Quantitative detection equipment and detection method for corrosion degree of section of inhaul cable

Abstract

The invention discloses quantitative detection equipment and a detection method for corrosion degree of a cross section of an inhaul cable. The quantitative detection equipment comprises a rack, a clamping jaw mechanism, an electrode electrifying mechanism and a mobile photographing mechanism, the clamping jaw mechanism comprises two electrodes located on the inner sides of the two clamping jaws. According to the method, a corrosion degree quantitative prediction model of the to-be-tested steel wire on the surface of the inhaul cable is established, an in-service or replaced bridge inhaul cable is windowed, the inhaul cables on the two sides of the windowing portion are clamped through the clamping jaw mechanism, the to-be-tested steel wire on the surface of one inhaul cable on the windowing portion is electrified through the electrode electrifying mechanism, and the to-be-tested steel wire on the surface of the other inhaul cable on the windowing portion is subjected to corrosion degree quantitative prediction. The mobile photographing mechanism detects the temperature of the detected steel wire before and after electrification, obtains a corrosion characteristic value of the detected steel wire on the surface of the inhaul cable according to a detection result and experimental data, and substitutes the corrosion characteristic value into the corrosion degree quantitative prediction model, with a determined correction coefficient, of the detected steel wire on the surface of the inhaul cable. Therefore, the mass loss rate of the tested steel wire on the surface of the inhaul cable is quantitatively obtained, and a bridge management unit is better assisted to judge whether the on-service bridge inhaul cable is replaced or not.

Description

Technical Field

[0001] The present invention relates to the technical field of civil engineering bridge detection, in particular to a device and method for quantitatively detecting the corrosion degree of a cable cross section. Background Art

[0002] Bridge cables, consisting of steel wire bundles and sheaths, are widely used in bridge construction due to their high strength, ability to carry and transmit the critical loads of bridges, and ability to maintain structural stability. These cables are commonly used in cable-supported bridges, such as cable-stayed bridges, suspension bridges, and tied-arch bridges. However, in-service cables often suffer from corrosion, causing damage and compromising the structural safety of the bridge. Currently, a large number of in-service cables require frequent replacement, which inevitably leads to significant steel consumption and waste.

[0003] Therefore, timely quantitative testing and assessment of the corrosion level of steel wires in some replaced bridge cables can better assist bridge management units in determining whether to replace these cables. This can also help users achieve more rational, efficient, and economical use of steel products. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to address the deficiencies of the above-mentioned existing technologies and to provide a quantitative detection device and method for the corrosion degree of the cable cross section. The quantitative detection device and method for the corrosion degree of the cable cross section can quantitatively detect and evaluate the corrosion degree of the steel wire in the cable, thereby better assisting bridge management units in determining whether to replace the bridge cables in service.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A method for quantitatively detecting the corrosion degree of a cable cross section includes the following steps.

[0007] Step 1: Establish a quantitative prediction model for the corrosion degree of the tested steel wire on the cable surface: Based on the quantitative prediction model for the corrosion degree of a single corroded steel wire, the mass loss rate X of the corroded steel wire is calculated. D , the length correction coefficient α1 and the in-situ detection correction coefficient α2 are used to make corrections, forming a quantitative prediction model for the corrosion degree of the tested steel wire on the cable surface.

[0008] Step 2: Calculate α1, which is the ratio of the energized length in the quantitative prediction model for the corrosion degree of a single corroded steel wire to the energized length in the quantitative prediction model for the corrosion degree of the steel wire being tested on the cable surface.

[0009] Step 3: For the replaced in-service bridge cables, determine α2 through corrosion pickling test.

[0010] Step 4. Quantitative detection of the corrosion degree of the cable cross section: A window is opened on the in-service or replaced bridge cable, and the cables on both sides of the window are clamped with a clamping claw mechanism. The electrode energization mechanism energizes one of the tested steel wires A in the window, and the mobile camera mechanism detects the temperature of the tested steel wire A before and after energization. Based on the test results and experimental data, the corrosion characteristic value F of the tested steel wire on the cable surface is obtained.

[0011] Step 5: Substitute the corrosion characteristic value F of the measured steel wire on the cable surface obtained in step 4 into the quantitative prediction model of the corrosion degree of the measured steel wire on the cable surface with a certain correction coefficient to obtain the mass loss rate X of the measured steel wire on the cable surface. D .

