the abscissa values ​​of the data points in the to-be-weighted set G0 are used as the target abscissa values ​​corresponding to the to-be-weighted set G0, and the abscissa values ​​of the data points in the to-be-weighted set G0 are the same, and finally the data points whose coordinate values ​​are the target ordinate value and the target abscissa value are obtained, and used as the weighted data points corresponding to the to-be-weighted set G0; and the u-th weighted ordinate value in the weighted ordinate value sequence corresponding to the to-be-weighted set G0 refers to the product of the ordinate value of the u-th data point in the to-be-weighted set G0 and the weighted value of the u-th data point.

[0066] After obtaining the target bonding stress-slip curve, the bonding performance analysis results of the batch to be tested are obtained according to the target bonding stress-slip curve. The method of obtaining the bonding performance analysis results of the batch to be tested according to the target bonding stress-slip curve is the same as the existing method of evaluating or obtaining the bonding performance analysis results of the reinforced concrete to be tested according to the bonding stress-slip curve of the reinforced concrete to be tested. Therefore, this embodiment will not be described in detail.

[0067] To summarize, this embodiment first obtains the bonding stress-slip curve corresponding to the test sample, and divides the bonding stress-slip curve to obtain a sequence of sub-curve sets; then, according to the coordinates of the data points on each sub-curve in the sub-curve set, a first importance characterization value of the sub-curve set is obtained, and according to the first importance characterization value, the characteristic weight values ​​of the first sub-curve set, the second sub-curve set, and each sub-curve in the first sub-curve set are obtained; according to the curvature and tangent slope corresponding to the data points on each sub-curve in the second sub-curve set, the second importance characterization value of each sub-curve in the second sub-curve set is obtained, and according to the second importance characterization value, the characteristic weight value of each sub-curve in the second sub-curve set is obtained; finally, according to the characteristic weight value of each sub-curve in the first sub-curve set and the characteristic weight value of each sub-curve in the second sub-curve set, each sub-curve in the sub-curve set is weightedly fused to obtain a target bonding stress-slip curve, and according to the target bonding stress-slip curve, the bonding performance analysis result of the batch to be tested is obtained. The target bonding stress-slip curve obtained by weighted fusion based on the feature weight values ​​in this embodiment is more reliable. Therefore, the bonding performance of the batch of reinforced concrete to be tested can also be accurately and reliably analyzed or evaluated based on the target bonding stress-slip curve. That is, the accuracy and reliability of analyzing or evaluating the bonding performance of the batch of reinforced concrete to be tested can be improved based on the target bonding stress-slip curve.

