Method and device for detecting corrosion and evaluating bearing capacity of steel wire based on spin correlation amplification
Patent Information
- Application Number
- CN202610889869.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-06-18
- Publication Date
- 2026-09-15
Smart Images
Figure CN122754291A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of bridge engineering technology and relates to the detection of steel wire corrosion and load-bearing capacity assessment of bridge cables. Specifically, it relates to a method and device for steel wire corrosion detection and load-bearing capacity assessment based on spin correlation amplification. Background Technology
[0002] With the rapid advancement of urbanization in my country, bridges, as key nodes and vital components of urban transportation networks, have seen their safety and durability increasingly become a focus of public attention. Bridge cables, as indispensable load-bearing and force-transmitting components in bridge structures, are typically composed of multiple strands of ferromagnetic metal materials bundled together, playing a decisive role in the overall stability and safety of bridges. Common cable structures fall into two main categories: parallel (or semi-parallel) galvanized high-strength steel wire bundle cables: The interior consists of steel wire bundles, with the entire exterior protected by a hot-extruded high-density polyethylene (HDPE) sheath. Polyethylene (PE) protected steel strand cables: The interior consists of a single steel strand with a PE sheath, with the entire exterior further encased in an extruded high-density polyethylene sheath. Generally, cables made with steel strands have approximately five layers of protection (each steel strand has an independent PE sheath), while parallel steel wire cables typically have only three to four layers of protection, and the galvanized layer on the steel wire surface is more prone to failure. Therefore, parallel wire cables have relatively weak corrosion resistance, and under the combined effects of long-term loads and corrosive environments, they are at relatively high risk of brittle fracture. For bridge structures, defects in the cable system will significantly reduce their operational safety and durability. Typical defects in cable systems include sheath cracking, wire corrosion, anchoring system corrosion, and sealing material failure.
[0003] The development of bridge cable corrosion detection technology represents a continuous effort to address the challenges of ferromagnetic steel wire material properties and the problem of hidden corrosion. Traditional methods rely on manual inspection and simple instruments, such as visually inspecting HDPE sheath aging and damage by tapping, and using hydraulic jacks to calibrate cable force when abnormal cable force is detected, indirectly inferring overall performance. However, these methods struggle to detect early corrosion of the steel wires within the sheath. With advancements in non-destructive testing (NDT) technology, methods targeting the ferromagnetic properties of cables have been applied. For example, magnetic flux density measurement calculates the effective cross-sectional area loss by measuring changes in the cable's magnetic flux to assess the degree of corrosion, while metal magnetic memory detection technology captures inherent leakage magnetic field signals to locate microscopic stress concentrations and corrosion initiation areas, enabling early qualitative identification of damage. However, existing magnetic methods face challenges in terms of signal-to-noise ratio and quantitative assessment. Accurately retrieving the remaining load-bearing capacity of the steel wire from magnetic signals remains a core research frontier.
[0004] In the field of metal fatigue detection, to overcome the limitations of traditional methods in early damage identification and accurate prediction, a new technological approach based on quantum mechanics principles—quantum spin correlation amplification technology—has made significant progress in recent years. The core innovation of this technology was proposed by Zhang et al. (Zhang B, Zhang L, Wu X, et al. High-accuracy fatiguelife prediction and early fracture warning for ferromagnetic metals via spincorrelation amplification[J]. Nature Communications, 2026.), and its theory is based on the discovery of a quantum symbiotic relationship between interatomic bonding forces and magnetic interactions in ferromagnetic materials. The study indicates that the weakening of atomic bonds caused by cyclic loading induces microscopic changes in interatomic spacing, which can simultaneously perturb the local magnetic interactions and electronic spin states of the material. Zhang et al. established quantum spin correlations in the material by introducing external magnetic field excitation, enabling extremely weak spin state changes caused by early damage such as dislocations to be chain-like propagated and amplified along the magnetic field direction through quantum exchange interactions. The amplification factor is directly related to the number of atomic layers involved in the correlation. This mechanism successfully converts sub-nanometer fatigue damage signals into macroscopically detectable magnetic flux change signals.
[0005] Therefore, given that existing magnetic detection methods generally suffer from weak signals, susceptibility to environmental interference, and difficulties in quantitative assessment, making it difficult to correlate corrosion detection with remaining load-bearing capacity assessment, this paper proposes a method for steel wire corrosion detection and load-bearing capacity assessment based on spin-correlation amplification technology. This method is of great significance for safety early warning, operation and maintenance decision-making, and life management of bridge cables. Summary of the Invention
[0006] In view of this, the purpose of the present invention is to provide a method and apparatus for detecting steel wire corrosion and evaluating its load-bearing capacity based on spin correlation amplification, which solves the problems of weak signal, susceptibility to environmental interference, difficulty in quantitative evaluation, and difficulty in achieving correlation between corrosion detection and remaining load-bearing capacity evaluation in the existing technology.
