Magnetic Field Measurement Method and Magnetic Field Measurement Device Based on Orthogonal Basis Mode Fluxgate Circuit

Abstract

The present application relates to a magnetic field measurement method and a magnetic field measurement device based on an orthogonal fundamental mode fluxgate circuit. The method detects a first output voltage signal output by a feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, a first excitation voltage signal output by a constant current power amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, the phase information of a first induction signal output by a preamplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, and a first external temperature information output by a temperature sensor at the current moment. Then, the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information are optimized to obtain an optimal target output voltage signal, and the target magnetic field value is determined according to the target output voltage signal. By combining multiple data for signal optimization processing, the above method can improve the measurement accuracy of the magnetic field.

Description

Technical Field

[0001] The present application relates to the technical field of magnetic field measurement, and in particular, to a magnetic field measurement method and a magnetic field measurement device based on an orthogonal fundamental mode fluxgate circuit. Background Technique

[0002] The geomagnetic field is a basic physical field that has existed on the earth for a long time. Detecting the magnetic field under the geomagnetic field can find ferromagnetic signal anomalies under the geological layer, etc., and can be used for positioning and navigation, geological resource exploration, space science research, and natural disaster monitoring and early warning. Among them, the detection of small target magnetic field signals is an important branch, which can locate and image small magnetic substances buried underground, pipeline cracks and other defects, and then eliminate potential hazards. Observing small-signal magnetic fields under the background of the geomagnetic field requires sensors to have a large dynamic magnetic field measurement range and excellent low-frequency vector magnetic field measurement capabilities. The fundamental wave orthogonal fluxgate sensor has the advantages of high sensitivity, good directivity, high resolution, and only a single coil and simple structure, and is commonly used for magnetic field measurement.

[0003] However, the method of using a fundamental wave orthogonal fluxgate sensor for magnetic field measurement recorded in the related art has the problem of inaccurate measurement. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a magnetic field measurement method and a magnetic field measurement device based on an orthogonal fundamental mode fluxgate circuit that can improve the accuracy of magnetic field measurement.

[0005] In a first aspect, the present application provides a magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit, which is applied to an orthogonal fundamental mode fluxgate circuit. The method includes:

[0006] Detecting a first output voltage signal output by a feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, a first excitation voltage signal output by a constant current power amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, the phase information of a first induction signal output by a pre-amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, and detecting a first external temperature information output by a temperature sensor at the current moment;

[0007] Performing optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal, and determining a target magnetic field value according to the target output voltage signal.

[0008] In some embodiments, performing optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal includes:

[0009] Obtain a preset state prediction model and a preset state observation model;

[0010] Input the estimated data and the estimated covariance at the previous moment into the preset state prediction model for prediction, to obtain the predicted data and the predicted covariance at the current moment;

[0011] Input the predicted data at the current moment, the predicted covariance at the current moment, and the observed data at the current moment into the preset state observation model for estimation, to obtain the estimated data and the estimated covariance at the current moment; the observed data at the current moment includes the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information;

[0012] Determine the target output voltage signal according to the estimated data at the current moment.

[0013] In some embodiments, the preset state prediction model includes a state prediction sub-model and a covariance prediction sub-model. Inputting the estimated data and the estimated covariance at the previous moment into the preset state model for prediction to obtain the predicted data and the predicted covariance at the current moment includes:

[0014] Input the estimated data at the previous moment into the state prediction sub-model for prediction to obtain the predicted data at the current moment;

[0015] Input the estimated covariance at the previous moment into the covariance prediction sub-model for prediction to obtain the predicted covariance at the current moment.

[0016] In some embodiments, the preset state observation model includes a gain estimation sub-model, an observation sub-model, and a covariance estimation sub-model. Inputting the predicted data at the current moment, the predicted covariance at the current moment, and the observed data at the current moment into the preset state observation model for estimation to obtain the estimated data and the estimated covariance at the current moment includes:

[0017] Input the predicted covariance at the current moment into the gain estimation sub-model for estimation to obtain the estimated gain at the current moment;

[0018] Input the estimated gain at the current moment, the predicted data at the current moment, and the observed data at the current moment into the observation sub-model for observation to obtain the estimated data at the current moment;

[0019] Input the predicted covariance at the current moment into the covariance estimation sub-model for estimation to obtain the estimated covariance at the current moment.

[0020] In some embodiments, determining the target output voltage signal according to the estimated data at the current moment includes:

[0021] Determine whether the current iteration count reaches a preset count, or whether the estimated covariance at the current moment satisfies a preset optimal condition;

[0022] If the current iteration count does not reach the preset count and the estimated covariance at the current moment does not satisfy the preset optimal condition, then use the estimated data at the current moment as the new estimated data at the previous moment, and use the estimated covariance at the current moment as the new estimated covariance at the previous moment, and return to execute the step of inputting the estimated data and the estimated covariance at the previous moment into a preset state prediction model for prediction to obtain the predicted data and the predicted covariance at the current moment;

[0023] If the current iteration count reaches the preset count or the estimated covariance at the current moment satisfies the preset optimal condition, then determine the value of the estimated output voltage signal at the current moment in the estimated data at the current moment as the target output voltage.

[0024] In some embodiments, determining the target magnetic field value according to the target output voltage signal includes:

[0025] Obtain a preset mapping relationship; the preset mapping relationship is the corresponding relationship between voltage and magnetic field;

[0026] Determine the target magnetic field value according to the preset mapping relationship and the value of the target output voltage signal.

