Miniature high-sensitivity magnetic field sensor and preparation method thereof

Abstract

The invention relates to the technical field of magnetic induction, and discloses a miniature high-sensitivity magnetic field sensor and a preparation method thereof.The miniature high-sensitivity magnetic field sensor comprises a plurality of sensing detection miniature probes and a sensitivity correction processor, and the sensing detection miniature probes are used for obtaining detected magnetic field signals; a detected magnetic field signal is sent to the sensitivity correction processor; the sensitivity correction processor is used for calculating at least one deviation signal according to the magnetic field signals detected by the plurality of sensing detection miniature probes, and is also used for calculating at least two correction signals of each deviation signal according to the magnetic field signals detected by the plurality of sensing detection miniature probes; and the sensitivity correction processor is also used for calculating and selecting at least one correct correction signal according to the at least two correction signals of each deviation signal and the magnetic field intensity distribution rule.

Description

Technical Field

[0001] The invention belongs to the field of magnetic induction technology, and in particular relates to a miniature high-sensitivity magnetic field sensor and a preparation method thereof. Background Art

[0002] In the current technological context, miniature high-sensitivity magnetic field sensors play a vital role in many fields such as biomedicine, geological exploration, aerospace and automatic control. They are widely used to monitor changes in weak magnetic fields to achieve precise positioning, navigation, material detection and other functions. However, while pursuing higher sensitivity, existing magnetic field sensor technology faces several key challenges that limit its performance and application scope:

[0003] Accuracy and stability issues: Traditional single-point magnetic field sensors are easily affected by environmental factors such as temperature fluctuations, electromagnetic interference, and mechanical vibration, which lead to large errors and instability in the measurement results. These errors are particularly significant when the magnetic field strength is weak or high-resolution measurement is required.

[0004] Individual differences in sensors: Even sensors from the same batch have subtle differences in performance due to manufacturing tolerances and material inhomogeneities, which makes it difficult to directly merge data in multi-sensor array applications, affecting overall measurement accuracy. Insufficient adaptability to complex magnetic field environments: In complex or non-uniform magnetic field environments, a single sensor cannot accurately distinguish between background magnetic fields and target signals, and is sensitive to local magnetic field disturbances, which can easily lead to misjudgments.

[0005] Limitations of data processing algorithms: Existing algorithms often focus on simple signal amplification or filtering. They lack advanced algorithms for multi-sensor data fusion to effectively identify and correct measurement deviations and fail to fully utilize the potential advantages of sensor arrays. Summary of the invention

[0006] The basic concept of the technical solution adopted in the present invention is:

[0007] A miniature high-sensitivity magnetic field sensor, comprising a plurality of sensing detection microprobes and a sensitivity correction processor, wherein the sensing detection microprobes are used to obtain detected magnetic field signals and send the detected magnetic field signals to the sensitivity correction processor; the sensitivity correction processor is used to calculate at least one deviation signal according to the magnetic field signals detected by the plurality of sensing detection microprobes, and the sensitivity correction processor is also used to calculate at least two correction signals for each deviation signal according to the magnetic field signals detected by the plurality of sensing detection microprobes;

[0008] The sensitivity correction processor is also used to calculate and select at least one correct correction signal based on at least two correction signals of each deviation signal and the distribution law of magnetic field intensity, and the correction signal is used to correct the sensor sensitivity.

[0009] As a preferred embodiment of the present invention, the sensing detection micro probe adopts a Hall effect sensor, a magnetoresistive element, or an optical fiber magneto-optical Kerr effect sensor.

[0010] As a preferred embodiment of the present invention, the sensitivity correction processor adopts a microcontroller / microprocessor or a DSP.

[0011] As a preferred embodiment of the present invention, the specific process of "calculating at least one deviation signal based on magnetic field signals detected by multiple sensing micro-probes" includes the following steps:

[0012] All the sensing micro-probes measure the magnetic field strength under the same magnetic field environment simultaneously or in sequence within a preset time; and record the magnetic field strength value detected by each sensing micro-probe;

[0013] The magnetic field strength values ​​of all sensing detection microprobes are averaged to obtain a representative magnetic field strength estimate; for each sensing detection microprobe's measured value, the difference between it and the average magnetic field strength is calculated. If the difference between the measured value of a certain sensing detection microprobe and the average value exceeds a preset threshold, it is considered that the measured value of the sensing detection microprobe constitutes a "deviation signal".