[0007] To achieve the above objectives, the present invention provides a method for detecting steel wire corrosion and assessing its load-bearing capacity based on spin-correlated amplification, the method comprising: The magnetic induction intensity data of the entire cable under test can be collected by combining local magnetization and segmented scanning, or by using a moving scanning method. Determine whether there are rusted areas on the cable wires based on the collected magnetic induction intensity data; If a rusted area exists, calculate the rate of change of magnetic intensity difference upstream and downstream of the rusted area, and input the rate of change of magnetic intensity difference into the pre-established residual bearing capacity assessment model to assess the residual bearing capacity of the rusted area of the steel wire; where upstream is the boundary point of the rusted area close to the applied magnetic field, and downstream is the boundary point of the rusted area far from the applied magnetic field. The remaining load-bearing capacity of the entire cable is finally determined based on the remaining load-bearing capacity of each corroded area.
[0008] Furthermore, the magnetic induction intensity data of the entire cable under test is collected by combining local magnetization and segmented scanning. This includes: applying an external magnetic field to the cable under test in sections to fully magnetize the steel wires in each section; and setting multiple measuring points along the cable axis on the cable surface away from the external magnetic field in each section, and measuring the magnetic induction intensity at each measuring point using a magnetic field sensor.
[0009] The method of collecting magnetic induction intensity data of the entire cable under test by moving scanning includes: collecting the magnetic induction intensity of the steel wire by moving a collection device along the cable axis. The collection device includes at least a permanent magnet, a magnetic field sensor and a signal processing unit, wherein the permanent magnet and the magnetic field sensor are spaced at a certain distance, and the signal processing unit is connected to the magnetic field sensor to receive the collected magnetic induction intensity data.
[0010] Furthermore, the method also includes preprocessing the collected raw magnetic induction intensity data, including: first removing extreme outliers, then filtering random noise using the sliding window averaging method to complete data screening and preliminary noise reduction; subsequently, performing unified standardization processing on the data from each measuring point, and then extracting the signal change trend.
[0011] Furthermore, determining whether there are rusted areas in the cable wires based on the collected magnetic induction intensity data includes plotting the magnetic induction intensity distribution curve of the entire cable based on the collected magnetic induction intensity data, looking for abnormal points in the curve where the magnetic induction intensity suddenly increases or decreases, and identifying the area between adjacent points of sudden increase and decrease in magnetic induction intensity as rusted areas.
[0012] Furthermore, the rate of change of magnetic intensity difference upstream and downstream of the rusted area is calculated using the following formula:
[0013] In the formula, The rate of change of magnetic intensity difference This represents the magnetic intensity difference between the upstream and downstream sides of the corroded area. This represents the initial magnetic induction intensity difference before the steel wire corrodes.
[0014] Furthermore, the residual bearing capacity assessment model is a first or second-order function of the residual bearing capacity with respect to the rate of change of magnetic intensity difference.
[0015] Furthermore, for a single cable composed of multiple steel wires, the remaining load-bearing capacity is assessed by introducing a correction factor for the multi-wire system. The actual remaining bearing capacity of the cable cross-section in a certain corroded area is corrected to... Take all rusted areas The minimum value is taken as the remaining load-bearing capacity of the entire cable.
[0016] Another aspect of the present invention provides a device for detecting steel wire corrosion and assessing its load-bearing capacity, comprising: A strong magnetic field source is used to apply a stable external magnetic field to cables to magnetize the steel wires in the cables; A magnetic field sensor is used to measure magnetic induction signals at measuring points set on the surface of a cable. The data acquisition unit is used to acquire the measurement signals from the magnetic field sensor. The processing unit is used to preprocess the data transmitted by the data acquisition unit and output the relevant measuring points of the steel wire corrosion area, as well as the remaining bearing capacity assessment value.
[0017] Furthermore, in the processing unit, the output of the measuring points related to the steel wire corrosion area includes: drawing the magnetic induction intensity distribution curve of the entire cable based on the magnetic induction intensity data of each measuring point measured by the magnetic field sensor; finding abnormal points in the curve where the magnetic induction intensity suddenly increases or decreases; and identifying the area between adjacent points of sudden increase and sudden decrease in magnetic induction intensity as the corrosion area.
[0018] Furthermore, in the processing unit, outputting the remaining bearing capacity assessment value includes: calculating the rate of change of magnetic intensity difference based on the magnetic induction intensity of two abnormal points related to the steel wire corrosion area; substituting the rate of change of magnetic intensity difference into a pre-established remaining bearing capacity assessment model to calculate the remaining bearing capacity assessment value; wherein, the remaining bearing capacity assessment model is a linear or quadratic function of the remaining bearing capacity with respect to the rate of change of magnetic intensity difference; subsequently, for the entire cable composed of multiple steel wires, the remaining bearing capacity of each corrosion area is corrected by a multi-steel wire system correction coefficient, and the minimum corrected remaining bearing capacity among all corrosion areas is taken as the remaining bearing capacity of the entire cable.
