Current detection method and system based on double-ring TMR nested structure

Abstract

The invention discloses a current detection method and system based on a double-ring TMR nested structure, and belongs to the technical field of current detection. The method comprises the following steps: based on a double-ring TMR system of a double-ring TMR nested structure, performing double-ring detection on the current of a to-be-detected wire in a current measurement scene; synchronously acquiring double-ring data obtained by double-ring detection through AD, and performing wavelet denoising on the double-ring data according to the structure data of the double-ring TMR nested structure; and based on a Kalman filtering algorithm, fusing the double-loop data after wavelet denoising to obtain current information of the to-be-measured wire in the current measurement scene. The method not only has outstanding advantages in the aspects of measurement accuracy and anti-interference performance, but also has a wide measurement range and stable linearity performance, and can be widely applied to complex electromagnetic environments with high requirements on current detection accuracy, such as new energy grid connection, electric vehicle charging piles and intelligent power grids.

Description

Technical Field

[0001] The present invention relates to the technical field of current detection, and more particularly to a current detection method and system based on a dual-ring TMR nested structure. Background Art

[0002] Current sensors play a vital role in key areas such as power electronics, motors, and energy. They are not only widely used in various scenarios, but are also core components for the proper and stable operation of modern infrastructure such as electric vehicles, photovoltaic systems, and charging stations. Furthermore, the development of ultra-high voltage flexible direct current transmission systems has also driven the demand for high-current DC measurement in power grids. Consequently, smart grids and new energy vehicles are placing higher demands on current monitoring performance and accuracy.

[0003] Currently, mainstream current sensor technologies include ferromagnetic current transformers, Hall current sensors, Rogowski coils, and all-fiber optic sensors. Ferromagnetic current transformers have a simple structure, low cost, and wide bandwidth, but they cannot measure DC current. Hall current sensors offer stable and reliable performance and can measure AC and DC currents, but they are susceptible to external environmental interference. Rogowski coils offer low cost and a wide detection bandwidth, but they cannot measure DC current. All-fiber optic current sensors offer high sensitivity, high precision, and a wide range, but they are expensive, technically complex, and susceptible to temperature. These limitations indicate that existing current sensing technologies have not yet fully adapted to the high-precision current measurement requirements of new power systems, which, to a certain extent, impacts the accuracy, real-time nature, and reliability of current measurement. Therefore, developing more advanced current sensing solutions to address these challenges is particularly urgent and important.

[0004] The operating principle of a TMR sensor is based on the quantum tunneling effect and magnetoresistance of a magnetic tunnel junction (MTJ). Its core structure consists of three thin films: a free layer at the top whose magnetization direction can change with the external magnetic field; an extremely thin nonmagnetic insulating layer in the middle; and a pinned layer at the bottom (with a fixed magnetization direction) composed of a composite of ferromagnetic and antiferromagnetic materials. When the magnetic moments of the free and pinned layers are parallel, electrons more easily tunnel through the insulating layer, resulting in a low-resistance state. When the magnetic moments of the free and pinned layers are antiparallel, the probability of electron tunneling decreases significantly, resulting in a high-resistance state. This magnetoresistance change, which can reach hundreds of times, is known as the tunneling magnetoresistance (TMR) effect.

[0005] In practical applications, four TMR resistors with identical characteristics form a push-pull Wheatstone bridge. When an external magnetic field acts on the sensor, the magnetization direction of the free layer is altered, causing the TMR resistances of adjacent bridge arms to change in opposite directions: as the resistance value of one pair increases, the resistance value of the other pair decreases. This differential structure converts the resistance change caused by the magnetic field into a voltage difference output, effectively offsetting temperature drift and common-mode noise. By monitoring the amplitude of the output voltage, the strength of the measured magnetic field can be linearly reflected.

[0006] In current measurement scenarios, the circular magnetic field generated around the current-carrying conductor is captured by the TMR sensor. By optimizing the sensor position so that its sensitive axis aligns with the magnetic field direction, the linear relationship between magnetic field strength and current is converted into a voltage signal at the output of the bridge, thus achieving non-contact, high-precision current detection.

[0007] The extensive use of power electronic devices such as wind, solar, and storage inverters, charging piles, etc. has resulted in currents with wide frequency domain, strong randomness, and fast time-varying characteristics, which has brought new challenges to the accurate measurement of current.

[0008] 1. Accuracy: The accuracy of traditional current sensors is limited by a variety of factors. For example, Hall-effect sensors are susceptible to temperature drift and bias current, which can increase measurement errors. Shunts, when measuring high currents, generate significant power consumption and self-heating, affecting measurement accuracy. When the primary current of a current transformer is excessive or a DC component is present, the core may saturate, causing output signal distortion and reducing measurement accuracy.

