A method and system for identifying effective tension of cable structures under complex stress based on resonance-enhanced magnetoelastic effect

Abstract

The present invention discloses a method and system for identifying the effective tension of a cable structure under complex stresses based on the resonance-enhanced magnetoelastic effect. The method is applied to the field of bridge engineering technology and involves obtaining the structural property parameters of a bridge cable. The method then determines the functional relationship between the induced voltage and the effective tension based on the cable structural property parameters. The functional relationship is then combined with an established coil optimization model to determine the number of turns for the primary and secondary coils. The method then uses the number of turns and the winding radius of the sensor coil to establish a transmission coupling model between the two coils and determine the optimal input current signal frequency. Fixed parameters are calibrated under the optimal input current signal frequency. A sensor is used to collect the induced voltage signal of the cable structure under complex stresses, which is then incorporated into the cable force identification formula to determine the actual effective tension of the cable structure. The method optimizes the coil based on the actual cable structural parameters, increasing the signal's sensitivity to cable force, determining the sensor's input signal parameters, and improving the sensor's transmission efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge engineering, and more particularly to a method and system for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect. Background Art

[0002] The cable structure is an important force-transmitting component of a cable-type bridge. It is responsible for transferring the load on the beam to load-bearing structures such as towers and arch rings. The effective tension of the cable structure is related to the life and bearing capacity of the bridge. For cable bridges in service, the accurate effective tension of the cable structure can fully reflect the service status of the bridge. Due to the concealed nature of the steel wires or steel strands inside the cable structure, it is difficult to simply, effectively and accurately identify the cable force. In addition, the cable structure often generates lateral forces under the action of complex boundary conditions, lateral dampers, etc., which puts the cable structure in a complex stress state, which makes it more difficult to identify the effective tension of the cable structure.

[0003] For ferromagnetic materials, the magnetoelastic method can describe the relationship between strain and magnetic parameters. Therefore, in cable tension monitoring, the purpose of cable tension can be achieved through magnetic parameters. Compared with other cable tension identification methods, the magnetoelastic method can directly identify the effective tension of the internal steel wire or steel strand outside the cable protective sheath, without being affected by the protective sheath. In addition, this method is low-cost, the sensor is small in size, and it is easy to apply to real bridge cable tension monitoring. However, in cable tension identification research, this technology is still stuck in the tension identification of axially stressed cable structures, and has not studied the identification of the effective tension of cable structures under complex stress conditions. The specific performance is as follows:

[0004] 1. The traditional magnetoelastic method for identifying cable tension often uses the time domain eigenvalue of the signal to represent the magnitude of the cable tension, but the accuracy of identifying the cable tension is insufficient.

[0005] 2. The current magnetoelastic coil sensor has low transmission efficiency and high loss, which requires a higher current input signal and increases the cost of cable force detection.

[0006] 3. The current identification of cable tension based on the magnetoelastic method does not take into account complex stress conditions, resulting in inaccurate identification of the effective tension of the cable structure.

[0007] Therefore, how to provide a method and system for identifying effective tension of cable structures under complex stress conditions is an urgent problem that those skilled in the art need to solve. Summary of the Invention

[0008] In view of this, the present invention provides a method and system for identifying the effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect, so as to solve the problems in the background technology.

[0009] In order to achieve the above object, the present invention adopts the following technical solutions:

[0010] In one aspect, the present invention discloses a method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect, comprising:

[0011] Obtaining structural attribute parameters of the bridge cable, wherein the attribute parameters include material and shape parameters of internal stress-bearing steel wires or steel strands;

[0012] Determining a functional relationship between the induced voltage and the effective tension based on the cable structure property parameters, and using the functional relationship in combination with a coil optimization model established based on the sensor's sensitivity to the effective tension to determine the number of turns of the primary coil and the secondary coil;

[0013] The number of turns of the primary coil and the secondary coil is used, and the winding radius of the sensor coil is determined according to the radius of the cable structure, a transmission coupling model of the two coils is established, and the optimal input current signal frequency is determined;

[0014] Calibrate fixed parameters under the optimal input current signal frequency condition;

[0015] The sensor is used to collect the induced voltage signal of the cable structure under complex stress, and the actual effective tension of the cable structure is obtained by applying it into the cable force identification formula.