[0014] As a preferred embodiment of the present invention, in the process of calculating at least two correction signals for each deviation signal based on the magnetic field signals detected by multiple sensing detection microprobes, for each deviation signal, the measurement values ​​of other sensing detection microprobes relative to the deviation signal are first determined, and the measurement values ​​of the sensing detection microprobes adjacent to and symmetrically located with the sensing detection microprobe generating the deviation signal are selected; the measurement values ​​of the sensing detection microprobes adjacent to and symmetrically located with the sensing detection microprobe generating the deviation signal are directly used as the correction signal, or the weighted average of "the measurement values ​​of the sensing detection microprobes adjacent to the sensing detection microprobe generating the deviation signal" and the weighted average of "the measurement values ​​of the sensing detection microprobes symmetrically located with the sensing detection microprobe generating the deviation signal" are used as the correction signal.

[0015] As a preferred embodiment of the present invention, at least one correct correction signal is selected based on at least two correction signals of each deviation signal and the distribution law of magnetic field intensity. The correction signal is used in the specific process of correcting the sensor sensitivity. In combination with the magnetic field distribution model, the consistency of each correction signal with the theoretical model is evaluated, and the magnetic field distribution model is interpolated or fitted to match the actual probe layout and measurement points. At least one correction signal with the best consistency with the theoretical model is selected as the correct correction signal.

[0016] Combined with the magnetic field distribution model, the consistency of each correction signal with the theoretical model is evaluated, the magnetic field distribution model is interpolated or fitted to match the actual probe layout and measurement points, and at least one correction signal with the best consistency with the theoretical model is selected as the correct correction signal. Specifically, it includes:

[0017] Establish the theoretical magnetic field distribution function B th (x, y, z), this function describes the distribution of the magnetic field in space under ideal conditions, where (x, y, z) represents the spatial coordinates; for each sensing microprobe, let its position be (x i ,y i , z j ), the measured magnetic field strength is B meas，i For each sensing microprobe, the deviation signal is defined as ΔB i =B meas，i -B avg , where B avg is the average of all probe measurements;

[0018] For the deviation signal ΔB i , at least two correction signals have been calculated and Specifically, it is the measurement value of adjacent and symmetrical probes or its weighted average;

[0019] Use interpolation or fitting in the theoretical magnetic field distribution model B th Find or generate the theoretical magnetic field strength value B corresponding to each probe position on (x, y, z) th，i ;

[0020] For each deviation signal corresponding to the correction signal Calculate its difference with the theoretical value B th，i The difference measure of

[0021] The residual sum of squares is used Or the absolute error For each deviation signal, compare the error metrics corresponding to the two correction signals or The correction signal with the smallest error is selected as the "correct correction signal", that is, or

[0022] The method for preparing a micro high-sensitivity magnetic field sensor comprises the following steps:

[0023] Choose Hall effect sensors, magnetoresistive elements, fiber optic magneto-optical Kerr effect sensors, and choose microcontrollers / microprocessors or DSPs to write customized firmware to achieve the following functions:

[0024] Implement synchronous or sequential control logic to ensure that all probes collect data at the same time or in a predetermined sequence to ensure the time consistency of the data; automatically identify and record deviation signals; implement the calculation logic of correction signals, including the direct use or weighted average of adjacent and symmetrical probe measurement values; combine the magnetic field distribution model to perform data fitting and interpolation, evaluate the consistency of the correction signal with the theoretical model, and automatically select the optimal correction signal.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] The theoretical magnetic field distribution model is tightly coupled with the actual measurement data, and the most suitable theoretical magnetic field strength value is matched for each measurement point within the theoretical framework through interpolation or fitting technology. Furthermore, by calculating the residual sum of squares or absolute error between the correction signal and the theoretical value, the system automatically selects the correction signal that is most consistent with the theoretical model as the final correction basis to optimize the measurement results. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of the method for preparing a micro high-sensitivity magnetic field sensor of the present application. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. The following embodiments are used to illustrate the present invention. The micro high-sensitivity magnetic field sensor disclosed in the present application includes multiple sensing detection micro probes and a sensitivity calibration processor. The sensing detection micro probe can use the following specific hardware in the application:

[0029] Hall effect sensor: Due to its small size, fast response speed and high sensitivity, it is suitable for detecting weak magnetic fields. The sensing detection micro probe can choose the highly sensitive CMOSA130250X series or similar micro Hall effect sensors.

[0030] Magnetoresistive elements (GMR or AMR): Giant magnetoresistive or anisotropic magnetoresistive elements have higher sensitivity and better temperature stability, suitable for precise measurement. Sensing detection microprobes can use magnetoresistive sensor elements such as TMR, which can provide high-resolution magnetic field measurement in a small volume.

[0031] Fiber-optic magneto-optic Kerr effect sensor: Fiber-optic magneto-optic Kerr effect sensor uses optical fiber to transmit light signals, is not subject to electromagnetic interference, has high sensitivity and long-distance transmission capability. The sensing detection micro probe can choose an integrated fiber Bragg grating magneto-optic Kerr sensor.

[0032] The sensitivity correction processor can use the following specific hardware in the application:

[0033] Microcontroller / microprocessor: ARM Cortex-M series (such as STM32 / STM32, STM32L4) or ESP32 series, with powerful processing capabilities, suitable for real-time data processing and complex algorithm operations.

[0034] DSP (digital signal processor): designed for high-speed, large-volume data processing, such as TI's TMS328x series, suitable for fast signal filtering and correction calculations.

[0035] The sensing detection microprobe is used to obtain the detected magnetic field signal and send the detected magnetic field signal to the sensitivity calibration processor;

[0036] The sensitivity correction processor is used to calculate at least one deviation signal according to the magnetic field signals detected by the plurality of sensing detection micro-probes,

[0037] "Deviation signal" refers to a signal that deviates significantly from the expected or average magnetic field strength value. This deviation may be caused by local magnetic field disturbances, individual differences in sensors, noise interference or other non-ideal factors. The specific process of "calculating at least one deviation signal based on magnetic field signals detected by multiple sensing microprobes" includes the following steps:

[0038] 1. Data Collection

[0039] Synchronous measurement: All sensor detection microprobes measure the magnetic field strength in the same magnetic field environment simultaneously or sequentially within a preset time to ensure the temporal and spatial consistency of the data.

[0040] The magnetic field strength values ​​detected by each sensing microprobe are recorded, which may contain noise and measurement errors.

[0041] 2. Mean calculation

[0042] Calculate the average magnetic field strength: Average the magnetic field strength values ​​from all the sensing microprobes to get a representative estimate of the magnetic field strength. This average should theoretically be closer to the true magnetic field strength because it reduces the impact of random errors.

[0043] 3. Difference Analysis

[0044] Deviation identification: For each sensor detection microprobe's measurement value, calculate its difference (deviation) from the average magnetic field strength. If the difference between the measurement value of a sensor detection microprobe and the average value exceeds a preset threshold), the measurement value of the sensor detection microprobe is considered to constitute a "deviation signal."

[0045] The sensitivity correction processor is also used to calculate at least two correction signals for each deviation signal based on the magnetic field signals detected by multiple sensing detection microprobes; in the process of calculating at least two correction signals for each deviation signal based on the magnetic field signals detected by multiple sensing detection microprobes, specifically, for each deviation signal, the measurement values ​​of other sensing detection microprobes relative to the deviation signal are first determined, and the measurement values ​​of the sensing detection microprobes adjacent to and symmetrically located with the sensing detection microprobe generating the deviation signal are selected, and the measurement values ​​of the sensing detection microprobes adjacent to and symmetrically located with the sensing detection microprobe generating the deviation signal are directly used as the correction signal, or the weighted average value of "the measurement values ​​of the sensing detection microprobes adjacent to the sensing detection microprobe generating the deviation signal" and the weighted average value of "the measurement values ​​of the sensing detection microprobes symmetrically located with the sensing detection microprobe generating the deviation signal" are used as the correction signal;