[0019] The beneficial effects of this invention are as follows: (1) This invention actively excites the orderly arrangement of spin correlation inside the steel wire by applying an external stable magnetic field. By utilizing the cumulative amplification effect of spin exchange coupling, the weak magnetic interaction changes caused by local corrosion are transformed into macroscopically measurable magnetic signals. Compared with the passive magnetic memory method that relies on the geomagnetic field, the signal strength is greatly improved, which can suppress the interference of environmental stray magnetic fields and improve the detection stability.
[0020] (2) Based on the sensitivity of spin-related chains to changes in interatomic spacing, this invention can detect significant shifts in the rate of change of magnetic intensity difference in the early stage of corrosion when the macroscopic cross-sectional loss is not yet significant, thus achieving early warning of the rust initiation stage, which is superior to the shortcomings of traditional magnetic detection methods in identifying early micro-corrosion pits.
[0021] (3) By establishing the transformation relationship between the rate of change of magnetic intensity difference and the rate of mass loss, and then constructing a functional model between the magnetic detection parameters and the remaining bearing capacity, the present invention can directly map the magnetic detection parameters into the structural bearing capacity index, thus solving the problem that existing methods cannot invert mechanical performance degradation from magnetic signals.
[0022] (4) This invention only requires a strong magnetic field source and a Hall sensor, without the need for large excitation equipment or coupling agent, and without the need to peel off the steel wire protective layer. It has low detection cost and is easy to operate, and is suitable for rapid non-destructive testing in complex on-site environments such as bridge cables.
[0023] Other advantages, objectives, and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination, or may be learned from practice of the invention. The objectives and other advantages of the invention can be realized and obtained through the following description. Attached Figure Description
[0024] To make the objectives, technical solutions, and advantages of the present invention clearer, the preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, wherein: Figure 1 A schematic diagram of a method for detecting steel wire corrosion and assessing load-bearing capacity based on self-selected correlation amplification provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the steel wire corrosion detection and load-bearing capacity assessment device provided in an embodiment of the present invention; Figure 3 The graph shows the change in magnetic field strength as a function of the degree of corrosion at the upstream and downstream ends of the rusted section of the steel wire. Figure 4 This is a schematic diagram showing the variation trend of magnetic field strength at the upstream and downstream of the rusted section of the steel wire during a single static test. Figure 5 This is a schematic diagram of the arrangement of magnets and measuring points in the experiment. Detailed Implementation
[0025] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Unless otherwise specified, the following embodiments and features can be combined with each other.
[0026] The accompanying drawings are for illustrative purposes only and are schematic diagrams, not actual pictures. They should not be construed as limiting the invention. To better illustrate the embodiments of the invention, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product dimensions. It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.
[0027] In the accompanying drawings of the embodiments of the present invention, the same or similar reference numerals correspond to the same or similar components. In the description of the present invention, it should be understood that if terms such as "upper," "lower," "left," "right," "front," and "rear" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, the terms used to describe positional relationships in the drawings are only for illustrative purposes and should not be construed as limiting the present invention. For those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.
[0028] Based on the electron spin exchange coupling mechanism in ferromagnetic materials, the macroscopic magnetism of ferromagnetic materials originates from the interaction between electron spins. Among them, spin exchange is the key factor determining the magnetic behavior of the material. Under the action of an external magnetic field, the electron spins inside the ferromagnetic steel wire form a spatially continuous orientation structure along the magnetization direction under the constraint of exchange interaction, that is, a stable spin-correlated structure is formed, thus exhibiting obvious magnetic order characteristics. However, when the material is subjected to external environmental effects (such as corrosion damage), its crystal structure will undergo local distortion, which will lead to changes in interatomic spacing and weakening of spin exchange. The spin correlation characteristics will change accordingly, causing local magnetization information transmission to be blocked and magnetic field redistribution. This is manifested as a characteristic magnetic anomaly where the magnetic induction intensity upstream of the rusted section tends to increase, while the magnetic induction intensity downstream of the rusted section tends to decrease. Therefore, by measuring the rate of change of the difference in magnetic intensity upstream and downstream of the rusted region, the degree of corrosion and the remaining load-bearing capacity of the steel wire can be inferred.
[0029] Corrosion of steel wire directly weakens the intensity of spin exchange interactions within the material, causing the originally stable spin-correlation structure to gradually degrade. The corroded region can be considered a "weak connection" or "blocking node" in the spin-correlation transmission path, resulting in reduced transmission efficiency of magnetization information in that region. The direct consequence is increased spatial non-uniformity of magnetization, manifested as a significant difference in magnetic signals upstream and downstream of the corroded region.