[0012] In step 1, the specific expression of the quantitative prediction model for the corrosion degree of the tested steel wire on the cable surface is:

[0013] F=a×(α1×α2×X D ) 3 +b×(α1×α2×X D ) 2 +c×(α1×α2×X D )+d

[0014] Where F is the corrosion characteristic value of the measured steel wire on the cable surface.

[0015] X D is the mass loss rate of the measured steel wire on the cable surface.

[0016] a, b, c, and d are the fitting coefficients in the quantitative prediction model of the corrosion degree of a single corroded steel wire.

[0017] In step 2, the energized length of a single corroded steel wire in the quantitative prediction model of the corrosion degree of a single corroded steel wire is assumed to be L0, and the length of the steel wire to be energized on the cable surface is assumed to be L1, then α1 is the ratio of L0 to L1.

[0018] In step 3, the method for determining α2 includes the following steps.

[0019] Step 3-1. Preliminarily determine the value range of α2: perform in-situ galvanic corrosion testing and offline testing on the steel wire A under test in the cable, respectively, to obtain the in-situ corrosion characteristic value F1 and the offline corrosion characteristic value F0 of the steel wire A under test, and the ratio of F1 to F0 is the initial value range of α2; wherein, in-situ galvanic corrosion testing means that the position of the steel wire A under test in the cable remains unchanged for testing; offline testing means that the steel wire A under test is peeled off from the cable to form a single steel wire for testing.

[0020] Step 3-2, calculate X D0: The steel wire A tested offline is subjected to a pickling test to obtain the mass loss rate X of the steel wire A after pickling. D0 .

[0021] Step 3-3: According to the initial value range of α2 determined in step 3-1, n different values ​​of α2 are selected to form a quantitative prediction model for the corrosion degree of the tested steel wires on the surface of the n cables.

[0022] Step 3-4: Substitute the n in-situ corrosion characteristic values ​​F1 obtained from n in-situ detection tests into the quantitative prediction model of the corrosion degree of the tested steel wire on the surface of the n cables to obtain the n in-situ detection quality loss rate X D1 .

[0023] Step 3-5: n in-situ detection mass loss rate X D1 Respectively with the mass loss rate after pickling X D0 Compare and select the X with the smallest error D1 The corresponding α2 is the optimal α2 value found.

[0024] In step 4, the mobile camera mechanism performs infrared detection on the temperature of the steel wire A before and after power is applied.

[0025] In step 4, the window length can be adjusted according to user needs, and thus the cable clamping spacing of the clamping jaw mechanism can be adjusted, and the power-on length in the electrode power-on mechanism can be adjusted.

[0026] A device for quantitatively detecting the corrosion degree of a cable cross section comprises a frame, a clamping claw mechanism, an electrode electrification mechanism and a mobile photographing mechanism.

[0027] The axis of the frame is parallel to the length direction of the cable.

[0028] The clamping mechanism comprises two clamping jaws arranged in parallel along the axis of the frame; each clamping jaw can actively open and close to clamp the cable.

[0029] The electrode power supply mechanism includes a power supply and two electrodes connected to the power supply; the two electrodes are located inside the two clamping jaws, and the bottom of each electrode has a conductive contact probe that can fit the surface of the measured steel wire.

[0030] The mobile photographing mechanism is slidably arranged on the frame and can slide back and forth between the two electrodes.

[0031] One or two jaws in the jaw mechanism can slide along the frame to adjust the distance between the two jaws. The opening and closing degree of each jaw can be adjusted. Each jaw is provided with at least one arc-shaped support foot with adjustable angle on the inside.

[0032] Two electrodes are arranged on two clamping jaws. The height of each electrode can be raised and lowered, and can slide back and forth in a direction perpendicular to the cable.

[0033] The mobile photographing mechanism comprises an infrared camera arranged just above the cable.

[0034] The present invention has the following beneficial effects:

[0035] Compared with the prior art, the present invention has the following characteristics and advantages:

[0036] 1. The infrared camera can automatically capture images of any radial or lateral position on the surface of the cable's window inspection area, and quickly obtain detailed temperature distribution information during the period when the wire maintains temperature. By analyzing this data, a quantitative prediction model for the degree of corrosion of the cable's surface wire can be established. Combined with the corrosion distribution patterns of each layer of the cable's cross-section, the degree of corrosion in the cable's cross-section can be quantified. This helps improve the reliability of corrosion assessments of in-service bridge cables, assists bridge management units in determining whether to replace in-service bridge cables, and achieves the goal of reducing resource waste and protecting the ecological environment.

