Cable current correction measurement method based on open-loop structure tmr sensor

Abstract

The application relates to a cable current correction measurement method based on an open-loop structure TMR sensor, which comprises the following steps: S1, installing TMR sensors S1 and S2 on an open-loop mechanical structure; S2, obtaining a magnetic field strength vector of a magnetic field excited by a cable current at positions of the sensors S1 and S2, and obtaining a magnetic field strength component in the direction of a sensor sensitive axis through vector operation; S3, obtaining a mathematical equation about unknowns introduced by only the sensor S1; S4, solving the nonlinear mathematical equation established in the step S3 to obtain a cable current value; S5, judging whether the obtained current value meets a preset condition, if yes, storing the current value, otherwise, continuing to perform optimization calculation; S6, discarding unreasonable current values after a sample capacity N is reached; S7, fitting sample current values by using an interpolation polynomial, and finally obtaining an average current value. Compared with the prior art, the application has the advantages that the cable current value can be effectively calculated.

Description

Technical Field

[0001] This invention relates to a cable current measurement method, and more particularly to a cable current correction measurement method based on an open-loop TMR sensor. Background Technology

[0002] A smart grid is a new generation of power system built upon the traditional power system, integrating new energy sources, new equipment, and advanced sensing and control technologies. To ensure the safe and stable operation of the smart grid, real-time data collection and analysis are necessary. Among these, current information is one of the most important and directly measurable data. Power cables, as crucial carriers for transmitting current across space, are widely used in smart grids. Real-time monitoring of the operating status of power cables using advanced sensing technologies is one of the current requirements for smart grid development.

[0003] Currently, current monitoring of power cables still relies on traditional current measurement methods such as shunts, current transformers, and Rogowski coils. Traditional contact-based current measurement introduces additional current measurement branches, increasing the complexity of current measurement and introducing unnecessary stray resistance into transmission lines. Furthermore, measuring devices with magnetic cores occupy significant space and introduce undesirable properties of ferromagnetic materials, such as hysteresis, magnetic saturation, and magnetic loss, into the measurement system. Moreover, measuring devices with magnetic cores cannot measure alternating current. Therefore, it is necessary to implement non-contact current measurement for power cables.

[0004] With the discovery and in-depth research of anisotropic magnetoresistance, giant magnetoresistance, and tunnel junction magnetoresistance effects, non-contact current measurement has gradually been realized. Compared with the other two magnetoresistance effects, the tunnel junction magnetoresistance effect has a higher rate of magnetoresistance change. Therefore, TMR current sensors made using tunnel junction magnetoresistance have higher sensitivity, resolution, and magnetic field measurement range. At the same time, TMR current sensors are small in size, low in power consumption, and have good temperature stability, showing broad development prospects.

[0005] Most novel non-contact measurement technologies currently employ closed-loop ring-type TMR sensor arrays. This is because closed-loop TMR sensor arrays use multiple sensors, improving measurement accuracy and electromagnetic interference resistance, making them suitable for power current measurement in complex electromagnetic environments such as those with cable crosstalk. However, closed-loop ring-type sensor arrays require a large number of sensors. In practical applications, not only is the sensor array structure designed, but the signal output of each sensor also needs to be calibrated to optimize signal gain. Therefore, closed-loop ring-type sensor arrays increase the complexity of power current measurement. Different measurement methods are needed for different application scenarios. Open-loop TMR sensor current measurement technology requires fewer sensors, offers faster sensor calibration, and is easier to install. Combined with appropriate algorithms and magnetic shielding devices, it can achieve excellent measurement accuracy.

[0006] Therefore, it is necessary to develop a new non-contact cable current measurement technology based on an open-loop structure, which can correct errors caused by cable eccentricity during the measurement process and achieve accurate current measurement. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a cable current correction measurement method based on an open-loop TMR sensor.