[0027] In a second aspect, the present application also provides a magnetic field measurement device, which includes a fluxgate circuit, an analog-to-digital converter, a processor, and a temperature sensor; the fluxgate circuit includes a constant current power supply, a magnetic core model, a preamplifier, a fundamental wave demodulator, a low-pass filter, and a feedback integrator; the constant current power supply is connected to the magnetic core in the magnetic core model, the induction coil in the magnetic core model is connected to the preamplifier and the feedback integrator, the preamplifier is also connected to the fundamental wave demodulator, the fundamental wave demodulator is connected to the low-pass filter, and the low-pass filter is connected to the feedback integrator; the analog-to-digital converter is connected to the temperature sensor, the constant current power supply, the preamplifier, the feedback integrator in the fluxgate circuit, and the processor;

[0028] The fluxgate circuit is configured to output the phase information of the first output voltage signal, the first excitation voltage signal, and the first induction signal according to the input controllable sine signal and the periodic flip bias signal;

[0029] An analog-to-digital converter is used to perform analog-to-digital conversion on the phase information of the first output voltage signal, the first excitation voltage signal, the first induction signal, and the first external temperature information output by the temperature sensor, and input the state data after the analog-to-digital conversion into the processor; the state data after the analog-to-digital conversion includes the first output voltage signal after the analog-to-digital conversion, the first excitation voltage signal after the analog-to-digital conversion, the phase information of the first induction signal after the analog-to-digital conversion, and the first external temperature information after the analog-to-digital conversion and input them into the processor;

[0030] A processor is used to execute the steps of the method in any one of the above first aspects according to the state data after the analog-to-digital conversion.

[0031] In a third aspect, the present application further provides a magnetic field measurement device based on an orthogonal basis-mode fluxgate circuit, and the device includes:

[0032] A detection module is used to detect the first output voltage signal output by the feedback integrator in the orthogonal basis-mode fluxgate circuit at the current moment, the first excitation voltage signal output by the constant current power amplifier in the orthogonal basis-mode fluxgate circuit at the current moment, the phase information of the first induction signal output by the preamplifier in the orthogonal basis-mode fluxgate circuit at the current moment, and the first external temperature information output by the detection temperature sensor at the current moment;

[0033] An optimization module is used to perform optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal, and determine a target magnetic field value according to the target output voltage signal.

[0034] In a fourth aspect, the present application further provides a computer device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0035] Detect the first output voltage signal output by the feedback integrator in the orthogonal basis-mode fluxgate circuit at the current moment, the first excitation voltage signal output by the constant current power amplifier in the orthogonal basis-mode fluxgate circuit at the current moment, the phase information of the first induction signal output by the preamplifier in the orthogonal basis-mode fluxgate circuit at the current moment, and the first external temperature information output by the detection temperature sensor at the current moment;

[0036] Perform optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal, and determine a target magnetic field value according to the target output voltage signal.

[0037] Fifth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0038] Detect the first output voltage signal output by the feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, the first excitation voltage signal output by the constant current power supply in the orthogonal fundamental mode fluxgate circuit at the current moment, the phase information of the first induction signal output by the preamplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, and detect the first external temperature information output by the temperature sensor at the current moment;

[0039] Perform optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal, and determine the target magnetic field value according to the target output voltage signal.

[0040] Sixth aspect, the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0041] Detect the first output voltage signal output by the feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, the first excitation voltage signal output by the constant current power supply in the orthogonal fundamental mode fluxgate circuit at the current moment, the phase information of the first induction signal output by the preamplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, and detect the first external temperature information output by the temperature sensor at the current moment;

[0042] Perform optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal, and determine the target magnetic field value according to the target output voltage signal.

[0043] The above-mentioned magnetic field measurement method and magnetic field measurement device based on an orthogonal fundamental mode fluxgate circuit. This method detects the first output voltage signal output by the feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, the first excitation voltage signal output by the constant current power supply in the orthogonal fundamental mode fluxgate circuit at the current moment, the phase information of the first induction signal output by the pre-amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, and detects the first external temperature information output by the temperature sensor at the current moment. Then, the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information are optimized to obtain the optimal target output voltage signal, and the target magnetic field value is determined according to the target output voltage signal. By combining the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information for signal optimization processing, the above method can perform temperature compensation on the output voltage signal of the traditional output to obtain the optimal target output voltage signal. Moreover, this optimization process can also remove the noise information in the measurement process, thereby improving the accuracy of the target output voltage signal, and further improving the measurement accuracy of the target magnetic field value. Description of the Drawings

[0044] Figure 1 It is the internal structure diagram of a computer device in some embodiments;

[0045] Figure 2 It is one of the flow diagrams of the magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit in some embodiments;

[0046] Figure 3 It is another flow diagram of the magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit in some embodiments;

[0047] Figure 4 It is yet another flow diagram of the magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit in some embodiments;

[0048] Figure 5 It is still another flow diagram of the magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit in some embodiments;

[0049] Figure 6 It is yet another flow diagram of the magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit in some embodiments;

[0050] Figure 7 It is still another flow diagram of the magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit in some embodiments;

[0051] Figure 8 It is the schematic diagram of a magnetic field measurement device in some embodiments;

[0052] Figure 9It is a structural block diagram of a magnetic field measurement device based on an orthogonal fundamental mode fluxgate circuit in some embodiments. Detailed implementation manners

[0053] In the embodiments of the present application, the term "and / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after.

[0054] In the embodiments of the present application, the term "a plurality of" refers to two or more, and other quantifiers are similar.

[0055] In the embodiments of the present application, the term "at least one kind" means one kind or more. For example, at least one of A, B, and C can represent: A exists alone, B exists alone, C exists alone, A and B exist simultaneously, A and C exist simultaneously, B and C exist simultaneously, and A, B, and C exist simultaneously.

[0056] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0057] The geomagnetic field is a basic physical field that has existed on the earth for a long time. Magnetic field detection under the geomagnetic field can find ferromagnetic signal anomalies under the geological layer, etc., and can be used for positioning and navigation, geological resource exploration, space science research, and natural disaster monitoring and early warning. Among them, the detection of small target magnetic field signals is an important branch, which can locate and image small magnetic substances buried underground, pipeline cracks and other defects, and then eliminate potential hazards. Under the background of the geomagnetic field, the observation of small signal magnetic fields requires the sensor to have a large dynamic magnetic field measurement range and excellent low-frequency vector magnetic field measurement ability. In terms of these two requirements, the fluxgate sensor has unique advantages. At the same time, the fluxgate sensor is mainly divided into two working modes: the second harmonic parallel fluxgate and the fundamental mode orthogonal fluxgate. The traditional second harmonic parallel fluxgate contains an excitation coil and a signal coil, which is a dual-coil design, with a complex structure and a large volume. And due to the influence of the Barkhausen effect, its noise level will be limited within a certain range, which will affect the sensitivity and accuracy of the sensor. The fundamental mode orthogonal fluxgate sensor has the advantages of high sensitivity, good directivity, high resolution, and only a single coil with a simple structure, and is often used for magnetic field measurement.