[0030] From a macroscopic perspective, the magnetization of ferromagnetic materials This can be expressed as the vector sum of magnetic moments per unit volume:
[0031] in, For the first The magnetic moment of an atom, For ferromagnetic materials per unit volume, This refers to the quality loss rate caused by steel wire corrosion. To account for the "ideal" magnetization intensity after the material's own magnetic properties change due to corrosion, This represents the initial volume of the ferromagnetic material before corrosion.
[0032] If we assume Considering the effect of the change in the exchange integral on the magnetization, it can be expressed as:
[0033] in, To reflect the coefficient of spin correlation degradation, The magnetization intensity is the value under the condition of no corrosion. A constant related to the magnetic structure and magnetization conditions of the material ( ).
[0034] magnetic induction intensity The following relationship exists between the magnetization intensity and the magnetization intensity:
[0035] Under experimental conditions where the applied magnetic field remains constant, the change in magnetic flux density primarily originates from the change in magnetization. Therefore, the change in magnetic flux density caused by corrosion can be expressed as:
[0036] Combining the above equations, we get:
[0037] This formula shows that the greater the degree of corrosion of the steel wire, the more obvious the spin correlation degradation, and the more significant the change in macroscopic magnetic induction intensity. Combined with the characteristic of disrupted spatial transmission paths, the magnetic induction intensity upstream and downstream of the corrosion region will exhibit significant differences. In actual detection, the magnetic signal measured by the sensor is not the magnetization intensity within the material itself, but rather the result of the disturbance of the spatial magnetic field distribution caused by the corrosion region. In the axial direction of the steel wire, this magnetic field gradient typically manifests as an enhanced magnetic field upstream of the corrosion region, a weakened magnetic field at the center of the corrosion region, and a restored magnetic field downstream.
[0038] This results in a significant difference in magnetic intensity between the upstream and downstream areas.
[0039] in, The magnetic induction intensity upstream of the rusted area, The magnetic induction intensity is downstream of the rust zone.
[0040] This difference reflects the degree of attenuation of magnetization information along the wire axis before and after passing through the rusted region. From the perspective of spin-correlated amplification theory, the rusted region can be regarded as a "weakened segment" in the spin-correlated chain, where magnetic interaction is hindered, thus creating a measurable difference in magnetic signals upstream and downstream. To eliminate the influence of differences in the initial magnetization state of different specimens and fluctuations in the environmental magnetic field, the rate of change of magnetic intensity difference is introduced as a normalized magnetic characteristic parameter:
[0041] in, This represents the initial difference in magnetic induction intensity before corrosion.
[0042] For steel wire subjected to tension and corrosion, corrosion damage is primarily manifested on a macroscopic scale as a reduction in the effective load-bearing cross-section. Let the original cross-sectional area of the steel wire be... The effective load-bearing cross-sectional area after corrosion is The cross-sectional area loss rate is defined as:
[0043] Then we have:
[0044] Under a constant tensile force P, the local true stress in the corroded area is:
[0045] It is evident that local stress continuously increases with the intensification of corrosion and the reduction of the effective cross-section. Based on the preceding analysis, corrosion not only leads to the loss of surface and subsurface atoms, increasing the average interatomic spacing and weakening the exchange integral, but also causes stress redistribution through the reduction of cross-sectional area, further altering the lattice spacing and spin exchange coupling state. Therefore, the effective cross-sectional area loss rate can serve as a bridging variable connecting corrosion damage, spin-related degradation, and the decrease in structural load-bearing capacity.
[0046] Under conditions of small damage, the interatomic spacing perturbation in the corrosion-stressed state can be approximated as a function of the cross-sectional area loss rate, and a weakly nonlinear response relationship of the exchange integral to the cross-sectional area loss rate can be further obtained. Since the transmission capability of the spin correlation chain depends on the continuity and integrity of the interatomic exchange integral, as the cross-sectional area loss rate increases, the corrosion zone gradually becomes a "weakened segment" in the spin correlation transmission path. The transmission efficiency of magnetization information across this region decreases, ultimately leading to an increase in the difference in magnetic induction intensity between the upstream and downstream of the corrosion zone. Therefore, the rate of change of magnetic intensity difference and the cross-sectional area loss rate can be approximated as follows:
[0047] in, This represents the first-order influence of the cross-sectional area loss rate on the rate of change of magnetic intensity difference. This represents the degree of second-order nonlinear influence of the cross-sectional area loss rate on the rate of change of magnetic intensity difference. This represents the cross-sectional area loss rate.
[0048] On the other hand, the residual ultimate bearing capacity of corroded steel wire is mainly determined by the material strength and the effective bearing section. Ignoring the effects of secondary bending and local buckling, it can be written as:
[0049] in, The remaining load-bearing capacity of the steel wire is the ultimate load that the steel wire can still withstand after corrosion. This refers to the tensile strength of the steel wire material, which is the strength value of the material when it reaches its ultimate failure limit. This represents the effective cross-sectional area after corrosion.
