Anchord cable corrosion state and stress level evaluation method based on double-source monitoring

Abstract

The application discloses a kind of anchor cable corrosion state and stress level evaluation method based on double-source monitoring, comprising: step S1: two kinds of sensors are simultaneously laid on key anchor cable to carry out double-source monitoring;Step S2: in the health state that anchor cable does not occur corrosion, the theoretical magnetic signal corresponding to different tension is collected, and the mapping function and "healthy state force-magnetic constitutive curve" are constructed by data fitting;Step S3. During operation, the tension value and magnetic flux signal under each time are measured;Step S4. The residual error of measured magnetic signal and theoretical magnetic signal is calculated;Step S5. Anchor cable corrosion state judgment is carried out, and the residual error is converted into effective metal cross-sectional area loss rate when corrosion occurs;Step S6: based on the tension value and effective metal cross-sectional area loss rate measured, the bearing capacity safety degree and material durability health degree are graded early warning.The application can accurately strip out corrosion signal, realize the synchronous monitoring of stress level and corrosion state, and have strong environmental anti-interference ability.

Description

Technical Field

[0001] This invention relates to the fields of structural health monitoring, non-destructive testing, and multi-sensor data fusion in geotechnical engineering, and in particular to a method for assessing the corrosion status and stress level of anchor cables based on dual-source monitoring. Background Technology

[0002] Prestressed anchor cables are the lifeline of slope and underground engineering projects. During long-term service, anchor cables face two core risks: prestress loss (relaxation / slippage) and steel strand corrosion (reduced cross-section / broken wires). Existing monitoring methods suffer from the following "blind spots" and "ambiguities": Anchor cable load cells (blind spots): Sensitive only to tension. If the anchor cable is severely corroded but has not yet broken, or if corrosion reduces the cross-section but the tension remains balanced, the load cell reading may not change significantly. This prevents managers from detecting the potential for "thinning anchor cables" until sudden breakage. Magnetic flux sensors (ambiguity / coupling problem): Based on the magneto-elastic effect, their output signal (permeability / induced voltage) is simultaneously affected by both "stress level" and "metal cross-sectional area (corrosion)." A decrease in the magnetic signal could be due to prestress loss or thinning of the steel strands due to corrosion. Existing technologies cannot distinguish between these two situations (i.e., "variable coupling"), which often leads to false alarms (treating corrosion as relaxation) or false negatives (relaxation masking corrosion). Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for assessing the corrosion status and stress level of anchor cables based on dual-source monitoring. By utilizing the data complementarity of dual-source sensors, a ternary mapping model of force, magnetism, and corrosion is established. By comparing the deviation between the theoretical pure stress magnetic signal and the measured magnetic signal, the corrosion signal is accurately extracted, thereby achieving synchronous monitoring of stress level and corrosion status.

[0004] The objective of this invention is achieved through the following technical solution: a method for assessing the corrosion status and stress level of anchor cables based on dual-source monitoring, comprising the following steps:

[0005] Step S1: Simultaneously deploy two types of sensors on the key anchor cables for dual-source monitoring;

[0006] Step S2: Under the healthy condition of the anchor cable without corrosion, perform a full-range tensioning and collect the theoretical magnetic signals corresponding to different tensions. Construct the "healthy state force-magnetic constitutive curve" and mapping function through data fitting.

[0007] Step S3. During long-term operation, the tensile force and magnetic flux signal are measured at various times.

[0008] Step S4. Calculate the residual between the measured magnetic signal and the theoretical magnetic signal;

[0009] Step S5. Determine the corrosion status of the anchor cable based on the residuals, and convert the residuals into the effective metal cross-sectional area loss rate when corrosion occurs;

[0010] Step S6: Based on the measured tensile force value and effective metal cross-sectional area loss rate, classify and issue early warnings for load-bearing capacity safety and material durability health.

[0011] The beneficial effects of the present invention are: (1) The present invention completely solves the industry problem of not being able to distinguish between "force change" and "deformation (corrosion)" in single magnetic flux monitoring.

[0012] (2) The present invention can simultaneously and accurately quantify the “effective prestress level” (characterizing mechanical bearing capacity) and “effective metal section loss rate” (characterizing material durability) of the anchor cable, thereby constructing a full-dimensional safety profile of the anchoring system that includes stress state and corrosion degree.

[0013] (3) The present invention can detect minute corrosion trends in the early stage before the cable breaks, which facilitates timely anti-corrosion maintenance. Attached Figure Description

[0014] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0015] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings, but the scope of protection of the present invention is not limited to the following description.

