Rock magnetism measuring method based on ultrahigh-sensitivity three-axis magnetic field measuring device

Abstract

According to the rock magnetism measurement method based on the ultrahigh-sensitivity three-axis magnetic field measurement device, a linearly polarized light rotation angle detection method is combined with a circularly polarized light absorption method, the ultrahigh-sensitivity three-axis magnetic field measurement device is built based on two beams of linearly polarized light and one beam of circularly polarized light, and three-axis magnetic field measurement of a rock sample to be measured can be achieved. A sample feeding system is used for controlling a sample to move in a measurement area, magnetic field responses of all measurement points of a three-axis magnetic field measurement device in the sample moving process are recorded, a machine learning model is trained through a stochastic gradient descent algorithm based on measurement data, the magnetic moment is determined through weight parameters completed through model training, and therefore measurement of the magnetism of the rock sample is achieved. A multi-channel sensor is built through the high-sensitivity magnetic field measuring device, compared with a traditional method, the magnetic field sensitivity of the device can be improved to the fT magnitude, and the substance magnetism, such as lunar soil magnetism, which is difficult to detect by a current instrument can be measured by placing a detected sample in a low-residual-magnetism environment.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of quantum sensing, and particularly relates to a rock magnetic measurement method based on an ultrahigh-sensitivity three-axis magnetic field measurement device. BACKGROUND

[0002] The measurement of rock magnetism is crucial for paleomagnetism and rock magnetism research. The rock age can be inferred, the plate tectonics theory can be verified, the dynamics of the earth's magnetic field can be studied, and the flow direction of ore veins and lava flows can be estimated through the rock magnetism. The strength of the rock magnetism is mainly represented by the size of the magnetic moment of the rock. The current instruments for measuring the magnetic moment use magnetic sensors including an induction coil, a fluxgate sensor, a magneto-impedance sensor, and a superconducting quantum interference device (SQUID). The induction coil is commonly used in high-frequency vibrating sample magnetometers or rotating magnetometers. Its structure limits it to measuring large-volume samples. The sensitivity of the fluxgate sensor and the magneto-impedance sensor is not outstanding, and they cannot measure rock samples with extremely weak magnetism. In comparison, the SQUID is mainly used in high-precision magnetic material analysis field due to its high sensitivity and high bandwidth, and it is irreplaceable. However, the SQUID can only measure small-volume samples. When measuring large-volume samples, the samples need to be crushed, which damages the integrity of the samples. On the other hand, the SQUID needs to be equipped with a low-temperature cooling device, which results in a large volume and high measurement cost. Compared with the SQUID, the magnetic field measurement device based on the spin-exchange-relaxation-free (SERF) effect has the advantages of ultrahigh sensitivity and no need for low-temperature cooling. It has surpassed the SQUID and become the instrument with the highest sensitivity for magnetic field measurement, reaching the sensitivity of sub-fT level. In recent years, it has been gradually applied to the research in the field of paleomagnetism.

[0003] Related document CN202411466136 describes a magnetic moment comparator device, including a background magnetic field generating component, an atomic magnetometer for measuring absolute magnetic fields, a first current-carrying standard coil component, a magnetic sample, and a measurement module. This invention provides a magnetic moment comparator device and measurement method. Using the condition that the background magnetic field remains constant, the current flowing through the standard coil is changed in real time. The magnetic moment of the magnetic sample is then equal in magnitude and opposite in direction to the magnetic moment of the current-carrying standard coil, thus the magnetic moment of the magnetic sample is measured using the magnetic moment of the current-carrying standard coil. This invention uses an atomic magnetometer as the magnetic field sensor, with a range of 100 nT to 100,000 nT. To ensure that the atomic magnetometer can effectively respond to the weak magnetic field generated by the magnetic sample, a background magnetic field of 200 nT to 20,000 nT needs to be generated within a magnetic shielding cylinder using a background magnetic field coil, confining the measured magnetic field within the sensor's range. However, for ultra-weak magnetic samples such as rocks, the magnetic field at 50 mm is only on the order of about 0.1 nT. At this time, the background magnetic field set by the device is significantly higher than the sample signal intensity. The strong background magnetic field will completely drown out the extremely weak rock sample signal, making it difficult to accurately measure its magnetic moment information. Summary of the Invention

