CN111913227A - Method and system for calculating frequency characteristics of magnetic anomaly signals - Google Patents

Method and system for calculating frequency characteristics of magnetic anomaly signals Download PDF

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CN111913227A
CN111913227A CN202010800622.8A CN202010800622A CN111913227A CN 111913227 A CN111913227 A CN 111913227A CN 202010800622 A CN202010800622 A CN 202010800622A CN 111913227 A CN111913227 A CN 111913227A
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CN111913227B (en
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沈莹
高俊奇
王嘉增
蒋泽坤
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Harbin Engineering University
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Abstract

The invention relates to a method and a system for calculating frequency characteristics of magnetic anomaly signals, wherein the upper limit frequency point of magnetic anomaly signal frequency domain energy is in a direct proportion relation with the movement speed of a ferromagnetic target object, the upper limit frequency point of the magnetic anomaly signal frequency domain energy is in an inverse proportion relation with the nearest contact path between the ferromagnetic target object and a sensor, and the upper limit frequency point of the magnetic anomaly signal frequency domain energy is in a nonlinear relation with the magnetic moment direction and the sensitive direction of the sensor through a magnetic dipole magnetic anomaly signal analysis model, a frequency spectrum formula of the magnetic anomaly signals and a control variable method.

Description

Method and system for calculating frequency characteristics of magnetic anomaly signals
Technical Field
The invention relates to the technical field of magnetic anomaly detection, in particular to a method and a system for calculating frequency characteristics of magnetic anomaly signals.
Background
Since the magnetic permeability of ferromagnetic targets is higher than that of most media such as air, water, seawater and soil, the geomagnetic field around the targets is disturbed, and Magnetic Anomaly Detection (MAD) is a method for detecting magnetic disturbance. Specifically, when there is relative movement between the sensor and the object being observed, the voltage information output by the sensor contains magnetic field variation information of unknown target characteristics. This physical phenomenon allows the magnetic anomaly features obtained to serve as important clues for hidden target detection, localization and identification, especially in cross-media detection scenarios.
Current research on MADs is mainly focused on two broad categories: target detection and feature analysis. Since the magnetic anomaly signal is concentrated in the very low frequency region, it is always drowned at 0<α<2 ambient low frequency (1/f)α) In the noise. Therefore, extracting weak signals from background noise is a primary task for any MAD measurement. For target detection, available noise suppression methods include: classical Orthogonal Basis Functions (OBFs), high order cross-spectra (HOC), and Minimum Entropy Detectors (MED). The OBF method uses a priori information (CPA, close path approximate) and velocity between the ferromagnetic target and the sensor) to construct the basis function of the matched filter. The MED method compares the information entropy difference between the noise and the target signal for detection. And HOC is a method of performing spectrum analysis using zero-crossing counting. These methods designed for detecting a target of discovery generally produce a filtered signal in the form of detection probabilities. Although the signal-to-noise ratio is improved, important waveform characteristics such as signal duration width, shape and peak are completely eliminated.
Target detection is only a primary purpose of the MAD, and further feature analysis is crucial to overall recognition of target features. For example, in object localization, object classification, object trajectory prediction, magnetic moment direction estimation, etc., a MAD signal with complete waveform is essential. The ability to eliminate the effects of magnetic noise as much as possible while preserving the original characteristics of the signal is a significant challenge in signal processing for magnetic anomalies.
Research has shown that the target motion speed and CPA have important effects on the MAD frequency characteristics. However, with the development of MAD technology, targets or sensor carrier platforms have evolved from airplanes for military reconnaissance to automobiles, surface vessels, unmanned underwater vehicles, conveyor belts and walkers. In various detection schemes, there are large differences in magnetic moment, sensing range, and velocity of the platform (or target). Even in the same scene, the consistency of the conditions cannot be ensured. Therefore, it is an urgent problem in the art to find out whether there are other factors that affect the frequency characteristics of the magnetic anomaly signal, in addition to the speed and the CPA.
Disclosure of Invention
The invention aims to provide a method and a system for calculating the frequency characteristics of magnetic anomaly signals, which can obtain the direct proportion relation between the upper limit frequency point of the frequency domain energy of the magnetic anomaly signals and the movement speed of a ferromagnetic target object, the inverse proportion relation between the upper limit frequency point of the frequency domain energy of the magnetic anomaly signals and the nearest contact path between the ferromagnetic target object and a sensor, and the nonlinear relation between the magnetic moment direction and the sensitive direction of the sensor through a magnetic dipole magnetic anomaly signal analysis model, a frequency spectrum formula of the magnetic anomaly signals and a control variable method, and can realize the quick estimation of the upper limit cut-off frequency of the magnetic anomaly signals under a certain detection scene according to the calculation formula of the upper limit frequency point of the frequency domain energy of the magnetic.
In order to achieve the purpose, the invention provides the following scheme:
a method for calculating an upper limit frequency point of frequency domain energy of a magnetic anomaly signal comprises the following steps:
establishing a magnetic dipole magnetic anomaly signal analysis model by utilizing the original sensitive direction of the sensor and the original induction magnetic field generated by the magnetic dipole; the parameters for establishing the magnetic dipole magnetic anomaly signal analysis model comprise magnetic moment strength, magnetic moment direction, coordinate sensitive direction of the sensor, a nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object; the coordinate sensitive direction of the sensor is a coordinate representation of the original sensitive direction of the sensor;
according to the magnetic dipole magnetic anomaly signal analysis model, the frequency spectrum of the magnetic anomaly signal and a control variable method, analyzing the relationship between the upper limit frequency point of the magnetic anomaly signal frequency domain energy and the magnetic moment intensity, the magnetic moment direction, the coordinate sensitive direction of the sensor, the nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object, and obtaining a calculation formula of the upper limit frequency point of the magnetic anomaly signal frequency domain energy.
Optionally, the establishing a magnetic dipole magnetic anomaly signal analysis model by using the original sensitive direction of the sensor and the original induced magnetic field generated by the magnetic dipole specifically includes:
establishing a magnetic dipole model equivalent to the ferromagnetic target object, and determining an original induction magnetic field generated by a magnetic dipole in the magnetic dipole model;
establishing a three-dimensional rectangular coordinate system by taking the sensor as an origin and taking a plane formed by the motion tracks of the sensor and the ferromagnetic target object as an XOY plane, wherein the motion direction of the ferromagnetic target object is the X direction, and the direction of a nearest contact path between the ferromagnetic target object and the sensor is the Y direction;
converting the original induction magnetic field into a coordinate induction magnetic field under the three-dimensional rectangular coordinate system by using the three-dimensional rectangular coordinate system, and converting the original sensitive direction of the sensor into a coordinate sensitive direction under the three-dimensional rectangular coordinate system;
and establishing a magnetic dipole magnetic anomaly signal analysis model according to the coordinate sensitive direction of the sensor and the coordinate induction magnetic field generated by the magnetic dipole.