[0037] 2. The hinged structure of the swing arm allows the diameter of the cable clamped by the equipment to be variable, improving the adaptability of the equipment;

[0038] 3. Through experiments, we can obtain the relationship between the mass loss rate of corroded steel wire on the surface of cables with different corrosion degrees and the surface temperature after electrical thermal excitation, which will help enrich the database of the prediction model and increase the accuracy of the prediction model evaluation results;

[0039] 4. Select key parts of the in-service cables for in-situ window quantitative testing. The detection effect is intuitive and can reduce the influence of air heat exchange and equipment operation on the steel wire collection temperature during the detection. Using the results of the front temperature of the tested steel wire to judge the degree of steel wire corrosion is conducive to improving the accuracy of the quantitative corrosion assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram showing the structure of a device for quantitatively detecting the degree of corrosion of a cable cross section according to the present invention is shown.

[0041] Figure 2 Shown is a schematic structural diagram of the clamping jaws of the present invention.

[0042] Figure 3 A schematic diagram showing the electrode energization mechanism of the present invention is shown.

[0043] Figure 4 A schematic diagram of the mobile photographing mechanism of the present invention is shown.

[0044] The picture includes:

[0045] 1. Gripping mechanism; 11. Gripping base; 12. Electric push rod; 13. Swing arm; 14. Support foot;

[0046] 2. Electrode energizing mechanism; 21. Lifting rod; 22. Electrode; 23. Energized contact probe; 24. Screw; 25. Screw nut; 26. Handwheel; 27. Horizontal guide rail; 28. Horizontal slider; 29. ​​Thermal insulation block;

[0047] 3. Mobile camera mechanism; 31. X-axis slide rail; 32. X-axis slider; 33. Infrared camera; 34. Camera bracket; 35. Motor; 36. Synchronous pulley; 37. Driven pulley; 38. Synchronous belt;

[0048] 4. Frame; 5. Cable. DETAILED DESCRIPTION

[0049] The present invention will be further described in detail below with reference to the accompanying drawings and specific preferred embodiments.

[0050] In the description of the present invention, it should be understood that the terms "left side," "right side," "upper," "lower," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Terms such as "first" and "second" do not indicate the importance of components and therefore should not be construed as limitations on the present invention. The specific dimensions used in this embodiment are intended only to illustrate the technical solution and do not limit the scope of protection of the present invention.

[0051] like Figure 1 As shown, a device for quantitatively detecting the corrosion degree of a cable cross section includes a clamping mechanism 1, an electrode power supply mechanism 2, a mobile camera mechanism 3 and a frame 4.

[0052] The axis of the frame is parallel to the X-direction of the cable length. In this embodiment, the frame includes two axial horizontal rods and two cross rods. The two axial horizontal rods are arranged along the cable length, and the two cross rods are arranged along the Y-direction perpendicular to the cable length and are used to connect the two axial horizontal rods. The two cross rods can be fixedly connected to the two axial horizontal rods, in which case the length between the two cross rods is not adjustable. Alternatively, the ends of one or both cross rods can be slidably connected to the two axial horizontal rods, in which case the length between the two cross rods can be adjusted as needed to accommodate different subsequent window opening requirements.

[0053] The clamping mechanism includes two clamping jaws arranged parallel to the axis of the frame; each clamping jaw can actively adjust the opening and closing angle, so as to clamp cables of different diameters.

[0054] like Figure 2As shown, each clamping jaw includes a clamping jaw base 11 , an electric push rod 12 and a swing arm 13 .

[0055] In this embodiment, the clamping jaws bases of the two clamping jaws are respectively installed at the bottom of the two cross bars, and are in an inverted U shape.

[0056] The top of the swing arm 13 is hinged to the top of the electric push rod 12, and the electric push rod is installed on the clamping jaw base; since the length of the electric push rod is adjustable, the opening and closing angle of the clamping jaw can be controlled.

[0057] The middle part of the swing arm adjacent to the electric push rod is hinged to the outer side of the bottom of the clamp base; the lower middle part of the swing arm is the gripping part of the clamp, and the inner side of the gripping part is provided with at least one angle-adjustable and arc-shaped support foot 14. Since the angle of each support foot can be adjusted, it can fit tightly with the surface of the cable.

