Method and system for detecting residual deformation of reinforcing steel bar sleeve

Abstract

The invention provides a steel bar sleeve residual deformation detection method and system, and the method comprises the steps: installing a residual deformation detection device on a steel bar of a to-be-detected object, and forming a to-be-detected structural body; respectively clamping two sections of steel bars of the to-be-detected structural body on a force applying device, and controlling the force applying device to apply corresponding loads to the steel bars based on specified detection conditions; a signal detected by the residual strain detector is obtained, and the residual deformation amount of the sleeve is obtained based on the obtained signal and serves as candidate residual deformation amount; obtaining a corresponding residual deformation detection error relational expression based on a specified detection condition, and obtaining a residual deformation detection error corresponding to the to-be-detected object based on the obtained expression; and based on the candidate residual deformation and a residual deformation error corresponding to the to-be-detected object, obtaining a target residual deformation of the sleeve of the to-be-detected object. According to the invention, the detection error is added into the detected residual deformation, so that the detection result is as accurate as possible.

Description

Technical Field

[0001] The present invention relates to the technical field of steel bar connection, and particularly to a method and system for detecting the residual deformation of a steel bar sleeve. Background Art

[0002] When evaluating the grade of a steel bar joint, it is necessary to accurately measure the residual deformation amount to evaluate the grade of the steel bar joint. The residual deformation of the steel bar is also called the irrecoverable deformation. When the steel bar is under load, it deforms, and after unloading, only part of the deformation can be restored, and the part that cannot be restored is called the residual deformation. A current residual deformation amount measuring device is to fix it on both sides of the steel bar through bolts, and then place a height vernier caliper on the platform to measure the height values of the steel bar at multiple points, and then measure the residual deformation amount of the steel bar. However, this steel bar residual deformation measuring device is more troublesome to use and requires multiple repeated measurements, and it is difficult to intuitively display the residual deformation amount of the steel bar. And it can only measure its deformation amount, but cannot detect the residual deformation amount under fatigue conditions. Based on this, the patent document (CN216694952U) provides a measuring instrument for the residual deformation of mechanical connection of steel bars. This measuring instrument adopts the bilateral synchronous detection method, sets clamping components on both sides of the steel bar, and the strain of the steel bar is synchronously amplified through a metal connecting rod and received by a residual strain detector, and the deformation data on both sides of the steel bar joint can be obtained to meet the requirements of the industry standard JGJ107-2016 for the residual deformation measuring device. However, in the current field of residual deformation amount measurement, only the measuring device has been improved, but the measurement errors are not considered in the measurement results, which will lead to inaccurate measurement results. Summary of the Invention

[0003] For the above technical problems, the technical solution adopted by the present invention is as follows:

[0004] According to the first aspect of the present invention, a method for detecting the residual deformation amount of a steel bar sleeve is provided, which is used to detect the residual deformation amount of the sleeve of the object to be detected. The object to be detected includes two steel bars and a sleeve connecting the two steel bars. The method includes the following steps:

[0005] S100, install a residual deformation amount detection device on the steel bars of the object to be detected to form a structure to be detected. The residual deformation amount detection device includes a residual strain detector, and the residual strain detector is communicatively connected to a data processing device.

[0006] S200, clamp the two steel bars of the structure to be detected on a force application device respectively, and control the force application device to apply corresponding loads to the steel bars based on specified detection conditions.

[0007] S300, Obtain the signal detected by the residual strain detector, and obtain the residual deformation amount of the sleeve based on the obtained signal as the candidate residual deformation amount.

[0008] S400, Based on the specified detection conditions, obtain the corresponding residual deformation amount detection error relationship expression, and obtain the residual deformation amount detection error corresponding to the object to be detected based on the obtained residual deformation amount detection error relationship expression. The residual deformation amount detection error relationship expression satisfies the following conditions: Y = f(D, L), where Y is the residual deformation amount detection error, D is the diameter of the steel bar, L is the length of the sleeve, and f() is a preset function expression.

[0009] S500, Based on the candidate residual deformation amount and the residual deformation amount error corresponding to the object to be detected, obtain the target residual deformation amount of the sleeve of the object to be detected.