[0016] Preferably, in the above-mentioned method for identifying the effective tension of a cable structure under complex stress based on the resonance-enhanced magnetoelastic effect, the functional relationship between the induced voltage and the effective tension is:

[0017]

[0018] Where u is the induced voltage, N1 and N2 are the turns of the primary coil and the secondary coil respectively, S iron is the area of the steel wire inside the cable structure, L is the length of the cable structure, a is the location where the lateral force is generated, and F s is the magnitude of the lateral force, F N is the effective tension, K u is the uniaxial anisotropic magnetic susceptibility constant, M s is the saturation magnetization intensity, θ0 is the angle between the magnetization direction and the easy magnetization axis of the steel wire, E is the elastic modulus of the steel wire, μ σ0 is the magnetic permeability of the steel wire inside the cable structure without stress, A is the signal amplitude of the input current, ω is the angular velocity of the input signal, is the phase of the input signal.

[0019] Preferably, in the above-mentioned method for identifying the effective tension of a cable structure under complex stress based on the resonance-enhanced magnetoelastic effect, a coil optimization model is established according to the sensitivity of the sensor to the effective tension, and the objective function is determined:

[0020]

[0021] Where α is the sensitivity function of the induced voltage signal to the effective tension of the cable structure; u1 and u2 represent the theoretical voltage signals under different tensions, and F N1 、F N2 For different effective tensions.

[0022] Preferably, in the above-mentioned method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect, the transmission coupling model of the two coils:

[0023]

[0024] Where η is the transmission efficiency, ω is the angular velocity of the input signal, M is the mutual inductance coefficient between the coils, and R T and R R are the equivalent resistances of the primary and secondary coils, R L is the internal resistance of the acquisition device, L R and C R are the inductance and capacitance of the secondary coil.

[0025] Preferably, in the above-mentioned method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect, when the receiving coil resonates, the transmission efficiency reaches a maximum, and the input signal parameter ω is calculated:

[0026]

[0027] L R and C R are the inductance and capacitance of the secondary coil.

[0028] Preferably, in the above-mentioned method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect, the specific steps of calibrating the fixed parameters under the optimal input current signal frequency condition are as follows: measuring the induced voltage signal under different axial force levels and different lateral forces;

[0029] Perform FFT transformation on the induced voltage signal;

[0030] Extract the maximum value A1 of the imaginary part amplitude of the frequency domain feature;

[0031] A linear regression fit is performed on the axial tension and A1 without lateral force. The intercept of the fit is the correction value b2, and the slope of the fit is the parameter k2.

[0032] A linear regression fit is performed on the lateral force and A1 under different axial tensions. The intercept of the fit is the correction value b1, and the slope of the fit is the parameter k1.

[0033] Preferably, in the above-mentioned method for identifying the effective tension of a cable structure under complex stress based on the resonance-enhanced magnetoelastic effect, the cable force identification formula is:

[0034]

[0035] Among them, A1 is the maximum value of the imaginary part amplitude of the frequency domain characteristic, k1, k2, b1, and b2 are linear regression parameters; and S is the magnitude of the lateral force on the cable structure under the complex stress state.

[0036] On the other hand, the present invention discloses a system for identifying the effective tension of a cable structure under complex stress based on the resonance-enhanced magnetoelastic effect, which applies the above method and includes:

[0037] An acquisition module is used to acquire attribute parameters of the bridge cable structure, wherein the attribute parameters include material and shape parameters of the internal stress-bearing steel wires or steel strands;

[0038] A coil turns optimization module determines the functional relationship between the induced voltage and the effective tension based on the cable structure attribute parameters, and uses the functional relationship combined with the sensitivity of the sensor to the effective tension to establish a coil optimization model to determine the winding turns of the primary coil and the secondary coil;

[0039] an optimal input signal determination module, which determines the sensor coil winding radius based on the number of turns of the primary coil and the secondary coil and the radius of the cable structure, establishes a transmission coupling model of the two coils, and determines the optimal input current signal frequency;

[0040] Calibration module, calibrates fixed parameters under the optimal input current signal frequency condition;

[0041] The identification module uses sensors to collect induced voltage signals from cable structures under complex stresses, and then uses the signals into the cable force identification formula to obtain the actual effective tension of the cable structure.

[0042] Preferably, in the above-mentioned system for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect, the coil turns optimization module includes:

[0043] Function unit, which determines the functional relationship between the induced voltage and the effective tension according to the cable structure attribute parameters;

[0044] Coil optimization model unit, which establishes a coil optimization model based on the sensitivity of the sensor to the effective tension;

[0045] The calculation unit, in combination with the function unit and the coil optimization model unit, determines the number of turns of the primary coil and the secondary coil using a gradient descent method.