Optionally, the converting, by using the three-dimensional rectangular coordinate system, the original induced magnetic field into a coordinate induced magnetic field in the three-dimensional rectangular coordinate system, and converting the original sensitive direction of the sensor into a coordinate sensitive direction in the three-dimensional rectangular coordinate system specifically include:
determining the original induction magnetic field generated by the magnetic dipole as follows:
Figure BDA0002627232880000031
wherein mu0Expressed as the vacuum permeability, μ0＝4π×10-7H/m, r is expressed as a coordinate vector of the magnetic dipole with respect to the sensor, r ═ x y z]TAnd m is represented as a magnetic moment vector,
Figure BDA0002627232880000032
determining a coordinate vector of the magnetic dipole relative to the sensor in the three-dimensional rectangular coordinate system as:
r＝[x y z]T＝[vt R0 0]T
wherein v represents the moving speed of the ferromagnetic object, t represents the moving time of the ferromagnetic object, R0Represented as the closest contact path between the ferromagnetic target and the sensor;
calculating the magnetic moment vector m under the three-dimensional rectangular coordinate system:
m＝|m|·m'(α,β)
where | m | represents the magnetic moment strength, m '(α, β) represents a unit vector of the magnetic moment direction, and m' (α, β) ═ cos α sin β sin α sin β cos β]TAlpha represents an included angle between the projection of the magnetic moment direction on the XOY plane and the X axis, beta represents an included angle between the magnetic moment direction and the Z axis, the value range of alpha is 0 to 360, and the value range of beta is 0 to 180;
substituting a calculation formula of the magnetic dipole relative to a coordinate vector of the sensor in the three-dimensional rectangular coordinate system and the calculation formula of the magnetic moment vector in the three-dimensional rectangular coordinate system into a calculation formula of an original induction magnetic field generated by the magnetic dipole to obtain a calculation formula of a coordinate induction magnetic field generated by the magnetic dipole:
Figure BDA0002627232880000041
wherein B (t) represents the coordinate induced magnetic field, μ, produced by the magnetic dipole0Expressed as the vacuum permeability, μ0＝4π×10-7H/m，R0Expressed as the closest contact path between the ferromagnetic target object and the sensor, | m | expressed as the magnetic moment strength, v expressed as the movement speed of the ferromagnetic target object, t expressed as the movement time of the ferromagnetic target object, m' expressed as the magnetic moment direction;
determining the coordinate sensitive direction of the sensor as:
k(θ,φ)＝[cos θ sin φ sin θ sin φ cos φ]
wherein k (theta, phi) is a unit vector of the coordinate sensitive direction of the sensor, theta is an included angle between the projection of the original sensitive direction of the sensor on an XOY plane of a three-dimensional rectangular coordinate system and an X axis, phi is an included angle between the sensitive direction of the sensor and a Z axis, the value range of theta is 0 to 360, and the value range of phi is 0 to 180.
Optionally, the magnetic dipole magnetic anomaly signal analysis model specifically includes:
Bs(t)＝k(θ,φ)·B(t)
wherein, Bs(t) is the projection of B (t) along the sensitive direction of the sensor coordinates, Bs(t) is a magnetic anomaly signal obtained by the sensor, k (theta, phi) is a unit vector of a coordinate sensitive direction of the sensor, and B (t) is a coordinate induced magnetic field generated by the magnetic dipole.
Optionally, the method for calculating the frequency-domain energy of the magnetic anomaly signal includes analyzing, according to the magnetic dipole magnetic anomaly signal analysis model, the frequency spectrum of the magnetic anomaly signal, and a control variable method, a relationship between an upper limit frequency point of the frequency-domain energy of the magnetic anomaly signal and the magnetic moment intensity, the magnetic moment direction, the coordinate sensitive direction of the sensor, a closest contact path between the ferromagnetic target object and the sensor, and a movement speed of the ferromagnetic target object, and obtaining a calculation formula of the upper limit frequency point of the frequency-domain energy of the magnetic anomaly signal, where the specific method includes:
determining the magnetic anomaly signal BsThe spectrum of (t) is:
Figure BDA0002627232880000042
where j represents the amount of imaginary units, f represents the amount of frequency, and t represents the amount of time;
according to the magnetic abnormal signal Bs(t) determining the upper limit frequency satisfying the frequency domain energy of the magnetic anomaly signalThe conditional formula for the points is:
Figure BDA0002627232880000051
wherein
Figure BDA0002627232880000052
Expressed as satisfying the condition;
according to the magnetic abnormal signal Bs(t) obtaining an upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal by using a frequency spectrum calculation formula, a conditional formula of the upper limit frequency point satisfying the frequency domain energy of the magnetic abnormal signal and the magnetic dipole magnetic abnormal signal analysis modelhWith the magnetic moment strength | m |, the magnetic moment direction m' (α, β), the coordinate sensitive direction k (θ, φ) of the sensor, the closest contact path R between the ferromagnetic target and the sensor0Is related to the moving speed v of the ferromagnetic target object;
determining the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal according to a control variable methodhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is in a direct proportion relation with the movement speed v of the ferromagnetic target objecthWith the nearest contact path R0In inverse proportion, the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is obtained in a nonlinear relation with a function formed by the magnetic moment direction and the coordinate sensitive directionhIs calculated by the formula
Figure BDA0002627232880000053
Where g (α, β, θ, φ) represents a non-linear function with respect to angles α, β, θ and φ.
A method for constructing an adaptive low-pass filter comprises the following steps:
estimating a value of a function formed by the magnetic moment direction and the coordinate sensitive direction of the sensor according to a Monte Carlo algorithm;
simplifying a calculation formula of an upper limit frequency point of the magnetic anomaly signal frequency domain energy according to the value of the function, the movement speed of the ferromagnetic target object and the nearest contact path between the ferromagnetic target object and the sensor;
acquiring a specific value of the movement speed of the ferromagnetic target object and a specific value of the nearest contact path, and obtaining a value of an upper limit frequency point of the magnetic anomaly signal frequency domain energy according to a simplified calculation formula of the upper limit frequency point of the magnetic anomaly signal frequency domain energy;
and designing the low-pass filter by taking the value of the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal as the value of the optimal cut-off frequency of the low-pass filter.
Optionally, the simplified calculation formula of the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal is as follows:
Figure BDA0002627232880000054
wherein v is represented by the speed of movement, R, of the ferromagnetic target0Represented as the closest contact path between the ferromagnetic target and the sensor.