[0009] 2. Linearity: The linearity of a current sensor directly impacts measurement accuracy. Hall effect sensors can exhibit nonlinearity at high currents, affecting measurement results. At high frequencies or high currents, hysteresis and eddy current losses in the core of a current transformer can lead to decreased linearity and increased measurement errors.

[0010] 3. Measurement range: Existing current sensors have limitations. Hall effect sensors have a limited measurement range, making it difficult to cover a wide range of currents, from low to high. Shunts are suitable for measuring low currents, but their measurement range is limited at high currents due to power consumption and heat generation. Current transformers are primarily used for AC current measurement and cannot directly measure DC current, limiting their application. Summary of the Invention

[0011] To address the above problems, the present invention proposes a current detection method based on a dual-ring TMR nested structure, comprising:

[0012] The dual-loop TMR system based on the dual-loop TMR nested structure performs dual-loop detection on the current of the conductor to be measured in the current measurement scenario;

[0013] Acquire dual-loop data obtained by dual-loop detection through AD synchronization, and perform wavelet denoising on the dual-loop data based on the structural data of the dual-loop TMR nested structure;

[0014] Based on the Kalman filter algorithm, the double-loop data after wavelet denoising is fused to obtain the current information of the conductor to be measured in the current measurement scenario.

[0015] Optionally, the double-ring TMR nested structure includes: a nested structure consisting of a ring core and a ring array, the ring array is nested in the ring core, and the wire to be tested passes through the center of the ring array.

[0016] Optionally, the annular array includes: an annular array TMR current measurement module composed of tunnel magnetoresistance, in which multiple TMR elements are evenly arranged into a circular array with a radius of r, and each TMR element is used to measure the magnetic field component of the conductor to be measured in the tangential direction of the circle.

[0017] Optionally, a ring array is used to detect the primary current of the conductor to be tested.

[0018] Optionally, the annular core is a double-gap open core structure with a compensation winding, which is used to detect the feedback current of the conductor to be measured and to measure the superimposed magnetic field generated by the primary current and the feedback current.

[0019] Optionally, the dual-loop data includes: primary current data and feedback current data obtained by detecting the conductor to be tested.

[0020] Optionally, permutation entropy is introduced as a regulating factor in the threshold function to construct a continuously differentiable nonlinear threshold function. Based on the continuously differentiable nonlinear threshold function, wavelet denoising is performed on the dual-loop data. The expression of the continuously differentiable nonlinear threshold function is as follows:

[0021]

[0022] Among them, λ is the obtained threshold, ω j,k is the wavelet coefficient of the original signal, is the updated wavelet coefficient, P is the adjustment factor with a value range of (0,1), γ is the adjustment constant of the logarithmic function, which is used to prevent the denominator from approaching zero, and e is a very small positive number, which is used to ensure that there are no negative or zero values ​​in the logarithmic function to ensure numerical stability.

[0023] Optionally, a fusion strategy for fusing the dual-loop data after wavelet denoising includes:

[0024] The dual-loop weights are dynamically allocated according to the real-time current amplitude, including: in the low range, the weight of the ring core detection data is greater than the weight of the ring array detection data; in the high range, the weight of the ring array detection data is greater than the weight of the ring core detection data, and smooth switching is achieved through the suppression factor during the smoothing process.

[0025] On the other hand, the present invention also proposes a current detection system based on a dual-ring TMR nested structure, comprising:

[0026] The detection unit is used in a dual-loop TMR system based on a dual-loop TMR nested structure to perform dual-loop detection on the current of the conductor to be measured in a current measurement scenario;

[0027] a denoising unit, configured to collect dual-loop data obtained by dual-loop detection through AD synchronization, and perform wavelet denoising on the dual-loop data according to the structural data of the dual-loop TMR nested structure;

[0028] The fusion unit is used to fuse the double-loop data after wavelet denoising based on the Kalman filter algorithm to obtain the current information of the conductor to be measured in the current measurement scenario.

[0029] Optionally, the double-ring TMR nested structure includes: a nested structure consisting of a ring core and a ring array, the ring array is nested in the ring core, and the wire to be tested passes through the center of the ring array.

[0030] Optionally, the annular array includes: an annular array TMR current measurement module composed of tunnel magnetoresistance, in which multiple TMR elements are evenly arranged into a circular array with a radius of r, and each TMR element is used to measure the magnetic field component of the conductor to be measured in the tangential direction of the circle.

[0031] Optionally, a ring array is used to detect the primary current of the conductor to be tested.