[0058] like Figure 3 As shown, the electrode energizing mechanism includes two electrodes 22 connected to an external power source; the two electrodes are located inside the two clamping jaws, and the bottom of each electrode has an energized contact probe 23 that can fit the surface of the steel wire to be measured.

[0059] The two electrodes are directly or indirectly arranged on the two clamping jaws. The height of each electrode can be raised or lowered, and can slide back and forth in a direction perpendicular to the cable.

[0060] In this embodiment, a two-dimensional movable frame is provided on the top of each electrode, and two two-dimensional movable frames are respectively installed on the top of the two crossbars.

[0061] Each two-dimensional moving frame includes a Y-moving component and a height lifting component.

[0062] The Y-direction movement assembly includes a transverse rail 27, a transverse slider 28, and a transverse sliding drive mechanism. The transverse rail is arranged along the Y-direction at the top of the corresponding crossbar. The transverse slider can slide along the transverse rail under the drive of the transverse sliding drive mechanism. The transverse sliding drive mechanism is conventional and can be a motor or a cylinder. In this embodiment, it is preferably a screw drive mechanism, including a screw 24, a screw nut 25, and a handwheel 26. The screw nut is mounted on the transverse slider, and the screw and screw nut are threaded together and can rotate under the drive of the handwheel, thereby driving the transverse slider to slide along the Y-direction.

[0063] The height lifting component is also a prior art. In this embodiment, it is preferably an electrically driven lifting rod 21 , and the bottom of the lifting rod is preferably connected to the electrode through an insulation block 29 .

[0064] Since the distance between the cross bars can be adjusted as needed, the distance between the two clamping jaws and the two electrodes can be adjusted synchronously as needed to meet different cable window opening length requirements.

[0065] The mobile photographing mechanism is slidably arranged on the frame and can slide back and forth between the two electrodes.

[0066] like Figure 4 As shown, the mobile photographing mechanism includes an X-direction moving component, a camera bracket 34 and an infrared camera 33; the infrared camera is installed on the top of the camera bracket and faces the cable below; the bottom of the camera bracket can slide along the X direction under the drive of the X-direction moving component.

[0067] The X-direction moving assembly includes an X-direction slide rail 31, an X-direction slider 32 and an X-direction sliding drive mechanism. The X-direction slide rail is arranged on one of the axial horizontal rods, and the X-direction slider can slide in the X direction along the X-direction slide rail under the drive of the X-direction sliding drive mechanism.

[0068] In this example, the X-direction sliding drive mechanism is preferably a synchronous belt drive mechanism installed on the outer wall of the frame, including a motor 35 , a synchronous wheel 36 , a driven wheel 37 and a synchronous belt 38 .

[0069] The synchronous pulley and driven pulley are mounted on either end of the outer wall of the frame. A synchronous belt is fitted around their circumferences. The X-axis slider is mounted on the top synchronous belt. When the motor drives the synchronous pulley to rotate, it in turn drives the X-axis slider to slide back and forth in the X-axis. Alternatively, the X-axis sliding drive mechanism may employ other structures known in the art.

[0070] A method for quantitatively detecting the corrosion degree of a cable cross section includes the following steps.

[0071] Step 1: Establish a quantitative prediction model for the corrosion degree of the tested steel wire on the cable surface: Based on the quantitative prediction model for the corrosion degree of a single corroded steel wire, the mass loss rate X of the corroded steel wire is calculated. D , the length correction coefficient α1 and the in-situ detection correction coefficient α2 are used to make corrections, forming a quantitative prediction model for the corrosion degree of the tested steel wire on the cable surface.

[0072] In the present invention, the specific expression of the quantitative prediction model of the corrosion degree of the measured steel wire on the cable surface is:

[0073] F=a×(α1×α2×X D ) 3 +b×(α1×α2×X D ) 2 +c×(α1×α2×X D )+d

[0074] Where F is the corrosion characteristic value of the measured steel wire on the cable surface.

[0075] X D is the mass loss rate of the measured steel wire on the cable surface.

[0076] a, b, c, and d are the fitting coefficients in the quantitative prediction model of the corrosion degree of a single corroded steel wire.