[0004] This invention addresses the deficiencies and shortcomings of existing technologies by proposing a method for measuring the magnetic properties of rocks based on an ultra-high sensitivity triaxial magnetic field measuring device. It employs a combination of linearly polarized light rotation angle detection and circularly polarized light absorption. The ultra-high sensitivity triaxial magnetic field measuring device is constructed using two linearly polarized beams and one circularly polarized beam to achieve triaxial magnetic field measurement of the sample. A sample delivery system controls the movement of the sample within the measurement area, recording the magnetic field response at each measurement point of the triaxial magnetic field measuring device during sample movement. Based on the measurement data, a machine learning model is trained using a stochastic gradient descent algorithm. The magnetic moment is determined through the weight parameters obtained from the model training, thereby achieving the measurement of the magnetic properties of the rock sample.

[0005] The technical solution of the present invention is as follows:

[0006] A method for measuring rock magnetism based on an ultra-high sensitivity triaxial magnetic field measuring device, characterized by comprising the following steps:

[0007] Step 1: Configure the ultra-high sensitivity triaxial magnetic field measuring device and the sample delivery system so that the rock sample to be tested can be located at each preset measuring point in the measurement area;

[0008] Step 2: The ultra-high sensitivity triaxial magnetic field measuring device is used to perform triaxial magnetic field measurement by combining the two-beam linearly polarized light rotation angle detection method with the one-beam circularly polarized light absorption method. The first beam of linearly polarized light passes through the gas cell along the Y-axis, the second beam of linearly polarized light passes through the gas cell along the X-axis, and the third beam of circularly polarized light passes through the gas cell along the Z-axis.

[0009] Step 3: Use the sample delivery system to control the movement of the rock sample to be tested within the measurement area, and record the magnetic field response of each measurement point of the triaxial magnetic field measuring device during the movement of the rock sample to be tested;

[0010] Step 4: Based on the measurement data, a machine learning model is trained using the stochastic gradient descent algorithm. The magnetic moment is determined by the weight parameters obtained after the model training, thereby realizing the measurement of the magnetism of the rock sample.

[0011] Step 3 includes: moving the rock sample to be tested horizontally along the Y-axis using the sample delivery system, stopping the rock sample for 5 seconds at distances of 30mm, 32mm, 34mm, 36mm, 38mm, 40mm, 42mm, 44mm, 46mm, 48mm, 50mm, and 52mm from the gas chamber, and recording the response signal of the triaxial magnetic field measuring device after stabilization at each point. , , and These are the measurement points. The x-axis magnetic field, y-axis magnetic field and z-axis magnetic field will As the corresponding measurement point A set of measured data Each measurement yielded 12 sets of data.

[0012] Step 4 involves using the stochastic gradient descent algorithm to optimize the regression machine learning model based on the 12 sets of data obtained from each measurement, thus transforming the problem of solving the unknown magnetic moment into a machine learning problem.

[0013] Step 4 includes the following expression:

[0014] ,

[0015] ,

[0016] ,

[0017] ,

[0018] in In magnetic dipole coordinates The theoretical magnetic field generated along the x-axis In magnetic dipole coordinates The theoretical magnetic field generated along the y-axis In magnetic dipole coordinates The theoretical magnetic field generated along the z-axis The permeability of free space, , , respectively are the x-axis magnetic moment, y-axis magnetic moment, z-axis magnetic moment of the measured rock sample, R is the measurement distance, G is the gradient function, is the gradient of the mean square error is the gradient operator, is the three-axis theoretical magnetic field, is the three-axis measured magnetic field, n is the total number of measurement points, i is the sequence number of the measurement point, is the updated weight parameter, is the model weight parameter, and s is the learning rate.

[0019] Step 4 includes: 12 groups of data are optimized by the random gradient descent algorithm to complete the optimization of the model as a training cycle, and the training cycle is set to 500 rounds. Finally, the weight parameter of the model convergence state can obtain the magnetic moment of the measured rock sample, thereby realizing the measurement of the magnetism of the measured rock sample.