A computing system of an upper limit frequency point of magnetic anomaly signal frequency domain energy comprises a magnetic dipole magnetic anomaly signal analysis model establishing module and an upper limit frequency point computing module;
the magnetic dipole magnetic anomaly signal analysis model establishing module establishes a magnetic dipole magnetic anomaly signal analysis model by utilizing the original sensitive direction of the sensor and the original induction magnetic field generated by the magnetic dipole; the parameters for establishing the magnetic dipole magnetic anomaly signal analysis model comprise magnetic moment strength, magnetic moment direction, coordinate sensitive direction of the sensor, a nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object; the coordinate sensitive direction of the sensor is a coordinate representation of the original sensitive direction of the sensor;
the upper limit frequency point calculation module is used for analyzing the relationship between the upper limit frequency point of the magnetic anomaly signal frequency domain energy and the magnetic moment intensity, the magnetic moment direction, the coordinate sensitive direction of the sensor, the nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object according to the magnetic dipole magnetic anomaly signal analysis model, the frequency spectrum of the magnetic anomaly signal and a control variable method, so as to obtain a calculation formula of the upper limit frequency point of the magnetic anomaly signal frequency domain energy.
Optionally, the magnetic dipole magnetic anomaly signal analysis model establishing module specifically includes: the device comprises a magnetic dipole model establishing unit, a three-dimensional rectangular coordinate system establishing unit, a coordinate conversion unit and a coordinated magnetic dipole magnetic anomaly signal analysis model establishing unit;
the magnetic dipole model establishing unit is used for establishing a magnetic dipole model equivalent to the ferromagnetic target object and determining an original induction magnetic field generated by the magnetic dipole in the magnetic dipole model equivalent to the ferromagnetic target object;
the three-dimensional rectangular coordinate system establishing unit is used for establishing a three-dimensional rectangular coordinate system by taking the sensor as an origin and taking a plane formed by the motion tracks of the sensor and the ferromagnetic target object as an XOY plane, wherein the motion direction of the ferromagnetic target object is the X direction, and the direction of a nearest contact path between the ferromagnetic target object and the sensor is the Y direction;
the coordinate conversion unit converts the original induction magnetic field into a coordinate induction magnetic field under the three-dimensional rectangular coordinate system by using the three-dimensional rectangular coordinate system, and converts the original sensitive direction of the sensor into a coordinate sensitive direction under the three-dimensional rectangular coordinate system;
the coordinated magnetic dipole magnetic anomaly signal analysis model establishing unit is used for establishing a magnetic dipole magnetic anomaly signal analysis model according to the coordinate sensitive direction of the sensor and the coordinate induction magnetic field generated by the magnetic dipole.
Optionally, the upper limit frequency point calculating module specifically includes: a spectrum calculating unit, a condition calculating unit, a relation analyzing unit and an upper limit frequency point calculating unit;
the frequency spectrum calculating unit is used for calculating the magnetic abnormal signal Bs(t) a spectrum of:
Figure BDA0002627232880000071
where j represents the amount of imaginary units, f represents the amount of frequency, and t represents the amount of time;
the condition calculating unit is used for calculating the magnetic abnormal signal B according to the magnetic abnormal signals(t), determining a conditional formula of an upper limit frequency point satisfying the frequency domain energy of the magnetic anomaly signal as follows:
Figure BDA0002627232880000072
wherein
Figure BDA0002627232880000073
Expressed as satisfying the condition;
the relation analysis unit is used for analyzing the magnetic abnormal signal Bs(t) obtaining an upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal by using a frequency spectrum calculation formula, a conditional formula of the upper limit frequency point satisfying the frequency domain energy of the magnetic abnormal signal and the magnetic dipole magnetic abnormal signal analysis modelhWith the magnetic moment strength | m |, the magnetic moment direction m' (α, β), the coordinate sensitive direction k (θ, φ) of the sensor, the closest contact path R between the ferromagnetic target and the sensor0Is related to the moving speed v of the ferromagnetic target object;
the upper limit frequency point calculation unit is used for determining an upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal according to a control variable methodhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is in a direct proportion relation with the movement speed v of the ferromagnetic target objecthWith the nearest contact path R0In inverse proportion, the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is obtained in a nonlinear relation with a function formed by the magnetic moment direction and the coordinate sensitive directionhIs calculated by the formula
Figure BDA0002627232880000074
Where g (α, β, θ, φ) represents a non-linear function with respect to angles α, β, θ and φ.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the method has the advantages that: according to the method and the device, the upper limit cut-off frequency under a certain detection scene can be quickly estimated, the magnetic moment strength | m |, the magnetic moment direction m' (alpha, beta), the sensitive direction k (theta, phi) of the sensor and the nearest contact path R between the ferromagnetic target object and the sensor are analyzed by analyzing the frequency domain characteristics of the magnetic anomaly signals in detail0And the upper limit frequency point f of the moving speed v of the ferromagnetic target object to the frequency domain energy of the magnetic abnormal signalhAccording to the formula
Figure BDA0002627232880000075
The method can realize the quick estimation of the upper limit cut-off frequency of the magnetic anomaly signal in a certain detection scene.
The method has the advantages that: the method estimates the value of a function formed by the magnetic moment direction and the sensitive direction of the sensor by a Monte Carlo method, and enables the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhIs calculated by
Figure BDA0002627232880000081
Simplified to
Figure BDA0002627232880000082
Thereby simplifying the upper limit frequency point f of the nonlinear parameter to the frequency domain energy of the magnetic abnormal signalhConsidering only R0F can be quickly calculated by the sum vh. The application also provides an experience numerical table under various detection scenes, and can quickly inquire the upper limit frequency point f for obtaining the frequency domain energy of the magnetic anomaly signalhAnd the calculation efficiency is improved.
The method has the advantages that: the method is implemented by using an upper limit frequency point f of frequency domain energy of a magnetic anomaly signalhObtained by investigating
Figure BDA0002627232880000083
Compared with the prior art of classical orthogonal basis function, high-order cross spectrum, minimum entropy detector and the like, the method does not generate filtering signals in the form of detection probability, and upper limit frequency point fhThe magnetic anomaly signal contains most of energy of the signal, and high-frequency noise is isolated as much as possible, so that the magnetic anomaly signal obtained by the method still retains the original characteristics of the magnetic anomaly signal while the influence of the magnetic noise is eliminated as much as possible.