[0058] However, in the method of magnetic field measurement using a fundamental wave orthogonal fluxgate sensor described in the related art, there are still the following disadvantages, resulting in inaccurate measurement problems. The specific disadvantages are as follows: (1) Noise: Due to circuit noise and the movement of magnetic domains inside the induction core, the output voltage fluctuates randomly. The magnitude of the noise directly affects the resolution index of the sensor. If the resolution level cannot be achieved, it is impossible to distinguish the perturbation of the magnetic anomaly target on the spatial magnetic field under the geomagnetic field, affecting the detection and positioning of small targets. (2) Zero drift: Since the anisotropic axis of the induction core is not orthogonal to the core axis, when the external magnetic field is zero, a part of the magnetic field generated by the excitation signal will still be received by the induction coil, resulting in a small bias in the final circuit output. The existence of zero drift will lead to inaccurate data when measuring the external magnetic field, thereby affecting the judgment of the position of the magnetic anomaly target. (3) Temperature drift: The defect of measurement data drift caused by temperature changes. Temperature affects the sensor in two aspects, one is the effect on sensitivity, and the other is the effect on zero drift. After the temperature changes, there will be different outputs for the same external field, resulting in inaccurate and unreliable data. At the same time, due to the existence of temperature drift, after the device runs for a period of time, due to the accumulation of heat generation such as power consumption, even if the external temperature changes little, there will still be errors. Therefore, temperature drift not only limits the usage scenarios but also the usage duration, etc. There are measurement errors caused by temperature, resulting in a reduction in the applicability of the fluxgate sensor.

[0059] In view of this, the embodiments of the present application propose a magnetic field measurement method and a magnetic field measurement device based on an orthogonal fundamental mode fluxgate circuit. By optimizing the phase information and the first external temperature information of the first output voltage signal, the first excitation voltage signal, and the first induction signal output by the orthogonal fundamental mode fluxgate circuit, the accuracy of magnetic field measurement can be improved.

[0060] It should be noted that the beneficial effects or the technical problems solved by the embodiments of the present application are not limited to this one, and there may be other implicit or related problems. For specific details, please refer to the description of the following embodiments.

[0061] The technical solutions of the present application and how the technical solutions of the present application solve the above technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below with reference to the accompanying drawings.

[0062] In some embodiments, the magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit provided by the embodiments of the present application can be applied to a Figure 1 computer device as shown. The computer device can be a terminal or a server, and its internal structure diagram can be asFigure 1 As shown in the figure, the computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a magnetic field measurement method based on an orthogonal base-mode fluxgate circuit. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or a button, a trackball, or a touchpad set on the outer shell of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0063] Those skilled in the art can understand that Figure 1 the structure shown in the figure is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0064] In some embodiments, as Figure 2 shown, a magnetic field measurement method based on an orthogonal base-mode fluxgate circuit is provided. Taking the method applied to the Figure 1 computer device in the figure as an example, the method includes the following steps:

[0065] S201, detecting a first output voltage signal output by a feedback integrator in the orthogonal base-mode fluxgate circuit at the current moment, a first excitation voltage signal output by a constant current power amplifier in the orthogonal base-mode fluxgate circuit at the current moment, phase information of a first induction signal output by a preamplifier in the orthogonal base-mode fluxgate circuit at the current moment, and first external temperature information output by a temperature sensor at the current moment.

[0066] Among them, the orthogonal basis mode fluxgate circuit includes a constant current power device, a magnetic core model, a preamplifier, a fundamental wave demodulator, a low-pass filter, and a feedback integrator. The first output voltage signal represents the output voltage output by the feedback integrator at the current moment. The first excitation voltage signal represents the excitation voltage signal output by the constant current power device at the current moment. The phase information of the first induction signal represents the magnetic induction signal output by the preamplifier at the current moment. The first external temperature information represents the external temperature output by the temperature sensor at the current moment.

[0067] In the embodiment of the present application, a signal acquisition device can be pre-set between the orthogonal basis mode fluxgate circuit and the computer device to collect the working state information of the orthogonal basis mode fluxgate circuit in real time, and transmit the real-time working state information to the computer device, and the computer device processes the real-time working state information. Specifically, the signal acquisition device is connected to the feedback integrator, the constant current power device, and the preamplifier in the orthogonal basis mode fluxgate circuit, and the signal acquisition device is connected to the temperature sensor, and the first output voltage signal output by the feedback integrator in the orthogonal basis mode fluxgate circuit at the current moment, the first excitation voltage signal output by the constant current power device at the current moment, the phase information of the first induction signal output by the preamplifier at the current moment, and the first external temperature information detected by the temperature sensor at the current moment are monitored in real time, and then the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information are sent to the computer device, and the computer device can obtain the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information. It should be noted that the above signal acquisition device can be used to collect the working state information of the orthogonal basis mode fluxgate circuit and transmit the collected working state information to the computer device, and the computer device processes the working state information. Optionally, the above signal acquisition device can first collect the working state information of the orthogonal basis mode fluxgate circuit, then perform analog-to-digital conversion on the collected working state information, and then transmit the converted information to the computer device.