[0077] The above-mentioned quantitative prediction model for the corrosion degree of a single corroded steel wire is specifically referred to the applicant's previously published patent "A portable automatic detection device and detection method for steel wire corrosion", corresponding to publication number CN117309668A, which will not be repeated here.

[0078] In CN117309668A, the preferred model for quantitative prediction of corrosion degree of a single corroded steel wire is:

[0079] F'=3.22×10 -9 X D 3 -1.543×10 -8 X D 2 +2.461×10 -8 X D -1.279×10 -8

[0080] Therefore, in this embodiment, the preferred expression of the quantitative prediction model for the corrosion degree of the measured steel wire on the cable surface is:

[0081] F = 3.22 × 10 -9 ×(1.3×1.25×X D ) 3 -1.543×10 -8 ×(1.3×1.25×X D ) 2 +

[0082] 2.461×10 -8 ×(1.3×1.25×X D )-1.279×10 -8

[0083] Step 2: Calculate α1, which is the ratio of the energized length in the quantitative prediction model for the corrosion degree of the measured steel wire on the cable surface to the energized length in the quantitative prediction model for the corrosion degree of a single corroded steel wire.

[0084] Assuming that the energized length of a single corroded steel wire in the quantitative prediction model of the corrosion degree of a single corroded steel wire is L0, and the length of the steel wire to be energized on the cable surface is L1, then α1 is the ratio of L0 to L1.

[0085] In CN117309668A, L0=650cm. Assuming that L1=500cm is required in this application, α1=650cm / 500cm=1.3. In this application, the energized length is reduced, that is, the window length is reduced, and the damage to the in-service cables is also reduced.

[0086] Step 3: For the replaced in-service bridge cables, determine α2 through corrosion testing, which specifically includes the following steps.

[0087] Step 3-1. Preliminarily determine the value range of α2: perform in-situ galvanic corrosion testing and offline testing on the steel wire A under test in the cable, respectively, to obtain the in-situ corrosion characteristic value F1 and the offline corrosion characteristic value F0 of the steel wire A under test, and the ratio of F1 to F0 is the initial value range of α2; wherein, in-situ galvanic corrosion testing means that the position of the steel wire A under test in the cable remains unchanged for testing; offline testing means that the steel wire A under test is peeled off from the cable to form a single steel wire for testing.

[0088] Since this technical application is for in-situ power-on detection of the cable (online detection), the tested cable wire does not need to be removed from the cable for detection. Therefore, the difference in heat loss after power-on heating between online and offline detection needs to be considered, and an in-situ detection correction factor α2 is introduced. The patent "A portable automatic detection device and detection method for steel wire corrosion" (patent publication number CN117309668A) uses offline detection of steel wires, where a single steel wire is directly exposed to room temperature air for power-on heating; while in this technical application, the equipment is placed directly on the cable to perform online detection of the tested steel wire. When the power is on and heated, the tested steel wire is closely fitted to adjacent steel wires, reducing the heat loss after power-on heating. Therefore, by comparing the two detection methods, it is initially determined that the in-situ detection correction coefficient α2 is greater than 1, indicating that under the same current and resistance of the tested steel wire, the heat obtained from online detection of the steel wire is higher than that from offline detection.

[0089] Offline testing and pickling tests were conducted on the tested wire to obtain the specific value of the in-situ testing correction factor α2. First, the cable sheath was removed from the tested cable section, and the tested wire was tested offline. The corrosion characteristic value F0 of the offline test was calculated. Multiple repeated tests were conducted for both online and offline testing. The F1 value calculated from the online test was 1.2 to 1.4 times that of the offline test, reflecting that the heat loss from online testing is less than that from offline testing. Therefore, the value range of the in-situ testing correction factor α2 was selected to be 1.2 to 1.4.

[0090] The above F1 and F0 can both be calculated using the following F calculation formula, specifically:

[0091]

[0092] in:

[0093] ΔT test =T1-T0

[0094] In the formula, ρ is the density of the iron matrix in the steel wire being tested, d test is the diameter of the steel wire being measured, I testis the constant current of the steel wire being tested, t test is the heating time of the tested steel wire; T1 is the temperature of the tested steel wire after power is applied; T0 is the temperature of the tested steel wire before power is applied; ΔT test It is the temperature difference before and after the steel wire is energized.

[0095] Step 3-2, calculate X D0 : The steel wire A tested offline is subjected to a pickling test to obtain the mass loss rate X of the steel wire A after pickling. D0 For the specific pickling test method, please refer to CN117309668A.