[0032] Optionally, the annular core is a double-gap open core structure with a compensation winding, which is used to detect the feedback current of the conductor to be measured and to measure the superimposed magnetic field generated by the primary current and the feedback current.

[0033] Optionally, the dual-loop data includes: primary current data and feedback current data obtained by detecting the conductor to be tested.

[0034] Optionally, permutation entropy is introduced as a regulating factor in the threshold function to construct a continuously differentiable nonlinear threshold function. Based on the continuously differentiable nonlinear threshold function, wavelet denoising is performed on the dual-loop data. The expression of the continuously differentiable nonlinear threshold function is as follows:

[0035]

[0036] Among them, λ is the obtained threshold, ω j,k is the wavelet coefficient of the original signal, is the updated wavelet coefficient, P is the adjustment factor with a value range of (0,1), γ is the adjustment constant of the logarithmic function, which is used to prevent the denominator from approaching zero, and e is a very small positive number, which is used to ensure that there are no negative or zero values ​​in the logarithmic function to ensure numerical stability.

[0037] Optionally, a fusion strategy for fusing the dual-loop data after wavelet denoising includes:

[0038] The dual-loop weights are dynamically allocated according to the real-time current amplitude, including: in the low range, the weight of the ring core detection data is greater than the weight of the ring array detection data; in the high range, the weight of the ring array detection data is greater than the weight of the ring core detection data, and smooth switching is achieved through the suppression factor during the smoothing process.

[0039] In yet another aspect, the present invention further provides a computing device comprising: one or more processors;

[0040] a processor for executing one or more programs;

[0041] When the one or more programs are executed by the one or more processors, the above-described method is implemented.

[0042] In another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method described above is implemented.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] The present invention provides a current detection method based on a dual-loop TMR nested structure, comprising: a dual-loop TMR system based on the dual-loop TMR nested structure, performing dual-loop detection on the current of a conductor to be measured in a current measurement scenario; synchronously acquiring dual-loop data obtained by the dual-loop detection through AD, and performing wavelet denoising on the dual-loop data based on the structural data of the dual-loop TMR nested structure; and fusing the wavelet-denoised dual-loop data based on a Kalman filter algorithm to obtain current information of the conductor to be measured in the current measurement scenario. The method of the present invention not only has outstanding advantages in measurement accuracy and anti-interference performance, but also has a wide measurement range and stable linearity performance. It can be widely used in complex electromagnetic environments with high requirements for current detection accuracy, such as new energy grid connection, electric vehicle charging piles, and smart grids. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a flow chart of the method of the present invention;

[0046] Figure 2 A real-time flow chart of an embodiment of the method of the present invention;

[0047] Figure 3 Schematic diagram of a ring array TMR current measurement module according to an embodiment of the method of the present invention;

[0048] Figure 4 Schematic diagram of a closed-loop iron-core TMR current measurement module according to an embodiment of the method of the present invention;

[0049] Figure 5 A schematic diagram of a core-ring array nested structure according to an embodiment of the method of the present invention;

[0050] Figure 6 A flow chart of a Kalman filter algorithm according to an embodiment of the method of the present invention;

[0051] Figure 7 This is a comparison diagram of measurement errors of an embodiment of the method of the present invention;

[0052] Figure 8 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0053] Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to provide a thorough and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments shown in the accompanying drawings is not intended to limit the present invention. In the accompanying drawings, identical elements are denoted by the same reference numerals.

[0054] Unless otherwise specified, the terms used herein (including technical terms) have the meanings commonly understood by those skilled in the art. In addition, it is understood that terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0055] Example 1:

[0056] The present invention proposes a current detection method based on a double-ring TMR nested structure, such as Figure 1 Shown, including:

[0057] Step 1: Based on the dual-loop TMR nested structure, a dual-loop TMR system performs dual-loop detection on the current of the conductor to be measured in a current measurement scenario;

[0058] Step 2: Acquire dual-loop data obtained by dual-loop detection through AD synchronization, and perform wavelet denoising on the dual-loop data according to the structural data of the dual-loop TMR nested structure;

[0059] Step 3: Based on the Kalman filter algorithm, the double-loop data after wavelet denoising is fused to obtain the current information of the conductor to be measured in the current measurement scenario.

[0060] The double-ring TMR nested structure includes a nested structure consisting of a ring core and a ring array, wherein the ring array is nested in the ring core, and the conductor to be tested passes through the center of the ring array.

[0061] Among them, the annular array includes: an annular array TMR current measurement module composed of tunnel magnetoresistance, in which multiple TMR elements are evenly arranged into a circular array with a radius of r, and each TMR element is used to measure the magnetic field component of the conductor to be measured in the tangential direction of the circle.

