Corrosion assessment method for bridge cable

Abstract

The invention discloses a bridge cable corrosion assessment method, which comprises the following steps of: firstly, respectively establishing a relation curve between each geometric characteristic parameter and each mechanical characteristic parameter of a bridge cable and a mass loss rate; then, the mass loss rate of the bridge inhaul cable is monitored in real time through the fiber bragg grating corrosion sensor. And then, according to the monitored mass loss rate, parameter values corresponding to various geometric characteristic parameters and mechanical characteristic parameters of the bridge cable are determined through a corresponding relation curve. And finally, respectively evaluating the fatigue life and the ultimate bearing capacity of the bridge inhaul cable through the parameter values of the geometric characteristic parameters and the mechanical characteristic parameters. Therefore, the fatigue life and the ultimate bearing capacity of the bridge inhaul cable can be evaluated without windowing detection or inhaul cable replacement, the cost is low, the steps are simple, and the corrosion state of the inhaul cable can be evaluated in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of measuring the corrosion resistance of materials, and in particular to a method for evaluating the corrosion of bridge cables. Background Art

[0002] Bridge cables are a crucial component of bridge construction, bearing the tensile forces of several structures. Severe damage to bridge cables can impact the normal operation of the bridge and, if not discovered promptly, could even result in serious safety incidents. Although bridge cables have multiple protection systems, over time, damage to the sheath can lead to moisture or water accumulation within the high-strength steel wires within the cable, corroding the high-strength wires. The long-term coupling of the corroded high-strength wires with the loads they bear can lead to wire breakage or even cable breakage, severely impacting the structural performance and posing a significant safety risk. Therefore, monitoring the corrosion status of high-strength cable wires is crucial for evaluating their performance.

[0003] Currently, corrosion assessment of parallel steel cables in bridges typically involves either window testing or post-cable dissection. Window testing is a destructive test that requires repairing the cable's polyethylene (PE) sheath, a complex procedure. While post-cable dissection testing eliminates the need for repairing the PE sheath, it carries significant costs. Therefore, a more cost-effective, simplified method is urgently needed to assess cable corrosion status in real time. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention proposes a bridge cable corrosion assessment method, which can simply assess the corrosion status of bridge cables in real time. The specific technical solution is as follows:

[0005] In a first aspect, a bridge cable corrosion assessment method is provided. In a first possible implementation of the first aspect, the method includes:

[0006] The relationship curves between the geometric characteristic parameters of bridge cables and the mass loss rate are established respectively;

[0007] The mass loss rate of bridge cables is monitored by installing fiber Bragg grating corrosion sensors in the cables.

[0008] Based on the mass loss rate of the bridge cable, the parameter values ​​corresponding to the various geometric characteristic parameters are determined through corresponding relationship curves;

[0009] The fatigue life of the bridge cables is evaluated based on the parameter values ​​of all geometric characteristic parameters.

[0010] In combination with the first implementable manner of the first aspect, in a second implementable manner of the first aspect, the geometric characteristic parameters include an average cross-sectional area, a maximum corrosion depth, and a critical crack size of the steel wire.

[0011] In combination with the first implementable manner of the first aspect, in a third implementable manner of the first aspect, a linear function fitting method is used to establish the relationship curve.

[0012] In conjunction with the first implementable manner of the first aspect, in a fourth implementable manner of the first aspect, monitoring the mass loss rate of the bridge cable includes:

[0013] Obtaining a wavelength change of the fiber grating corrosion sensor;

[0014] According to the wavelength variation, the mass loss rate of the bridge cable is determined by establishing a corrosion characteristic curve, wherein the corrosion characteristic curve represents a mapping relationship between the wavelength variation and the mass loss rate.

[0015] In combination with the fourth implementable manner of the first aspect, in a fifth implementable manner of the first aspect, establishing the corrosion characteristic curve includes:

[0016] Acquire multiple sets of test data of steel wire corrosion tests, the test data including test values ​​of wavelength variation of the fiber Bragg grating corrosion sensor and test values ​​of mass loss rate of the steel wire at different measurement times;

[0017] The corrosion characteristic curve is established by performing function fitting on all test data.