[0096] Step 3-3: According to the initial value range of α2 determined in step 3-1, n different values ​​of α2 are selected to form a quantitative prediction model for the corrosion degree of the tested steel wires on the surface of the n cables.

[0097] Step 3-4: Substitute the n in-situ corrosion characteristic values ​​F1 obtained from n in-situ detection tests into the quantitative prediction model of the corrosion degree of the tested steel wire on the surface of the n cables to obtain the n in-situ detection quality loss rate X D1 .

[0098] Step 3-5: n in-situ detection mass loss rate X D1 Respectively with the mass loss rate after pickling X D0 Compare and select the X with the smallest error D1 The corresponding α2 is the optimal α2 value found. In this embodiment, α2=1.25 is preferred.

[0099] Step 4: Quantitative detection of the corrosion degree of the cable cross section: A window is opened on the in-service or replaced bridge cable, and the cables on both sides of the window are clamped with a clamping claw mechanism. The electrode energization mechanism energizes one of the tested steel wires A in the window. The mobile camera mechanism performs infrared detection on the temperature of the tested steel wire A before and after energization. Based on the test results and experimental data, the corrosion characteristic value F of the tested steel wire on the cable surface is obtained.

[0100] Furthermore, the window length can be adjusted according to user needs, and thus the cable clamping spacing of the clamping jaw mechanism can be adjusted, and the power-on length in the electrode power-on mechanism can be adjusted.

[0101] Step 5: Substitute the corrosion characteristic value F of the measured steel wire on the cable surface obtained in step 4 into the quantitative prediction model of the corrosion degree of the measured steel wire on the cable surface with a certain correction coefficient to obtain the mass loss rate X of the measured steel wire on the cable surface. D .

[0102] The present invention utilizes a device for quantitatively detecting the corrosion level of cable cross sections and a model correction method. Based on the heat conduction characteristics of in-situ testing, a length correction factor and an in-situ detection correction factor are introduced to establish a quantitative prediction model for the corrosion level of the cable surface steel wire. During actual testing, the device is powered on for heating and the prediction model is used to calculate the mass loss rate of the cable's outermost layer of steel wire. Combined with the corrosion distribution patterns of each layer of steel wire in the cable cross section, this allows for quantitative detection of the corrosion level of in-service cable cross sections. This facilitates a comprehensive assessment of the corrosion status of in-service bridge cable cross sections. Furthermore, it addresses the daily maintenance challenges of large-scale, widespread bridge cables nationwide, enabling economical, efficient, low-carbon, and scientific decision-making. This minimizes unnecessary cable replacements and thus reduces carbon emissions at the root.

[0103] The preferred embodiments of the present invention are described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, various equivalent transformations can be made to the technical solutions of the present invention, and these equivalent transformations all fall within the scope of protection of the present invention.

Claims

1. A method for quantitatively detecting the corrosion degree of a cable cross section, characterized by: The steps include: Step 1: Establish a quantitative prediction model for the corrosion degree of the tested steel wire on the cable surface: Based on the quantitative prediction model for the corrosion degree of a single corroded steel wire, the mass loss rate X of the corroded steel wire is calculated. D , using the length correction coefficient α1 and the in-situ detection correction coefficient α2 to make corrections, forming a quantitative prediction model for the corrosion degree of the tested steel wire on the cable surface; Step 2: Calculate α1, which is the ratio of the energized length in the quantitative prediction model for the corrosion degree of a single corroded steel wire to the energized length in the quantitative prediction model for the corrosion degree of the steel wire being tested on the cable surface; Step 3: For the replaced in-service bridge cables, determine α2 through corrosion pickling test: Step 4: Quantitative detection of the corrosion degree of the cable cross section: A window is opened on the in-service or replaced bridge cable, and the cables on both sides of the window are clamped using a clamping mechanism. An electrode energizing mechanism energizes one of the tested steel wires A in the window. A mobile camera mechanism detects the temperature of the tested steel wire A before and after energization. Based on the test results and experimental data, the corrosion characteristic value F of the tested steel wire on the cable surface is obtained; Step 5: Substitute the corrosion characteristic value F of the measured steel wire on the cable surface obtained in step 4 into the quantitative prediction model of the corrosion degree of the measured steel wire on the cable surface with a certain correction coefficient to obtain the mass loss rate X of the measured steel wire on the cable surface. D .