[0016] like Figure 1 As shown, a method for assessing the corrosion status and stress level of anchor cables based on dual-source monitoring includes the following steps:

[0017] Step S1: Simultaneously deploy two types of sensors on the key anchor cables for dual-source monitoring;

[0018] In step S1, the two types of sensors include:

[0019] Force source sensors, using vibrating wire or fiber optic grating anchor cable force gauges, are used to obtain accurate tension values;

[0020] The magnetic source sensor, employing either a through-hole or bypass magnetic flux sensor, is used to acquire a comprehensive magnetic flux signal.

[0021] Step S2: Under the healthy condition of the anchor cable without corrosion, perform a full-range tensioning and collect the theoretical magnetic signals corresponding to different tensions. Construct the "healthy state force-magnetic constitutive curve" and mapping function through data fitting.

[0022] Under healthy conditions where the anchor cable is free from corrosion, a full-range tensioning is performed, and force and magnetic source sensors are used to collect different tension forces F and corresponding magnetic flux signals. The magnetic flux signal at this time is the theoretical magnetic signal corresponding to that tension force under the condition of no corrosion, denoted as U. theory According to different tensile forces F and corresponding U theory Construct a "force-magnetic constitutive curve for a healthy state";

[0023] The corresponding force-magnetic mapping function is fitted, denoted as:

[0024] U theory = f(F);

[0025] Where f() is a calibration function that characterizes the mapping relationship between tensile force and theoretical magnetic signal, obtained by fitting measured data under healthy conditions, i.e., force-magnetic mapping function.

[0026] Step S3. During long-term operation, the tensile force and magnetic flux signal are measured at various times.

[0027] Step S3 includes:

[0028] During long-term operation, the tensile force is measured at various moments using a force source sensor, and the magnetic flux signal is measured using a magnetic source sensor. For any given moment t, the measured tensile force is denoted as F. t The measured magnetic flux signal is denoted as Umeasured(t).

[0029] Step S4. Calculate the residual between the measured magnetic signal and the theoretical magnetic signal;

[0030] Using the measured tensile force F t Substituting the force-magnetic mapping function f(), the theoretical magnetic signal U that should be exhibited under the current tensile force is calculated. theory_t :

[0031] U theory_t = f(F t ) ;

[0032] Calculate the residual between the measured magnetic signal and the theoretical magnetic signal:

[0033] ΔU = U measured(t) - U theory_t .

[0034] Step S5. Determine the corrosion status of the anchor cable based on the residuals, and convert the residuals into the effective metal cross-sectional area loss rate when corrosion occurs;

[0035] Step S5 includes:

[0036] Set the system error threshold to δ;

[0037] When |ΔU| ≤ δ, it indicates that the change in magnetic signal is entirely caused by the change in tension, the anchor cable is healthy, and only stress fluctuations occur;

[0038] When |ΔU| > δ, this deviation is the "corrosion component". Using the "magnetic signal-cross-sectional area" relationship model, ΔU is converted into the effective metal cross-sectional area loss rate:

[0039] η = g(ΔU);

[0040] Wherein, g() is the cross-sectional area loss rate conversion function, which is pre-constructed by mathematical fitting of different corrosion rates and their corresponding magnetic signal residuals through calibration tests on anchor cable samples with known different corrosion rates.

[0041] Step S6: Based on the measured tensile force value and effective metal cross-sectional area loss rate, classify and issue early warnings for load-bearing capacity safety and material durability health.

[0042] Step S6 includes: pre-setting multiple warning thresholds for load-bearing capacity safety and material durability health; based on F t Assess load-bearing capacity safety based on To assess the durability and health of materials, F t and Each indicator is compared with its corresponding warning threshold, and the warning level is determined based on the range in which the comparison occurs. When any indicator exceeds the safety threshold, the corresponding warning level is triggered.

[0043] In an embodiment of this application, step S1 further includes deploying temperature sensors on the key anchor cable to obtain the ambient temperature T; based on this, in step S4, the residual calculation includes a temperature compensation mechanism, U theory_t The calculation formula is revised as follows:

[0044] U theory_t = f(F t ) ×[1+α(T t - T0)] ;

[0045] Where α is the pre-calibrated temperature compensation coefficient, T t T0 is the measured temperature at the current moment, and T0 is the calibration reference temperature.

[0046] In the embodiments of this application, in step S3, the magnetic flux signal is smoothed by a sliding window moving average algorithm or Kalman filtering during acquisition; and a rate of change threshold is set, and signals whose rate of change exceeds the threshold at adjacent times are discarded as abnormal electromagnetic interference noise.