[0062] Among them, the ring array is used to detect the primary current of the conductor to be tested.

[0063] Among them, the annular iron core is a double-air-gap open iron core structure with a compensation winding, which is used to detect the feedback current of the conductor to be tested and to measure the superimposed magnetic field generated by the primary current and the feedback current.

[0064] The dual-loop data includes: primary current data and feedback current data obtained by detecting the conductor to be tested.

[0065] Among them, permutation entropy is introduced as a regulating factor in the threshold function to construct a continuously differentiable nonlinear threshold function. Based on the continuously differentiable nonlinear threshold function, wavelet denoising is performed on the double-loop data. The expression of the continuously differentiable nonlinear threshold function is as follows:

[0066]

[0067] Among them, λ is the obtained threshold, ω j,k is the wavelet coefficient of the original signal, is the updated wavelet coefficient, P is the adjustment factor with a value range of (0,1), γ is the adjustment constant of the logarithmic function, which is used to prevent the denominator from approaching zero, and e is a very small positive number, which is used to ensure that there are no negative or zero values ​​in the logarithmic function to ensure numerical stability.

[0068] Among them, the fusion strategy for fusing the dual-loop data after wavelet denoising includes:

[0069] The dual-loop weights are dynamically allocated according to the real-time current amplitude, including: in the low range, the weight of the ring core detection data is greater than the weight of the ring array detection data; in the high range, the weight of the ring array detection data is greater than the weight of the ring core detection data, and smooth switching is achieved through the suppression factor during the smoothing process.

[0070] The present invention will be described below with reference to specific cases:

[0071] Case process as follows Figure 2 Shown, including:

[0072] Step 1: Detect the current to be measured through the dual-loop TMR system;

[0073] The principle of the double-ring TMR nested structure is as follows

[0074] The ring array TMR current measurement module is a single-axis coreless measurement method based on Ampere's loop law. According to the magnetic field distribution model of a long straight wire perpendicular to the array plane, multiple TMR elements are evenly arranged in a circular array with a radius of r. Each TMR element measures the magnetic field component in the tangential direction of the circle. The structure is as follows: Figure 3 shown.

[0075] All single-axis TMR elements have the same sensitivity and linearity. Under the same magnetic field, the output voltage of the TMR element is equal, that is, V i =K×B i (K is the sensitivity coefficient).

[0076] When the wire is located at the center of the array, the magnetic induction intensity measured by the i-th TMR element is Bi, and we can get

[0077] V i =K·B i (1)

[0078] The output voltages of all TMR elements are equal, and the total output voltage of N TMR elements is:

[0079]

[0080] in,

[0081] The coefficient between the total output voltage of the ring TMR current sensor and the measured current is K*. K* is related to factors such as the magnetic permeability μ0 in vacuum, the number of TMR elements N, the output sensitivity coefficient K, and the distance r. K* can be easily obtained through known parameter values. Therefore, the ring TMR current sensor measures the total output voltage V all The current value I of the array center conductor can be indirectly calculated.

[0082] Typically, the conductors are placed eccentrically or tilted within the array. Based on Ampere's loop law, using N uniaxial TMR elements evenly distributed around the circumference, the relationship between the total output voltage and the measured current is as follows:

[0083]

[0084] When the number N is large enough, the equation still holds true. This shows that if a sufficient number of TMR elements are evenly distributed around the circumference, and the sensitive axis of each TMR element is tangential to the circumference at that measurement point, then the current measurement result based on Ampere's loop law is independent of the eccentricity and tilt of the conductor being measured. Furthermore, the integral of the magnetic field for any current outside the array is zero, demonstrating strong resistance to interference from external magnetic fields.

[0085] Closed-loop TMR current sensor such as Figure 4 shown.

[0086] When the air gap of the magnetic ring is constant, the above formula shows that the magnetic induction intensity generated by the current-carrying wire at the air gap of the magnetic ring is proportional to the current of the wire.

[0087] In the closed-loop TMR structure, the energized conductor and coil generate magnetic induction intensity at the air gap of the magnetic focusing ring. The resulting magnetic field and current satisfy the following relationship:

[0088]

[0089] Where: N is the number of coil turns; i is the coil current; d is the air gap length; μ0 is the magnetic permeability of the magnetic ring.