The advantages are that: the application relates to an upper limit frequency point f of frequency domain energy of a magnetic anomaly signalhEquivalent to a low-pass filtering cut-off frequency point, and can realize the construction of the self-adaptive low-pass filter in the magnetic anomaly detection of any scene. Because the low-pass filter is based on the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhConstructed at fhOn the basis of the advantages of containing most of energy of the signal and isolating high-frequency noise as much as possible, the low-pass filter under the design can obtain a high signal-to-noise ratio while keeping the original signal, and is favorable for further characteristic analysis of the signal after the signal is preprocessed based on the low-pass filter.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flowchart of a method for calculating an upper limit frequency point of frequency domain energy of a magnetic anomaly signal according to embodiment 1 of the present invention;
fig. 2 is a schematic diagram of a magnetic anomaly detection principle including a moving magnetic dipole and a stationary sensor in a method for calculating an upper limit frequency point of frequency domain energy of a magnetic anomaly signal according to embodiment 1 of the present invention;
FIG. 3 shows example 1 of the present inventionIn the provided method for calculating the upper limit frequency point of the magnetic anomaly signal frequency domain energyhRespectively with | m |, v, R0M' (α, β) and k (θ, φ), wherein graph (a) represents | m | vs. fhThe influence of (a); FIG. b shows v and R0To fhThe influence of (a); FIG. c shows m' (α, β) vs. fhThe influence of (a); graph (d) shows k (θ, φ) versus fhThe influence of (a);
fig. 4 is a probability distribution diagram of a function g (α, β, θ, Φ) obtained through monte carlo simulation in the method for constructing an adaptive low-pass filter according to embodiment 2 of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a method and a system for calculating frequency characteristics of magnetic anomaly signals, so that the relations between an upper limit frequency point of frequency domain energy of the magnetic anomaly signals and the movement speed of a ferromagnetic target object, the nearest contact path between the ferromagnetic target object and a sensor, the magnetic moment direction and the sensitivity direction of the sensor are obtained, a calculation formula of the upper limit frequency point of the frequency domain energy of the magnetic anomaly signals is obtained, and the quick estimation of the upper limit cut-off frequency of the magnetic anomaly signals under a certain detection scene is realized.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Example 1:
fig. 1 is a flowchart of a method for calculating a frequency characteristic of a magnetic anomaly signal according to the present invention. Referring to fig. 1, the method for calculating the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal provided by the invention comprises the following steps:
the method comprises the following steps: the method comprises the following steps of establishing a magnetic dipole magnetic anomaly signal analysis model by utilizing an original sensitive direction of a sensor and an original induction magnetic field generated by a magnetic dipole, and specifically comprises the following steps:
(1) establishing a magnetic dipole model equivalent to a ferromagnetic target
In Magnetic Anomaly Detection (MAD), a ferromagnetic target can be equivalent to a magnetic dipole model when the closest Contact Path (CPA) between the target and the sensor is at least three times larger than the maximum linear dimension of the target. Therefore, a magnetic dipole model is established to analyze the induced magnetic anomaly signal, and the original induced magnetic field generated by the magnetic dipole is expressed as:
Figure BDA0002627232880000101
wherein mu0Expressed as the vacuum permeability, μ0＝4π×10-7H/m, r is expressed as a coordinate vector of the magnetic dipole with respect to the sensor, r ═ x y z]TAnd m is represented as a magnetic moment vector,
Figure BDA0002627232880000102
(2) obtaining a coordinate induction magnetic field and a coordinate sensitive direction by coordinating the original sensitive direction of the sensor and the original induction magnetic field generated by the magnetic dipole
FIG. 2 is a diagram illustrating the detection principle of a vector sensor and a ferromagnetic target moving at a constant velocity v in a straight line, wherein a plane formed by the motion tracks of the sensor and the target is used as an XOY plane to construct a coordinate system, the sensor is defined as an origin, the moving direction of the ferromagnetic target is an X direction, and CPA is set as R0Then the coordinate vector of the magnetic dipole relative to the sensor in the three-dimensional rectangular coordinate system is:
r＝[x y z]T＝[vt R0 0]T (2)
wherein v represents the moving speed of the ferromagnetic object, t represents the moving time of the ferromagnetic object,R0represented as the closest contact path between the ferromagnetic target and the sensor;
the magnetic moment vector m is expressed in the three-dimensional rectangular coordinate system as:
m＝|m|·m'(α,β) (3)
where | m | represents the magnetic moment strength, m '(α, β) represents a unit vector of the magnetic moment direction, and m' (α, β) ═ cos α sin β sin α sin β cos β]TAlpha represents an included angle between the projection of the magnetic moment direction on the XOY plane and the X axis, beta represents an included angle between the magnetic moment direction and the Z axis, the value range of alpha is 0 to 360, and the value range of beta is 0 to 180;
substituting the formula (2) and the formula (3) into the formula (1) to obtain a calculation formula of the coordinate induction magnetic field generated by the magnetic dipole:
Figure BDA0002627232880000103
wherein B (t) represents the coordinate induced magnetic field, μ, produced by the magnetic dipole0Expressed as the vacuum permeability, μ0＝4π×10-7H/m，R0Expressed as the closest contact path between the ferromagnetic target object and the sensor, | m | expressed as the magnetic moment strength, v expressed as the movement speed of the ferromagnetic target object, t expressed as the movement time of the ferromagnetic target object, m' expressed as the magnetic moment direction;
in actual magnetic anomaly detection, the sensitive direction of the sensor is known, but the motion direction of the ferromagnetic target object is unknown, so in the three-dimensional rectangular coordinate system, the magnetic anomaly signal received by the sensor needs to be obtained through the included angle relationship (sensitive direction) between the sensor and the coordinate system. The coordinate sensitive directions of the sensors are as follows:
k(θ,φ)＝[cos θ sin φ sin θ sin φ cos φ] (5)
wherein k (theta, phi) is a unit vector of a coordinate sensitive direction of the sensor, theta is an included angle between a projection of an original sensitive direction of the sensor on an XOY plane of a three-dimensional rectangular coordinate system and an X axis, phi is an included angle between the sensitive direction of the sensor and a Z axis, the value range of theta is 0 to 360, and the value range of phi is 0 to 180;
(3) establishing a magnetic dipole magnetic anomaly signal analysis model
Establishing a magnetic dipole magnetic anomaly signal analysis model according to the coordinate sensitive direction of the sensor and a coordinate induction magnetic field generated by the magnetic dipole, wherein the magnetic dipole magnetic anomaly signal analysis model specifically comprises the following steps:
Bs(t)＝k(θ,φ)·B(t) (6)
wherein, Bs(t) is the projection of B (t) along the sensitive direction of the sensor coordinates, Bs(t) represents the magnetic anomaly signal obtained by the sensor, k (theta, phi) represents a unit vector of the coordinate sensitive direction of the sensor, and B (t) represents a coordinate induced magnetic field generated by the magnetic dipole;
therefore, the establishment of a parameterized magnetic dipole magnetic anomaly signal analysis model is completed, and the magnetic anomaly signal B obtained by the sensor can be known according to the formulas (4) to (6)s(t) depends on the parameters α, β, θ, φ, R0V and | m |.