[0020] Step 2 includes obtaining the voltage value output by the Z-axis photoelectric acquisition module by using the third beam of circularly polarized light along the Z-axis passing through the gas chamber , obtaining the voltage value output by the X-axis photoelectric acquisition module by using the second beam of linearly polarized light along the X-axis passing through the gas chamber , and obtaining the voltage value output by the Y-axis photoelectric acquisition module by using the first beam of linearly polarized light along the Y-axis passing through the gas chamber .

[0021] In step 1, the ultra-high sensitivity three-axis magnetic field measuring device includes a beam splitter connected to the first laser, a first detection light barrel module, a first detection light barrel channel, a gas chamber, a first detection light barrel channel, a first detection light barrel channel, a first detection light barrel module and a first photoelectric acquisition module connected in sequence. The second split output end of the beam splitter is connected to the second detection light barrel module, the second detection light barrel channel, the gas chamber, the second detection light barrel channel, the second mirror, the second detection light barrel module, the second photoelectric acquisition module and the upper computer in sequence. The upper computer is connected to the sample feeding system through the sample feeding system driver, and the sample feeding system includes a dovetail slot sliding table and a rotating shaft connected to the motor, respectively. One end of the rotating shaft is connected to the dovetail slot sliding table, and the other end is connected to the sample groove and extends into the measurement area.

[0022] In step 1, the ultra-high sensitivity three-axis magnetic field measuring device includes a second laser, a pump light barrel module, a pump light barrel channel, a gas chamber, a pump light barrel channel, a third mirror and a third photoelectric acquisition module connected in sequence. The gas chamber is located in the oven, and the oven is located in the coil. The coil includes a Y-axis magnetic compensation coil, a Z-axis magnetic compensation coil and an X-axis magnetic compensation coil. The coil is located in an amorphous magnetic shielding barrel, which is located in a five-layer permalloy magnetic shielding barrel. The coil is connected to the signal generator. ​

[0023] The technical effects of the present application are as follows: the rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device can realize three-axis magnetic field measurement of the rock sample to be measured by adopting the linearly polarized light optical rotation angle detection method combined with the circularly polarized light absorption method, based on two linearly polarized lights and one circularly polarized light to build an ultra-high sensitivity three-axis magnetic field measurement device. The sample is controlled to move in the measurement area by using the sample feeding system, the magnetic field response of each measurement point of the three-axis magnetic field measurement device during the movement of the sample is recorded, the machine learning model is trained based on the measurement data using the stochastic gradient descent algorithm, and the magnetic moment is determined through the weight parameters of the model training, so as to realize the measurement of the magnetism of the rock sample.

[0024] Compared with the prior art, the present application has the following characteristics:

[0025] 1. The present application proposes a method for realizing three-axis magnetic field measurement by adopting the linearly polarized light optical rotation angle detection method combined with the circularly polarized light absorption method, which has not been seen in domestic patent publications;

[0026] 2. The present application proposes a rock magnetic measurement method based on an ultra-high sensitivity three-axis magnetic field measurement device, which is compared with the array magnetometer commonly used in the existing rock magnetic multi-channel measurement scheme. The present application builds a multi-channel sensor through a high-sensitivity magnetic field measurement device, and the magnetic field sensitivity of the device can be improved to the fT level compared with the traditional method;

[0027] 3. The present application uses a high-sensitivity three-axis magnetic field measurement device to place the sample to be measured in a low remanence environment, which can measure the magnetism of substances that are difficult to detect by the current instrument, such as the magnetism of lunar soil. BRIEF DESCRIPTION OF DRAWINGS

[0028] Fig. 1 is the XY plane structure schematic diagram of the ultra-high sensitivity three-axis magnetic field measurement device with a sample feeding system involved in the rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device of the present application.

[0029] Fig. 2 is the YZ plane structure schematic diagram of the ultra-high sensitivity three-axis magnetic field measurement device involved in the rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device of the present application.