[0010] According to the second aspect of the present invention, there is provided a detection system for the residual deformation amount of a steel bar sleeve. The system includes a processor and a database. The database stores a reference table of residual deformation amount detection error relationship expressions. Each row of data in the reference table of residual deformation amount detection error relationship expressions includes the corresponding detection conditions and the corresponding residual deformation amount detection error relationship expressions. The processor is connected to the residual strain detector of the residual deformation amount detection device. The residual deformation amount detection device is installed on the object to be detected. The object to be detected includes two steel bars and a sleeve connecting the two steel bars. The object to be detected is installed on a force application device. Among them, the processor is used to execute a computer program to implement the following steps:

[0011] S1, Control the force application device to apply a corresponding load to the steel bar based on the specified detection conditions.

[0012] S2, Obtain the signal detected by the residual strain detector, and obtain the residual deformation amount of the sleeve based on the obtained signal as the candidate residual deformation amount.

[0013] S3, Based on the detection conditions to be detected, obtain the corresponding residual deformation amount detection error relationship expression from the reference table of residual deformation amount detection error relationship expressions, and obtain the residual deformation amount detection error corresponding to the object to be detected based on the obtained residual deformation amount detection error relationship expression. The residual deformation amount detection error relationship expression satisfies the following conditions: Y = f(D, L), where Y is the residual deformation amount detection error, D is the diameter of the steel bar, L is the length of the sleeve, and f() is a preset function expression.

[0014] S4, Based on the candidate residual deformation amount and the residual deformation amount error corresponding to the object to be detected, obtain the target residual deformation amount of the sleeve of the object to be detected.

[0015] The present invention has at least the following beneficial effects:

[0016] A method and system for detecting the residual deformation of a steel bar sleeve provided by an embodiment of the present invention add detection errors to the detected residual deformation amount, so that the detection result can be as accurate as possible.

[0017] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0019] Figure 1 It is a schematic structural diagram of an object to be detected in an embodiment of the present invention;

[0020] Figure 2 It is a flowchart of a method for detecting the residual deformation of a steel bar sleeve provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present invention.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs. The terms used in the description of the present invention herein are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0023] It should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts depict the steps as sequential processes, many of the steps can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the steps can be rearranged. The process can be terminated when its operations are completed, but it can also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, and so on.

[0024] An embodiment of the present invention provides a method for detecting the residual deformation amount of a steel bar sleeve, which is used to detect the residual deformation amount of the sleeve of an object to be detected. As Figure 1 shown, the object to be detected 1 includes two steel bars 1 and a sleeve 2 connecting the two steel bars. The sleeve can be an existing steel bar joint.

[0025] Furthermore, as Figure 2 shown, the method for detecting the residual deformation amount of a steel bar sleeve provided by an embodiment of the present invention may include the following steps:

[0026] S100, install a residual deformation amount detection device on the steel bars of the object to be detected to form a structure to be detected. The residual deformation amount detection device includes a residual strain detector, and the residual strain detector is communicatively connected to a data processing device.

[0027] In an embodiment of the present invention, the residual deformation amount detection device can be a residual deformation measuring instrument for mechanical connection of steel bars provided in the patent document CN216694952U. The data processing device can be an upper computer or a PC, etc. The residual strain detector can be a resistance strain gauge.

[0028] S200, clamp the two steel bars of the structure to be detected on a force application device respectively, and control the force application device to apply a corresponding load to the steel bars based on specified detection conditions, so as to apply tensile force and / or compressive force to the steel bars.

[0029] In an embodiment of the present invention, the force application device can be an existing hydraulic testing machine. The detection conditions can include multiple set detection conditions, which can be the loading system specified in JG / T 163-2013. For example, the detection conditions can include unidirectional tension, high-stress repeated tension-compression, and large-deformation repeated tension-compression.

[0030] S300, obtain the signal detected by the residual strain detector, and obtain the residual deformation amount of the sleeve based on the obtained signal as a candidate residual deformation amount.