[0090] When the magnetic induction intensity approaches zero, the magnetic field closed-loop equilibrium condition is reached, and we can get:

[0091] I=Ni(5)

[0092] Formula (13) shows that when the magnetic induction intensity at the air gap is 0, the current in the measured conductor is proportional to the current in the coil, and the proportional coefficient is the number of coil turns. Figure 5 As shown, the relationship between the voltage on the output resistor R and the current to be measured is:

[0093]

[0094] That is, the current to be measured is proportional to the terminal voltage on the resistor R. As long as the number of coil turns and the resistance value are known in advance, the current to be measured can be calculated based on the terminal voltage of the resistor.

[0095] The present invention proposes a core-ring array nested structure, which consists of ring 1, ring 2, and a digital signal processing unit. Figure 5 shown.

[0096] Ring 1 utilizes a double-gap open-core structure with a compensation winding. Its core sensing function is achieved by measuring the superimposed magnetic field generated by the primary and feedback currents. Its double-gap design effectively improves the linearity of the magnetic field distribution. The compensation winding dynamically offsets the nonlinearity of the core's magnetization curve, maintaining high-precision measurement performance over a wide dynamic range. This unit primarily establishes a baseline current-magnetic field conversion relationship, demonstrating excellent linear response characteristics, particularly in the low and medium ranges.

[0097] Ring 2 consists of four tunnel magnetoresistive (TMR) chips in a circular array magnetic sensor, using a spatially symmetrical design to achieve fast dynamic measurement. Real-time fusion processing of multi-sensor spatial sampling data effectively suppresses magnetic field distribution distortion errors caused by conductor eccentricity. A mutual verification mechanism for data from each sensor node automatically eliminates magnetic field crosstalk errors between adjacent channels at high-range measurements, significantly extending the sensor's measurement range.

[0098] The digital signal processing part uses a high-precision timing controller to synchronously collect the sensor signals of ring one and ring two, and adopts a dual-channel 16-bit A / D converter to achieve phase-aligned digital conversion at a rate of 100KSPS to ensure the timing consistency of the dual-ring data. A digital low-pass filter with a cutoff frequency of 200Hz is applied to the original sampled data to effectively suppress high-frequency noise interference. The processing results are output through the UART serial port to provide sample data for the wavelet denoising algorithm.

[0099] The present invention proposes a dual-ring fusion structure of closed-loop iron core TMR and ring array TMR. The high linearity of ring one solves the problem of accuracy in medium and low ranges, and the coreless wide-range sampling of ring two breaks through the high-range limitation, forming the complementary advantages of "low-range high precision and high-range wide coverage".

[0100] Step 2: AD synchronously samples the dual-loop data and performs wavelet denoising based on the characteristics of the dual-loop structure;

[0101] The principle of wavelet denoising is as follows:

[0102] The principle of wavelet denoising is to select an appropriate wavelet basis to decompose the measured signal into several layers of wavelet coefficients. The wavelet coefficients reflect the different details of the data. Due to the characteristics of the signal and noise, the noise signal is generally concentrated in the coefficients with small amplitudes. By selecting an appropriate threshold, the coefficients with values ​​less than the given threshold are eliminated, while the values ​​greater than the threshold are retained, thus achieving the desired noise reduction effect.

[0103] Traditional threshold functions, including soft and hard threshold functions, offer some noise reduction effectiveness. However, as signal complexity increases, both soft and hard threshold functions face significant drawbacks. Hard threshold functions exhibit discontinuities at the input, with cutoff points, which can lead to jumps and oscillations when reconstructing the processed coefficients. While soft threshold functions maintain overall continuity, they shrink data above the threshold, causing discrepancies between the reconstructed, noise-reduced signal and the actual signal, leading to signal distortion and increased error.

[0104] In order to overcome the above shortcomings, the present invention proposes an adaptive wavelet threshold that combines an improved threshold function and permutation entropy, which is expressed as follows:

[0105]

[0106] Where: λ is the obtained threshold; ω j,k is the wavelet coefficient of the original signal before processing; is the new wavelet coefficient; P is the adjustment factor, that is, the permutation entropy value, and its value range is (0,1).

[0107] From the calculation, we know that when |ω j,k |→λ + And when, its value is (1-P)λ, so the formula is continuous;

[0108]

[0109] From the above formula, we can see that the deviation of this function is small. j,k >0 o'clock:

[0110]

[0111] It can be seen that this function is asymptotic. In summary, this function overcomes the corresponding shortcomings of soft and hard threshold functions, has high smoothness and is continuously differentiable.

[0112] The threshold function is flexibly adjusted using permutation entropy as a regulating factor, with a time delay and a P value range of (0, 1). A larger value indicates a more chaotic wavelet coefficient sequence, while a smaller value indicates a more regular wavelet coefficient sequence. The proposed threshold function shows that the closer P is to 1, the closer the function is to a soft threshold function, removing more noise signals. The closer P is to 0, the closer it is to a hard threshold function, retaining more useful data. Regardless of the value of P, the function is continuously differentiable and has strong adaptability.