[0008] The objective of this invention can be achieved through the following technical solutions:

[0009] According to one aspect of the present invention, a cable current correction measurement method based on an open-loop TMR sensor is provided, the method comprising the following steps:

[0010] Step S1: Install TMR sensors S1 and S2 onto the open-loop mechanical structure;

[0011] Step S2: According to the Biot-Savart law, obtain the magnetic field strength vector of the magnetic field excited by the cable current at the positions of sensors S1 and S2, and obtain the magnetic field strength component along the sensor sensitive axis through vector operation.

[0012] Step S3: Obtain the mathematical equations for the unknowns introduced only by sensor S1;

[0013] Step S4: Solve the nonlinear mathematical equation established in step S3 using a stochastic optimization algorithm to obtain the cable current value;

[0014] Step S5: Determine whether the obtained current value meets the preset conditions. If it does, store it; otherwise, continue with the optimization calculation.

[0015] Step S6: After reaching the sample size N, use the bad value elimination algorithm to eliminate unreasonable current values.

[0016] Step S7: Use interpolation polynomials to fit the sample current values ​​and finally calculate the average current value.

[0017] As a preferred technical solution, in step S1, the included angle between the two sensors is 180°, the sensitive axis direction of the TMR sensor is in the same plane as the cross-section of the cable, the connecting line S1-S2 between the sensors intersects the circle where the cable core is located, and the midpoint of the connecting line S1-S2 is the center of the circle where the sensor is located.

[0018] The line connecting the sensor measurement points intersects the circle containing the cable core at point P. The radius of the large circle containing the sensor is R. The distance from sensor S1 to point P is m1, and the distance from point P to the midpoint O is n1. The radius of the cable core is r, and the distances from the center O' of the cable circle to sensors S1 and S2 are ρ1 and ρ2, respectively. The eccentricity of the cable is l. The angles between ρ1, ρ2 and R are α and β, respectively.

[0019] As a preferred technical solution, step S3 specifically includes:

[0020] By analyzing the geometric relationship of the figure formed by sensors S1-S2, the center of the circle where the sensors are located, and the center of the cable, the unknowns ρ2 and β introduced by sensor S2 are transformed into functions of the unknowns ρ1 and n1 introduced by sensor S1, and finally, a mathematical equation is obtained that only relates to the unknowns introduced by sensor S1.

[0021] As a preferred technical solution, the stochastic optimization algorithm in step S4 includes heuristic algorithms such as genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm.

[0022] As a preferred technical solution, the preset conditions in step S5 include:

[0023] (1) The minimum value of the objective function is less than the set value e;

[0024] (2) The ratio of magnetic field strength measured by TMR sensors S1 and S2 The ratio of the two calculated magnetic field strengths The absolute error between the two is less than the set value e;

[0025] The objective function is the magnetic field strength H measured by sensors S1 and S2. s1 H s2 The calculated magnetic field strength H' s1 ,H' s2 The Euclidean length between them.

[0026] As a preferred technical solution, the sample size N in step S6 is a preset value.

[0027] As a preferred technical solution, the bad value elimination algorithm in step S6 is based on the statistical principles of the Leita criterion, the probability integral criterion, and the Schovene criterion.

[0028] As a preferred technical solution, the interpolation polynomial in step S7 includes interpolation polynomials constructed by Lagrange interpolation and Newton interpolation methods.

[0029] As a preferred technical solution, the average current value in step S7 is the current value obtained by integral averaging.

[0030] As a preferred technical solution, this method sets an upper limit I for the current value. set The current measurement range of the proposed measurement method can be adjusted.