[0047] In embodiments of this application, the method further includes a dynamic baseline calibration step, the specific process of which is as follows: During the service period of the anchor cable, the readings of the force source sensor within a continuously set time window are extracted; the fluctuation rate of the force source sensor readings within the time window is calculated, and if the fluctuation rate is lower than a set stability threshold, it is determined that the current period is within the baseline calibration window; the average residual between the measured magnetic signal and the theoretical magnetic signal within the window is extracted, and the average residual is used as a drift compensation amount to perform superposition fine-tuning correction on the baseline intercept of the mapping function f() to eliminate the time drift error of the sensor.

[0048] In the embodiments of this application, taking the No. 10 anchor cable of a certain slope as an example, the initial locking load is 1000kN and the initial magnetic signal is 500mV.

[0049] Baseline establishment: Establish a health model U = 0.5 * F (simplified linear model). The baseline temperature is 20℃, and the error threshold δ is set to 5mV.

[0050] Operational monitoring (Year 3, current temperature 20℃):

[0051] Force gauge reading F t = 980 kN (prestress loss 2%).

[0052] Magnetic flux meter reading U measured = 450 mV (signal drops significantly).

[0053] Traditional misjudgment: If only the magnetic signal is considered, 450 / 0.5 = 900 kN, it may be mistakenly assumed that the anchor cable has slackened to 900 kN, causing a false alarm.

[0054] This invention first calculates the theoretical magnetic signal: U theory = 0.5 × 980 = 490 mV.

[0055] Calculate the residual: ΔU = 450 - 490 = -40 mV. Since |-40| > 5, corrosion is confirmed.

[0056] The stress loss was indeed 20kN (confirmed by the force gauge). However, the additional -40mV deviation was not due to relaxation, but rather to corrosion reducing the cross-sectional area of ​​the steel strand. Corrosion rate calculation: The project's preset function g() corresponds to a 1% cross-sectional loss per 10mV, so the current loss rate η is approximately 4%. Graded warning execution: The system judges the current prestress loss to be 2% (normal range), but the 4% cross-sectional loss rate falls into the "2%~5% secondary warning range". The system triggers a level-two durability warning, indicating a "high stress + moderate corrosion" state, and recommends rust removal and anti-corrosion treatment instead of simple compensation tensioning.

[0057] Dynamic baseline calibration execution (Year 5):

[0058] The system extracted monitoring data from a consecutive 30 days in the fifth year. The force source sensor readings were extremely stable, with a fluctuation rate of only 0.2% (below the set stability threshold of 1%), indicating that the baseline calibration window had been entered. At this point, the system calculations revealed a persistent, small residual of -2mV between the measured magnetic signal and the theoretical magnetic signal over these 30 days. Since the stress remained unchanged and the corrosion characteristic threshold was not reached, this -2mV was determined to be a long-term zero-point drift due to instrument aging. The system automatically used this average residual as a drift compensation amount to fine-tune the intercept of the original health model, updating the constitutive curve function to: U = 0.5 × F - 2. Subsequent residual calculations will be based on the updated baseline, effectively avoiding error accumulation caused by long-term instrument drift.

[0059] The foregoing description illustrates and describes a preferred embodiment of the present invention. However, as previously stated, it should be understood that the present invention is not limited to the forms disclosed herein and should not be construed as excluding other embodiments. It can be used in various other combinations, modifications, and environments, and can be altered within the scope of the inventive concept described herein through the foregoing teachings or techniques or knowledge in related fields. Any modifications and variations made by those skilled in the art that do not depart from the spirit and scope of the present invention should be within the protection scope of the appended claims.

Claims

1. A method for assessing the corrosion status and stress level of anchor cables based on dual-source monitoring, characterized in that: Includes the following steps: Step S1: Simultaneously deploy two types of sensors on the key anchor cables for dual-source monitoring; Step S2: Under the healthy condition of the anchor cable without corrosion, perform a full-range tensioning and collect the theoretical magnetic signals corresponding to different tensions. Construct the "healthy state force-magnetic constitutive curve" and mapping function through data fitting. Step S3. During long-term operation, the tensile force and magnetic flux signal are measured at various times. Step S4. Calculate the residual ΔU between the measured magnetic signal and the theoretical magnetic signal; Step S5. Determine the corrosion status of the anchor cable based on the residuals, and convert the residuals into the effective metal cross-sectional area loss rate when corrosion occurs; Step S6: Based on the measured tensile force value and effective metal cross-sectional area loss rate, classify and issue early warnings for load-bearing capacity safety and material durability health.

2. The method for assessing the corrosion state and stress level of anchor cables based on dual-source monitoring according to claim 1, characterized in that: In step S1, the two types of sensors include: Force source sensors, using vibrating wire or fiber optic grating anchor cable force gauges, are used to obtain accurate tension values; The magnetic source sensor, employing either a through-hole or bypass magnetic flux sensor, is used to acquire a comprehensive magnetic flux signal.