[0046] As can be seen from the above technical solutions, compared with the prior art, the present invention provides a method and system for identifying the effective tension of cable structures under complex stresses based on the resonance-enhanced magnetoelastic effect. Compared to the traditional magnetoelastic method for measuring the effective tension of cable structures, this method optimizes the coil sensor according to the actual cable structure parameters, improving the signal sensitivity to cable force. Utilizing the coil's resonance principle, the sensor's input signal parameters are determined, thereby improving the sensor's transmission efficiency. This establishes an effective tension identification method suitable for cable structures under complex stress states. This method achieves higher cable force identification accuracy, lower energy consumption, and greater applicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0048] Figure 1 This is a flow chart of a method for identifying the effective tension of a cable structure under complex stresses based on the resonance-enhanced magnetoelastic effect.

[0049] Figure 2 This is a schematic diagram of the working principle of the coil sensor;

[0050] Figure 3 Schematic diagram of the acquisition system;

[0051] Figure 4 Collect raw data for the induced voltage signal of a cable structure;

[0052] Figure 5 Relative error diagram of effective tension of cable structure identified by different methods. DETAILED DESCRIPTION

[0053] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0054] The embodiment of the present invention discloses a method for identifying the effective tension of a cable structure under complex stress based on resonance enhanced magnetoelastic effect, such as Figure 1 Shown, including:

[0055] S1 obtains structural attribute parameters of the bridge cable, wherein the attribute parameters include material and shape parameters of the internal stress-bearing steel wires or steel strands;

[0056] S2 determines the functional relationship between the induced voltage and the effective tension according to the cable structure attribute parameters, and uses the functional relationship in combination with the sensitivity of the sensor to the effective tension to establish a coil optimization model to determine the number of turns of the primary coil and the secondary coil;

[0057] S3 determines the winding radius of the sensor coil based on the number of turns of the primary coil and the secondary coil and the radius of the cable structure, establishes a transmission coupling model of the two coils, and determines the optimal input current signal frequency;

[0058] S4 calibrates fixed parameters under the optimal input current signal frequency condition;

[0059] S5 uses sensors to collect induced voltage signals from cable structures under complex stresses, and brings them into the cable force identification formula to obtain the actual effective tension of the cable structure.

[0060] In order to further optimize the above technical solution, in S2, the functional relationship between the induced voltage and the effective tension is:

[0061]

[0062] Where u is the induced voltage, N1 and N2 are the turns of the primary coil and the secondary coil respectively, S iron is the area of the steel wire inside the cable structure, L is the length of the cable structure, a is the location where the lateral force is generated, and F s is the magnitude of the lateral force, F N is the effective tension, K u is the uniaxial anisotropic magnetic susceptibility constant, M s is the saturation magnetization intensity, θ0 is the angle between the magnetization direction and the easy magnetization axis of the steel wire, E is the elastic modulus of the steel wire, μ σ0 is the magnetic permeability of the steel wire inside the cable structure without stress, A is the signal amplitude of the input current, ω is the angular velocity of the input signal, is the phase of the input signal.

[0063] In order to further optimize the above technical solution, in S2, a coil optimization model is established based on the sensitivity of the sensor to the effective tension, and the objective function is determined:

[0064]

[0065] Where α is the sensitivity function of the induced voltage signal to the effective tension of the cable structure; u1 and u2 represent the theoretical voltage signals under different tensions, and F N1 、F N2 For different effective tensions.

[0066] Furthermore, in S3 , the winding radius of the sensor coil is determined according to the radius of the cable structure.

[0067] r s =r+0.5

[0068] Where r s is the coil winding radius, r is the cable structure radius, both units are in cm.

[0069] In order to further optimize the above technical solution, in S3, the transmission coupling model of the two coils is:

[0070]

[0071] Where η is the transmission efficiency, ω is the angular velocity of the input signal, M is the mutual inductance coefficient between the coils, and R T and R R are the equivalent resistances of the primary and secondary coils, R L is the internal resistance of the acquisition device, L R and C R are the inductance and capacitance of the secondary coil.

[0072] In S2, a functional relationship between the induced voltage and the effective tension is determined based on the cable structure property parameters. The functional relationship is combined with a coil optimization model established based on the sensor's sensitivity to the effective tension to determine the number of turns of the primary coil and the secondary coil. The number of turns of the primary coil and the secondary coil is optimized using a gradient descent method:

[0073] Step 1: Define the objective function: First, define an objective function that describes the optimization goal. Taking the number of turns of the primary and secondary coils as input parameters, the objective function outputs a value representing the coil's sensitivity to cable force.

[0074] Step 2, Initialize Parameters: Set initial values for the number of turns of the primary and secondary coils. These initial values can be random or based on some prior knowledge or empirical rules.