[0030] Reference signs are explained as follows: 1- five-layer permalloy magnetic shielding barrel; 2- first detection light barrel access channel; 3- first detection light barrel module; 4- first laser; 5- beam splitter; 6- second detection light barrel access channel; 7- second detection light barrel module; 8- signal generator; 9- Y-axis magnetic compensation coil; 10- Z-axis magnetic compensation coil; 11- X-axis magnetic compensation coil; 12- amorphous magnetic shielding barrel; 13- oven; 14- air chamber; 15- first detection light barrel exit channel; 16- first mirror; 17- first detection light barrel exit module; 18- first photoelectric acquisition module (i.e. y-axis photoelectric acquisition module); 19- second detection light barrel exit channel; 20- second mirror; 21- second detection light barrel exit module; 22- second photoelectric acquisition module (i.e. x-axis photoelectric acquisition module); 23- upper computer; 24- sample feeding system driver; 25- motor; 26- dovetail sliding table; 27- rotating shaft; 28- sample groove; 29- second laser; 30- pumping light barrel module; 31- pumping light barrel access channel; 32- pumping light barrel exit channel; 33- third mirror; 34- third photoelectric acquisition module (i.e. z-axis photoelectric acquisition module); XYZ- orthogonal coordinate system three-axis (i.e. X-axis, Y-axis, and Z-axis). DETAILED DESCRIPTION

[0031] The present application will be described below in conjunction with the accompanying drawings Figs. 1-2 ) and examples.

[0032] Fig. 1 is a XY plane structure schematic diagram of the super-high-sensitivity three-axis magnetic field measuring device with a sample feeding system involved in the rock magnetic measurement method based on the super-high-sensitivity three-axis magnetic field measuring device. Fig. 2 is a YZ plane structure schematic diagram of the super-high-sensitivity three-axis magnetic field measuring device involved in the rock magnetic measurement method based on the super-high-sensitivity three-axis magnetic field measuring device. Referring to Figs. 1-2 , a rock magnetic measurement method based on a super-high-sensitivity three-axis magnetic field measuring device includes the following steps: step 1, configuring the super-high-sensitivity three-axis magnetic field measuring device with a sample feeding system, so that the rock sample to be measured can be positioned at the preset measurement points in the measurement area; step 2, using the super-high-sensitivity three-axis magnetic field measuring device to measure the three-axis magnetic field by adopting two linearly polarized light optical rotation angle detection method combined with one circularly polarized light absorption method, the first linearly polarized light passes through the air chamber along the Y-axis, the second linearly polarized light passes through the air chamber along the X-axis, and the third circularly polarized light passes through the air chamber along the Z-axis; step 3, using the sample feeding system to control the movement of the rock sample to be measured in the measurement area, and recording the magnetic field response of each measurement point of the three-axis magnetic field measuring device during the movement of the rock sample to be measured; step 4, training a machine learning model based on the measurement data using a stochastic gradient descent algorithm, and determining the magnetic moment through the weight parameters of the model training, thereby realizing the measurement of the magnetism of the rock sample.

[0033] Step 3 includes: moving the rock sample to be tested horizontally along the Y-axis using the sample delivery system, stopping the rock sample for 5 seconds at distances of 30mm, 32mm, 34mm, 36mm, 38mm, 40mm, 42mm, 44mm, 46mm, 48mm, 50mm, and 52mm from the gas chamber, and recording the response signal of the triaxial magnetic field measuring device after stabilization at each point. , , and These are the measurement points. The x-axis magnetic field, y-axis magnetic field and z-axis magnetic field will As the corresponding measurement point A set of measured data Each measurement yields 12 sets of data. Step 4 involves using the stochastic gradient descent algorithm to optimize the regression machine learning model based on each of the 12 sets of data obtained from the measurements, transforming the problem of solving for the unknown magnetic moment into a machine learning problem.

[0034] Step 4 includes the following expression:

[0035] ,

[0036] ,

[0037] ,

[0038] ,

[0039] in In magnetic dipole coordinates The theoretical magnetic field generated along the x-axis In magnetic dipole coordinates The theoretical magnetic field generated along the y-axis In magnetic dipole coordinates The theoretical magnetic field generated along the z-axis The permeability of free space, , , These represent the x-axis, y-axis, and z-axis magnetic moments of the rock sample being tested, respectively; R is the measurement distance; and G is the gradient function. Mean square error gradient, It is a triaxial theoretical magnetic field. This is a triaxial measurement of the magnetic field, where n is the total number of measurement points and i is the index of each measurement point. It updates the weight parameters. is the model weight parameter, and s is the learning rate.