Step two: the upper limit frequency point characteristic analysis and calculation of the magnetic anomaly signal frequency domain energy specifically comprises the following steps:
determining the magnetic anomaly signal BsThe spectrum of (t) is:
Figure BDA0002627232880000111
where j represents the amount of imaginary units, f represents the amount of frequency, and t represents the amount of time;
because the energy of the magnetic anomaly signal in the magnetic anomaly detection is mainly concentrated on the extremely low frequency even the quasi-static frequency, the lower limit frequency point of the frequency domain energy distribution of the magnetic anomaly signal can be regarded as 0Hz, and the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal satisfies the following conditions:
Figure BDA0002627232880000112
wherein
Figure BDA0002627232880000113
Expressed as satisfying the condition, fhThe frequency point corresponding to 99% of the accumulated energy of the magnetic abnormal signal from the low frequency to the high frequency can be considered;
according to the formulas (4) to (8), the upper limit frequency point f of the frequency domain energy of the magnetic anomaly signalhDepending on the magnetic moment strength | m |, the magnetic moment direction m' (α, β), the coordinate sensitive direction k (θ, φ) of the sensor, the closest contact path R between the ferromagnetic target and the sensor0And the speed of movement v of the ferromagnetic target;
next, f was investigated using a controlled variable methodhThe value is changed under different conditions, and the initial variable is | m | ═ 2Am2,R01.2m, v 0.8m/s, m' (α, β) 143 °,72 °, and k (θ, Φ) 115 °,28 °, provided that the initial variable is unchanged when the other variables are changed. It should be noted that these seven variables are arbitrarily chosen and their characteristic correlation curves or contour plots are shown in fig. 3. The variation range of | m | is 1 to 20Am when the intensity of magnetic moment influences the calculation2. Obtained fhThe curve along with | m | is shown in FIG. 3(a), and f can be seenhIs independent of | m |. In contrast, fhAnd R0And v there is a linear relationship as in FIG. 3(b), i.e., fhProportional to v, fhInverse ratio to R0. However, m' (α, β) and k (θ, φ) are relative to fhThe effect of (c) is non-linear, as shown in fig. 3(c) (d). Therefore, f can be summarized preliminarilyhThe formula satisfied is
Figure BDA0002627232880000121
Where g (α, β, θ, φ) represents a non-linear function with respect to angles α, β, θ and φ.
The embodiment analyzes the magnetic moment strength | m |, the magnetic moment direction m' (alpha, beta), the sensitive direction k (theta, phi) of the sensor, and the nearest contact path R between the ferromagnetic target and the sensor0And the moving speed v of the ferromagnetic target object and the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhThe calculation formula of the upper limit frequency point of the magnetic anomaly signal frequency domain energy is obtained, and the quick estimation of the upper limit cut-off frequency of the magnetic anomaly signal under a certain detection scene can be realized according to the formula.
Example 2:
the construction methods of Low Pass Filters (LPF) used for detecting magnetic abnormal signals in different fields are different, for example, for aviation electromagnetic detection, the band-pass filtering frequency is set to be 0.06-0.6Hz, 0.06-1.6Hz and 0.1-0.3 Hz; vehicle sensing studies have employed filtering frequencies of 0.001-7Hz and 0.6-10 Hz; for small magnetic foreign metal detection, attempts have been made to use 2<f<A filter frequency of 20Hz is used in the commercial product manufacturing industry; in public safety applications, 0.5 is used for equipment for detecting people carrying suspicious metal objects<f<A sampling frequency of 5 Hz. However, researchers often select the cut-off frequency empirically to construct the low-pass filter without theoretical basis, which results in that the low-pass filter constructed by the method cannot achieve the noise reduction effect well. In order to solve such a problem, the present application has obtained the upper limit frequency point f of the frequency domain energy of the magnetic anomaly signal in the above embodiment 1hOn the basis of the calculation formula, the self-adaptive low-pass filter is constructed, and the specific method comprises the following steps:
the method comprises the following steps: upper limit frequency point f for simplifying magnetic abnormal signal frequency domain energyhIs calculated by
It should be noted that the analytic form of g (α, β, θ, φ) is difficult to derive. Therefore, in order to estimate the upper limit of the g function, the present application adopts a processing method based on the monte carlo algorithm to perform estimation. The Monte Carlo method is an effective simulation approximation method, can search approximate suboptimal solutions with less workload, and does not need complex calculation. This application chooses 10 randomly6The simulation was performed by combining variables in the uniformly distributed argument space. Fig. 4 shows the probability distribution of the result of the g function calculation, and it can be seen that g (α, β, θ, Φ) is an interval-limited function whose maximum value max (g) is approximately equal to 0.85. To be able to contain most of the detectionIn this case, we select the maximum value of the g function to calculate the upper limit frequency point at a certain speed and at CPA. Therefore, the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhThe calculation formula of (c) can be simplified as:
Figure BDA0002627232880000131
it can be seen that f in the formula (10)hIs dependent only on R0And v, then f is judgedhIs reduced to estimate R0And v. In fact, for different detection scenes, R can be judged in advance0And the limit of v. Take aeromagnetic as an example, R0And v is usually very large, 100. ltoreq.R respectively01000m or less and 50 v or less and 300m/s, and the characteristic results are shown in Table 1. When (R)0When v) — (1000,50), the minimum value fh0.04Hz, maximum value fh2.5Hz (R)0V) ═ 100,300. Estimated 0.04 ≦ fhThe interval less than or equal to 2.5Hz can be selected as the frequency distribution characteristic interval of the aeromagnetic detection.
TABLE 1 upper limit frequency f for aeromagnetic detectionh(Hz)
Figure BDA0002627232880000132
TABLE 2 detection upper limit frequency f of surface shiph(Hz)
Figure BDA0002627232880000141
TABLE 3 vehicle detection upper limit frequency fh(Hz)
Figure BDA0002627232880000142
TABLE 4 indoor detection upper limit frequency fh(Hz)
Figure BDA0002627232880000143
Figure BDA0002627232880000151
By applying a parameter R0And v adjustment, the estimation method is applicable to other detection scenes, such as water surface ship detection, vehicle detection and indoor test, which are respectively shown in tables 2, 3 and 4. As can be seen from the table, different applications of the MAD can identify the distribution of upper limit frequency points in the intermediate frequency domain in aeromagnetic detection, and the aeromagnetic detection is f is more than or equal to 0.04hNot more than 2.55Hz, and not less than 0.0017 and not more than f of surface shiphNot more than 0.255Hz, and not less than 0.04 f for automobilehNot more than 4.25Hz, and indoor f is not less than 0.04h≤21.25Hz。
The process simplifies the upper limit frequency point f of the nonlinear parameter to the frequency domain energy of the magnetic abnormal signalhOnly need to consider R0F can be quickly calculated by the sum vh. The experience numerical table comprises a plurality of detection scenes, and the upper limit frequency point f of the frequency domain energy of the magnetic anomaly signal can be obtained by inquiring the experience numerical tablehThe calculation efficiency is improved. Further, f is represented by the formula (10)hResearch opens up the possibility of accurately extracting target signals severely blurred by external noise by using signal frequency boundaries.