[0068] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A reinforced concrete overall bonding performance test data analysis method, characterized in that: The method comprises the following steps: In the batch to be tested, A reinforced concretes are selected as test samples, and the test samples are subjected to an adhesion performance test to obtain an adhesion stress-slip curve corresponding to the test samples, where A is greater than 1; The adhesive stress-slip curve is divided to obtain a sub-curve set sequence; according to the coordinates of the data points on each sub-curve in the sub-curve set, a first importance degree characterization value of the sub-curve set is obtained, and the sub-curve set belongs to the sub-curve set sequence; Obtaining, according to the first importance representation value, a feature weight value of each subcurve in the first subcurve set, the second subcurve set, and the first subcurve set; Obtaining a second importance characterization value of each subcurve in the second subcurve set according to the curvature and the tangent slope corresponding to the data point on each subcurve in the second subcurve set, and obtaining a feature weight value of each subcurve in the second subcurve set according to the second importance characterization value; According to the characteristic weight value of each sub-curve in the first sub-curve set and the characteristic weight value of each sub-curve in the second sub-curve set, weighted fusion is performed on each sub-curve in the sub-curve set to obtain a target bonding stress-slip curve, and according to the target bonding stress-slip curve, an adhesion performance analysis result of the batch to be tested is obtained; The method for obtaining the first importance representation value of the sub-curve set includes: For any subcurve set C in the subcurve set sequence: the cumulative sum of the total number of data points on all subcurves in the subcurve set C is recorded as the comprehensive characterization value corresponding to the subcurve set C; according to the data points on the subcurves in the subcurve set C, a first quantity characterization value and a second quantity characterization value corresponding to the subcurve set C are obtained; the ratio of the first quantity characterization value to the comprehensive characterization value is recorded as a first ratio; the ratio of the second quantity characterization value to the comprehensive characterization value is recorded as a second ratio; the first ratio and the second ratio are weightedly summed, and the result of the weighted summation is recorded as the first importance characterization value of the subcurve set C; The method for obtaining the first quantity characterization value and the second quantity characterization value corresponding to the sub-curve set C includes: On all subcurves in the subcurve set C, all sets constructed by data points with the same horizontal coordinate value are recorded as the to-be-analyzed sets corresponding to the subcurve set C, and all the to-be-analyzed sets corresponding to the subcurve set C are sorted in ascending order of the horizontal coordinates to obtain a sequence of sets to be analyzed corresponding to the subcurve set C, wherein the target label value of the dth set to be analyzed in the sequence of sets to be analyzed is d; If the ordinate values ​​of all data points in the dth set to be analyzed in the sequence of sets to be analyzed are the same, the dth set to be analyzed is recorded as a feature set; in the sequence of sets to be analyzed, each sequence constructed by feature sets with continuous target label values ​​is recorded as a feature set sequence corresponding to the subcurve set C; The number of feature sets in the feature set sequence is recorded as the first index value of the corresponding feature set sequence; the maximum value in the first index value set is used as the first quantity representation value corresponding to the sub-curve set C, and the first index value set is composed of the first index values ​​of all feature set sequences corresponding to the sub-curve set C; Among all feature set sequences corresponding to the sub-curve set C, the number of feature set sequences whose first index value is greater than a preset index threshold is counted and recorded as a second quantity representation value; The method for obtaining the feature weight value of the first sub-curve set, the second sub-curve set, and each sub-curve in the first sub-curve set includes: For any subcurve set in the subcurve set sequence, determine whether a first importance representation value of the subcurve set is greater than a preset first threshold; if so, record the subcurve set as a first subcurve set; otherwise, record the subcurve set as a second subcurve set; For any first sub-curve set, taking the inverse of the total number of sub-curves in the first sub-curve set as the feature weight value of each sub-curve in the first sub-curve set; The method for obtaining the second importance representation value of each sub-curve in the second sub-curve set includes: For the i-th subcurve in any second subcurve set F: obtain the curvature of each data point on the i-th subcurve, and use the mean curvature of all data points on the i-th subcurve as the mean curvature corresponding to the i-th subcurve, and use the inverse of the mean curvature as the smoothness representation value of the i-th subcurve; obtain the sequence of data points to be analyzed corresponding to each subcurve in the second subcurve set F and the slope representation value corresponding to each data point in the sequence of data points to be analyzed, the sequence of data points to be analyzed corresponding to the subcurve refers to the sequence formed by the remaining data points after removing the first data point and the last data point on the corresponding subcurve; according to the corresponding values ​​of each data point in the sequence of data points to be analyzed corresponding to each subcurve in the second subcurve set F, Slope characterization value, obtain the fluctuation amplitude characterization value corresponding to each sub-curve in the second sub-curve set F, the fluctuation amplitude characterization value corresponding to the i-th sub-curve in the second sub-curve set F refers to the cumulative sum of the slope characterization values ​​corresponding to all data points in the sequence of data points to be analyzed corresponding to the i-th sub-curve; obtain the mean of the fluctuation amplitude characterization values ​​corresponding to all sub-curves in the second sub-curve set F, and record it as the characteristic mean; normalize the absolute value of the difference between the fluctuation amplitude characterization value corresponding to the i-th sub-curve and the characteristic mean, and record it as the fluctuation difference characterization value corresponding to the i-th sub-curve; perform weighted summation on the smoothness characterization value and the inverse of the fluctuation difference characterization value, and use the result of the weighted summation as the second importance characterization value of the i-th sub-curve; The method for obtaining the slope characterization value corresponding to each data point in the sequence of data points to be analyzed comprises: for the jth data point in the sequence of data points to be analyzed corresponding to the i-th sub-curve, on the i-th sub-curve, recording the data point located on the left side and adjacent to the jth data point as the left adjacent data point of the jth data point, recording the data point located on the right side and adjacent to the jth data point as the right adjacent data point of the jth data point, recording the absolute value of the difference between the tangent slope of the jth data point and the tangent slope of the left adjacent data point as the first slope difference, recording the absolute value of the difference between the tangent slope of the jth data point and the tangent slope of the right adjacent data point as the second slope difference, recording the absolute value of the difference between the tangent slope of the left adjacent data point and the tangent slope of the right adjacent data point as the third slope difference, and recording the absolute value of the difference between the maximum value of the first slope difference and the second slope difference and the third slope difference as the slope characterization value of the jth data point; The method for obtaining the characteristic weight value of each sub-curve in the second sub-curve set includes: For the second sub-curve set F, the cumulative sum of the second importance representation values ​​of all sub-curves in the second sub-curve set F is used as the comprehensive importance of the second sub-curve set F, and the ratio of the second importance representation value of each sub-curve in the second sub-curve set F to the comprehensive importance is used as the feature weight value of the corresponding sub-curve; The method for obtaining the target adhesion stress-slip curve comprises: Obtain a weighted data point set corresponding to the first sub-curve set and a weighted data point set corresponding to the second sub-curve set; construct a new set of weighted data point sets corresponding to all first sub-curve sets and all second sub-curve sets, and record it as a target data point set; connect the data points in the target data point set in ascending order of the horizontal coordinate value, and record the connected curve as a target adhesion stress-slip curve; The method for obtaining the weighted data point set includes: For any sub-curve set G: in the sub-curve set G, the sets constructed by all data points with the same horizontal coordinate value are all recorded as the to-be-weighted sets corresponding to the sub-curve set G, and the weighted values ​​of each data point in the to-be-weighted sets are obtained, and the weighted data points of the to-be-weighted sets are obtained according to the weighted values ​​of each data point in the to-be-weighted sets; the sets constructed by all weighted data points of the to-be-weighted sets corresponding to the sub-curve set G are recorded as the weighted data point set corresponding to the sub-curve set G; The method for obtaining the weighted value of each data point in the to-be-weighted set includes: if the g-th data point in the to-be-weighted set belongs to the subcurve g0 in the subcurve set G, then using the feature weight value of the subcurve g0 as the weighted value of the g-th data point; The method for obtaining weighted data points corresponding to any to-be-weighted set G0 corresponding to the sub-curve set G includes: obtaining a weighted ordinate value sequence corresponding to the to-be-weighted set G0, taking the cumulative sum of the weighted ordinate value sequence as the target ordinate value corresponding to the to-be-weighted set G0, taking the abscissa values ​​of the data points in the to-be-weighted set G0 as the target abscissa values ​​corresponding to the to-be-weighted set G0, and taking the data points whose coordinate values ​​are the target ordinate value and the target abscissa value as the weighted data points corresponding to the to-be-weighted set G0; the u-th weighted ordinate value in the weighted ordinate value sequence corresponding to the to-be-weighted set G0 refers to the product of the ordinate value of the u-th data point in the to-be-weighted set G0 and the weighted value of the u-th data point.