[0018] In conjunction with the first implementable manner of the first aspect, in a sixth implementable manner of the first aspect, monitoring the mass loss rate of a bridge cable using a fiber Bragg grating corrosion sensor includes:

[0019] The volume expansion coefficient in the mass loss rate theoretical calculation formula is obtained through the wavelength change in the corrosion characteristic curve, and the mass loss rate is verified through the mass loss rate theoretical calculation formula based on the volume expansion coefficient.

[0020] In combination with the first implementable manner of the first aspect, in a seventh implementable manner of the first aspect, evaluating the fatigue life of the bridge cable includes:

[0021] According to the parameter values ​​corresponding to the corresponding geometric characteristic parameters, the crack shape correction coefficient and critical crack size of the steel wire are calculated. The specific calculation formula is as follows:

[0022]

[0023] The fatigue life of bridge cables is calculated using the Paris formula, combining the crack shape correction coefficient, critical crack size, average stress, and maximum corrosion depth of the steel wire. The specific calculation formula is as follows:

[0024]

[0025] Among them, a is the maximum corrosion depth, A ave is the average cross-sectional area of ​​the steel wire after corrosion, a c is the critical crack size, a0 is the initial crack size, △σ is the average stress, Y is the crack shape correction coefficient, and m and C are the set Paris formula parameters.

[0026] In a second aspect, a bridge cable corrosion assessment method is provided. In a first possible implementation of the second aspect, the method includes:

[0027] The relationship curves between the mechanical characteristic parameters of bridge cables and the mass loss rate were established respectively;

[0028] The mass loss rate of bridge cables is monitored by installing fiber Bragg grating corrosion sensors in the cables.

[0029] Based on the mass loss rate of the bridge cable, the parameter values ​​corresponding to the mechanical characteristic parameters are determined through the corresponding relationship curves;

[0030] The ultimate bearing capacity of the bridge cable is evaluated according to the parameter values ​​of all mechanical characteristic parameters.

[0031] In combination with the first implementable manner of the second aspect, in the second implementable manner of the second aspect, the function corresponding to the established relationship curve between the mechanical characteristic parameters and the mass loss rate is:

[0032] σ b '=(-5.530ρ m 2 -0.723ρ m +1.017)σ b ;

[0033] Among them, σ b is the ultimate strength of the bridge cable steel wire before corrosion, ρ m is the mass loss rate, σ b ' is the ultimate strength of the steel wire after corrosion.

[0034] In combination with the first possible implementation of the second aspect, in a third possible implementation of the second aspect, the specific calculation formula for the ultimate bearing capacity of the bridge cable is as follows:

[0035]

[0036] Where n is the number of steel wires in the bridge cable, d is the diameter of the uncorroded steel wire, and σ bi is the ultimate strength of the i-th steel wire after corrosion.

[0037] Beneficial Effects: The bridge cable corrosion assessment method of the present invention uses a fiber Bragg grating corrosion sensor to detect the mass loss rate of bridge cables in real time. Based on this mass loss rate, the values ​​of various geometric characteristic parameters of the bridge cables are determined using established relationship curves. Finally, combining these values ​​of all geometric characteristic parameters allows the fatigue life of the bridge cables to be assessed. This method allows for corrosion assessment of bridge cables without requiring window testing or cable replacement, resulting in low cost, simple procedures, and real-time assessment of cable corrosion status. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the specific embodiments of the present invention, the following briefly introduces the drawings required for use in the specific embodiments. In all the drawings, each element or part is not necessarily drawn according to the actual scale.