[0068] The rationality and sources of the four data sources, namely the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information, are described as follows: (1) Excitation voltage signal: As is well known, the resistance of a ferromagnetic material changes significantly with temperature, mainly due to the interaction between its internal magnetic structure and the electron scattering mechanism. At lower temperatures, the magnetic moments inside the ferromagnetic material are arranged more orderly, and the magnetic scattering experienced by electrons during conduction is relatively weak, resulting in a smaller resistance. As the temperature increases, the thermal excitation enhances the thermal fluctuations of the magnetic moments, gradually reducing the spin order. Especially near the Curie temperature, the ferromagnetic material transforms from an ordered ferromagnetic state to a disordered paramagnetic state, and the magnetic scattering increases significantly, leading to a rapid rise in resistance. Since the excitation current passes directly through the iron core and its amplitude is constant, the excitation voltage changes with the change in the core resistance. And temperature can change the core resistance, thereby changing the voltage drop across the core. Measuring the excitation signal voltage can reflect the change in the external temperature. (2) Phase information of the induction signal: Temperature can change the inductance of a ferromagnetic coil, mainly because the magnetic permeability of the ferromagnetic material varies with temperature. When the temperature rises, the magnetism of the ferromagnetic material weakens. Especially near the Curie temperature, the material transforms from a ferromagnetic state to a paramagnetic state, and the magnetic permeability decreases significantly, resulting in a reduction in the inductance value of the coil. Since the inductance is proportional to the magnetic permeability, the effect of temperature on the magnetic permeability is directly reflected in the change in the inductance of the coil. Therefore, when the temperature changes, the inductance of the induction coil changes, leading to a change in impedance and further causing a change in the phase of the induction signal. So measuring the phase of the induction signal can characterize the temperature change to a certain extent. (3) External temperature information: The output of the temperature sensor often represents the temperature value of the environment where the instrument is located. However, this value does not fully represent the core temperature (because there is current in the core, generating heat), but it can characterize the core temperature to a certain extent. Therefore, introducing this information can strengthen the monitoring of temperature. (4) Output voltage signal: The original output data of the orthogonal fundamental mode fluxgate circuit sensor. In the embodiments of the present application, accurate output data can be obtained by compensating the original output data by combining multiple data sources.

[0069] S202. Optimize the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain the optimal target output voltage signal, and determine the target magnetic field value based on the target output voltage signal.

[0070] Among them, the target output voltage signal represents the output voltage signal after optimization processing. The target magnetic field value is the magnetic field value corresponding to the measured magnetic field environment at the current location.

[0071] In the embodiments of the present application, after the computer device obtains the phase information of the first output voltage signal, the first excitation voltage signal, the first induction signal, and the first external temperature information based on the above steps, the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information can be input into a preset optimization model for optimization processing. When the preset optimization conditions are met, the optimal target output voltage signal is output, and then based on the corresponding relationship between voltage and magnetic field, the target magnetic field value is determined based on the target output voltage signal. It should be noted that the above preset optimization model can be a linear regression model or a neural network model. Specifically, the initial optimization model can be trained in advance based on the output voltage signal samples, excitation voltage signal samples, phase information samples of the induction signal, and external temperature information samples, and the trained initial optimization model is used as the preset optimization model.

[0072] The specific training process can be as follows: First, obtain a sample set composed of voltage signal samples, excitation voltage signal samples, phase information samples of the induction signal, and external temperature information samples, and divide the sample set into a training sample set, a validation sample set, and a test sample set. For example, the division ratio is 70%:15%:15. Then, use the mean squared error, cross-entropy loss, or mean absolute error as the loss function, and use other algorithms that minimize the loss function, such as stochastic gradient descent and adaptive moment estimation, as the optimization algorithm to minimize the loss function. Then, use the training sample set to train the initial optimization model based on the loss function and the optimization algorithm, and continuously adjust the parameters of the model to minimize the value of the loss function, obtaining a preliminarily trained optimization model. Further, the mean squared error or mean absolute error method can be used to verify the preliminarily trained optimization model based on the validation sample set, evaluate the performance of the model, and adjust the hyperparameters of the model (such as the learning rate or the number of neurons in the hidden layer, etc.) according to the verification results to improve the performance of the model. Finally, use the test sample set to perform a final test on the tuned model to evaluate the generalization ability of the model. If the test results meet the requirements, the preliminarily trained optimization model that passes the test is determined as the preset optimization model used in the aforementioned application.

[0073] The magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit provided by an embodiment of the present application detects the first output voltage signal output by a feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, the first excitation voltage signal output by a constant current power amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, the phase information of the first induction signal output by a preamplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, and the first external temperature information output by a temperature sensor at the current moment. Then, the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information are optimized to obtain an optimal target output voltage signal, and the target magnetic field value is determined according to the target output voltage signal. By combining the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information for signal optimization, the above method can perform temperature compensation on the output voltage signal of the traditional output to obtain an optimal target output voltage signal. Moreover, the optimization process can also remove the noise information in the measurement process, thereby improving the accuracy of the target output voltage signal and further improving the measurement accuracy of the target magnetic field value.

[0074] In some embodiments, a specific implementation manner for optimizing the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information is also provided. As Figure 3 shown, the "optimizing the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal" in S202 above includes:

[0075] S301, obtaining a preset state prediction model and a preset state observation model.

[0076] Among them, the preset state prediction model is used to predict the estimated data of the state at time k-1 to obtain the predicted data of the state at time k; the preset state prediction model can be a neural network model, specifically a convolutional neural network or a fully connected neural network, or a machine learning model, or a mathematical relationship model. The preset state observation model is used to observe and estimate the predicted data of the state at time k, the estimation gain at time k, and the observation data at time k to obtain the estimated data at time k and the estimated covariance at time k; the preset state observation model can be a neural network model, specifically a convolutional neural network or a fully connected neural network, or a machine learning model, or a mathematical relationship model.

[0077] In the embodiments of the present application, a computer device may construct an initial state prediction model based on a neural network or a machine learning algorithm. After the initial state prediction model is constructed, voltage signal samples, excitation voltage signal samples, phase information samples of induction signals, and external temperature information samples can be input into the initial state prediction model for training to obtain a prediction result. Then, based on the prediction result, voltage signal samples, excitation voltage signal samples, phase information samples of induction signals, and external temperature information samples, a training loss is determined, and the parameters of the initial state prediction model are adjusted according to the training loss until the training loss reaches a preset training condition. For example, the preset training condition includes that the value of the training loss is less than a preset loss threshold, or the training loss converges. Finally, the initial state prediction model obtained after adjusting the parameters is used as the preset state prediction model. Similarly, the computer device may train an initial state observation model based on voltage signal samples, excitation voltage signal samples, phase information samples of induction signals, and external temperature information samples to obtain a preset state observation model. It should be noted that the preset state prediction model and the preset state observation model may be obtained by training the above initial models, or existing trained models may be obtained.

[0078] S302. Input the estimated data and the estimated covariance at the previous moment into the preset state prediction model for prediction to obtain the predicted data and the predicted covariance at the current moment.

[0079] In the embodiments of the present application, when the computer device performs iterative calculations each time, it may input the estimated data and the estimated covariance at the previous moment into the preset state prediction model for prediction to obtain the predicted data and the predicted covariance at the current moment.