[0031] When the sleeve deforms, the resistance value of the residual strain detector will change accordingly. Then, this resistance change is converted into a change in voltage (or current) through a resistance strain gauge, and then converted into a strain value or a signal outputting a voltage (or current) proportional to this strain. Recorded by a resistance strain acquisition instrument, the deformation amount of the measured sleeve can be obtained.

[0032] S400, based on the specified detection conditions, obtain the corresponding residual deformation amount detection error relationship expression, and based on the obtained residual deformation amount detection error relationship expression, obtain the residual deformation amount detection error corresponding to the object to be detected. The residual deformation amount detection error relationship expression satisfies the following conditions: Y = f(D, L), where Y is the residual deformation amount detection error, D is the diameter of the steel bar, L is the length of the sleeve, and f() is a preset function expression.

[0033] In an embodiment of the present invention, f() can be set according to actual needs. In a schematic embodiment, f() can be a multiple linear function of D and L. Preferably, it is a first-order linear function of D and L.

[0034] S500, based on the candidate residual deformation amount and the residual deformation amount error corresponding to the object to be detected, obtain the target residual deformation amount of the sleeve of the object to be detected.

[0035] In an embodiment of the present invention, the target residual deformation amount of the sleeve of the object to be detected is the difference obtained by subtracting the residual deformation amount error from the corresponding candidate residual deformation amount.

[0036] In an embodiment of the present invention, since the detection error is added to the detected residual deformation amount, the detection result can be made as accurate as possible.

[0037] Further, the residual deformation amount error relationship expression corresponding to any set of detection conditions is obtained through the following steps:

[0038] S10, prepare a first sample detection object group and a second sample detection object group. Among them, both the first sample detection object group and the second sample detection object group include n sample detection objects. The i-th sample detection object in the first sample detection object group and the second sample detection object group is the same, and both include two steel bars with a diameter of D i and a sleeve with a length of L i , and the value of i ranges from 1 to n.

[0039] In an embodiment of the present invention, at least one of the diameter of the steel bar and the length of the sleeve corresponding to at least some of the sample detection objects is different. The value of n can be determined according to actual needs.

[0040] S11. Under the same set detection conditions, use the first residual deformation amount detection device to perform residual deformation amount detection tests on n sample detection objects in the first sample detection object group respectively, and obtain n first candidate residual deformation amounts; wherein, the detection error of the first residual deformation amount detection device is E0.

[0041] In the embodiment of the present invention, the first residual deformation amount detection device can be an existing device different from the steel bar mechanical connection residual deformation measuring instrument provided in the patent document CN216694952U. The detection error of the first residual deformation amount detection device is known.

[0042] S12. Based on the n first candidate residual deformation amounts and E0, obtain the target residual deformation amounts corresponding to the n sample detection objects.

[0043] In the embodiment of the present invention, the target residual deformation amount corresponding to the sample detection object is the difference obtained by subtracting the residual deformation amount error from the candidate residual deformation amount corresponding thereto.

[0044] S13. Under the same set detection conditions, use the second residual deformation amount detection device to perform residual deformation amount detection tests on n sample detection objects in the second sample detection object group respectively, and obtain n second candidate residual deformation amounts.

[0045] In the embodiment of the present invention, the second residual deformation amount detection device can be the existing steel bar mechanical connection residual deformation measuring instrument provided in the patent document CN216694952U, and the detection error of this device is unknown.

[0046] S14. Obtain the difference between the i-th target residual deformation amount among the target residual deformation amounts corresponding to the n sample detection objects and the i-th second candidate residual deformation amount among the n second candidate residual deformation amounts as the i-th sample detection error; obtain n sample detection errors.

[0047] S15. Based on the diameters of the steel bars, the lengths of the sleeves, and the sample detection errors corresponding to the n sample detection objects in the second sample detection object group, obtain the correlation weight between the detection error and the diameter of the steel bar, and the correlation weight between the detection error and the length of the sleeve, and further obtain the residual deformation amount error relationship expression corresponding to this set detection condition.