[0050] It can also be written as:
[0051] in, This represents the ultimate load-bearing capacity of the steel wire in its uncorroded state. This represents the ultimate bearing capacity of the steel wire in its uncorroded state. If we further consider the additional effects of localized stress concentration, non-uniform corrosion, and defect propagation on the bearing capacity, then... Revised to:
[0052] in, This is a correction factor for the degradation of remaining bearing capacity. This is the secondary correction factor for the degradation of remaining bearing capacity.
[0053] The relationship between the rate of change of magnetic intensity difference and the cross-sectional area loss rate can be used to... The approximate inverse solution is The function is substituted into the expression for residual bearing capacity, thereby eliminating intermediate variables. The final relationship between the remaining bearing capacity and the rate of change of the magnetic intensity difference is as follows:
[0054] in, The constant coefficient reflects the theoretical remaining bearing capacity level when the rate of change of magnetic intensity is zero. The coefficient for the first term reflects the degree of influence of the rate of change of magnetic intensity difference on the first-order bearing capacity; The coefficient of the quadratic term reflects the degree of second-order nonlinear influence of the rate of change of magnetic intensity difference on the remaining bearing capacity.
[0055] Example 1 Based on the above, this embodiment provides a method for detecting steel wire corrosion and assessing its load-bearing capacity based on self-selected correlation amplification, such as... Figure 1 As shown, it includes: 1. Apply an external magnetic field to magnetize the steel wire to be tested.
[0056] In actual testing, there is no need for overall magnetization; "local magnetization + segmented scanning" can be used to achieve comprehensive testing of large cables.
[0057] Specifically, the cable is divided into several testing sections along its axis. For each section, a stable magnetic field is applied at one (or both) end using a permanent magnet to fully magnetize the steel wires within that section. Then, within that section, a Hall effect sensor collects signals at a location away from the permanent magnet. After testing, the permanent magnet is moved to the next section, and the process is repeated.
[0058] For very thick cables (such as main cables, which consist of thousands of steel wires), multiple permanent magnets can be arranged circumferentially on the cable surface to form a ring magnetic field, causing most of the internal steel wires to be radially or axially magnetized. Alternatively, two magnets (N-S) can be placed at a certain distance axially to form a locally closed magnetic circuit.
[0059] If a stronger magnetic field or an adjustable magnetic field strength is required, a DC electromagnet can be used. The magnetization intensity can be changed by adjusting the current, making it suitable for detection scenarios with different degrees of corrosion.
[0060] 2. Within each testing section, measuring points are set along the cable axis on the cable surface away from the external magnetic field, and a Hall sensor is used to measure the magnetic induction intensity at each measuring point.
[0061] 3. Based on the magnetic induction intensity measured by multiple Hall sensors, determine whether there are rusted areas in the steel wire.
[0062] Specifically, when the steel wire is normal, its magnetic induction intensity exhibits a clear gradient decay pattern. As the distance from the applied magnetic field increases, the surface magnetic induction intensity continuously decreases, and the rate of decay gradually slows down with increasing distance. According to the spin correlation principle mentioned above, when there is a rusted area on the cable wire, there will be a significant difference in magnetic induction intensity upstream and downstream of the rusted area. On a time scale, as the degree of rust deepens, the magnetic induction intensity upstream of the rusted area shows a trend of first decreasing and then increasing, while the magnetic induction intensity downstream of the rusted area shows a trend of first increasing and then decreasing. Figure 3 As shown. However, in a single static test, there was a sudden increase in magnetic induction intensity upstream of the corroded area and a sharp drop in magnetic induction intensity downstream, as shown... Figure 4 As shown in the diagram. Upstream refers to the boundary point of the corroded area closest to the applied magnetic field, while downstream refers to the boundary point of the corroded area furthest from the applied magnetic field.
[0063] Based on this, a magnetic flux density distribution curve for the entire cable can be plotted according to the magnetic flux density at each measuring point. The region with the lowest value and the flattest fluctuation on the curve (or the median of the entire cable data) is determined as the "relatively healthy section" acceptable for the project. The magnetic flux density difference between the upstream and downstream of the relatively healthy section is used as the initial benchmark. Meanwhile, the upstream and downstream boundaries of the corroded section are located by searching for "sudden increase-sudden decrease" characteristic areas on the curve.
[0064] It should be noted that static testing in engineering does not require the sensor to be precisely positioned at the corrosion boundary beforehand. Instead, by analyzing and plotting the complete spatial distribution curve of the cable's magnetic field strength, the actual locations of points of sudden increases and decreases in magnetic induction intensity are identified afterward. Even if the measuring point does not fall exactly on the boundary of the corrosion section, as long as the measuring point density is sufficient or continuous scanning is used, the characteristic change trend can be captured. Therefore, the Hall sensor does not need to be precisely aligned with the upstream and downstream boundaries of the corrosion section to effectively measure the magnetic anomaly caused by corrosion.