[0046] The sensitivity correction processor is also used to calculate and select at least one correct correction signal according to at least two correction signals of each deviation signal and the magnetic field intensity distribution law, and the correction signal is used to correct the sensor sensitivity;

[0047] At least one correct correction signal is selected based on at least two correction signals of each deviation signal and the magnetic field intensity distribution law. The correction signal is used to correct the sensor sensitivity. In the specific process, the consistency of each correction signal with the theoretical model is evaluated in combination with the magnetic field distribution model, and the magnetic field distribution model is interpolated or fitted to match the actual probe layout and measurement points. At least one correction signal with the best consistency with the theoretical model is selected as the correct correction signal, specifically:

[0048] 1. Establishment of magnetic field distribution model

[0049] Establish the theoretical magnetic field distribution function B th (x, y, z), this function describes the distribution of magnetic field in space under ideal conditions, where (x, y, z) represents the spatial coordinates;

[0050] 2. Measured data and deviation signals

[0051] For each sensing microprobe, let its position be (x i ,y i , z i ), the measured magnetic field strength is B meas，i For each sensing microprobe, the deviation signal is defined as ΔB i =B meas，i -B avg , where B avg is the average of all probe measurements;

[0052] 3. Correction signal selection and evaluation

[0053] For the deviation signal ΔB i , at least two correction signals have been calculated and Specifically, it is the measurement value of adjacent and symmetrical probes or its weighted average;

[0054] 4. Model matching and consistency assessment

[0055] Interpolation / fitting: Use interpolation or fitting to calculate the theoretical magnetic field distribution model B. th Find or generate the theoretical magnetic field strength value B corresponding to each probe position on (x, y, z) th，i ;

[0056] Consistency assessment: For each deviation signal corresponding to the correction signal

[0057] Calculate its difference with the theoretical value B th，i The difference measure of

[0058] The residual sum of squares is used Or the absolute error

[0059] 5. Optimal correction signal selection

[0060] For each deviation signal, compare the error metrics corresponding to the two correction signals or Select the correction signal with the smallest error as the "correct correction signal" or

[0061] The mathematical expression of the example is as follows:

[0062] Known theoretical model B th (x, y, z) = B0·f(x, y, z), where f(x, y, z) is a position-dependent function, B o is a constant; for the deviation signal ΔB i , the correction signal and Calculate the theoretical value B th，i =B0·f(x i ,y i , z i )choose The mathematical expression can be summarized as: Through this process, combining theoretical models with actual measurements, accurate correction of deviation signals is achieved, improving the measurement accuracy and reliability of the miniature high-sensitivity magnetic field sensor.

[0063] The technical effects of this application are summarized as follows:

[0064] Multi-source fusion and deviation identification: The sensor array uses a variety of technologies such as Hall effect sensors, magnetoresistive elements, and fiber-optic magneto-optical Kerr effect sensors to ensure wide-spectrum, high-sensitivity magnetic field detection capabilities. Through synchronous or sequential measurements, the system can capture the instant response of each probe under the same magnetic field conditions, and then identify the "deviation signal" caused by local disturbances, equipment differences, or environmental noise based on big data, which is the first step to improve measurement accuracy.

[0065] Intelligent correction algorithm: The core lies in its unique deviation signal correction mechanism, which not only calculates at least one deviation signal, but also generates at least two candidate correction signals for each deviation signal. This is based on the measurement values ​​of adjacent and symmetrical probes or their weighted average, cleverly utilizing the symmetry and proximity advantages of the probe layout, and correcting the deviation with physically adjacent reliable measurement values, significantly enhancing the adaptive correction capability of the data.