[0048] Further, S15 specifically includes:

[0049] S1501. Based on the n relationship expressions corresponding to the n sample detection objects in the second sample detection object group, obtain the corresponding correlation weight combination set C=(C 1 , C 2 , ……, C r , ……, C m ), Cr is the r-th associated weight combination in C, where r ranges from 1 to m, and m is the number of associated weight combinations in C, C r =(C r D , C r L ), C r D is the r-th detection error - diameter associated weight, C r L is the r-th detection error - length associated weight; each relational expression represents the association relationship between the detection error and the diameter of the steel bar and the length of the sleeve. The detection error - diameter associated weight is the associated weight between the detection error and the diameter of the steel bar, and the detection error - length associated weight is the associated weight between the detection error and the length of the sleeve.

[0050] S1502, draw a square with a length of L1 along the x-axis and a length of L2 along the y-axis in a rectangular coordinate system; where L1 = (C D-max - C D-min ), C D-max is the maximum detection error - diameter associated weight in C, C D-min is the minimum detection error - diameter associated weight in C, L2 = (C L-max - C L-min ), C L-max is the maximum detection error - length associated weight in C, C L-max is the minimum detection error - length associated weight in C, and the upper left corner coordinates of the square are (C D-min , C L-min ).

[0051] In the embodiment of the present invention, the scale units of the x-axis and y-axis of the rectangular coordinate system can both be cm.

[0052] S1053, obtain min((C s D - C s-1 D ) s＝2……m ) as the length of the cell along the x-axis and obtain min((C s L - C s-1 L ) s＝2……m ) as the length of the cell along the y-axis. min() represents taking the minimum value.

[0053] S1054, use the cells to divide the square into Q cells, that is, draw cells along the x-axis in sequence until covering the line where L1 is located and draw cells along the y-axis in sequence until covering the line where L2 is located.

[0054] In the embodiment of the present invention, since L1 may not be min((C s D -C s-1 D ) s＝2……m ), L2 may not be an integer multiple of min((C s L -C s-1 L ) s＝2……m ), the total area of ​​Q cells can be greater than or equal to the area of ​​the square.

[0055] S1055, for the zth cell among the Q cells, traverse C, if C r Belongs to the zth cell, C r Add to the counting set corresponding to the zth cell. The initial value of the counting set corresponding to the zth cell is empty. The value of z ranges from 1 to Q, and the initial value is 1.

[0056] S1056: Take the cell corresponding to the count set with the most associated weight combinations among the Q count sets as the target cell.

[0057] In the embodiment of the present invention, if the number of association weights in a certain counting set is the largest, it means that more association weights are located in the cells corresponding to the counting set, which can be used as representative association weights.

[0058] S1057, based on the target cell, obtain the association weight between the detection error and the diameter of the steel bar, and the association weight between the detection error and the length of the sleeve.

[0059] Further, in an exemplary embodiment, in S1057, the association weight between the detection error and the diameter of the steel bar is the x-coordinate value of the center coordinate of the target cell, and the association weight between the detection error and the length of the sleeve is the y-coordinate value of the center coordinate of the target cell.

[0060] Further, in another exemplary embodiment, in S1057, the association weight between the detection error and the diameter of the steel bar is the x-coordinate value of the lower right corner coordinate of the target cell, and the association weight between the detection error and the length of the sleeve is the y-coordinate value of the lower right corner coordinate of the target cell.

[0061] Based on the same inventive concept, an embodiment of the present invention provides a detection system for the residual deformation amount of a steel bar sleeve. The system includes a processor and a database. A reference table of residual deformation amount detection error relationship expressions is stored in the database. Each row of data in the reference table of residual deformation amount detection error relationship expressions includes corresponding detection conditions and corresponding residual deformation amount detection error relationship expressions. The processor is connected to the residual strain detector of the residual deformation amount detection device. The residual deformation amount detection device is installed on the object to be detected. The object to be detected includes two steel bars and a sleeve connecting the two steel bars. The object to be detected is installed on a force application device.

[0062] In an embodiment of the present invention, the residual deformation amount detection device may be a residual deformation measuring instrument for mechanical connection of steel bars provided in the patent document CN216694952U. The residual strain detector may be a resistance strain gauge. In an embodiment of the present invention, the force application device may be an existing hydraulic testing machine.