[0039] Figure 1 A flow chart of a bridge cable corrosion assessment method provided by one embodiment of the present invention;

[0040] Figure 2 A flow chart of a bridge cable corrosion assessment method provided by another embodiment of the present invention;

[0041] Figure 3 is the relationship curve between the minimum cross-sectional area and the mass loss rate;

[0042] Figure 4 is the relationship curve between the maximum corrosion depth and mass loss rate;

[0043] Figure 5 is the relationship curve between ultimate strength and mass loss rate;

[0044] Figure 6 is the corrosion characteristic curve between wavelength change and mass loss rate;

[0045] Figure 7 The volume expansion coefficient fitting curve of the wound fiber Bragg grating corrosion sensor;

[0046] Figure 8 This is the volume expansion coefficient fitting curve of the stretched fiber Bragg grating corrosion sensor. DETAILED DESCRIPTION

[0047] The following embodiments of the technical solution of the present invention will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention and are therefore only examples and are not intended to limit the scope of protection of the present invention.

[0048] like Figure 1 A flow chart of a bridge cable corrosion assessment method is shown, which includes:

[0049] Step 1: Establish a relationship curve between the geometric characteristic parameters of the bridge cable and the mass loss rate;

[0050] Step 2: monitoring the mass loss rate of the bridge cables by installing fiber grating corrosion sensors in the bridge cables;

[0051] Step 3: Based on the mass loss rate of the bridge cable, determine the parameter values ​​corresponding to the geometric characteristic parameters through the corresponding relationship curves;

[0052] Step 4: Evaluate the fatigue life of the bridge cables based on the parameter values ​​of all geometric characteristic parameters.

[0053] Specifically, first, relationship curves between the various geometric characteristic parameters associated with the fatigue life of the bridge cable and the mass loss rate can be established. Then, the mass loss rate of the bridge cable can be monitored in real time using a fiber optic Bragg grating corrosion sensor installed on the bridge cable. Afterwards, the mass loss rate can be substituted into the relationship curve corresponding to each geometric characteristic parameter to determine the parameter values ​​corresponding to each geometric characteristic parameter of the current bridge cable. Finally, by combining the parameter values ​​of all geometric characteristic parameters associated with the fatigue life of the bridge cable, the fatigue life of the bridge cable can be evaluated. In this way, the fatigue life of the bridge cable can be evaluated without opening the cable for inspection or replacing the cable. This is low-cost, simple, and can evaluate the corrosion status of the cable in real time.

[0054] In this embodiment, optionally, the geometric characteristic parameters include an average cross-sectional area and a maximum corrosion depth.

[0055] In this embodiment, optionally, in step 1, a linear function fitting method is used to establish the relationship curve.

[0056] Specifically, a sufficient number of steel wire corrosion test parameters can be obtained by conducting multiple sets of steel wire corrosion tests. These steel wire corrosion test parameters include the steel wire's mass loss rate test values, geometric characteristic parameter test values, and mechanical characteristic test values. By performing linear function fitting on the mass loss rate test values ​​and the test values ​​of different geometric characteristic parameters, the relationship curves between the various geometric characteristic parameters and the mass loss rate can be determined. Similarly, by performing linear function fitting on the mass loss rate test values ​​and the test values ​​of different mechanical characteristic parameters, the relationship curves between the mass loss rate and each mechanical characteristic parameter can be determined.

[0057] The fitting function corresponding to the relationship curve between the average cross-sectional area and the mass loss rate established by the linear function fitting method is:

[0058] A ave =-0.298ρ m +38.316.

[0059] The fitting function corresponding to the relationship curve between maximum corrosion depth and mass loss rate is:

[0060]

[0061] In this embodiment, optionally, in step 2, monitoring the mass loss rate of the bridge cables by installing a fiber Bragg grating corrosion sensor in the bridge cables includes:

[0062] Obtaining a wavelength change of the fiber grating corrosion sensor;

[0063] According to the wavelength variation, the mass loss rate of the bridge cable is determined by establishing a corrosion characteristic curve, wherein the corrosion characteristic curve represents a mapping relationship between the wavelength variation and the mass loss rate.

[0064] Specifically, the wavelength change can be determined based on the monitoring signal from the fiber Bragg grating corrosion sensor. This wavelength change is then substituted into a fitting function corresponding to a pre-built corrosion characteristic curve. This corrosion characteristic curve maps the wavelength change of the fiber Bragg grating corrosion sensor to the mass loss rate of the bridge cable. Using this corrosion characteristic curve, the mass loss rate of the bridge cable can be determined based on the wavelength change.