3. The method for assessing the corrosion state and stress level of anchor cables based on dual-source monitoring according to claim 2, characterized in that: Step S2 includes: Under healthy conditions where the anchor cable is free from corrosion, a full-range tensioning is performed, and force and magnetic source sensors are used to collect different tension forces F and corresponding magnetic flux signals. The magnetic flux signal at this time is the theoretical magnetic signal corresponding to that tension force under the condition of no corrosion, denoted as U. theory According to different tensile forces F and corresponding U theory Construct a "force-magnetic constitutive curve for a healthy state"; The corresponding force-magnetic mapping function is fitted, denoted as: U theory = f(F) ; Where f() is a calibration function that characterizes the mapping relationship between tensile force and theoretical magnetic signal, obtained by fitting measured data under healthy conditions, i.e., force-magnetic mapping function.

4. The method for assessing the corrosion state and stress level of anchor cables based on dual-source monitoring according to claim 1, characterized in that: Step S3 includes: During long-term operation, the tensile force is measured at various moments using a force source sensor, and the magnetic flux signal is measured using a magnetic source sensor. For any given moment t, the measured tensile force is denoted as F. t The measured magnetic flux signal is denoted as U. measured(t) .

5. The method for assessing the corrosion state and stress level of anchor cables based on dual-source monitoring according to claim 1, characterized in that: Step S4 includes: Using the measured tensile force F t Substituting the force-magnetic mapping function f(), the theoretical magnetic signal U that should be exhibited under the current tensile force is calculated. theory_t : U theory_t = f(F t ) ; Calculate the residual between the measured magnetic signal and the theoretical magnetic signal: ΔU = U measured(t) -U theory_t .

6. The method for assessing the corrosion state and stress level of anchor cables based on dual-source monitoring according to claim 1, characterized in that: Step S5 includes: Set the system error threshold to δ; When |ΔU| ≤ δ, it indicates that the change in magnetic signal is entirely caused by the change in tension, the anchor cable is healthy, and only stress fluctuations occur; When |ΔU| > δ, this deviation is the "corrosion component". Using the "magnetic signal-cross-sectional area" relationship model, ΔU is converted into the effective metal cross-sectional area loss rate: η = g(ΔU); Wherein, g() is the cross-sectional area loss rate conversion function, which is pre-constructed by mathematical fitting of different corrosion rates and their corresponding magnetic signal residuals through calibration tests on anchor cable samples with known different corrosion rates.

7. The method for assessing the corrosion state and stress level of anchor cables based on dual-source monitoring according to claim 1, characterized in that: Step S6 includes: pre-setting multiple warning thresholds for load-bearing capacity safety and material durability health; based on F t Assess load-bearing capacity safety based on To assess the durability and health of materials, F t and Each indicator is compared with its corresponding warning threshold, and the warning level is determined based on the range in which the comparison occurs. When any indicator exceeds the safety threshold, the corresponding warning level is triggered.

8. The method for assessing the corrosion state and stress level of anchor cables based on dual-source monitoring according to claim 5, characterized in that: Step S1 also includes installing temperature sensors on the key anchor cables to obtain the ambient temperature T. In step S4, the residual calculation includes a temperature compensation mechanism, U theory_t The calculation formula is revised as follows: U theory_t = f(F t ) ×[1+α(T t - T0)] ; Where α is the pre-calibrated temperature compensation coefficient, T t T0 is the measured temperature at the current moment, and T0 is the calibration reference temperature.

9. A method for assessing the corrosion status and stress level of anchor cables based on dual-source monitoring according to any one of claims 4, characterized in that: In step S3, the magnetic flux signal is smoothed by a sliding window moving average algorithm or Kalman filtering during acquisition; and a rate of change threshold is set, and signals whose rate of change exceeds the threshold at adjacent times are discarded as abnormal electromagnetic interference noise.

10. A method for assessing the corrosion state and stress level of anchor cables based on dual-source monitoring according to any one of claims 1-7, characterized in that: The method also includes a dynamic baseline calibration step, the specific process of which is: during the service of the anchor cable, extracting the force source sensor readings within a continuously set time window; Calculate the fluctuation rate of the force source sensor reading within the time window. If the fluctuation rate is lower than the set stability threshold, it is determined that the current period is the baseline calibration window. Extract the average residual between the measured magnetic signal and the theoretical magnetic signal within the window, and use the average residual as the drift compensation amount to perform superposition fine-tuning correction on the baseline intercept of the mapping function f() to eliminate the time drift error of the sensor.

Images