(2) The upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhIs equivalent to the optimum cut-off frequency f of the low-pass filtercA value of (i), i.e. fc＝fhAnd designing a low-pass filter. The low-pass filter under the design can obtain a higher signal-to-noise ratio while retaining the original signal.
Example 3:
the invention also provides a computing system of the upper limit frequency point of the magnetic anomaly signal frequency domain energy, which comprises a magnetic dipole magnetic anomaly signal analysis model establishing module and an upper limit frequency point computing module;
the magnetic dipole magnetic anomaly signal analysis model establishing module establishes a magnetic dipole magnetic anomaly signal analysis model by utilizing the original sensitive direction of the sensor and the original induction magnetic field generated by the magnetic dipole; the parameters for establishing the magnetic dipole magnetic anomaly signal analysis model comprise magnetic moment strength, magnetic moment direction, coordinate sensitive direction of the sensor, a nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object; the coordinate sensitive direction of the sensor is a coordinate representation of the original sensitive direction of the sensor;
the upper limit frequency point calculation module is used for analyzing the relationship between the upper limit frequency point of the magnetic anomaly signal frequency domain energy and the magnetic moment intensity, the magnetic moment direction, the coordinate sensitive direction of the sensor, the nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object according to the magnetic dipole magnetic anomaly signal analysis model, the frequency spectrum of the magnetic anomaly signal and a control variable method, so as to obtain a calculation formula of the upper limit frequency point of the magnetic anomaly signal frequency domain energy;
the magnetic dipole magnetic anomaly signal analysis model establishing module specifically comprises: the device comprises a magnetic dipole model establishing unit, a three-dimensional rectangular coordinate system establishing unit, a coordinate conversion unit and a coordinated magnetic dipole magnetic anomaly signal analysis model establishing unit;
the magnetic dipole model establishing unit is used for establishing a magnetic dipole model equivalent to the ferromagnetic target object and determining an original induction magnetic field generated by the magnetic dipole in the magnetic dipole model equivalent to the ferromagnetic target object;
the three-dimensional rectangular coordinate system establishing unit is used for establishing a three-dimensional rectangular coordinate system by taking the sensor as an origin and taking a plane formed by the motion tracks of the sensor and the ferromagnetic target object as an XOY plane, wherein the motion direction of the ferromagnetic target object is the X direction, and the direction of a nearest contact path between the ferromagnetic target object and the sensor is the Y direction;
the coordinate conversion unit converts the original induction magnetic field into a coordinate induction magnetic field under the three-dimensional rectangular coordinate system by using the three-dimensional rectangular coordinate system, and converts the original sensitive direction of the sensor into a coordinate sensitive direction under the three-dimensional rectangular coordinate system;
the coordinated magnetic dipole magnetic anomaly signal analysis model establishing unit is used for establishing a magnetic dipole magnetic anomaly signal analysis model according to the coordinate sensitive direction of the sensor and a coordinate induction magnetic field generated by the magnetic dipole;
the upper limit frequency point calculating module specifically includes: a spectrum calculating unit, a condition calculating unit, a relation analyzing unit and an upper limit frequency point calculating unit;
the frequency spectrum calculating unit is used for calculating the magnetic abnormal signal Bs(t) a spectrum of:
Figure BDA0002627232880000161
where j represents the amount of imaginary units, f represents the amount of frequency, and t represents the amount of time;
the condition calculating unit is used for calculating the magnetic abnormal signal B according to the magnetic abnormal signals(t), determining a conditional formula of an upper limit frequency point satisfying the frequency domain energy of the magnetic anomaly signal as follows:
Figure BDA0002627232880000162
wherein
Figure BDA0002627232880000163
Expressed as satisfying the condition;
the relation analysis unit is used for analyzing the magnetic abnormal signal Bs(t) obtaining an upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal by using a frequency spectrum calculation formula, a conditional formula of the upper limit frequency point satisfying the frequency domain energy of the magnetic abnormal signal and the magnetic dipole magnetic abnormal signal analysis modelhWith the magnetic moment strength | m |, the magnetic moment direction m' (α, β), the coordinate sensitive direction k (θ, φ) of the sensor, the closest contact path R between the ferromagnetic target and the sensor0Is related to the moving speed v of the ferromagnetic target object;
the upper limit frequency point calculation unit is used for determining an upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal according to a control variable methodhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is in a direct proportion relation with the movement speed v of the ferromagnetic target objecthWith the nearest contact path R0In inverse proportion, the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is obtained in a nonlinear relation with a function formed by the magnetic moment direction and the coordinate sensitive directionhIs calculated by the formula
Figure BDA0002627232880000171
Where g (α, β, θ, φ) represents a non-linear function with respect to angles α, β, θ and φ.
The emphasis of each embodiment in the present specification is on the difference from the other embodiments, and the same and similar parts among the various embodiments may be referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. A method for calculating an upper limit frequency point of magnetic anomaly signal frequency domain energy is characterized by comprising the following steps:
establishing a magnetic dipole magnetic anomaly signal analysis model by utilizing the original sensitive direction of the sensor and the original induction magnetic field generated by the magnetic dipole; the parameters for establishing the magnetic dipole magnetic anomaly signal analysis model comprise magnetic moment strength, magnetic moment direction, coordinate sensitive direction of the sensor, a nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object; the coordinate sensitive direction of the sensor is a coordinate representation of the original sensitive direction of the sensor;
according to the magnetic dipole magnetic anomaly signal analysis model, the frequency spectrum of the magnetic anomaly signal and a control variable method, analyzing the relationship between the upper limit frequency point of the magnetic anomaly signal frequency domain energy and the magnetic moment intensity, the magnetic moment direction, the coordinate sensitive direction of the sensor, the nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object, and obtaining a calculation formula of the upper limit frequency point of the magnetic anomaly signal frequency domain energy.