[0066] Combination of theoretical model and practical optimization: The highlight of the technical solution is to closely couple the theoretical magnetic field distribution model with the actual measurement data, and match the most suitable theoretical magnetic field strength value for each measurement point within the theoretical framework through interpolation or fitting technology. Furthermore, by calculating the residual sum of squares or absolute error between the correction signal and the theoretical value, the system automatically selects the correction signal that is most consistent with the theoretical model as the final correction basis. This dynamic optimization process ensures the scientificity and effectiveness of the correction, and significantly reduces the error introduced by the non-ideal factors of the sensor.

[0067] Improve measurement accuracy and reliability: The implementation of the entire technical solution, from hardware selection to software algorithm design, revolves around improving the accuracy and reliability of magnetic field measurement. Through the above multi-level and multi-dimensional signal processing and correction strategies, external interference is effectively suppressed and the measurement results are optimized, so that the micro high-sensitivity magnetic field sensor can provide more accurate and stable magnetic field information in scientific research, medical testing, industrial monitoring and other fields, meeting the growing demand for high-precision magnetic field measurement.

[0068] This application also discloses a method for preparing a micro high-sensitivity magnetic field sensor, referring to Figure 1 , including the steps of:

[0069] 1. Microprobe array design and integration

[0070] Design and selection: First, carefully design the layout of the sensor detection micro-probe array according to the application scenario requirements. Select the appropriate type of Hall effect sensor, GMR / AMR magnetoresistive element, and fiber magneto-optical Kerr effect sensor to achieve wide-spectrum and high-sensitivity magnetic field detection capabilities. For example, for the needs of weak magnetic field detection, high-sensitivity CMOSA130250X series Hall effect sensors or TMR magnetoresistive sensor elements are given priority.

[0071] 2. Sensitivity correction processor development and programming

[0072] Hardware configuration: Select a high-performance microcontroller / microprocessor (such as the STM32 series) or DSP (such as the TI TMS328x series), and customize the hardware platform according to the processing speed and power consumption requirements to ensure efficient operation of real-time data analysis and correction algorithms.

[0073] Write customized firmware to achieve the following functions:

[0074] Synchronous data acquisition: Programming implements synchronization or sequential control logic to ensure that all probes collect data at the same time or in a predetermined sequence to ensure the time consistency of the data.

[0075] Deviation signal recognition: Automatically recognize and record deviation signals.

[0076] Correction signal calculation: Implement the calculation logic of the correction signal, including direct adoption or weighted averaging of adjacent and symmetrical probe measurement values.

[0077] Model matching: Combine the magnetic field distribution model to perform data fitting and interpolation, evaluate the consistency of the correction signal with the theoretical model, and automatically select the optimal correction signal.

[0078] 3. Construction and optimization of magnetic field distribution model

[0079] Theoretical model establishment: Establish a magnetic field distribution model and adjust the model parameters according to the actual sensor array layout to ensure that the model is highly consistent with the actual application scenario.

Claims

1. A miniature high-sensitivity magnetic field sensor, characterized in that: It includes a plurality of sensing detection micro-probes and a sensitivity correction processor, wherein the sensing detection micro-probes are used to obtain detected magnetic field signals and send the detected magnetic field signals to the sensitivity correction processor; The sensitivity correction processor is used to calculate at least one deviation signal based on the magnetic field signals detected by the plurality of sensing detection micro-probes, and the sensitivity correction processor is also used to calculate at least two correction signals for each deviation signal based on the magnetic field signals detected by the plurality of sensing detection micro-probes; The sensitivity correction processor is also used to calculate and select at least one correct correction signal based on at least two correction signals of each deviation signal and the distribution law of magnetic field intensity, and the correction signal is used to correct the sensor sensitivity.

2. The miniature high-sensitivity magnetic field sensor according to claim 1, characterized in that: The sensing detection micro probe adopts Hall effect sensor, magnetoresistive element, and optical fiber magneto-optical Kerr effect sensor.

3. The miniature high-sensitivity magnetic field sensor according to claim 1, characterized in that: The sensitivity correction processor adopts a microcontroller / microprocessor and a DSP.