[0113] In response to the noise characteristics of TMR, the present invention uses the multi-scale analysis technology of wavelet transform for signal processing. By selecting wavelets suitable for the characteristics of transient signals, the original signal is decomposed into layers. The high-frequency layer mainly captures the white noise component, while the low-frequency layer is a mixture of effective signals and 1 / f noise. On this basis, the permutation entropy is introduced as a regulating factor to dynamically adjust the threshold function. The permutation entropy quantifies the noise intensity by analyzing the local pattern complexity of the signal sequence. When the entropy value is high, it indicates that the signal is highly random and the denoising efforts need to be strengthened; when the entropy value is low, it indicates that the signal is significantly regular and the coefficient modification needs to be reduced to retain details. For example, for the high-frequency layer dominated by white noise, a larger threshold and soft threshold characteristics are used to preferentially suppress random interference; while for the low-frequency layer mixed with 1 / f noise, the entropy value is combined to dynamically adjust the threshold to avoid excessive weakening of the effective signal. During the reconstruction process, the processed wavelet coefficients of each layer are synthesized into a denoised signal through inverse transformation to ensure that the waveform is smooth and the key features are fully preserved.

[0114] Aiming at the complex noise characteristics of TMR sensors, the present invention introduces permutation entropy as a regulating factor for the first time, constructs a "continuously differentiable nonlinear threshold function", and dynamically balances noise suppression and signal fidelity.

[0115] Step 3: Use the adaptive Kalman filter algorithm to perform data fusion on the results after wavelet denoising to obtain the final current information;

[0116] The principle of adaptive Kalman filter data fusion is as follows:

[0117] like Figure 6 As shown, the present invention uses an adaptive Kalman filter algorithm to fuse the dual-loop output. The closed-loop core and the ring array filtered data are used as measurement vectors and input into the state estimation model to complete the recursive filtering update and obtain the final current estimate:

[0118] The state prediction and update process is as follows:

[0119]

[0120] Where: is the prior state estimate, is the posterior state estimate at the previous moment, is the prior state covariance matrix, is the posterior state covariance matrix of the previous moment.

[0121] The update step of the Kalman filter can be expressed as:

[0122]

[0123] Where: K kis the Kalman gain, which determines the weight of the new measurement value and the predicted value in the state update, and its size is mainly affected by Q k and R k impact.

[0124] The present invention realizes cross-modal data fusion strategy: dynamic allocation of dual-loop weights according to real-time current amplitude, low range (I<I 阈值 ) is mainly based on closed-loop iron core, high range (I 阈值 ≤I) is mainly based on a ring array and achieves smooth switching through the suppression factors α and β, solving the problem of "fixed weights leading to range connection errors" in traditional fusion algorithms.

[0125] In summary, this invention successfully achieves high-precision, wide-range, and broadband current detection through an innovative dual-loop TMR nested structure design, combined with a closed-loop feedback mechanism and an adaptive signal processing algorithm. The dual-loop collaborative operation (the core ring optimizes low-range linearity, while the annular TMR array increases measurement range) overcomes the range limitations of traditional sensors; an improved wavelet threshold denoising algorithm significantly enhances signal interference resistance; and an adaptive Kalman filter data fusion strategy further optimizes the reliability and consistency of dual-loop measurement results.

[0126] In order to verify the actual effect of the proposed high-precision and wide-range current detection system based on the dual-ring TMR nested structure, detailed comparative experiments were carried out.

[0127] The experimental equipment included the conductor to be tested, a dual-loop TMR sensor (a closed-loop iron core structure and a ring array structure), and a high-precision data acquisition system. The measured current range was set between 0 and 100A, with the output controlled by a standard calibrated current source. The sensor output signal was collected by an ADC and analyzed on a PC.

[0128] During the experiment, open-loop wavelet, closed-loop wavelet, dual-loop wavelet and Kalman filter fusion schemes were used to process the current signal, and the relative error of each scheme was measured. Figure 8 The comparison curves of measurement errors under different current conditions are shown.

[0129] Depend on Figure 7 It can be seen that under the same experimental conditions, the data fusion scheme of the dual-loop TMR nested structure combined with wavelet denoising and Kalman filtering proposed in the present invention shows obvious advantages. Its measurement error is stably maintained at around 0.1%, which is much lower than the open-loop TMR scheme (the maximum error reaches 0.35%), and is also significantly better than the error performance of the scheme using only the closed-loop TMR structure (the error fluctuates between 0.1% and 0.2%).