[0063] Further, the processor is used to execute a computer program to implement the following steps:

[0064] S1, controlling the force application device to apply a corresponding load to the steel bar based on specified detection conditions.

[0065] In an embodiment of the present invention, the detection conditions may include multiple set detection conditions, which may be the loading system specified in JG / T 163-2013. For example, the detection conditions may include unidirectional tension, high-stress repeated tension-compression, and large-deformation repeated tension-compression.

[0066] S2, obtaining the signal detected by the residual strain detector, and obtaining the residual deformation amount of the sleeve based on the obtained signal as a candidate residual deformation amount.

[0067] S3, obtaining the corresponding residual deformation amount detection error relationship expression from the reference table of residual deformation amount detection error relationship expressions based on the detection conditions to be detected, and obtaining the residual deformation amount detection error corresponding to the object to be detected based on the obtained residual deformation amount detection error relationship expression. The residual deformation amount detection error relationship expression satisfies the following conditions: Y = f(D, L), where Y is the residual deformation amount detection error, D is the diameter of the steel bar, L is the length of the sleeve, and f() is a preset function expression.

[0068] S4, obtaining the target residual deformation amount of the sleeve of the object to be detected based on the candidate residual deformation amount and the residual deformation amount error corresponding to the object to be detected.

[0069] Further, any residual deformation amount detection error relationship expression in the reference table of residual deformation amount detection error relationship expressions is obtained through the following steps:

[0070] S10. Prepare a first sample test object group and a second sample test object group. Among them, both the first sample test object group and the second sample test object group include n sample test objects. The i-th sample test object in the first sample test object group and the second sample test object group is the same, and both include two steel bars with a diameter of D i and a sleeve with a length of L i . The value of i ranges from 1 to n;

[0071] S11. Under the same set detection conditions, use the first residual deformation amount detection device to conduct residual deformation amount detection tests on the n sample test objects in the first sample test object group respectively, and obtain n first candidate residual deformation amounts; among them, the detection error of the first residual deformation amount detection device is E0;

[0072] S12. Based on the n first candidate residual deformation amounts and E0, obtain the target residual deformation amounts corresponding to the n sample test objects;

[0073] S13. Under the same set detection conditions, use the second residual deformation amount detection device to conduct residual deformation amount detection tests on the n sample test objects in the second sample test object group respectively, and obtain n second candidate residual deformation amounts;

[0074] S14. Obtain the difference between the i-th target residual deformation amount among the target residual deformation amounts corresponding to the n sample test objects and the i-th second candidate residual deformation amount among the n second candidate residual deformation amounts as the i-th sample detection error; obtain n sample detection errors;

[0075] S15. Based on the diameters of the steel bars, the lengths of the sleeves, and the sample detection errors corresponding to the n sample test objects in the second sample test object group, obtain the correlation weights between the detection error and the diameter of the steel bar, and the correlation weights between the detection error and the length of the sleeve, and then obtain the residual deformation amount error relationship expression corresponding to the set detection conditions.

[0076] Further, S15 specifically includes:

[0077] S1501. Based on the n relationship expressions corresponding to the n sample test objects in the second sample test object group, obtain the corresponding correlation weight combination set C=(C 1 , C 2 , ……, C r , ……, C m ), C r is the r-th correlation weight combination in C, the value of r ranges from 1 to m, m is the number of correlation weight combinations in C, C r =(C r D , Cr L ), C r D is the r-th detection error-diameter correlation weight, C r L is the r-th detection error-length correlation weight; each relational expression characterizes the correlation relationship between the detection error and the diameter of the steel bar and the length of the sleeve.

[0078] S1502, draw a square with a length of L1 along the x-axis direction and a length of L2 along the y-axis direction in a rectangular coordinate system; where, L1 = (C D-max -C D-min ), C D-max is the maximum detection error-diameter correlation weight in C, C D-min is the minimum detection error-diameter correlation weight in C, L2 = (C L-max -C L-min ), C L-max is the maximum detection error-length correlation weight in C, C L-max is the minimum detection error-length correlation weight in C, and the upper left corner coordinates of the square are (C D-min , C L-min ).