[0031] Compared with existing technologies, this invention achieves open-loop, non-contact measurement of power cable current, takes into account measurement errors caused by cable eccentricity, and can effectively calculate the cable current value. Furthermore, this invention minimizes the number of magnetic sensors used, facilitating future expansion. Attached Figure Description

[0032] Figure 1 This is a schematic diagram showing the arrangement of the TMR current sensor and the cable position of the present invention;

[0033] Figure 2 This is a schematic diagram of the geometric relationship between the TMR current sensor and the cable of the present invention;

[0034] Figure 3 This is a flowchart of the calculation process of the present invention;

[0035] Figure 4 This is a simulation result of the magnetic field of a DC power cable embodiment of the present invention;

[0036] Figure 5 This is a diagram showing the DC current calculation results obtained from the DC current embodiment of the power cable of the present invention;

[0037] Figure 6 This is a simulation result of the magnetic field of an AC power cable embodiment of the present invention;

[0038] Figure 7 This is a diagram showing the AC power calculation results obtained from the AC power embodiment of the power cable of the present invention;

[0039] Labels in the diagram: 1: TMR sensor; 2: Power cable core. Detailed Implementation

[0040] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0041] This invention relates to a cable current correction measurement method based on an open-loop TMR sensor, belonging to the field of non-contact power current measurement technology. The technical solution is as follows: Two TMR sensors with an included angle of 180° are arranged in an open loop. The sensitive axis of the magnetic sensor is on the same plane as the cable cross-section, and the midpoint of the sensor connection line is made as close as possible to the center of the cable. The tangential component of the magnetic field strength excited by the cable current is measured. Next, the mathematical relationship between the magnetic field measured by the two TMR sensors and the cable current is derived according to the Biot-Savart law. Finally, based solely on the distance between the magnetic sensors and the cable design parameters, a stochastic optimization algorithm and data processing method are used to reconstruct the cable current value when eccentricity exists. This invention achieves non-contact measurement of power cable current in an open-loop manner, minimizes the number of magnetic sensors used, considers the measurement error caused by cable eccentricity, and can effectively calculate the cable current value.

[0042] Please refer to Figure 2 This invention relates to a cable current correction measurement method based on an open-loop TMR sensor, comprising the following steps:

[0043] Step 1: TMR sensors S1 and S2 are installed on an open-loop mechanical structure with a sensor angle of 180°. The sensor's sensitive axis is in the same plane as the cable cross-section. The line connecting the sensor measurement points intersects the circle containing the cable core at point P, with the midpoint of the line as close as possible to the center of the cable circle. The radius of the large circle containing the sensor is R. The distance from sensor S1 to point P is m1, and the distance from point P to the midpoint O is n1. The radius of the cable core is r, and the distances from the cable center O' to sensors S1 and S2 are ρ1 and ρ2, respectively. The eccentricity of the cable is l.

[0044] Step 2: According to the Biot-Savart law, obtain the magnetic field strength vector of the magnetic field excited by the cable current at the sensor positions S1 and S2; through vector operation, obtain the magnetic field strength component along the sensor sensitive axis.

[0045] Step 3: By analyzing the geometric relationship of the figure formed by the sensors S1-S2, the center of the circle where the sensors are located, and the center of the cable, we finally obtain the mathematical equation for the unknowns introduced only by the sensor S1.

[0046] The specific implementation of steps 2 to 3 is as follows:

[0047] According to the Biot-Savart law, the magnitude of the magnetic field strength along the sensitive axes of sensors S1 and S2 is:

[0048]

[0049]

[0050] For the five triangles formed by the sensor locations S1 and S2, the center O of the circle containing the sensor, the center O' of the cable circle, and the intersection point P, write down the mathematical relationships between the inscribed angles α and β according to the Law of Cosines.

[0051]

[0052]

[0053]

[0054]

[0055]

[0056] There are also

[0057] m1+n1=R (8)

[0058] Based on equations (3) to (8), equations (1) to (2) can be simplified to:

[0059]

[0060] In the formula

[0061]

[0062]

[0063] Step 4: Use a stochastic optimization algorithm to solve the nonlinear mathematical model established in Step 3 to obtain the cable current value; the stochastic optimization algorithm includes heuristic algorithms such as genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm.