[0065] When searching for characteristic areas, as long as the magnetic induction intensity can be clearly identified on the spatial distribution curve as first showing a sudden increase and then a sudden decrease, the cable section covered by all measuring points between the point of sudden increase and the point of sudden decrease in magnetic induction intensity can be identified as the corrosion area.
[0066] Furthermore, in static testing, the magnetic induction intensity of measuring points located in the core corrosion zone typically exhibits a lower value than the baseline value of the healthy section, situated in a trough area between the upstream surge point and the downstream drop point. As the corrosion deepens, this trough value further decreases, but no sudden increase or drop is observed on the spatial curve of a single test. Therefore, in practical engineering testing, measuring points located in the core corrosion zone are not used as the primary criterion; instead, the upstream and downstream boundary features of the corrosion zone are relied upon to locate the corrosion area.
[0067] Since the raw magnetic induction intensity data is affected by environmental electromagnetic interference and sensor noise, MATLAB software can be used for data preprocessing, including: first, removing extreme outliers, then filtering random noise using the sliding window averaging method to complete data screening and preliminary noise reduction; then, standardizing the data from each measurement point to ensure data comparability, and finally extracting the signal change trend.
[0068] 4. Calculate the rate of change of magnetic intensity difference between upstream and downstream of the rusted area.
[0069] Specifically, the magnetic intensity difference between the upstream and downstream sides of the corroded section is first calculated. The magnetic intensity difference between the upstream and downstream of the rusted area can be calculated using the following formula:
[0070] Then based on the magnetic intensity difference Calculate the rate of change of magnetic intensity difference:
[0071] 5. Evaluate the remaining load-bearing capacity of the steel wire based on the pre-established remaining load-bearing capacity evaluation model.
[0072] The pre-established model is represented as follows:
[0073] Parameters in the formula , , It can be obtained through high-order fitting.
[0074] The above formula calculates the remaining bearing capacity of a single anomaly detection section. For a whole cable composed of multiple steel wires, its remaining bearing capacity is evaluated using the following method: Introducing correction coefficients for multi-wire systems The actual remaining bearing capacity of the cable section in a certain abnormal section is corrected to... Finally, select from all abnormal segments. The minimum value is taken as the remaining load-bearing capacity of the entire cable.
[0075] Correction coefficient Determined based on cable structure: For parallel wire bundles (such as the main cable of a suspension bridge). Take 0.7 to 0.8; for steel strands (such as stay cables). Take a value of 0.5 to 0.6; when the structural type is unclear or leans towards safety, Take 0.6 for all values.
[0076] The basis for this value is that when multiple steel wires are arranged side by side, the air gaps between the wires and the galvanized layer increase the magnetic reluctance of the magnetic circuit. Furthermore, the leakage magnetic fields of each wire exhibit spatial superposition and mutual shielding effects, resulting in a lower macroscopic magnetic response amplitude for a multi-wire system compared to a single steel wire under the same degree of corrosion. Experiments show that the rate of change in magnetic intensity difference when seven steel wires are arranged side by side is approximately 60% to 80% of that of a single steel wire. Therefore, the aforementioned correction coefficient has a reasonable physical basis and experimental support for engineering applications.
[0077] The following experiments will verify the correlation and stability of the remaining bearing capacity assessment model.
[0078] like Figure 5 As shown, the measuring points for real-time monitoring of the magnetic induction intensity of the steel wire were arranged on the side away from the magnet, with a total of three measuring points: one located on the healthy section of the steel wire (measuring point 1), one upstream of the rusted section (measuring point 2), and one downstream of the rusted section (measuring point 3). Measuring point 1, located 5 cm from the edge of the rusted area on the healthy section, was used to obtain the original magnetic intensity baseline value of the steel wire before corrosion. Measuring point 2 was located upstream of the beginning of the rusted section, and measuring point 3 was located downstream of the end of the rusted section. These two points were used to monitor the influence range and trend of corrosion damage on the magnetic field of the steel wire before and after the rusted area. Non-contact magnetic sensors were used for data acquisition at each measuring point to ensure that mechanical interference was avoided during the measurement process and to guarantee data consistency.
[0079] Three linear Hall sensors were used to collect magnetic intensity data at the upstream, core, and downstream measurement points of the steel wire corrosion area, respectively. The acquisition frequency was set to 100 Hz, and the acquisition process was carried out throughout the entire corrosion experiment. The raw data was stored as an h5 file in the form of the number of acquisitions and the magnetic intensity value of each measurement point.
[0080] The raw magnetic field data is affected by environmental electromagnetic interference and sensor noise. MATLAB software is used for data preprocessing. First, extreme outliers are removed, and then random noise is filtered by the sliding window averaging method to complete data screening and preliminary noise reduction. Subsequently, the data from the three measuring points are standardized to ensure data comparability.