2. The method for calculating the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal according to claim 1, wherein the establishing of the magnetic dipole magnetic anomaly signal analysis model by using the original sensitive direction of the sensor and the original induced magnetic field generated by the magnetic dipole specifically comprises:
establishing a magnetic dipole model equivalent to the ferromagnetic target object, and determining an original induction magnetic field generated by a magnetic dipole in the magnetic dipole model;
establishing a three-dimensional rectangular coordinate system by taking the sensor as an origin and taking a plane formed by the motion tracks of the sensor and the ferromagnetic target object as an XOY plane, wherein the motion direction of the ferromagnetic target object is the X direction, and the direction of a nearest contact path between the ferromagnetic target object and the sensor is the Y direction;
converting the original induction magnetic field into a coordinate induction magnetic field under the three-dimensional rectangular coordinate system by using the three-dimensional rectangular coordinate system, and converting the original sensitive direction of the sensor into a coordinate sensitive direction under the three-dimensional rectangular coordinate system;
and establishing a magnetic dipole magnetic anomaly signal analysis model according to the coordinate sensitive direction of the sensor and the coordinate induction magnetic field generated by the magnetic dipole.
3. The method according to claim 2, wherein the step of converting the original sensing magnetic field into a coordinate sensing magnetic field in a three-dimensional rectangular coordinate system and converting the original sensitive direction of the sensor into a coordinate sensitive direction in the three-dimensional rectangular coordinate system by using the three-dimensional rectangular coordinate system specifically comprises:
determining the original induction magnetic field generated by the magnetic dipole as follows:
Figure FDA0002627232870000021
wherein mu0Expressed as the vacuum permeability, μ0＝4π×10-7H/m, r is expressed as a coordinate vector of the magnetic dipole with respect to the sensor, r ═ x y z]TAnd m is represented as a magnetic moment vector,
Figure FDA0002627232870000023
determining a coordinate vector of the magnetic dipole relative to the sensor in the three-dimensional rectangular coordinate system as:
r＝[x y z]T＝[vt R0 0]T
wherein v represents the moving speed of the ferromagnetic object, t represents the moving time of the ferromagnetic object, R0Represented as the closest contact path between the ferromagnetic target and the sensor;
calculating the magnetic moment vector m under the three-dimensional rectangular coordinate system:
m＝|m|·m'(α,β)
where | m | represents the magnetic moment strength, m '(α, β) represents a unit vector of the magnetic moment direction, and m' (α, β) ═ cos α sin β sin α sin β cos β]TAlpha represents an included angle between the projection of the magnetic moment direction on the XOY plane and the X axis, beta represents an included angle between the magnetic moment direction and the Z axis, the value range of alpha is 0 to 360, and the value range of beta is 0 to 180;
substituting a calculation formula of the magnetic dipole relative to a coordinate vector of the sensor in the three-dimensional rectangular coordinate system and the calculation formula of the magnetic moment vector in the three-dimensional rectangular coordinate system into a calculation formula of an original induction magnetic field generated by the magnetic dipole to obtain a calculation formula of a coordinate induction magnetic field generated by the magnetic dipole:
Figure FDA0002627232870000022
wherein B (t) represents the coordinate induced magnetic field, μ, produced by the magnetic dipole0Expressed as the vacuum permeability, μ0＝4π×10-7H/m，R0Expressed as the closest contact path between the ferromagnetic target object and the sensor, | m | expressed as the magnetic moment strength, v expressed as the movement speed of the ferromagnetic target object, t expressed as the movement time of the ferromagnetic target object, m' expressed as the magnetic moment direction;
determining the coordinate sensitive direction of the sensor as:
k(θ,φ)＝[cosθsinφ sinθsinφ cosφ]
wherein k (theta, phi) is a unit vector of the coordinate sensitive direction of the sensor, theta is an included angle between the projection of the original sensitive direction of the sensor on an XOY plane of a three-dimensional rectangular coordinate system and an X axis, phi is an included angle between the sensitive direction of the sensor and a Z axis, the value range of theta is 0 to 360, and the value range of phi is 0 to 180.
4. The method for calculating the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal according to claim 3, wherein the magnetic dipole magnetic anomaly signal analysis model is specifically as follows:
Bs(t)＝k(θ,φ)·B(t)
wherein, Bs(t) is the projection of B (t) along the sensitive direction of the sensor coordinates, Bs(t) is a magnetic anomaly signal obtained by the sensor, k (theta, phi) is a unit vector of a coordinate sensitive direction of the sensor, and B (t) is a coordinate induced magnetic field generated by the magnetic dipole.
5. The method for calculating the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal according to claim 4, wherein the method for calculating the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal is obtained by analyzing the relationship between the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal and the magnetic moment strength, the magnetic moment direction, the coordinate sensitivity direction of the sensor, the closest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object according to the magnetic dipole magnetic anomaly signal analysis model, the frequency spectrum of the magnetic anomaly signal and a control variable method, and specifically comprises the following steps:
determining the magnetic anomaly signal BsThe spectrum of (t) is:
Figure FDA0002627232870000031
where j represents the amount of imaginary units, f represents the amount of frequency, and t represents the amount of time;
according to the magnetic abnormal signal Bs(t), determining a conditional formula of an upper limit frequency point meeting the frequency domain energy of the magnetic anomaly signal as follows:
Figure FDA0002627232870000032
wherein
Figure FDA0002627232870000033
Expressed as satisfying the condition;
according to the magnetic abnormal signal Bs(t) obtaining an upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal by using a frequency spectrum calculation formula, a conditional formula of the upper limit frequency point satisfying the frequency domain energy of the magnetic abnormal signal and the magnetic dipole magnetic abnormal signal analysis modelhWith the magnetic moment strength | m |, the magnetic moment direction m' (α, β), the coordinate sensitive direction k (θ, φ) of the sensor, theClosest contact path R between ferromagnetic target and the sensor0Is related to the moving speed v of the ferromagnetic target object;
determining the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal according to a control variable methodhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is in a direct proportion relation with the movement speed v of the ferromagnetic target objecthWith the nearest contact path R0In inverse proportion, the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is obtained in a nonlinear relation with a function formed by the magnetic moment direction and the coordinate sensitive directionhIs calculated by the formula
Figure FDA0002627232870000041
Where g (α, β, θ, φ) represents a non-linear function with respect to angles α, β, θ and φ.
6. A method for constructing an adaptive low-pass filter, comprising:
estimating a value of a function formed by the magnetic moment direction and the coordinate sensitive direction of the sensor according to a Monte Carlo algorithm;
simplifying the calculation formula of the upper limit frequency point of the magnetic anomaly signal frequency domain energy in claim 1 according to the value of the function, the movement speed of the ferromagnetic target object and the nearest contact path between the ferromagnetic target object and the sensor;
acquiring a specific value of the movement speed of the ferromagnetic target object and a specific value of the nearest contact path, and obtaining a value of an upper limit frequency point of the magnetic anomaly signal frequency domain energy according to a simplified calculation formula of the upper limit frequency point of the magnetic anomaly signal frequency domain energy;
and designing the low-pass filter by taking the value of the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal as the value of the optimal cut-off frequency of the low-pass filter.