[0064] The nonlinear mathematical model is as follows:

[0065]

[0066] In the formula, I set The current is a preset upper limit, and c is a preset constant between (0,1); I set It can be set according to the application scenario; c is generally set to 1.

[0067] Step 5: Determine whether the obtained current value meets the preset conditions. If it does, store it; otherwise, continue the optimization calculation. The preset conditions are: (1) the minimum value of the objective function is less than the set value e; (2) the ratio of the magnetic field strength measured by TMR sensors S1 and S2. The ratio of the two calculated magnetic field strengths The absolute error between the two is less than the set value e; the objective function is the magnetic field strength H measured by sensors S1 and S2. s1 H s2 The calculated magnetic field strength H' s1 ,H' s2 The Euclidean length between them.

[0068] Step 6: After reaching the sample size N, use the bad value elimination algorithm to remove unreasonable current values; the sample size N is a pre-set value; the bad value elimination algorithm is based on statistical principles such as the Leita criterion, probability integral criterion, and Schovene criterion.

[0069] Step 7: Fit the sample current values ​​using an interpolation polynomial to finally obtain the average current value. The interpolation polynomial includes interpolation polynomials constructed using a series of equivalent methods such as Lagrange interpolation and Newton interpolation; the average current value is the current value obtained by integral averaging.

[0070] Finite element analysis and numerical calculation

[0071] To verify the effectiveness of the cable current correction measurement method based on an open-loop TMR sensor proposed in this invention, finite element simulation was used to calculate the cable simulation models (nominal cross-sectional area of ​​cable core is 1×300 [mm2]) for both DC and AC currents, obtaining the magnetic field strength values ​​along the tangent direction of the sensor circle at the positions of magnetic sensors S1 and S2. The simulation parameters are as follows: R=30 [mm], r=9.77 [mm]; DC current I=100 [A], AC power frequency f=50 [Hz], current I=100sin(2πf·t) [A]; eccentricity l=2.83 [mm].

[0072] DC numerical verification

[0073] The simulated magnetic field strength H-cloud diagram is shown below. Figure 4 As shown in Table 1, the components of the tangential magnetic field intensity at the sensor positions S1 and S2 excited by the DC current are shown in Table 1.

[0074] Table 1

[0075]

[0076] The simulated tangential component of the magnetic field strength is used as the value measured by sensors S1 and S2. Based on the mathematical model established according to this invention, the sample size is set to N = 50, and e = 10. -6 ,I set =200A, c=1, the genetic algorithm in Matlab Global Optimization Toolbox was used to solve the problem. Based on the Schovene criterion, out-of-current values ​​were eliminated, and a quadratic polynomial was used for fitting to calculate the average current. Table 2 shows the reconstruction results of the DC current of the power cable using the mathematical and physical model established in this invention. Figure 5 All effective current values ​​obtained in this calculation are given.

[0077] Table 2

[0078]

[0079] AC numerical verification

[0080] The simulation results show the variation of the tangential magnetic field strength H at positions S1 and S2 with time t as follows: Figure 6 As shown.

[0081] A magnetic field strength value was selected with a time step of 0.4 ms. The simulated tangential magnetic field strength H values ​​at positions S1 and S2 were used as the values ​​measured by sensors S1 and S2. Based on the mathematical model established according to this invention, the sample size was set to N = 20 and e = 10. -6 I set =200, c=1, the same genetic algorithm is used to solve the problem. Based on the Schovné criterion, bad current values ​​are eliminated, and a quadratic polynomial is selected for fitting to calculate the average current value within one cycle. Figure 7 The reconstruction results of alternating current in power cables using the mathematical and physical model established in this invention are presented. The maximum relative error between the reconstructed current value and the actual current value using the mathematical and physical model established in this invention is 1.33%.

[0082] In summary, the mathematical and physical model proposed in this invention can effectively calculate the current value of a power cable when there is eccentricity in the measurement, thereby realizing non-contact measurement of power cable current in an open-loop manner, and minimizing the number of magnetic sensors used, which facilitates subsequent expansion.