[0040] The step 4 includes: completing the optimization of the model by the random gradient descent algorithm with 12 groups of data as a training period, setting the training period as 500 rounds, and finally obtaining the magnetic moment of the measured rock sample through the weight parameter of the model convergence state, so as to realize the measurement of the magnetism of the measured rock sample.

[0041] The step 2 includes obtaining the voltage value output by the Z-axis photoelectric acquisition module by using the third beam of circularly polarized light passing through the gas chamber along the Z-axis , obtaining the voltage value output by the X-axis photoelectric acquisition module by using the second beam of linearly polarized light passing through the gas chamber along the X-axis , and obtaining the voltage value output by the Y-axis photoelectric acquisition module by using the first beam of linearly polarized light passing through the gas chamber along the Y-axis .

[0042] The super-high sensitivity three-axis magnetic field measuring device in step 1 includes a beam splitter 5 connected to the input end of the first laser 4, a first detection light-in bucket module 3, a first detection light-in bucket channel 2, a gas chamber 14, a first detection light-out bucket channel 15, a first mirror 16, a first detection light-out bucket module 17, and a first photoelectric acquisition module 18 connected in sequence to the first split output end of the beam splitter 5, a second detection light-in bucket module 7, a second detection light-in bucket channel 6, the gas chamber 14, a second detection light-out bucket channel 19, a second mirror 20, a second detection light-out bucket module 21, a second photoelectric acquisition module 22, and an upper computer 23 connected in sequence to the second split output end of the beam splitter 5, and the upper computer 23 is connected to a sample feeding system through a sample feeding system driver 24, the sample feeding system includes a dovetail slot sliding table 26 and a rotating shaft 27 connected to the motor 25 respectively, one end of the rotating shaft 27 is connected to the dovetail slot sliding table 26, and the other end is connected to a sample groove 28 and extends into the measurement area.

[0043] The super-high sensitivity three-axis magnetic field measuring device in step 1 includes a second laser 29, a pump light-in bucket module 30, a pump light-in bucket channel 31, a gas chamber 14, a pump light-out bucket channel 32, a third mirror 33, and a third photoelectric acquisition module 34 connected in sequence, the gas chamber 14 is located in an oven 13, the oven 13 is located in a coil, the coil includes a Y-axis magnetic compensation coil 9, a Z-axis magnetic compensation coil 10, and an X-axis magnetic compensation coil 11, the coil is located in an amorphous magnetic shielding bucket 12, the amorphous magnetic shielding bucket 12 is located in a five-layer permalloy magnetic shielding bucket 1, and the coil is connected to a signal generator 8.

[0044] The present application relates to a kind of rock magnetic measurement methods based on ultra-high sensitivity three-axis magnetic field measuring device, characterized by: linearly polarized light optical rotation angle detection method is combined with circularly polarized light absorption method, based on two linearly polarized light and a circularly polarized light Ultra-high sensitivity three-axis magnetic field measuring device is built, the three-axis magnetic field measurement of sample to be measured is realized.Sample moving in measurement area using sample delivery system is controlled, the magnetic field response of each measuring point of three-axis magnetic field measuring device in the process of sample moving is recorded, based on measurement data using stochastic gradient descent algorithm trains machine learning model, the magnetic moment is determined by the weight parameter of model training completion, to realize the measurement of rock sample magnetism.