4. The miniature high-sensitivity magnetic field sensor according to claim 1, characterized in that: The specific process of "calculating at least one deviation signal based on magnetic field signals detected by multiple sensing microprobes" includes the following steps: All the sensing micro-probes measure the magnetic field strength under the same magnetic field environment simultaneously or in sequence within a preset time; and record the magnetic field strength value detected by each sensing micro-probe; The magnetic field strength values ​​of all sensing detection microprobes are averaged to obtain a representative magnetic field strength estimate; for each sensing detection microprobe's measured value, the difference between it and the average magnetic field strength is calculated. If the difference between the measured value of a sensing detection microprobe and the average value exceeds a preset threshold, it is considered that the measured value of the sensing detection microprobe constitutes a "deviation signal".

5. The miniature high-sensitivity magnetic field sensor according to claim 1, characterized in that: In the process of calculating at least two correction signals for each deviation signal based on the magnetic field signals detected by multiple sensing detection microprobes, specifically, for each deviation signal, the measurement values ​​of other sensing detection microprobes relative to the deviation signal are first determined, and the measurement values ​​of the sensing detection microprobes adjacent to and symmetrically located with the sensing detection microprobe generating the deviation signal are selected; the measurement values ​​of the sensing detection microprobes adjacent to and symmetrically located with the sensing detection microprobe generating the deviation signal are directly used as the correction signal; or the weighted average of "the measurement values ​​of the sensing detection microprobes adjacent to the sensing detection microprobe generating the deviation signal" and the weighted average of "the measurement values ​​of the sensing detection microprobes symmetrically located with the sensing detection microprobe generating the deviation signal" are used as the correction signal.

6. The miniature high-sensitivity magnetic field sensor according to claim 1, characterized in that: At least one correct correction signal is selected based on at least two correction signals of each deviation signal and the distribution law of magnetic field intensity. The correction signal is used in the specific process of correcting the sensor sensitivity. In combination with the magnetic field distribution model, the consistency of each correction signal with the theoretical model is evaluated, and the magnetic field distribution model is interpolated or fitted to match the actual probe layout and measurement points. At least one correction signal with the best consistency with the theoretical model is selected as the correct correction signal.

7. The miniature high-sensitivity magnetic field sensor according to claim 6, characterized in that: Combined with the magnetic field distribution model, the consistency of each correction signal with the theoretical model is evaluated, the magnetic field distribution model is interpolated or fitted to match the actual probe layout and measurement points, and at least one correction signal with the best consistency with the theoretical model is selected as the correct correction signal. Specifically, it includes: Establish the theoretical magnetic field distribution function B th (x, y, z), this function describes the distribution of the magnetic field in space under ideal conditions, where (X, y, Z) represents the spatial coordinates; for each sensing microprobe, let its position be (x i ,y i , z i ), the measured magnetic field strength is B meas,i ,For each sensing microprobe, the deviation signal is defined as ΔB i =B meas，i -B avg , where B avg is the average of all probe measurements; For the deviation signal ΔB i , at least two correction signals have been calculated and Specifically, it is the measurement value of adjacent and symmetrical probes or its weighted average; Use interpolation or fitting in the theoretical magnetic field distribution model B th Find or generate the theoretical magnetic field strength value B corresponding to each probe position on (x, y, z) th,i ; For each deviation signal corresponding to the correction signal Calculate its difference with the theoretical value B th,i The difference measure of The residual sum of squares is used Or the absolute error For each deviation signal, compare the error metrics corresponding to the two correction signals or Select the correction signal with the smallest error as the "correct correction signal", that is, or 8. The method for preparing a micro high-sensitivity magnetic field sensor according to claim 1, characterized in that: Includes steps: Choose Hall effect sensors, magnetoresistive elements, fiber optic magneto-optical Kerr effect sensors, and choose microcontrollers / microprocessors or DSPs to write customized firmware to achieve the following functions: Implement synchronous or sequential control logic to ensure that all probes collect data at the same time or in a predetermined sequence to ensure the time consistency of the data; automatically identify and record deviation signals; implement the calculation logic of correction signals, including the direct use or weighted average of adjacent and symmetrical probe measurement values; combine the magnetic field distribution model to perform data fitting and interpolation, evaluate the consistency of the correction signal with the theoretical model, and automatically select the optimal correction signal.

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