[0079] S1053, obtain min((C s D -C s-1 D ) s＝2……m ) as the length of the cell along the x-axis direction and obtain min((C s L -C s-1 L ) s＝2……m ) as the length of the cell along the y-axis direction.

[0080] S1054, divide the square into Q cells using the cells.

[0081] S1055, for the z-th cell among the Q cells, traverse C, if C r belongs to the z-th cell, add C r to the counting set corresponding to the z-th cell. The initial value of the counting set corresponding to the z-th cell is empty. The value of z ranges from 1 to Q, and the initial value is 1.

[0082] S1056, take the cell corresponding to the counting set with the most combined correlation weights among the Q counting sets as the target cell;

[0083] S1057. Obtain the correlation weight between the detection error and the diameter of the steel bar, and the correlation weight between the detection error and the length of the sleeve based on the target cell.

[0084] Further, in S1057, the correlation weight between the detection error and the diameter of the steel bar is the x-coordinate value of the center coordinate of the target cell, and the correlation weight between the detection error and the length of the sleeve is the y-coordinate value of the center coordinate of the target cell.

[0085] Further, in S1057, the correlation weight between the detection error and the diameter of the steel bar is the x-coordinate value of the lower-right corner coordinate of the target cell, and the correlation weight between the detection error and the length of the sleeve is the y-coordinate value of the lower-right corner coordinate of the target cell.

[0086] It should be understood that the various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution disclosed in the present invention can be achieved. No limitations are imposed herein.

[0087] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for detecting residual deformation of a steel bar sleeve, for detecting the residual deformation of a sleeve of an object to be detected, wherein the object to be detected comprises two sections of steel bars and a sleeve connecting the two sections of steel bars, characterized in that: The method comprises the following steps: S100, installing a residual deformation detection device on a steel bar of an object to be detected to form a structure to be detected, wherein the residual deformation detection device includes a residual strain detector, and the residual strain detector is communicatively connected to a data processing device; S200, clamping two sections of steel bars of the structure to be tested on force applying devices respectively, and controlling the force applying devices to apply corresponding loads to the steel bars based on specified testing conditions; S300, acquiring a signal detected by a residual strain detector, and acquiring a residual deformation amount of the sleeve based on the acquired signal as a candidate residual deformation amount; S400, based on the specified detection condition, obtain a corresponding residual deformation detection error relationship expression, and obtain a residual deformation detection error corresponding to the object to be detected based on the obtained residual deformation detection error relationship expression, wherein the residual deformation detection error relationship expression satisfies the following condition: Y=f(D, L), wherein Y is the residual deformation detection error, D is the diameter of the steel bar, L is the length of the sleeve, and f() is a preset function expression; S500, obtaining a target residual deformation of a sleeve of the object to be detected based on the candidate residual deformation and a residual deformation error corresponding to the object to be detected.

2. The method according to claim 1, characterized in that The detection conditions include multiple set detection conditions, and the residual deformation error relationship expression corresponding to any set detection condition is obtained by the following steps: S10, preparing a first sample detection object group and a second sample detection object group, wherein the first sample detection object group and the second sample detection object group both include n sample detection objects, and the i-th sample detection object in the first sample detection object group and the second sample detection object group is the same, and both include two segments with a diameter of D i The steel bar and length L i The sleeve, i ranges from 1 to n; S11, under the same set detection conditions, using the first residual deformation detection device to perform residual deformation detection tests on n sample detection objects in the first sample detection object group, respectively, to obtain n first candidate residual deformations; wherein the detection error of the first residual deformation detection device is E0; S12, based on the n first candidate residual deformations and E0, obtaining target residual deformations corresponding to n sample detection objects; S13, under the same set detection conditions, using a second residual deformation detection device to perform residual deformation detection tests on n sample detection objects in the second sample detection object group, respectively, to obtain n second candidate residual deformations; S14, obtaining a difference between an i-th target residual deformation amount among the target residual deformation amounts corresponding to the n sample detection objects and an i-th second candidate residual deformation amount among the n second candidate residual deformation amounts as an i-th sample detection error; obtaining n sample detection errors; S15, based on the diameter of the steel bar, the length of the sleeve and the sample detection error corresponding to the n sample detection objects in the second sample detection object group, obtain the association weight between the detection error and the diameter of the steel bar, and the association weight between the detection error and the length of the sleeve, and then obtain the residual deformation error relationship expression corresponding to the set detection condition.