[0130] These experimental results clearly demonstrate that the technical solution employed by the present invention significantly improves the accuracy and stability of current measurement, while effectively reducing the impact of environmental noise and magnetic interference on the measurement results. The improvement in measurement accuracy is particularly pronounced under highly dynamic current conditions.

[0131] Example 2:

[0132] The present invention also proposes a current detection system 200 based on a double-ring TMR nested structure, such as Figure 8 Shown, including:

[0133] The detection unit 201 is used for performing dual-loop detection on the current of the conductor to be measured in a current measurement scenario based on a dual-loop TMR system with a dual-loop TMR nested structure;

[0134] A denoising unit 202 is configured to collect dual-loop data obtained by dual-loop detection through AD synchronization, and perform wavelet denoising on the dual-loop data based on the structural data of the dual-loop TMR nested structure;

[0135] The fusion unit 203 is used to fuse the double-loop data after wavelet denoising based on the Kalman filter algorithm to obtain the current information of the conductor to be measured in the current measurement scenario.

[0136] The double-ring TMR nested structure includes a nested structure consisting of a ring core and a ring array, wherein the ring array is nested in the ring core, and the conductor to be tested passes through the center of the ring array.

[0137] Among them, the annular array includes: an annular array TMR current measurement module composed of tunnel magnetoresistance, in which multiple TMR elements are evenly arranged into a circular array with a radius of r, and each TMR element is used to measure the magnetic field component of the conductor to be measured in the tangential direction of the circle.

[0138] Among them, the ring array is used to detect the primary current of the conductor to be tested.

[0139] Among them, the annular iron core is a double-air-gap open iron core structure with a compensation winding, which is used to detect the feedback current of the conductor to be tested and to measure the superimposed magnetic field generated by the primary current and the feedback current.

[0140] The dual-loop data includes: primary current data and feedback current data obtained by detecting the conductor to be tested.

[0141] Among them, permutation entropy is introduced as a regulating factor in the threshold function to construct a continuously differentiable nonlinear threshold function. Based on the continuously differentiable nonlinear threshold function, wavelet denoising is performed on the double-loop data. The expression of the continuously differentiable nonlinear threshold function is as follows:

[0142]

[0143] Among them, λ is the obtained threshold, ω j,k is the wavelet coefficient of the original signal, is the updated wavelet coefficient, P is the adjustment factor with a value range of (0,1), γ is the adjustment constant of the logarithmic function, which is used to prevent the denominator from approaching zero, and e is a very small positive number, which is used to ensure that there are no negative or zero values ​​in the logarithmic function to ensure numerical stability.

[0144] Among them, the fusion strategy for fusing the dual-loop data after wavelet denoising includes:

[0145] The dual-loop weights are dynamically allocated according to the real-time current amplitude, including: in the low range, the weight of the ring core detection data is greater than the weight of the ring array detection data; in the high range, the weight of the ring array detection data is greater than the weight of the ring core detection data, and smooth switching is achieved through the suppression factor during the smoothing process.

[0146] The method of the present invention not only has outstanding advantages in measurement accuracy and anti-interference performance, but also has a wide measurement range and stable linearity performance. It can be widely used in complex electromagnetic environments such as new energy grid connection, electric vehicle charging piles and smart grids that require high current detection accuracy.

[0147] Example 3:

[0148] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of the method in the above embodiment.

[0149] Example 4:

[0150] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It can be understood that the computer-readable storage medium here can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space that stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space. These instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiment.

[0151] It will be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention may be implemented in various computer languages, for example, the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0152] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0153] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0154] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0155] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0156] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A current detection method based on a double-ring TMR nested structure, characterized in that: include: The dual-loop TMR system based on the dual-loop tunnel magnetoresistance (TMR) structure performs dual-loop detection on the current of the conductor under test in current measurement scenarios. Acquire dual-loop data obtained by dual-loop detection through AD synchronization, and perform wavelet denoising on the dual-loop data based on the structural data of the dual-loop TMR nested structure; Based on the Kalman filter algorithm, the double-loop data after wavelet denoising is fused to obtain the current information of the conductor to be measured in the current measurement scenario.

2. The current detection method according to claim 1, characterized in that: The dual-ring TMR nested structure includes a nested structure consisting of a ring core and a ring array, wherein the ring array is nested in the ring core, and the conductor to be tested passes through the center of the ring array.

3. The current detection method according to claim 2, characterized in that: The annular array includes: an annular array TMR current measurement module composed of tunnel magnetoresistance, in which multiple TMR elements are evenly arranged into a circular array with a radius of r, and each TMR element is used to measure the magnetic field component of the conductor to be measured in the tangential direction of the circle.