[0065] In this embodiment, optionally, establishing the corrosion characteristic curve includes:

[0066] Acquire multiple sets of test data of steel wire corrosion tests, the test data including test values ​​of wavelength variation of the fiber Bragg grating corrosion sensor and test values ​​of mass loss rate of the steel wire at different measurement times;

[0067] The corrosion characteristic curve is established by performing function fitting on all test data.

[0068] Specifically, to ensure the accuracy of the established corrosion characteristic curve, test data from multiple sets of steel wire corrosion tests can be obtained. These test data include wavelength change test values ​​monitored by the fiber Bragg grating corrosion sensor at different measurement times, as well as measured steel wire mass loss rate test values. By statistically analyzing the test data from different test groups at the same measurement time, the mean wavelength change test value and the mean mass loss rate test value corresponding to each measurement time can be determined. Finally, a function fitting is performed on the mean wavelength change test value and the mean mass loss rate test value corresponding to all measurement times to establish the corrosion characteristic curve.

[0069] In this embodiment, optionally, monitoring the mass loss rate of bridge cables using a fiber Bragg grating corrosion sensor includes:

[0070] The volume expansion coefficient in the mass loss rate theoretical calculation formula is obtained through the wavelength change in the corrosion characteristic curve, and the mass loss rate is verified through the mass loss rate theoretical calculation formula based on the volume expansion coefficient.

[0071] Specifically, to further ensure the accuracy of the mass loss rate, after establishing the corrosion characteristic curve, the corresponding mass loss rate theoretical algorithm can be selected based on the type of fiber Bragg grating corrosion sensor used in the corrosion test. The volume expansion coefficient corresponding to the wavelength change of the fiber Bragg grating corrosion sensor is determined by fitting the relationship between the wavelength change and the volume expansion coefficient of the corroded steel wire. Based on the determined volume expansion coefficient, the theoretical value of the mass loss rate of the bridge cable is obtained through the mass loss rate theoretical calculation formula, and a theoretical relationship between the sensor's wavelength change and the corresponding steel wire mass loss rate is established. The mass loss rate determined by the corrosion characteristic curve is verified using the theoretical mass loss rate value.

[0072] It should be understood that the corrosion sensors currently used in bridge cables include wound fiber Bragg grating corrosion sensors and stretched fiber Bragg grating corrosion sensors. When the fiber Bragg grating corrosion sensor is wound, the following formula is used to calculate the theoretical value of the mass loss rate of the bridge cable:

[0073]

[0074] ρ m is the mass loss rate of the steel wire, △λ B is the experimental value of the fiber Bragg grating wavelength variation, D is the initial diameter of the bridge cable steel wire, ξ is the volume expansion coefficient of steel wire corrosion, k T is the strain sensitivity coefficient of the fiber Bragg grating corrosion sensor, and β is the fiber winding pitch of the fiber Bragg grating corrosion sensor.

[0075] For the volume expansion coefficient of the wound fiber Bragg grating corrosion sensor, the curve obtained by fitting the experimental data is as follows: Figure 7 The specific calculation formula is:

[0076]

[0077] When the fiber Bragg grating corrosion sensor is of the tensile type, the following calculation formula is used to determine the theoretical value of the mass loss rate of the bridge cable:

[0078]

[0079] L is the free length of the fiber Bragg grating in the stretched fiber Bragg grating corrosion sensor.