[0075] Step 3, Calculate the Gradient: Using the gradient descent method, you need to calculate the gradient of the objective function with respect to the number of turns in the primary and secondary coils. The gradient represents the slope or directional derivative of a function at a given point; it indicates the direction in which the function value increases most rapidly.

[0076] Step 4: Update parameters: Based on the calculated gradient, update the number of turns in the primary and secondary coils according to the rules of gradient descent. Typically, a small step is made in the opposite direction of the gradient (i.e., the direction in which the function value decreases). This step size is also called the learning rate.

[0077] Step 5, repeat iterations: Repeat steps 3 and 4 until a stopping condition is met. The stopping condition can be when a preset number of iterations is reached or when the magnitude of the gradient is less than a certain threshold.

[0078] Step 6, Evaluation and Adjustment: After each iteration, re-evaluate the value of the objective function. If you find that the performance has not improved or has deteriorated, you may need to adjust the learning rate or other parameters.

[0079] Step 7, result output: When the stop condition is met, the optimized number of turns of the primary coil and the secondary coil is output.

[0080] In order to further optimize the above technical solution, in S3, when the receiving coil resonates, the transmission efficiency reaches the maximum, and the input signal parameter ω is calculated:

[0081]

[0082] L R and C R are the inductance and capacitance of the secondary coil.

[0083] In order to further optimize the above technical solution, in S4, the fixed parameters are calibrated under the optimal input current signal frequency condition. The specific steps are as follows: measuring the induced voltage signal under different axial force levels and different lateral forces;

[0084] Perform FFT transformation on the induced voltage signal;

[0085] Extract the maximum value A1 of the imaginary part amplitude of the frequency domain feature;

[0086] A linear regression fit is performed on the axial tension and A1 without lateral force. The intercept of the fit is the correction value b2, and the slope of the fit is the parameter k2.

[0087] A linear regression fit is performed on the lateral force and A1 under different axial tensions. The intercept of the fit is the correction value b1, and the slope of the fit is the parameter k1.

[0088] In order to further optimize the above technical solution, in S2, the cable force identification formula is:

[0089]

[0090] Among them, A1 is the maximum value of the imaginary part amplitude of the frequency domain characteristic, k1, k2, b1, and b2 are linear regression parameters; and S is the magnitude of the lateral force on the cable structure under the complex stress state.

[0091] Specifically, in S5, Figure 3 :

[0092] S501 sequentially connects a signal generator, a power amplifier, an oscilloscope, and a PC to collect the induced voltage signal of the actual cable structure.

[0093] S502: Perform FFT transformation on the induced voltage signal to extract the eigenvalue A1.

[0094] S503: Substitute the cable force identification formula into the calculation of the effective tension of the cable structure.

[0095]

[0096] Another embodiment of the present invention discloses a system for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect, which applies the above method and includes:

[0097] An acquisition module is used to acquire attribute parameters of the bridge cable structure, wherein the attribute parameters include material and shape parameters of the internal stress-bearing steel wires or steel strands;

[0098] A coil turns optimization module determines the functional relationship between the induced voltage and the effective tension based on the cable structure attribute parameters, and uses the functional relationship combined with the sensitivity of the sensor to the effective tension to establish a coil optimization model to determine the winding turns of the primary coil and the secondary coil;

[0099] an optimal input signal determination module, which determines the sensor coil winding radius based on the number of turns of the primary coil and the secondary coil and the radius of the cable structure, establishes a transmission coupling model of the two coils, and determines the optimal input current signal frequency;

[0100] Calibration module, calibrates fixed parameters under the optimal input current signal frequency condition;

[0101] The identification module uses sensors to collect induced voltage signals from cable structures under complex stresses, and then uses the signals into the cable force identification formula to obtain the actual effective tension of the cable structure.

[0102] To further optimize the above technical solution, the coil turns optimization module includes:

[0103] Function unit, which determines the functional relationship between the induced voltage and the effective tension according to the cable structure attribute parameters;

[0104] Coil optimization model unit, which establishes a coil optimization model based on the sensitivity of the sensor to the effective tension;

[0105] The calculation unit, in combination with the function unit and the coil optimization model unit, determines the number of turns of the primary coil and the secondary coil using a gradient descent method.