4. The current detection method according to claim 2, wherein: The annular array is used to detect the primary current of the conductor to be tested.

5. The current detection method according to claim 2, characterized in that: The annular iron core is a double-gap open iron core structure with a compensation winding, which is used to detect the feedback current of the conductor to be tested and to measure the superimposed magnetic field generated by the primary current and the feedback current.

6. The current detection method according to claim 1, characterized in that: The dual-loop data includes: primary current data and feedback current data obtained by detecting the conductor to be tested.

7. The current detection method according to claim 1, characterized in that: Permutation entropy is introduced as a regulating factor in the threshold function to construct a continuously differentiable nonlinear threshold function. Based on the continuously differentiable nonlinear threshold function, wavelet denoising is performed on the dual-loop data. The expression of the continuously differentiable nonlinear threshold function is as follows: Among them, λ is the obtained threshold, ω j,k is the wavelet coefficient of the original signal, is the updated wavelet coefficient, P is the adjustment factor with a value range of (0,1), γ is the adjustment constant of the logarithmic function, which is used to prevent the denominator from approaching zero, and e is a very small positive number, which is used to ensure that there are no negative or zero values ​​in the logarithmic function to ensure numerical stability.

8. The current detection method according to claim 1, wherein: The fusion strategy for fusing the dual-loop data after wavelet denoising includes: The dual-loop weights are dynamically allocated according to the real-time current amplitude, including: in the low range, the weight of the ring core detection data is greater than the weight of the ring array detection data; in the high range, the weight of the ring array detection data is greater than the weight of the ring core detection data, and smooth switching is achieved through the suppression factor during the smoothing process.

9. A current detection system based on a dual-ring TMR nested structure, characterized in that: include: The detection unit is used in a dual-loop TMR system based on a dual-loop TMR nested structure to perform dual-loop detection on the current of the conductor to be measured in a current measurement scenario; a denoising unit, configured to collect dual-loop data obtained by dual-loop detection through AD synchronization, and perform wavelet denoising on the dual-loop data according to the structural data of the dual-loop TMR nested structure; The fusion unit is used to fuse the double-loop data after wavelet denoising based on the Kalman filter algorithm to obtain the current information of the conductor to be measured in the current measurement scenario.

10. The current detection system according to claim 9, characterized in that: The dual-ring TMR nested structure includes a nested structure consisting of a ring core and a ring array, wherein the ring array is nested in the ring core, and the conductor to be tested passes through the center of the ring array.

11. The current detection system according to claim 10, characterized in that: The annular array includes: an annular array TMR current measurement module composed of tunnel magnetoresistance, in which multiple TMR elements are evenly arranged into a circular array with a radius of r, and each TMR element is used to measure the magnetic field component of the conductor to be measured in the tangential direction of the circle.

12. The current detection system according to claim 10, characterized in that: The annular array is used to detect the primary current of the conductor to be tested.

13. The current detection system according to claim 10, characterized in that: The annular core is a double-gap open core structure with a compensation winding, which is used to detect the feedback current of the conductor to be tested and to measure the superimposed magnetic field generated by the primary current and the feedback current.

14. The current detection system according to claim 9, characterized in that: The dual-loop data includes: primary current data and feedback current data obtained by detecting the conductor to be tested.

15. The current detection system according to claim 9, characterized in that: Permutation entropy is introduced as a regulating factor in the threshold function to construct a continuously differentiable nonlinear threshold function. Based on the continuously differentiable nonlinear threshold function, wavelet denoising is performed on the dual-loop data. The expression of the continuously differentiable nonlinear threshold function is as follows: Among them, λ is the obtained threshold, ω j,k is the wavelet coefficient of the original signal, is the updated wavelet coefficient, P is the adjustment factor with a value range of (0,1), γ is the adjustment constant of the logarithmic function, which is used to prevent the denominator from approaching zero, and e is a very small positive number, which is used to ensure that there are no negative or zero values ​​in the logarithmic function to ensure numerical stability.

16. The current detection system according to claim 9, characterized in that: The fusion strategy for fusing the dual-loop data after wavelet denoising includes: The dual-loop weights are dynamically allocated according to the real-time current amplitude, including: in the low range, the weight of the ring core detection data is greater than the weight of the ring array detection data; in the high range, the weight of the ring array detection data is greater than the weight of the ring core detection data, and smooth switching is achieved through the suppression factor during the smoothing process.

17. A computer device, characterized in that: include: one or more processors; a processor for executing one or more programs; When the one or more programs are executed by the one or more processors, the method according to any one of claims 1 to 8 is implemented.

18. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1 to 8 is implemented.

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