[0080] For the volume expansion coefficient of the stretched fiber Bragg grating corrosion sensor, the curve obtained by fitting the experimental data is as follows: Figure 8 The specific calculation formula is:

[0081]

[0082] By establishing the corrosion characteristic curve, we can not only determine the mass loss rate of bridge cables, but also classify the corrosion levels and determine the corresponding boundaries of each corrosion level. Figure 6 As shown,

[0083] In this embodiment, optionally, evaluating the fatigue life of the bridge cables includes:

[0084] According to the parameter values ​​corresponding to the corresponding geometric characteristic parameters, the crack shape correction coefficient and critical crack size of the steel wire are calculated. The specific calculation formula is as follows:

[0085]

[0086] The fatigue life of bridge cables is calculated using the Paris formula, combining the crack shape correction coefficient, critical crack size, average stress, and maximum corrosion depth of the steel wire. The specific calculation formula is as follows:

[0087]

[0088] Among them, a is the maximum corrosion depth, A ave is the average cross-sectional area of ​​the steel wire after corrosion, a c is the critical crack size, a0 is the initial crack size, △σ is the average stress, Y is the crack shape correction coefficient, and m and C are the set Paris formula parameters.

[0089] Specifically, after obtaining the current mass loss rate of the bridge cable, the aforementioned relationship curve can be used to calculate the current maximum corrosion depth and average cross-sectional area of ​​the bridge cable. Furthermore, the aforementioned formula can be used to calculate the crack shape correction factor and critical crack size of the bridge cable wire. Finally, combining the maximum corrosion depth, crack shape correction factor, critical crack size, and the set Paris formula parameters, the current fatigue life of the bridge cable can be calculated.

[0090] In this embodiment, the Paris formula parameters can be set according to the stress ratio R of the bridge cable steel wire. The specific calculation formula is as follows:

[0091] m=2.39871+0.28143R-0.98571R 2 ;

[0092] C = 1.317 × 10 -11 -2.987×10 -11 ·R+8.915×10 -11 ·R 2 .

[0093] like Figure 2 A flow chart of a bridge cable corrosion assessment method is shown, which includes:

[0094] Step S1, establishing relationship curves between mechanical characteristic parameters of bridge cables and mass loss rate;

[0095] Step S2: monitoring the mass loss rate of the bridge cables by installing fiber grating corrosion sensors in the bridge cables;

[0096] Step S3: Based on the mass loss rate of the bridge cable, determine the parameter values ​​corresponding to the mechanical characteristic parameters through the corresponding relationship curves;

[0097] Step S4: Evaluate the ultimate bearing capacity of the bridge cable according to the parameter values ​​of all mechanical characteristic parameters.

[0098] Specifically, first, relationship curves between the various mechanical characteristic parameters associated with the ultimate bearing capacity of the bridge cable and the mass loss rate can be established. Then, the mass loss rate of the bridge cable can be monitored in real time using a fiber optic Bragg grating corrosion sensor installed on the bridge cable. Afterwards, the mass loss rate can be substituted into the relationship curve corresponding to the various mechanical characteristic parameters to determine the parameter values ​​corresponding to the various mechanical characteristic parameters of the current bridge cable. Finally, by combining the parameter values ​​of all mechanical characteristic parameters associated with the ultimate bearing capacity of the bridge cable, the ultimate bearing capacity of the bridge cable can be evaluated. In this way, the ultimate bearing capacity of the bridge cable can be evaluated without opening the cable for inspection or replacing the cable. This is low-cost, simple, and can evaluate the corrosion status of the cable in real time.

[0099] In this embodiment, optionally, the mechanical characteristic parameter includes ultimate strength.

[0100] The relationship curve between the ultimate strength and the mass loss rate was established using the linear function fitting method. The fitting function corresponding to the relationship curve between the mechanical property parameters and the mass loss rate is:

[0101] σ b '=(-5.530ρ m 2 -0.723ρ m +1.017)σ b ;

[0102] Among them, σ bis the ultimate strength of the bridge cable steel wire before corrosion, ρ m is the mass loss rate, σ b ' is the ultimate strength of the steel wire after corrosion.

[0103] In this embodiment, optionally, the specific calculation formula for the ultimate bearing capacity of the bridge cable is as follows:

[0104]

[0105] Where n is the number of steel wires in the bridge cable, d is the diameter of the uncorroded steel wire, and σ bi is the ultimate strength of the i-th steel wire after corrosion.