[0083] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A cable current correction measurement method based on an open-loop TMR sensor, characterized in that, The method includes the following steps: Step S1: Install TMR sensors S1 and S2 onto the open-loop mechanical structure; Step S2: According to the Biot-Savart law, obtain the magnetic field strength vector of the magnetic field excited by the cable current at the positions of sensors S1 and S2, and obtain the magnetic field strength component along the sensor sensitive axis through vector operation. Step S3: Obtain a nonlinear mathematical model that only relates to the unknowns introduced by sensor S1; Step S4: Solve the nonlinear mathematical model established in step S3 using a stochastic optimization algorithm to obtain the cable current value. I ; Step S5: Determine whether the obtained current value meets the preset conditions. If it does, store it; otherwise, continue with the optimization calculation. Step S6, reaching the sample size Then, a bad value elimination algorithm is used to eliminate unreasonable current values; Step S7: Use interpolation polynomials to fit the sample current values ​​and finally calculate the average current value. In step S1, the angle between the two sensors is 180°. The sensitive axis of the TMR sensor is in the same plane as the cross-section of the cable and is tangent to the large circle where the sensor is located. The line S1-S2 connecting the sensors intersects the circle where the cable core is located. The midpoint of the line S1-S2 is the center of the circle where the sensor is located. The connection between the sensors intersects the circle containing the cable core at point [point missing]. The radius of the great circle where the sensor is located is Sensor S1 arrives at point The distance is ,point to the midpoint The distance is The cable core radius is cable center The distances to sensors S1 and S2 are respectively , The eccentricity of the cable is ; , and The included angles are respectively , ; The specific steps of step S3 are as follows: By analyzing the geometric relationship of the figure formed by the connection lines S1-S2 between the sensors, the center of the circle containing the sensor, and the center of the cable, the unknown quantity introduced by sensor S2 is determined. , Convert to the unknown introduced by sensor S1 , The function ultimately yields a nonlinear mathematical model that depends only on the unknowns introduced by sensor S1; The nonlinear mathematical model in step S4 is as follows: In the formula, Let be the magnetic field strength measured by the i-th sensor. The magnetic field strength calculated for the i-th sensor. The preset upper limit of the current value, Preset The constants between; The preset conditions in step S5 include: (1) The minimum value of the objective function is less than the set value. ; (2) The ratio of magnetic field strength measured by TMR sensors S1 and S2 The ratio of the two calculated magnetic field strengths The absolute error between the two is less than the set value. ; The objective function is the magnetic field strength measured by sensors S1 and S2. The calculated magnetic field strength The Euclidean length between.

2. The cable current correction measurement method based on an open-loop TMR sensor according to claim 1, characterized in that, The stochastic optimization algorithm in step S4 includes genetic algorithm, particle swarm optimization algorithm, or simulated annealing algorithm.

3. The cable current correction measurement method based on an open-loop TMR sensor according to claim 1, characterized in that, The sample size in step S6 The value is a preset value.

4. The cable current correction measurement method based on an open-loop TMR sensor according to claim 1, characterized in that, The bad value elimination algorithm in step S6 is based on the statistical principles of the Leita criterion, the probability integral criterion, or the Schovene criterion.

5. The cable current correction measurement method based on an open-loop TMR sensor according to claim 1, characterized in that, The interpolation polynomial in step S7 includes interpolation polynomials constructed using Lagrange interpolation or Newton interpolation methods.

6. The cable current correction measurement method based on an open-loop TMR sensor according to claim 1, characterized in that, The average current value in step S7 is the current value obtained by integral averaging.

7. The cable current correction measurement method based on an open-loop TMR sensor according to claim 1, characterized in that, This method involves setting an upper limit for the current value. The current measurement range of the proposed measurement method can be adjusted.

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