[0081] A quadratic function was used to fit the test data under each working condition, and the goodness of fit R² was used to characterize the correlation between the rate of change of magnetic intensity difference and the remaining bearing capacity during the test. 2The value is an indicator of the regression effect of the fitted function; the closer it is to 1, the better the regression effect, that is, the closer it is to the true situation. The fitting results are shown in Table 1.
[0082] Table 1
[0083] As can be seen from the data in Table 1, in the case where the corrosion width is 3 cm, there is a set of data with R... 2 The value reached 0.9991, indicating a good fit; R0 was found for a corrosion width of 5 cm. 2 The value also remained stable above 0.93, while the R value under the 1 cm condition was... 2 The values are generally lower than those for the 3 cm and 5 cm conditions, with a maximum of 0.84312. This indicates that quadratic function fitting can effectively capture the nonlinear variation of the magnetic signal for steel wire corrosion conditions.
[0084] Example 2 This embodiment is basically the same as Embodiment 1, the only difference being that the pre-established residual bearing capacity assessment model in this embodiment adopts a linear function form, as shown below:
[0085] Parameters in the formula , The data was obtained through high-order fitting.
[0086] Similarly, experiments were conducted to verify the correlation and stability of the remaining bearing capacity assessment model. The experimental conditions and methods were the same as in Example 1.
[0087] A linear function was used to fit the test data for each working condition, and the goodness of fit R² was used to characterize the correlation between the rate of change of magnetic intensity difference and the remaining bearing capacity during the test. The fitting results are shown in Table 2.
[0088] Table 2
[0089] As can be seen from the data in Table 2, the condition with a corrosion width of 3 cm exhibits the best regression effect in the linear function fitting, with an R² value of [missing value]. 2 The value can reach as high as 0.9991, which is significantly higher than that of the 1 cm and 5 cm conditions (R1 value for the 1 cm condition). 2 The highest value is 0.82312, and the highest R² value is 0.974 under the 5 cm working condition. It can be seen that linear function fitting can also achieve a high degree of accuracy in the linear correlation calculation between magnetic intensity difference and corrosion parameters.
[0090] Example 3 Compared to Example 1, this example uses a continuous moving scan method to collect the magnetic induction intensity of the cable and plots a complete spatial distribution curve of the magnetic induction intensity. Specifically, the continuous moving scan method involves using a data acquisition device that moves along the cable axis to collect the magnetic induction intensity of the steel wire. This data acquisition device includes at least a permanent magnet (or electromagnet), a Hall sensor, and a signal processing unit. The permanent magnet (or electromagnet) and the Hall sensor are spaced a certain distance apart to avoid the magnetic field source affecting the signal collected by the Hall sensor.
[0091] By analyzing the curve, abnormal points (i.e. points where the magnetic induction intensity suddenly increases or decreases) in the magnetic induction intensity curve are identified. The cable sections between the abnormal points are then identified as abnormal sections, specifically the cable sections between the points where the magnetic induction intensity suddenly increases and the points where the magnetic induction intensity suddenly decreases.
[0092] Hall effect sensors are installed at measurement points at both ends of the abnormal section to further monitor the changing trend of the magnetic induction signal, thereby improving measurement accuracy, confirming characteristic boundaries, and verifying whether the changing trends of magnetic induction intensity upstream and downstream of the abnormal section conform to corrosion characteristics (i.e., a sudden increase upstream and a sharp drop downstream), thus avoiding misjudgments caused by noise or placement deviations. Specifically, the further monitoring of the changing trend of the magnetic induction signal involves repeatedly measuring both ends of the abnormal section under a static detection framework, and taking the average value of multiple measurements as the magnetic induction intensity at that point.
[0093] Subsequently, following the method of Example 1, based on the magnetic induction signals measured at both ends of the abnormal section, the rate of change of magnetic intensity difference and the remaining bearing capacity of the abnormal section are calculated, and then corrected using a correction factor. The remaining bearing capacity is adjusted by taking the minimum adjusted remaining bearing capacity among all abnormal sections as the remaining bearing capacity of the entire cable. This includes calculating the magnetic intensity difference. and the rate of change of magnetic intensity difference At that time, the magnetic induction intensity data (or the average value of multiple measurements) measured at the upstream and downstream measuring points of the abnormal section in the current single detection were used.
[0094] Example 4 This embodiment provides a device for detecting steel wire corrosion and assessing its load-bearing capacity, such as... Figure 2 As shown, the device includes: A strong magnetic field source is used to apply a stable external magnetic field to cables to magnetize the steel wires within them. A strong magnetic field source can be implemented using a permanent magnet.
[0095] A magnetic field sensor is used to measure magnetic induction signals at measuring points set on the surface of a cable. A Hall effect sensor is preferred.
[0096] The data acquisition unit is used to acquire the measurement signals from the magnetic field sensor and transmit them to the processing unit. The data acquisition unit may employ an analog-to-digital converter.
[0097] The processing unit preprocesses the data transmitted by the data acquisition unit and outputs the relevant measuring points of the rusted section of the steel wire, as well as the remaining bearing capacity assessment value. The processing unit can be a host computer or a microcontroller.