[0080] Optionally, as Figure 4 shown, the above preset state prediction model includes a state prediction sub-model and a covariance prediction sub-model. On this basis, the specific implementation method of the above S302 may include:

[0081] S3021. Input the estimated data at the previous moment into the state prediction sub-model for prediction to obtain the predicted data at the current moment.

[0082] S3022. Input the estimated covariance at the previous moment into the covariance prediction sub-model for prediction to obtain the predicted covariance at the current moment.

[0083] Among them, the preset state prediction model includes a state prediction sub-model and a covariance prediction sub-model. Specifically, the prediction sub-model and the covariance prediction sub-model can be respectively represented by the following relational expressions:

[0084]

[0085]

[0086] Among them, represents the predicted data at the current moment (moment k), specifically including the predicted output voltage signal, predicted excitation voltage signal, phase information of the predicted induction signal, and predicted external temperature information at the current moment; represents the estimated data at the previous moment (moment k-1); represents the predicted covariance at the current moment (moment k); A represents the state transition matrix; represents the transpose of; represents the estimated covariance at the previous moment (moment k-1); Q represents the noise error corresponding to the preset state prediction model; among them, A and Q are preset values.

[0087] In the embodiments of the present application, when the computer device performs iterative calculations each time, it can input the estimated data at the previous moment into the state prediction sub-model for prediction to obtain the predicted data at the current moment, and input the estimated covariance at the previous moment into the covariance prediction sub-model for prediction to obtain the predicted covariance at the current moment.

[0088] S303. Input the predicted data at the current moment, the predicted covariance at the current moment, and the observed data at the current moment into the preset state observation model for estimation to obtain the estimated data at the current moment and the estimated covariance at the current moment;

[0089] Among them, the observed data at the current moment includes the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information in the foregoing embodiments. The estimated data at the current moment includes the estimated output voltage signal, the estimated excitation voltage signal, the phase information of the estimated induction signal, and the estimated external temperature information at the current moment.

[0090] In the embodiments of the present application, when the computer device performs iterative calculations each time, it can input the predicted data at the previous moment, the predicted covariance at the current moment, and the observed data at the current moment into the preset state observation model for estimation to obtain the estimated data at the current moment and the estimated covariance at the current moment.

[0091] Optionally, as Figure 5 shown, the foregoing preset state prediction model includes a state prediction sub-model and a covariance prediction sub-model. On this basis, the specific implementation method of the foregoing S303 may include:

[0092] S3031. Input the predicted covariance at the current moment and into the gain estimation sub-model for estimation to obtain the estimated gain at the current moment.

[0093] S3032, input the estimated gain at the current moment, the predicted data at the current moment, and the observed data at the current moment into the observation sub-model for observation to obtain the estimated data at the current moment.

[0094] S3033, input the predicted covariance at the current moment into the covariance estimation sub-model for estimation to obtain the estimated covariance at the current moment.

[0095] Among them, the above gain preset state observation model includes a gain estimation sub-model, an observation sub-model, and a covariance estimation sub-model, which can be respectively represented by the following relational expressions:

[0096]

[0097]

[0098]

[0099] Among them, represents the estimated gain at the current moment (k moment); H represents the observation matrix; represents the transpose of; R represents the noise error corresponding to the preset state observation model; represents the estimated data at the current moment, specifically including the estimated output voltage signal, the estimated excitation voltage signal, the phase information of the estimated induction signal, and the estimated external temperature information at the current moment; represents the observed data at the current moment; represents the estimated covariance at the current moment (k moment); I represents the identity matrix; among them, H, R, and I are preset values.

[0100] In the embodiment of the present application, when the computer device performs iterative calculation each time, it can input the predicted covariance at the current moment into the gain estimation sub-model for estimation to obtain the estimated gain at the current moment, input the estimated gain at the current moment, the predicted data at the current moment, and the observed data at the current moment into the observation sub-model for observation to obtain the estimated data at the current moment, and input the predicted covariance at the current moment into the covariance estimation sub-model for estimation to obtain the estimated covariance at the current moment.

[0101] S304, determine the target output voltage signal according to the estimated data at the current moment.

[0102] In the embodiment of the present application, after the computer device obtains the estimated data at the current moment based on the above steps, it can determine whether the estimated data at the current moment meets the iteration termination condition, and when the iteration termination condition is met, substitute the estimated data at the current moment into the preset functional relational expression to calculate the target output voltage signal.

[0103] Optionally, as Figure 6 shown, the specific implementation method of the above S304 may include:

[0104] S3041, determine whether the current iteration number reaches a preset number, or whether the estimated covariance at the current moment satisfies a preset optimal condition.

[0105] Among them, the preset number can be determined according to the optimization accuracy or actual requirements. The preset optimal condition is that the estimated covariance at the current moment is within the preset covariance error range. Optionally, the preset optimal condition may further include that at least one of the predicted output voltage signal value at the current moment is within the error range of the preset output voltage value, the predicted excitation voltage signal value at the current moment is within the error range of the preset excitation voltage value, the phase value of the predicted induction signal at the current moment is within the error range of the preset phase value, and the predicted external temperature value at the current moment is within the error range of the preset temperature value.

[0106] In the embodiments of the present application, the computer device may pre-determine the iteration termination condition according to the optimization accuracy or actual requirements. For example, the iteration termination condition includes that the current iteration number reaches the preset number, or the estimated covariance at the current moment satisfies the preset optimal condition. During each iteration, the current iteration number is obtained, and then it is judged whether the current iteration number reaches the preset number, or whether the estimated covariance at the current moment obtained by this prediction satisfies the preset optimal condition.

[0107] S3042, if the current iteration number does not reach the preset number and the estimated covariance at the current moment does not satisfy the preset optimal condition, then take the estimated data at the current moment as the new estimated data at the previous moment, and take the estimated covariance at the current moment as the new estimated covariance at the previous moment, and return to execute the step of inputting the estimated data at the previous moment and the estimated covariance at the previous moment into the preset state prediction model for prediction to obtain the predicted data at the current moment and the predicted covariance at the current moment.