3. The method according to claim 2, characterized in that S15 specifically includes: S1501, based on n relational expressions corresponding to n sample detection objects in the second sample detection object group, obtain a corresponding association weight combination set C=(C1, C2, . . . , C r , ..., C m ), C r is the rth association weight combination in C, r ranges from 1 to m, m is the number of association weight combinations in C, C r =(C r D , C r L ), C r D is the rth detection error-diameter association weight, C r L is the rth detection error-length association weight; each relational expression represents the association between the detection error and the diameter of the steel bar and the length of the sleeve; S1502, draw a square in a rectangular coordinate system with a length of L1 along the x-axis and a length of L2 along the y-axis; wherein L1=(C D-max -C D-min ), C D-max is the maximum detection error-diameter association weight in C, C D-min is the minimum detection error-diameter association weight in C, L2=(C L-max -C L-min ), C L-max is the maximum detection error-length association weight in C, C L-max is the minimum detection error-length association weight in C, and the coordinate of the upper left corner of the square is (C D-min , C L-min ); S1053, obtain min((C s D -C s-1 D ) s＝2……m ) as the length of the cell along the x-axis and get min((C s L -C s-1 L ) s＝2……m ) as the length of the cell along the y-axis; S1054, using cells to divide the square into Q cells; S1055, for the zth cell among the Q cells, traverse C, if C r Belongs to the zth cell, C r Add to the counting set corresponding to the zth cell. The initial value of the counting set corresponding to the zth cell is empty. The value of z ranges from 1 to Q, and the initial value is 1. S1056, taking the cell corresponding to the counting set with the most associated weight combinations among the Q counting sets as the target cell; S1057, based on the target cell, obtain the association weight between the detection error and the diameter of the steel bar, and the association weight between the detection error and the length of the sleeve.

4. The method according to claim 3, characterized in that In S1057, the association weight between the detection error and the diameter of the steel bar is the x-coordinate value of the center coordinate of the target cell, and the association weight between the detection error and the length of the sleeve is the y-coordinate value of the center coordinate of the target cell.

5. The method according to claim 3, characterized in that: In S1057, the association weight between the detection error and the diameter of the steel bar is the x-coordinate value of the lower right corner coordinate of the target cell, and the association weight between the detection error and the length of the sleeve is the y-coordinate value of the lower right corner coordinate of the target cell.

6. A steel sleeve residual deformation detection system, characterized in that: The system includes a processor and a database, wherein a reference table of residual deformation detection error relationship expressions is stored in the database, wherein each row of data in the reference table of residual deformation detection error relationship expressions includes a corresponding detection condition and a corresponding residual deformation detection error relationship expression; the processor is connected to a residual strain detector of a residual deformation detection device, wherein the residual deformation detection device is installed on an object to be detected, wherein the object to be detected includes two sections of steel bars and a sleeve connecting the two sections of steel bars, and wherein the object to be detected is installed on a force applying device; wherein the processor is used to execute a computer program to implement the following steps: S1, controlling the force applying device to apply a corresponding load to the steel bar based on a specified detection condition; S2, acquiring a signal detected by a residual strain detector, and acquiring a residual deformation amount of the sleeve based on the acquired signal as a candidate residual deformation amount; S3, based on the detection condition to be detected, obtain the corresponding residual deformation detection error relationship expression from the residual deformation detection error relationship expression reference table, and obtain the residual deformation detection error corresponding to the object to be detected based on the obtained residual deformation detection error relationship expression, and the residual deformation detection error relationship expression satisfies the following condition: Y=f(D, L), where Y is the residual deformation detection error, D is the diameter of the steel bar, L is the length of the sleeve, and f() is a preset function expression; S4, obtaining a target residual deformation amount of a sleeve of the object to be detected based on the candidate residual deformation amount and a residual deformation amount error corresponding to the object to be detected.