7. The method as claimed in claim 6, wherein the simplified calculation formula of the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal is:
Figure FDA0002627232870000042
wherein v is represented by the speed of movement, R, of the ferromagnetic target0Represented as the closest contact path between the ferromagnetic target and the sensor.
8. A computing system of an upper limit frequency point of magnetic anomaly signal frequency domain energy is characterized by comprising a magnetic dipole magnetic anomaly signal analysis model establishing module and an upper limit frequency point computing module;
the magnetic dipole magnetic anomaly signal analysis model establishing module establishes a magnetic dipole magnetic anomaly signal analysis model by utilizing the original sensitive direction of the sensor and the original induction magnetic field generated by the magnetic dipole; the parameters for establishing the magnetic dipole magnetic anomaly signal analysis model comprise magnetic moment strength, magnetic moment direction, coordinate sensitive direction of the sensor, a nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object; the coordinate sensitive direction of the sensor is a coordinate representation of the original sensitive direction of the sensor;
the upper limit frequency point calculation module is used for analyzing the relationship between the upper limit frequency point of the magnetic anomaly signal frequency domain energy and the magnetic moment intensity, the magnetic moment direction, the coordinate sensitive direction of the sensor, the nearest contact path between the ferromagnetic target object and the sensor and the movement speed of the ferromagnetic target object according to the magnetic dipole magnetic anomaly signal analysis model, the frequency spectrum of the magnetic anomaly signal and a control variable method, so as to obtain a calculation formula of the upper limit frequency point of the magnetic anomaly signal frequency domain energy.
9. The system for calculating the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal according to claim 8, wherein the magnetic dipole magnetic anomaly signal analysis model establishing module specifically comprises: the device comprises a magnetic dipole model establishing unit, a three-dimensional rectangular coordinate system establishing unit, a coordinate conversion unit and a coordinated magnetic dipole magnetic anomaly signal analysis model establishing unit;
the magnetic dipole model establishing unit is used for establishing a magnetic dipole model equivalent to the ferromagnetic target object and determining an original induction magnetic field generated by the magnetic dipole in the magnetic dipole model equivalent to the ferromagnetic target object;
the three-dimensional rectangular coordinate system establishing unit is used for establishing a three-dimensional rectangular coordinate system by taking the sensor as an origin and taking a plane formed by the motion tracks of the sensor and the ferromagnetic target object as an XOY plane, wherein the motion direction of the ferromagnetic target object is the X direction, and the direction of a nearest contact path between the ferromagnetic target object and the sensor is the Y direction;
the coordinate conversion unit converts the original induction magnetic field into a coordinate induction magnetic field under the three-dimensional rectangular coordinate system by using the three-dimensional rectangular coordinate system, and converts the original sensitive direction of the sensor into a coordinate sensitive direction under the three-dimensional rectangular coordinate system;
the coordinated magnetic dipole magnetic anomaly signal analysis model establishing unit is used for establishing a magnetic dipole magnetic anomaly signal analysis model according to the coordinate sensitive direction of the sensor and the coordinate induction magnetic field generated by the magnetic dipole.
10. The system for calculating the upper limit frequency point of the frequency domain energy of the magnetic anomaly signal according to claim 8, wherein the upper limit frequency point calculating module specifically comprises: a spectrum calculating unit, a condition calculating unit, a relation analyzing unit and an upper limit frequency point calculating unit;
the frequency spectrum calculating unit is used for calculating the magnetic abnormal signal Bs(t) a spectrum of:
Figure FDA0002627232870000061
where j represents the amount of imaginary units, f represents the amount of frequency, and t represents the amount of time;
the condition calculating unit is used for calculating the magnetic abnormal signal B according to the magnetic abnormal signals(t), determining a conditional formula of an upper limit frequency point satisfying the frequency domain energy of the magnetic anomaly signal as follows:
Figure FDA0002627232870000062
wherein
Figure FDA0002627232870000063
Expressed as satisfying the condition;
the relation analysis unit is used for analyzing the magnetic abnormal signal Bs(t) obtaining an upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal by using a frequency spectrum calculation formula, a conditional formula of the upper limit frequency point satisfying the frequency domain energy of the magnetic abnormal signal and the magnetic dipole magnetic abnormal signal analysis modelhWith the magnetic moment strength | m |, the magnetic moment direction m' (α, β), the coordinate sensitive direction k (θ, φ) of the sensor, the closest contact path R between the ferromagnetic target and the sensor0Is related to the moving speed v of the ferromagnetic target object;
the upper limit frequency point calculation unit is used for determining an upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal according to a control variable methodhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is in a direct proportion relation with the movement speed v of the ferromagnetic target objecthWith the nearest contact path R0In inverse proportion, the upper limit frequency point f of the frequency domain energy of the magnetic abnormal signalhThe upper limit frequency point f of the frequency domain energy of the magnetic abnormal signal is obtained in a nonlinear relation with a function formed by the magnetic moment direction and the coordinate sensitive directionhIs calculated by the formula
Figure FDA0002627232870000064
Where g (α, β, θ, φ) represents a non-linear function with respect to angles α, β, θ and φ.
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CN112698412A (en) * 2020-11-27 2021-04-23 北京自动化控制设备研究所 Shaft frequency magnetic abnormal signal processing method based on magnetic buoy
CN113218393A (en) * 2021-04-06 2021-08-06 青岛海月辉科技有限公司 Underwater target distributed networking positioning method based on magnetic anomaly total field matching positioning algorithm
CN113866834A (en) * 2021-09-15 2021-12-31 吉林大学 Entropy filtering-based field source center position inversion method
CN114296140A (en) * 2021-11-18 2022-04-08 电子科技大学 Magnetic anomaly detection method based on gradient information entropy orthogonal basis decomposition
CN114296140B (en) * 2021-11-18 2023-08-18 电子科技大学 Magnetic anomaly detection method based on gradient information entropy orthogonal basis decomposition
CN115236755A (en) * 2022-07-25 2022-10-25 中国自然资源航空物探遥感中心 Aeromagnetic abnormal boundary detection method and device based on tensor eigenvalue
CN115236755B (en) * 2022-07-25 2023-10-03 中国自然资源航空物探遥感中心 Tensor eigenvalue-based aeromagnetic anomaly boundary detection method and device

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