[0106] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A bridge cable corrosion assessment method, characterized in that: include: The relationship curves between the geometric characteristic parameters of bridge cables and the mass loss rate are established respectively; The mass loss rate of bridge cables is monitored by installing fiber grating corrosion sensors in the bridge cables; Based on the mass loss rate of the bridge cable, the parameter values ​​corresponding to the various geometric characteristic parameters are determined through corresponding relationship curves; The fatigue life of the bridge cables is evaluated according to the parameter values ​​of all geometric characteristic parameters.

2. The bridge cable corrosion assessment method according to claim 1, characterized in that: The geometric characteristic parameters include average cross-sectional area and maximum corrosion depth.

3. The bridge cable corrosion assessment method according to claim 1, characterized in that: The relationship curve is established by using a linear function fitting method.

4. The bridge cable corrosion assessment method according to claim 1, characterized in that: Monitoring the mass loss rate of bridge cables includes: Obtaining a wavelength change of the fiber grating corrosion sensor; According to the wavelength variation, the mass loss rate of the bridge cable is determined by establishing a corrosion characteristic curve, and the corrosion characteristic curve represents a mapping relationship between the wavelength variation and the mass loss rate.

5. The bridge cable corrosion assessment method according to claim 4, characterized in that: Establishing the corrosion characteristic curve includes: Acquire multiple groups of test data of steel wire corrosion test, the test data including test values ​​of wavelength variation of the fiber grating corrosion sensor at different measuring moments and test values ​​of mass loss rate of the steel wire; The corrosion characteristic curve is established by performing function fitting on all test data.

6. The bridge cable corrosion assessment method according to claim 1, characterized in that: Monitoring the mass loss rate of bridge cables by fiber Bragg grating corrosion sensors includes: The volume expansion coefficient in the mass loss rate theoretical calculation formula is obtained through the wavelength change in the corrosion characteristic curve, and the mass loss rate is verified through the mass loss rate theoretical calculation formula based on the volume expansion coefficient.

7. The bridge cable corrosion assessment method according to claim 1, characterized in that: Evaluate the fatigue life of the bridge cables, including: According to the parameter values ​​corresponding to the corresponding geometric characteristic parameters, the crack shape correction coefficient and critical crack size of the steel wire are calculated. The specific calculation formula is as follows: Combining the crack shape correction coefficient, critical crack size, average stress and maximum corrosion depth of the steel wire, the fatigue life of the bridge cable is calculated using the Paris formula. The specific calculation formula is as follows: Among them, a is the maximum corrosion depth, A ave is the average cross-sectional area of ​​the steel wire after corrosion, a c is the critical crack size, a0 is the initial crack size, △σ is the average stress, Y is the crack shape correction coefficient, and m and C are the set Paris formula parameters.

8. A bridge cable corrosion assessment method, characterized in that: include: The relationship curves between the mechanical characteristic parameters of bridge cables and the mass loss rate are established respectively; The mass loss rate of bridge cables is monitored by installing fiber grating corrosion sensors in the bridge cables; Based on the mass loss rate of the bridge cable, the parameter values ​​corresponding to the mechanical characteristic parameters are determined through the corresponding relationship curves; The ultimate bearing capacity of the bridge cables is evaluated according to the parameter values ​​of all mechanical characteristic parameters.

9. The bridge cable corrosion assessment method according to claim 8, characterized in that: The function corresponding to the relationship curve between the established mechanical property parameters and mass loss rate is: s b '=(-5.530ρ m 2 -0.723r m +1.017)s b ; Among them, σ b is the ultimate strength of the bridge cable steel wire before corrosion, ρ m is the mass loss rate, σ b ' is the ultimate strength of the steel wire after corrosion.

10. The bridge cable corrosion assessment method according to claim 8, characterized in that: The specific calculation formula of the ultimate bearing capacity of the bridge cable is as follows: Where n is the number of steel wires in the bridge cable, d is the diameter of the uncorroded steel wire, and σ b ' i is the ultimate strength of the i-th steel wire after corrosion.

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