7. The system according to claim 6, characterized in that Residual deformation detection error relationship expression reference table Any residual deformation detection error relationship expression can be obtained by the following steps: S10, preparing a first sample detection object group and a second sample detection object group, wherein the first sample detection object group and the second sample detection object group both include n sample detection objects, and the i-th sample detection object in the first sample detection object group and the second sample detection object group is the same, and both include two segments with a diameter of D i The steel bar and length L i The sleeve, i ranges from 1 to n; S11, under the same set detection conditions, using the first residual deformation detection device to perform residual deformation detection tests on n sample detection objects in the first sample detection object group, respectively, to obtain n first candidate residual deformations; wherein the detection error of the first residual deformation detection device is E0; S12, based on the n first candidate residual deformations and E0, obtaining target residual deformations corresponding to n sample detection objects; S13, under the same set detection conditions, using a second residual deformation detection device to perform residual deformation detection tests on n sample detection objects in the second sample detection object group, respectively, to obtain n second candidate residual deformations; S14, obtaining a difference between an i-th target residual deformation amount among the target residual deformation amounts corresponding to the n sample detection objects and an i-th second candidate residual deformation amount among the n second candidate residual deformation amounts as an i-th sample detection error; obtaining n sample detection errors; S15, based on the diameter of the steel bar, the length of the sleeve and the sample detection error corresponding to the n sample detection objects in the second sample detection object group, obtain the association weight between the detection error and the diameter of the steel bar, and the association weight between the detection error and the length of the sleeve, and then obtain the residual deformation error relationship expression corresponding to the set detection condition.

8. The system according to claim 7, characterized in that S15 specifically includes: S1501, based on n relational expressions corresponding to n sample detection objects in the second sample detection object group, obtain a corresponding association weight combination set C=(C1, C2, . . . , C r , ..., C m ), C r is the rth association weight combination in C, r ranges from 1 to m, m is the number of association weight combinations in C, C r =(C r D , C r L ), C r D is the rth detection error-diameter association weight, C r L is the rth detection error-length association weight; each relational expression represents the association between the detection error and the diameter of the steel bar and the length of the sleeve; S1502, draw a square in a rectangular coordinate system with a length of L1 along the x-axis and a length of L2 along the y-axis; wherein L1=(C D-max -C D-min ), C D-max is the maximum detection error-diameter association weight in C, C D-min is the minimum detection error-diameter association weight in C, L2=(C L-max -C L-min ), C L-max is the maximum detection error-length association weight in C, C L-max is the minimum detection error-length association weight in C, and the coordinate of the upper left corner of the square is (C D-min , C L-min ); S1053, obtain min((C s D -C s-1 D ) s＝2……m ) as the length of the cell along the x-axis and get min((C s L -C s-1 L ) s＝2……m ) as the length of the cell along the y-axis; S1054, using cells to divide the square into Q cells; S1055, for the zth cell among the Q cells, traverse C, if C r Belongs to the zth cell, C r Add to the counting set corresponding to the zth cell. The initial value of the counting set corresponding to the zth cell is empty. The value of z ranges from 1 to Q, and the initial value is 1. S1056, taking the cell corresponding to the counting set with the most associated weight combinations among the Q counting sets as the target cell; S1057, based on the target cell, obtain the association weight between the detection error and the diameter of the steel bar, and the association weight between the detection error and the length of the sleeve.

9. The system according to claim 8, characterized in that In S1057, the association weight between the detection error and the diameter of the steel bar is the x-coordinate value of the center coordinate of the target cell, and the association weight between the detection error and the length of the sleeve is the y-coordinate value of the center coordinate of the target cell.

10. The system according to claim 8, characterized in that In S1057, the association weight between the detection error and the diameter of the steel bar is the x-coordinate value of the lower right corner coordinate of the target cell, and the association weight between the detection error and the length of the sleeve is the y-coordinate value of the lower right corner coordinate of the target cell.

Images