[0108] In the embodiments of the present application, if the computer device determines that the current iteration number does not reach the preset number and the estimated covariance at the current moment does not satisfy the preset optimal condition, then take the estimated data at the current moment as the new estimated data at the previous moment, and take the estimated covariance at the current moment as the new estimated covariance at the previous moment, and return to execute the step of inputting the estimated data at the previous moment and the estimated covariance at the previous moment into the preset state prediction model for prediction to obtain the predicted data at the current moment and the predicted covariance at the current moment, that is, return to execute the step of S302.

[0109] S3043, if the current iteration count reaches a preset count or the estimated covariance at the current moment meets a preset optimal condition, then determine the value of the estimated output voltage signal at the current moment in the estimated data at the current moment as the target output voltage.

[0110] In the embodiments of the present application, if the computer device determines that the current iteration count reaches a preset count or the estimated covariance at the current moment meets a preset optimal condition, then determine the value of the estimated output voltage signal at the current moment in the estimated data at the current moment as the target output voltage.

[0111] In some embodiments, a specific implementation manner for determining a target magnetic field value according to a target output voltage signal is also provided, such as Figure 7 shown, "determining a target magnetic field value according to a target output voltage signal" in the above S202 includes:

[0112] S401, obtain a preset mapping relationship.

[0113] Among them, the preset mapping relationship is the corresponding relationship between voltage and magnetic field.

[0114] In the embodiments of the present application, a preset mapping relationship can be pre-constructed based on the physical principles of voltage and magnetic field and stored in a preset path. For example, the preset mapping relationship can be represented by the following linear relationship:

[0115]

[0116] Among them, represents the target magnetic field value, k represents the sensitivity of the fundamental wave orthogonal fluxgate sensor, represents the value of the target output voltage signal, and b represents the zero drift of the fundamental wave orthogonal fluxgate sensor.

[0117] When the computer device needs to measure the magnetic field, it can obtain the preset mapping relationship from the preset path.

[0118] S402, determine the target magnetic field value according to the preset mapping relationship and the value of the target output voltage signal.

[0119] In the embodiments of the present application, after the computer device obtains the value of the target output voltage signal and the preset mapping relationship, it can substitute the value of the target output voltage signal into the above relationship for calculation to obtain the target magnetic field value. Optionally, the computer device can query the magnetic field value corresponding to the value of the target output voltage signal in the preset mapping relationship and determine the magnetic field value corresponding to the value of the target output voltage signal as the target magnetic field value.

[0120] In some embodiments, a magnetic field measurement device is also provided, such as Figure 8As shown in the figure, the device includes a fluxgate circuit 10, an analog-to-digital converter 20, a processor 30, and a temperature sensor 40; the fluxgate circuit 10 includes a constant-current power supply 101, a magnetic core model 102, a preamplifier 103, a fundamental wave demodulator 104, a low-pass filter 105, and a feedback integrator 106; the constant-current power supply 101 is connected to the magnetic core 1021 in the magnetic core model 102, the induction coil 1022 in the magnetic core model 102 is connected to the preamplifier 103 and the feedback integrator 106, the preamplifier 103 is also connected to the fundamental wave demodulator 104, the fundamental wave demodulator 104 is connected to the low-pass filter 105, and the low-pass filter 105 is connected to the feedback integrator 106; the analog-to-digital converter 20 is connected to the temperature sensor 40, the constant-current power supply 101, the preamplifier 103, the feedback integrator 106 in the fluxgate circuit 10, and the processor 30;

[0121] The fluxgate circuit 10 is configured to measure an external magnetic field according to an input controllable sine signal and a periodic flip bias signal, and output a first output voltage signal, a first excitation voltage signal, and phase information of a first induction signal;

[0122] The analog-to-digital converter 20 is configured to perform analog-to-digital conversion on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information output by the temperature sensor 40, and input the state data after analog-to-digital conversion into the processor; the state data after analog-to-digital conversion includes the first output voltage signal after analog-to-digital conversion, the first excitation voltage signal after analog-to-digital conversion, the phase information of the first induction signal after analog-to-digital conversion, and the first external temperature information after analog-to-digital conversion and input into the processor 30;

[0123] The processor 30 is configured to execute the steps of the method according to any one of the above embodiments based on the state data after analog-to-digital conversion.

[0124] Specifically, the above fundamental wave demodulator 104 may be a phase-sensitive detector. The above first excitation voltage signal is obtained by superimposing a controllable sine signal and a periodic flip bias signal. The controllable sine signal and the periodic flip bias signal may be respectively represented by the following relational expressions:

[0125] ;

[0126] ;

[0127] Wherein, is voltage, with the unit of volt; is time, with the unit of second; is the target frequency of the fundamental wave, is the periodic DC bias flip frequency, both with the unit of hertz, ; represents a sine wave waveform, Represents a periodic inversion bias signal waveform (such as a square wave waveform); is the amplitude of the sine wave waveform, is the amplitude of the square wave waveform, and . Specifically, in a typical example, volts, volts.

[0128] In the method described in the embodiments of the present application, by detecting the first output voltage signal output by the feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, the first excitation voltage signal output by the constant current power amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, the phase information of the first induction signal output by the preamplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, and detecting the first external temperature information output by the temperature sensor at the current moment, and then optimizing the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information, an optimal target output voltage signal is obtained, and the target magnetic field value is determined according to the target output voltage signal. The above method can perform temperature compensation on the output voltage signal of the traditional output by combining the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal. Moreover, this optimization process can also remove the noise information in the measurement process, thereby improving the accuracy of the target output voltage signal, and further improving the measurement accuracy of the target magnetic field value.

[0129] Combining all the above embodiments, a magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit is further provided. The method includes:

[0130] S501, detecting the first output voltage signal output by the feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, the first excitation voltage signal output by the constant current power amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, the phase information of the first induction signal output by the preamplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, and detecting the first external temperature information output by the temperature sensor at the current moment.

[0131] S502, obtaining a preset state prediction model and a preset state observation model.

[0132] S503, inputting the state data at the current moment into the preset state prediction model for prediction to obtain the state data at the next moment. Among them, the state data at the current moment includes the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information. The state data at the next moment includes the second output voltage signal, the second excitation voltage signal, the phase information of the second induction signal, and the second external temperature information.

[0133] S504, input the state data at the current moment into a preset state observation model for observation to obtain the observation data at the current moment.