2. The method for quantitatively detecting the corrosion degree of a cable cross section according to claim 1, characterized in that: In step 1, the specific expression of the quantitative prediction model for the corrosion degree of the tested steel wire on the cable surface is: F=a×(α1×α2×X D ) 3 +b×(α1×α2×X D ) 2 +c×(α1×α2×X D )+d Where F is the corrosion characteristic value of the steel wire on the cable surface; X D is the mass loss rate of the measured steel wire on the cable surface; a, b, c, and d are the fitting coefficients in the quantitative prediction model of the corrosion degree of a single corroded steel wire.

3. The method for quantitatively detecting the corrosion degree of a cable cross section according to claim 1, characterized in that: In step 2, the energized length of a single corroded steel wire in the quantitative prediction model of the corrosion degree of a single corroded steel wire is assumed to be L0, and the length of the steel wire to be energized on the cable surface is assumed to be L1, then α1 is the ratio of L0 to L1.

4. The method for quantitatively detecting the corrosion degree of a cable cross section according to claim 1, characterized in that: In step 3, the method for determining α2 includes the following steps: Step 3-1. Preliminarily determine the value range of α2: Perform in-situ galvanic corrosion testing and offline testing on the steel wire A in the cable, respectively, to obtain the in-situ corrosion characteristic value F1 and the offline corrosion characteristic value F0 of the steel wire A. The ratio of F1 to F0 is the initial value range of α2. In-situ galvanic corrosion testing refers to testing the steel wire A while maintaining its position in the cable; offline testing refers to stripping the steel wire A from the cable to form a single steel wire for testing. Step 3-2, calculate X D0 : The steel wire A tested offline is subjected to a pickling test to obtain the mass loss rate X of the steel wire A after pickling. D0 ; Step 3-3: selecting n different values ​​of α2 according to the initial value range of α2 determined in step 3-1, thereby forming a quantitative prediction model for the corrosion degree of the tested steel wires on the surface of the n cables; Step 3-4: Substitute the n in-situ corrosion characteristic values ​​F1 obtained from n in-situ detection tests into the quantitative prediction model of the corrosion degree of the tested steel wire on the surface of the n cables to obtain the n in-situ detection quality loss rate X D1 ; Step 3-5: n in-situ detection mass loss rate X D1 Respectively with the mass loss rate after pickling X D0 Compare and select the X with the smallest error D1 The corresponding α2 is the optimal α2 value found.

5. The method for quantitatively detecting the corrosion degree of a cable cross section according to claim 1, characterized in that: In step 4, the mobile camera mechanism performs infrared detection on the temperature of the steel wire A before and after power is applied.

6. The method for quantitatively detecting the corrosion degree of a cable cross section according to claim 1, characterized in that: In step 4, the window length can be adjusted according to user needs, and thus the cable clamping spacing of the clamping jaw mechanism can be adjusted, and the power-on length in the electrode power-on mechanism can be adjusted.

7. A device for quantitatively detecting the corrosion degree of a cable cross section, characterized by: It includes a frame, a clamping mechanism, an electrode power supply mechanism and a mobile camera mechanism; The axis of the frame is parallel to the length direction of the cable; The clamping mechanism includes two clamping jaws arranged parallel to the axis of the frame, each of which can actively open and close to clamp the cable; The electrode power supply mechanism includes a power supply and two electrodes connected to the power supply; the two electrodes are located inside the two clamping jaws, and the bottom of each electrode has a conductive contact probe that can fit the surface of the measured steel wire; The mobile photographing mechanism is slidably arranged on the frame and can slide back and forth between the two electrodes.

8. The cable cross-section corrosion degree quantitative detection device according to claim 7, characterized in that: One or two jaws in the jaw mechanism can slide along the frame to adjust the distance between the two jaws. The opening and closing degree of each jaw can be adjusted. Each jaw is provided with at least one arc-shaped support foot with adjustable angle on the inside.

9. The cable cross-section corrosion degree quantitative detection device according to claim 7, characterized in that: Two electrodes are arranged on two clamping jaws. The height of each electrode can be raised and lowered, and can slide back and forth in a direction perpendicular to the cable.

10. The cable cross-section corrosion degree quantitative detection device according to claim 7, characterized in that: The mobile photographing mechanism comprises an infrared camera arranged just above the cable.

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