2. A reinforced concrete overall bonding performance test data analysis method as claimed in claim 1, characterized in that: The method for obtaining the adhesive stress-slip curve corresponding to the test sample comprises: Obtaining a preset slip interval, recording the maximum value in the preset slip interval as a preset maximum slip; evenly dividing the preset slip interval, recording the slip corresponding to each division position as a target slip; Constructing a mapping space, wherein the abscissa of the mapping space is the slip amount and the ordinate is the bonding stress; For any test sample: a center pull-out test is performed on the test sample, and each time the relative slip between the steel bar and the concrete in the test sample reaches the target slip, the bonding stress is recorded once, and the test is stopped when the relative slip between the steel bar and the concrete in the test sample reaches the preset maximum slip, and a mapping vector sequence corresponding to the test sample is obtained, wherein the ath mapping vector in the mapping vector sequence is composed of the ath target slip in the preset slip interval and the bonding stress recorded when the relative slip between the steel bar and the concrete in the test sample reaches the ath target slip; each mapping vector in the mapping vector sequence is mapped to the mapping space, and the data points obtained after the mapping is completed are recorded as the data points corresponding to the test sample, and the data points corresponding to the test sample are connected in sequence in the order of the horizontal coordinate value from small to large, and the connected curve is recorded as the bonding stress-slip curve corresponding to the test sample.

3. A reinforced concrete overall bonding performance test data analysis method as claimed in claim 2, characterized in that: The method for obtaining the sub-curve set sequence includes: Obtaining a preset division length, dividing each of the adhesion stress-slip curves using the preset division length, obtaining a sub-curve sequence corresponding to the adhesion stress-slip curve and a first label value of each sub-curve in the sub-curve sequence; the first label value of the b-th sub-curve in the sub-curve sequence is b; the sub-curve sequence corresponding to the adhesion stress-slip curve refers to a sequence constructed by each curve segment obtained by dividing the corresponding adhesion stress-slip curve; A set constructed by all subcurves with the same first label value is recorded as a subcurve set, and the first label value of the subcurve in the subcurve set is used as a characteristic label value of the corresponding subcurve set; all the obtained subcurve sets are sorted in ascending order of the characteristic label value, and the sequence after sorting is recorded as a subcurve set sequence.

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