[0098] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.
Claims
1. A method for detecting corrosion and evaluating load bearing capacity of a steel wire based on spin-dependent electron transport, characterized in that, The magnetic induction intensity data of the entire cable under test can be collected by combining local magnetization and segmented scanning, or by using a moving scanning method. Determine whether there are rusted areas on the cable wires based on the collected magnetic induction intensity data; If a rusted area exists, calculate the rate of change of magnetic intensity difference upstream and downstream of the rusted area, and input the rate of change of magnetic intensity difference into the pre-established residual bearing capacity assessment model to assess the residual bearing capacity of the rusted area of the steel wire; where upstream is the boundary point of the rusted area close to the applied magnetic field, and downstream is the boundary point of the rusted area far from the applied magnetic field. The remaining load-bearing capacity of the entire cable is finally determined based on the remaining load-bearing capacity of each corroded area.
2. The method of claim 1, wherein, The magnetic induction intensity data of the entire cable under test is collected by combining local magnetization and segmented scanning. This includes: applying an external magnetic field to the cable under test in sections to fully magnetize the steel wires in each section; and setting multiple measuring points along the cable axis on the cable surface away from the external magnetic field in each section, and measuring the magnetic induction intensity at each measuring point using a magnetic field sensor.
3. The method of claim 1, wherein, The method of collecting magnetic induction intensity data of the entire cable under test by moving scanning includes: collecting the magnetic induction intensity of the steel wire by moving a collection device along the cable axis. The collection device includes at least a permanent magnet, a magnetic field sensor and a signal processing unit, wherein the permanent magnet and the magnetic field sensor are spaced at a certain distance, and the signal processing unit is connected to the magnetic field sensor to receive the collected magnetic induction intensity data.
4. The method according to claim 1, characterized in that, Determining whether there are rusted areas in the cable wires based on the collected magnetic induction intensity data involves plotting the magnetic induction intensity distribution curve of the entire cable based on the collected magnetic induction intensity data, looking for abnormal points in the curve where the magnetic induction intensity suddenly increases or decreases, and identifying the area between adjacent points of sudden increase and decrease in magnetic induction intensity as rusted areas.
5. The method according to claim 1, characterized in that, The rate of change of magnetic intensity difference upstream and downstream of the rusted area is calculated using the following formula: In the formula, The rate of change of magnetic intensity difference This represents the magnetic intensity difference between the upstream and downstream sides of the corroded area. This represents the initial magnetic induction intensity difference before the steel wire corrodes.
6. The method according to claim 5, characterized in that, For a single cable composed of multiple steel wires, the remaining load-bearing capacity is assessed as follows: Introducing correction coefficients for multi-wire systems The actual remaining bearing capacity of the cable cross-section in a certain corroded area is corrected to... Take all rusted areas The minimum value is taken as the remaining load-bearing capacity of the entire cable.
7. The method according to claim 1, characterized in that, The residual bearing capacity assessment model is a quadratic or linear function of the residual bearing capacity with respect to the rate of change of magnetic intensity difference.
8. A device for detecting steel wire corrosion and assessing its load-bearing capacity, characterized in that, include: A strong magnetic field source is used to apply a stable external magnetic field to cables to magnetize the steel wires in the cables; A magnetic field sensor is used to measure magnetic induction signals at measuring points set on the surface of a cable. The data acquisition unit is used to acquire the measurement signals from the magnetic field sensor. The processing unit is used to preprocess the data transmitted by the data acquisition unit and output the relevant measuring points of the steel wire corrosion area, as well as the remaining bearing capacity assessment value.
9. The apparatus according to claim 8, characterized in that, The processing unit outputs the measurement points related to the steel wire corrosion area, including plotting the magnetic induction intensity distribution curve of the entire cable based on the magnetic induction intensity data of each measurement point measured by the magnetic field sensor, finding abnormal points in the curve where the magnetic induction intensity suddenly increases or decreases, and identifying the area between adjacent points of sudden increase and sudden decrease in magnetic induction intensity as the corrosion area.
10. The apparatus according to claim 9, characterized in that, In the processing unit, the output of the remaining bearing capacity assessment value includes: calculating the rate of change of magnetic intensity difference based on the magnetic induction intensity of two abnormal points related to the steel wire corrosion area; substituting the rate of change of magnetic intensity difference into the pre-established remaining bearing capacity assessment model to calculate the remaining bearing capacity assessment value; wherein, the remaining bearing capacity assessment model is a linear or quadratic function of the remaining bearing capacity with respect to the rate of change of magnetic intensity difference; Subsequently, for the entire cable composed of multiple steel wires, the remaining bearing capacity of each corroded area is corrected by the multi-steel wire system correction coefficient, and the minimum corrected remaining bearing capacity of all corroded areas is taken as the remaining bearing capacity of the entire cable.