[0045] Fig. 1The XY plane structure is the XY plane structure of the application, mainly comprising a precise sample feeding system and a three-axis magnetic field measuring device, wherein the precise sample feeding system is composed of a dovetail groove sliding table 26, a motor 25, a rotating shaft 27 and a sample groove 28, the signal input end of the sample feeding system driver 24 is connected to the upper computer 23, the signal output end is connected to the motor 25, and the motor 25 is used for driving the motor 25 to work; the motor 25, the rotating shaft 27 and the sample groove 28 are located above the dovetail groove sliding table 26, the measured sample is placed in the sample groove 28, and the rotating table and the sample groove 28 are controlled to rotate and move by the motor 25. The three-axis magnetic field measuring device comprises five layers of permalloy magnetic shielding barrels 1, an amorphous magnetic shielding barrel 12, a signal generator 8, an X-axis magnetic compensation coil 11, a Y-axis magnetic compensation coil 9, a Z-axis magnetic compensation coil 10, an oven 13, an air chamber 14, a laser (a first laser 4), a beam splitter 5, a first detection light into barrel channel 2, a second detection light into barrel channel 6, a first detection light out of barrel channel 15, a second detection light out of barrel channel 19, a first detection light into barrel module 3, a second detection light into barrel module 7, a first detection light out of barrel module 17, a second detection light out of barrel module 21, a first reflecting mirror 16, a second reflecting mirror 20, a first photoelectric acquisition module 18 and a second photoelectric acquisition module 22, wherein the five layers of permalloy magnetic shielding barrels 1 are located in the outermost layer, the amorphous magnetic shielding barrel 12 is located inside the five layers of permalloy magnetic shielding barrels 1, and the five layers of permalloy magnetic shielding barrels 1 and the amorphous magnetic shielding barrel 12 are both used for shielding the interference of external magnetic fields, and after shielding and demagnetizing, the central residual magnetism of the X, Y and Z directions can all reach 0.3 nT; the three-axis magnetic compensation coil is located inside the amorphous magnetic shielding barrel 12, the X-axis coil constant is 16.2 nT / mA, the Y-axis coil constant is 16.16 nT / mA, and the Z-axis coil constant is 77.71 nT / mA, and the coil can be used for further eliminating the residual magnetism in the barrel under the driving of the signal generator 8, so that a near-zero magnetic environment is achieved in the barrel. The oven 13 is located inside the three-axis magnetic compensation coil, is used for providing high-temperature working conditions for the air chamber 14, and the air chamber 14 is located in the center of the oven 13. The first beam of light after the laser passes through the beam splitter enters the first detection light into barrel module 7, the light emitted by the first detection light into barrel module 7 enters the air chamber 14 through the first detection light into barrel channel 2, enters the reflecting mirror (the first reflecting mirror 16) through the first detection light out of barrel channel 15, is reflected into the first detection light out of barrel module 17, the photoelectric information is collected by the first photoelectric acquisition module 18, and Y-axis linearly polarized light optical rotation angle detection is realized; another beam of light after the laser passes through the beam splitter 5 enters the second detection light into barrel module 7, the light emitted by the second detection light into barrel module 7 enters the air chamber 14 through the second detection light into barrel channel 6, enters the reflecting mirror (the second reflecting mirror 20) through the second detection light out of barrel channel 19, is reflected into the second detection light out of barrel module 21, photoelectric information is collected by the second photoelectric acquisition module 22, and X-axis linearly polarized light optical rotation angle detection is realized; the upper computer 23 is connected to the first photoelectric acquisition module 18 and the second photoelectric acquisition module 22 for real-time display and control.

[0046] Fig. 2 XY plane structure of the present application, the laser (second laser 29) is connected to the pumping light into the barrel module 30, the light emitted by the pumping light into the barrel channel 31 into the gas chamber 14, the alkali metal atoms inside the gas chamber 14 can be highly sensitive to the change of external magnetic field after the pumping light polarization reaches the SERF state, the pumping light emitted by the gas chamber 14 enters the mirror (third mirror 33) through the pumping light out of the barrel channel 32, and the photoelectric information is collected by the third photoelectric collection module 34 to realize the Z axis circularly polarized light absorption detection.

[0047] The above completes the construction of the three-axis magnetic field measuring device. The measured sample is moved to the preset measurement point by the precision sample feeding system, and the magnetic field response signal of the three-axis magnetic field device at each point is recorded. Based on the collected magnetic field spatial distribution data set, the machine learning model is trained using the stochastic gradient descent (Stochastic Gradient Descent, SGD) algorithm, the magnetic moment solving problem is converted into a machine learning problem, and finally the equivalent magnetic moment vector parameters of the sample are determined. The specific measurement method is as follows:

[0048] The circularly polarized pumping light in the Z-axis direction not only completes the polarization of the atoms in the alkali metal gas chamber, but also reflects the changes of the atomic polarization rate along the direction. Therefore, the atomic spin precession signal is first detected by the Z-axis direction circularly polarized light absorption method, so as to realize the coarse compensation of the three-axis magnetic field. The magnetic field generated by the measured rock sample is a static magnetic field. When the external magnetic field changes, the absorption of circularly polarized light by alkali metal atoms will change, and this change is reflected in the detection signal of the photodetector at the end of the light path. The output of the Z-axis magnetic field measuring device is as follows:

[0049]

[0050]

[0051]

[0052]

[0053] wherein, is the voltage value output by the Z-axis photoelectric collection module, is the optical depth of the pumping light, is the frequency of the pumping light, is the initial polarization rate, , , is a dimensionless parameter related to the X, Y and Z three-axis magnetic field, is the electronic gyromagnetic ratio, ,​​​​ , is the magnetic field in X, Y, Z direction, R op is the optical pumping rate, R rel is the transverse relaxation rate of the atom, represents the initial voltage value of the photodetector; first adjust the magnetic compensation coils in X, Y, Z direction, the Z-axis voltage output is adjusted to the maximum, and the magnetic field rough compensation is completed.

[0054] When there is an external magnetic field input, the optical rotation angle of the linearly polarized light as the detection light will change accordingly; when the detection light direction is along the X direction, the X direction magnetic field measurement device outputs as follows:

[0055] ,

[0056] wherein, is the voltage value output by the X-axis photoelectric acquisition module, is the conversion coefficient of the photodetector, is the incident light intensity of the detection light before the gas chamber, is the modulation angle, is the optical depth of the detection light, is the detection light frequency, represents the optical path of the pumping light and the atom interaction, is the alkali metal atom density, represents the classical electron radius, and c represents the speed of light, , are the D1 and D2 line oscillation intensities of the alkali metal atom respectively, , are the center frequencies of the D1 and D2 lines of the alkali metal atom respectively, , are the pressure broadening of the atomic spectral lines in D1 and D2 lines respectively. Adjust to the minimum using triangular wave scanning Y-axis magnetic field, and then continue to adjust Vout to close to 0 mV using triangular wave scanning Z-axis magnetic field, at this time the Y and Z axis magnetic field compensation is completed, and the compensation magnetic field of Y and Z axis at this time is , .

[0057] When the detection light direction is along the Y direction, the Y direction magnetic field measurement device outputs as follows:

[0058] ,

[0059] wherein, is the voltage value output by the Y-axis photoelectric acquisition module. Adjust to close to 0 mV using triangular wave scanning X-axis magnetic field, at this time the compensation magnetic field of X axis is .

[0060] The sample was moved horizontally in the Y-axis direction by the sample delivery system, and the sample was stopped at 30 mm, 32 mm, 34 mm, 36 mm, 38 mm, 40 mm, 42 mm, 44 mm, 46 mm, 48 mm, 50 mm, and 52 mm from the gas chamber, respectively, for 5 seconds, and the response signal of the three-axis magnetic field measuring device at each point was recorded after stabilization , As each measurement point Corresponding , 12 groups of data can be obtained for each measurement, and the regression type machine learning model is optimized based on the measured data using the stochastic gradient descent algorithm, and the unknown magnetic moment solving problem is converted into a machine learning problem.

[0061] Assuming that the dipole of the measured object is located at the coordinate origin, the coordinates of the three-axis magnetic field measuring device relative to the magnetic dipole of the measured object are , and the theoretical calculation formula of the magnetic field generated by the magnetic dipole is:

[0062] ,

[0063] ,

[0064] Among them , , are the theoretical magnetic fields generated by the three axes, is the vacuum permeability, , , is the three-axis magnetic moment of the measured rock sample, and R is the measurement distance.

[0065] The position coordinates of each measurement point are set as is the input layer of the model, is the output layer of the model, and the target magnetic moment measured is as the weight parameter of the training process. Randomly divide the 12 groups of data into 3 batches, each batch containing 4 groups, and randomly select a batch of data to start training the model to ensure that the model does not fall into a local optimal solution and enhance the generalization ability of the model. First, a group of is randomly generated within the specified magnetic moment range as the model weight, and the gradient function G , of the current weight is calculated, which is the gradient of the mean squared error (MSE) between the theoretical magnetic field in three directions at this position and the actual measured , and the calculation is as follows:

[0066] ,

[0067] The learning rate is defined as s, which is used to update the weight parameters jointly with the gradient function , which is calculated as follows:

[0068]

[0069] This process is repeated until the minimum value of the gradient function for the current set of data is converged, and then the iteration process is repeated for the next set of data in the current batch. After the current batch of data is trained, the next batch of data is trained. When the four batches of data are all trained, that is, the complete 12 sets of data are optimized by the stochastic gradient descent algorithm, this is called a training cycle. The training cycle is set to 500 rounds. Finally, the weight parameters of the model convergence state can be obtained, and the magnetic moment of the measured sample can be obtained, thereby realizing the measurement of the magnetic properties of the sample.