[0134] S505, determine whether the current iteration number has reached the preset number, or whether the state data at the next moment meets the preset optimal condition.

[0135] S506, if the current iteration number has not reached the preset number and the state data at the next moment does not meet the preset optimal condition, then use the state data at the next moment as the state data at the new current moment, and return to execute step S504.

[0136] S507, if the current iteration number has reached the preset number or the state data at the next moment meets the preset optimal condition, then determine the output voltage at the next moment in the state data at the next moment as the target output voltage, and obtain a preset mapping relationship. The preset mapping relationship is the corresponding relationship between voltage and magnetic field.

[0137] S508, query the magnetic field value corresponding to the value of the target output voltage signal in the preset mapping relationship, and determine the magnetic field value corresponding to the value of the target output voltage signal as the target magnetic field value.

[0138] The methods described in the above steps have been described in the foregoing embodiments. For detailed content, please refer to the foregoing description and will not be elaborated here.

[0139] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same moment, but can be executed at different moments. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0140] Based on the same inventive concept, the embodiments of the present application also provide a magnetic field measurement device based on an orthogonal fundamental mode fluxgate circuit for implementing the above-mentioned magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit. The implementation solutions provided by this device to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more embodiments of the magnetic field measurement device based on an orthogonal fundamental mode fluxgate circuit provided below can refer to the limitations on the magnetic field measurement method based on an orthogonal fundamental mode fluxgate circuit in the above text and will not be elaborated here.

[0141] In some embodiments, such as Figure 9 shown, a magnetic field measurement device based on an orthogonal fundamental mode fluxgate circuit is provided, including:

[0142] A detection module 50 for detecting a first output voltage signal output by a feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, a first excitation voltage signal output by a constant current power amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, phase information of a first induction signal output by a preamplifier in the orthogonal fundamental mode fluxgate circuit, and first external temperature information output by a detection temperature sensor at the current moment.

[0143] An optimization module 60 for performing optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal, and determining a target magnetic field value according to the target output voltage signal.

[0144] In some embodiments, the above optimization module includes:

[0145] A first acquisition unit for acquiring a preset state prediction model and a preset state observation model.

[0146] A prediction unit for inputting the estimated data and the estimated covariance at the previous moment into the preset state prediction model for prediction to obtain the predicted data and the predicted covariance at the current moment.

[0147] An estimation unit for inputting the predicted data, the predicted covariance at the current moment, and the observed data at the current moment into the preset state observation model for estimation to obtain the estimated data and the estimated covariance at the current moment; the observed data at the current moment includes the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information.

[0148] A determination unit for determining the target output voltage signal according to the estimated data at the current moment.

[0149] In some embodiments, the above prediction unit includes:

[0150] A first prediction sub-unit for inputting the estimated data at the previous moment into the state prediction sub-model for prediction to obtain the predicted data at the current moment.

[0151] A second observation sub-unit for inputting the estimated covariance at the previous moment into the covariance prediction sub-model for prediction to obtain the predicted covariance at the current moment.

[0152] In some embodiments, the above estimation unit includes:

[0153] A first estimation subunit, configured to estimate the predicted covariance at the current moment and input it into the gain estimation sub-model to obtain the estimated gain at the current moment.

[0154] A second estimation subunit, configured to input the estimated gain at the current moment, the predicted data at the current moment, and the observed data at the current moment into the observation sub-model for observation to obtain the estimated data at the current moment.

[0155] A third estimation subunit, configured to input the predicted covariance at the current moment into the covariance estimation sub-model for estimation to obtain the estimated covariance at the current moment.

[0156] In some embodiments, the above determination unit includes:

[0157] A first determination subunit, configured to determine whether the current iteration number reaches a preset number or the estimated covariance at the current moment meets a preset optimal condition;

[0158] A loop subunit, configured to, if the current iteration number does not reach the preset number and the estimated covariance at the current moment does not meet the preset optimal condition, use the estimated data at the current moment as the new estimated data at the previous moment, and use the estimated covariance at the current moment as the new estimated covariance at the previous moment, and return to execute the step of inputting the estimated data at the previous moment and the estimated covariance at the previous moment into a preset state prediction model for prediction to obtain the predicted data at the current moment and the predicted covariance at the current moment;

[0159] A second determination subunit, configured to, if the current iteration number reaches the preset number or the estimated covariance at the current moment meets the preset optimal condition, determine the value of the estimated output voltage signal in the estimated data at the current moment as the target output voltage.

[0160] In some embodiments, the above optimization module includes:

[0161] A second acquisition unit, configured to acquire a preset mapping relationship; the preset mapping relationship is the corresponding relationship between voltage and magnetic field.

[0162] A query unit, configured to determine the target magnetic field value according to the preset mapping relationship and the value of the target output voltage signal.

[0163] Each module in the above magnetic field measurement device based on an orthogonal basis mode fluxgate circuit can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above respective modules.

[0164] In some embodiments, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps of the magnetic field measurement method based on the orthogonal base-mode fluxgate circuit described in any of the above embodiments are implemented.

[0165] For the computer device provided in the above embodiments, its implementation principle and technical effects are similar to those of the above method embodiments, and will not be elaborated here.

[0166] In some embodiments, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the magnetic field measurement method based on the orthogonal base-mode fluxgate circuit described in any of the above embodiments are implemented.

[0167] For the computer-readable storage medium provided in the above embodiments, its implementation principle and technical effects are similar to those of the above method embodiments, and will not be elaborated here.

[0168] In some embodiments, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps of the magnetic field measurement method based on the orthogonal base-mode fluxgate circuit described in any of the above embodiments are implemented.

[0169] For the computer program product provided in the above embodiments, its implementation principle and technical effects are similar to those of the above method embodiments, and will not be elaborated here.