[0106] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0107] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect, characterized in that: include: Obtaining structural attribute parameters of the bridge cable, wherein the attribute parameters include material and shape parameters of internal stress-bearing steel wires or steel strands; Determining a functional relationship between the induced voltage and the effective tension based on the cable structure property parameters, and using the functional relationship in combination with a coil optimization model established based on the sensor's sensitivity to the effective tension to determine the number of turns of the primary coil and the secondary coil; The number of turns of the primary coil and the secondary coil is used, and the winding radius of the sensor coil is determined according to the radius of the cable structure, a transmission coupling model of the two coils is established, and the optimal input current signal frequency is determined; Calibrate fixed parameters under the optimal input current signal frequency condition; The sensor is used to collect the induced voltage signal of the cable structure under complex stress, and the actual effective tension of the cable structure is obtained by applying it into the cable force identification formula. Functional relationship between induced voltage and effective tension: Where u is the induced voltage, N1 and N2 are the turns of the primary coil and the secondary coil respectively, S iron is the area of the steel wire inside the cable structure, L is the length of the cable structure, a is the location where the lateral force is generated, and F s is the magnitude of the lateral force, F N is the effective tension, K u is the uniaxial anisotropic magnetic susceptibility constant, M s is the saturation magnetization intensity, θ0 is the angle between the magnetization direction and the easy magnetization axis of the steel wire, E is the elastic modulus of the steel wire, μ σ0 is the magnetic permeability of the steel wire inside the cable structure without stress, A is the signal amplitude of the input current, ω is the angular velocity of the input signal, is the phase of the input signal; According to the sensitivity of the sensor to the effective tension, a coil optimization model is established to determine the objective function: Where α is the sensitivity function of the induced voltage signal to the effective tension of the cable structure; u1 and u2 represent the theoretical voltage signals under different tensions, and F N1 、F N2 For different effective tensions.

2. The method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect according to claim 1, characterized in that: Transmission coupling model of two coils: Where η is the transmission efficiency, ω is the angular velocity of the input signal, M is the mutual inductance coefficient between the coils, and R T and R R are the equivalent resistances of the primary and secondary coils, R L is the internal resistance of the acquisition device, L R and C R are the inductance and capacitance of the secondary coil.

3. The method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect according to claim 1, characterized in that: When the receiving coil resonates, the transmission efficiency reaches its maximum, and the input signal parameter ω is calculated as: L R and C R are the inductance and capacitance of the secondary coil.

4. The method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect according to claim 1, characterized in that: The specific steps for calibrating the fixed parameters under the optimal input current signal frequency condition are as follows: measuring the induced voltage signal under different axial force levels and different lateral forces; Perform FFT transformation on the induced voltage signal; Extract the maximum value A1 of the imaginary part amplitude of the frequency domain feature; A linear regression fit is performed on the axial tension and A1 without lateral force. The intercept of the fit is the correction value b2, and the slope of the fit is the parameter k2. A linear regression fit is performed on the lateral force and A1 under different axial tensions. The intercept of the fit is the correction value b1, and the slope of the fit is the parameter k1.

5. The method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect according to claim 4, characterized in that: Cable force identification formula: Among them, A1 is the maximum value of the imaginary part amplitude of the frequency domain characteristic, k1, k2, b1, and b2 are linear regression parameters; and S is the magnitude of the lateral force on the cable structure under the complex stress state.

6. A system for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect, using the method for identifying effective tension of a cable structure under complex stress based on resonance-enhanced magnetoelastic effect according to any one of claims 1 to 5, characterized in that: include: An acquisition module is used to acquire attribute parameters of the bridge cable structure, wherein the attribute parameters include material and shape parameters of the internal stress-bearing steel wires or steel strands; A coil turns optimization module determines the functional relationship between the induced voltage and the effective tension based on the cable structure attribute parameters, and uses the functional relationship combined with the sensitivity of the sensor to the effective tension to establish a coil optimization model to determine the winding turns of the primary coil and the secondary coil; an optimal input signal determination module, which determines the sensor coil winding radius based on the number of turns of the primary coil and the secondary coil and the radius of the cable structure, establishes a transmission coupling model of the two coils, and determines the optimal input current signal frequency; Calibration module, calibrates fixed parameters under the optimal input current signal frequency condition; The identification module uses sensors to collect induced voltage signals from cable structures under complex stresses, and then uses the signals into the cable force identification formula to obtain the actual effective tension of the cable structure.

7. The system for identifying effective tension of cable structures under complex stresses based on resonance-enhanced magnetoelastic effect according to claim 6, characterized in that: The coil turns optimization module includes: Function unit, which determines the functional relationship between the induced voltage and the effective tension according to the cable structure attribute parameters; Coil optimization model unit, which establishes a coil optimization model based on the sensitivity of the sensor to the effective tension; The calculation unit, in combination with the function unit and the coil optimization model unit, determines the number of turns of the primary coil and the secondary coil using a gradient descent method.

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