[0170] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0171] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0172] The above-described embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A magnetic field measurement method based on an orthogonal basis mode fluxgate circuit, characterized in that Applied to an orthogonal base-mode fluxgate circuit, the method includes: Detecting a first output voltage signal output by a feedback integrator in the orthogonal base-mode fluxgate circuit at the current moment, a first excitation voltage signal output by a constant-current power supply in the orthogonal base-mode fluxgate circuit at the current moment, phase information of a first induction signal output by a preamplifier in the orthogonal base-mode fluxgate circuit at the current moment, and first external temperature information output by a temperature sensor at the current moment; Performing optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal, and determining a target magnetic field value according to the target output voltage signal; The performing optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal includes: Obtaining a preset state prediction model and a preset state observation model; Inputting the estimated data and the estimated covariance at the previous moment into the preset state prediction model for prediction to obtain the predicted data and the predicted covariance at the current moment; Inputting the predicted data, the predicted covariance, and the observed data at the current moment into the preset state observation model for estimation to obtain the estimated data and the estimated covariance at the current moment; the observed data at the current moment includes the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information; Determining the target output voltage signal according to the estimated data at the current moment.

2. The method according to claim 1, wherein The preset state prediction model includes a state prediction sub-model and a covariance prediction sub-model. The inputting the estimated data and the estimated covariance at the previous moment into the preset state prediction model for prediction to obtain the predicted data and the predicted covariance at the current moment includes: Inputting the estimated data at the previous moment into the state prediction sub-model for prediction to obtain the predicted data at the current moment; Inputting the estimated covariance at the previous moment into the covariance prediction sub-model for prediction to obtain the predicted covariance at the current moment.

3. The method according to claim 1, wherein The preset state observation model includes a gain estimation sub-model, an observation sub-model, and a covariance estimation sub-model. The inputting the predicted data, the predicted covariance, and the observed data at the current moment into the preset state observation model for estimation to obtain the estimated data and the estimated covariance at the current moment includes: Inputting the predicted covariance at the current moment into the gain estimation sub-model for estimation to obtain the estimated gain at the current moment; Inputting the estimated gain, the predicted data, and the observed data at the current moment into the observation sub-model for observation to obtain the estimated data at the current moment; Input the predicted covariance at the current moment into the covariance estimation sub-model for estimation to obtain the estimated covariance at the current moment.

4. The method according to any one of claims 1-3, characterized in that, Determining the target output voltage signal according to the estimated data at the current moment includes: Determining whether the current iteration number reaches a preset number, or whether the estimated covariance at the current moment meets a preset optimal condition; If the current iteration number does not reach the preset number and the estimated covariance at the current moment does not meet the preset optimal condition, then use the estimated data at the current moment as the new estimated data at the previous moment, and use the estimated covariance at the current moment as the new estimated covariance at the previous moment, and return to execute the step of inputting the estimated data at the previous moment and the estimated covariance at the previous moment into the preset state prediction model for prediction to obtain the predicted data at the current moment and the predicted covariance at the current moment; If the current iteration number reaches the preset number or the estimated covariance at the current moment meets the preset optimal condition, then determine the value of the estimated output voltage signal at the current moment in the estimated data at the current moment as the target output voltage.

5. The method according to claim 4, wherein The preset optimal condition is that the estimated covariance at the current moment is within a preset covariance error range; or, the preset optimal condition includes at least one of the predicted output voltage signal value at the current moment being within the error range of the preset output voltage value, the predicted excitation voltage signal value at the current moment being within the error range of the preset excitation voltage value, the phase value of the predicted induction signal at the current moment being within the preset phase value error range, and the predicted external temperature value at the current moment being within the preset temperature value error range.

6. The method according to claim 1, wherein Determining the target magnetic field value according to the target output voltage signal includes: Obtain a preset mapping relationship; the preset mapping relationship is the corresponding relationship between voltage and magnetic field; Determine the target magnetic field value according to the preset mapping relationship and the value of the target output voltage signal.

7. A magnetic field measuring device, characterized in that, The magnetic field measurement device includes a fluxgate circuit, an analog-to-digital converter, a processor, and a temperature sensor; the fluxgate circuit includes a constant current power supply, a magnetic core model, a pre-amplifier, a fundamental wave demodulator, a low-pass filter, and a feedback integrator; the constant current power supply is connected to the magnetic core in the magnetic core model, the induction coil in the magnetic core model is connected to the pre-amplifier and the feedback integrator, the pre-amplifier is also connected to the fundamental wave demodulator, the fundamental wave demodulator is connected to the low-pass filter, and the low-pass filter is connected to the feedback integrator; the analog-to-digital converter is connected to the temperature sensor, the constant current power supply, the pre-amplifier, the feedback integrator in the fluxgate circuit, and the processor; The fluxgate circuit is configured to output the phase information of the first output voltage signal, the first excitation voltage signal, and the first induction signal according to the input controllable sine signal and the periodic inversion bias signal. The analog-to-digital converter is used to perform analog-to-digital conversion on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information output by the temperature sensor, and input the state data after analog-to-digital conversion into the processor; the state data after analog-to-digital conversion includes the first output voltage signal after analog-to-digital conversion, the first excitation voltage signal after analog-to-digital conversion, the phase information of the first induction signal after analog-to-digital conversion, and the first external temperature information after analog-to-digital conversion and input them into the processor; The processor is used to execute the steps of the method according to any one of claims 1-6 based on the state data after analog-to-digital conversion.

8. A magnetic field measurement device based on an orthogonal basis mode fluxgate circuit, characterized in that, The device includes: A detection module, which is used to detect the first output voltage signal output by the feedback integrator in the orthogonal fundamental mode fluxgate circuit at the current moment, the first excitation voltage signal output by the constant current power amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, the phase information of the first induction signal output by the pre-amplifier in the orthogonal fundamental mode fluxgate circuit at the current moment, and the first external temperature information output by the detection temperature sensor at the current moment; An optimization module, which is used to perform optimization processing on the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information to obtain an optimal target output voltage signal, and determine the target magnetic field value according to the target output voltage signal; The optimization module includes: A first acquisition unit, which is used to acquire a preset state prediction model and a preset state observation model; A prediction unit, which is used to input the estimated data and the estimated covariance at the previous moment into the preset state prediction model for prediction to obtain the predicted data and the predicted covariance at the current moment; An estimation unit, which is used to input the predicted data at the current moment, the predicted covariance at the current moment, and the observed data at the current moment into the preset state observation model for estimation to obtain the estimated data and the estimated covariance at the current moment; the observed data at the current moment includes the first output voltage signal, the first excitation voltage signal, the phase information of the first induction signal, and the first external temperature information; A determination unit, which is used to determine the target output voltage signal according to the estimated data at the current moment.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 6.

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