[0070] The contents not described in detail in the specification of the present application belong to the prior art known to those skilled in the art. It is pointed out that the above description is helpful for those skilled in the art to understand the present application, but does not limit the protection scope of the present application. Any implementation of equivalent replacement, modification, improvement and / or deletion of the above description without departing from the essential content of the present application falls within the protection scope of the present application.​

Claims

1. A rock magnetic measurement method based on an ultra-high sensitivity three-axis magnetic field measurement device, characterized by, The method comprises the following steps: Step 1: configure the ultra-high sensitivity three-axis magnetic field measuring device with the sample feeding system, so that the rock sample to be measured can be positioned at the preset measurement points in the measurement area; Step 2: measure the three-axis magnetic field by using the ultra-high sensitivity three-axis magnetic field measuring device with two linearly polarized light optical rotation angle detection methods and one circularly polarized light absorption method, the first linearly polarized light passes through the gas chamber along the Y axis, the second linearly polarized light passes through the gas chamber along the X axis, and the third circularly polarized light passes through the gas chamber along the Z axis; Step 3: use the sample feeding system to control the movement of the rock sample to be measured in the measurement area, and record the magnetic field response of each measurement point of the three-axis magnetic field measuring device during the movement of the rock sample to be measured; Step 4: train the machine learning model based on the measurement data using the stochastic gradient descent algorithm, and determine the magnetic moment through the weight parameters of the model training to realize the measurement of the magnetism of the rock sample.

2. The rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device according to claim 1, characterized in that, Step 3 includes: moving the rock sample to be tested horizontally along the Y-axis using the sample delivery system, stopping the rock sample for 5 seconds at distances of 30mm, 32mm, 34mm, 36mm, 38mm, 40mm, 42mm, 44mm, 46mm, 48mm, 50mm, and 52mm from the gas chamber, and recording the response signal of the triaxial magnetic field measuring device after stabilization at each point. , , and These are the measurement points. The x-axis magnetic field, y-axis magnetic field and z-axis magnetic field will As the corresponding measurement point A set of measured data Each measurement yielded 12 sets of data.

3. The rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device according to claim 2, characterized in that, In step 4, 12 groups of data obtained by each measurement are used to optimize the regression type machine learning model by using the stochastic gradient descent algorithm, and the solution of the unknown magnetic moment is converted into a machine learning problem.

4. The rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device according to claim 1, characterized in that, In step 4, the following expression is included: ， ， ， ， in In magnetic dipole coordinates The theoretical magnetic field generated along the x-axis In magnetic dipole coordinates The theoretical magnetic field generated along the y-axis In magnetic dipole coordinates The theoretical magnetic field generated along the z-axis The permeability of free space, , , These represent the x-axis, y-axis, and z-axis magnetic moments of the rock sample being tested, respectively; R is the measurement distance; and G is the gradient function. Mean squared error gradient, It is the gradient operator. It is a triaxial theoretical magnetic field. This is a triaxial measurement of the magnetic field, where n is the total number of measurement points and i is the index of each measurement point. It updates the weight parameters. is the model weight parameter, and s is the learning rate.

5. The rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device according to claim 3, characterized in that, In step 4, 12 groups of data are optimized by the stochastic gradient descent algorithm to complete the optimization of the model as a training cycle, and the training cycle is set to 500 rounds. Finally, the weight parameters of the model convergence state can obtain the magnetic moment of the rock sample to be measured, so as to realize the measurement of the magnetism of the rock sample to be measured.

6. The rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device according to claim 1, characterized in that, The third beam of circularly polarized light along the Z axis through the gas cell is used to obtain the voltage value of the Z-axis photoelectric acquisition module output in step 2 The second beam of linearly polarized light along the X axis through the gas cell is used to obtain the voltage value of the X-axis photoelectric acquisition module output The first beam of linearly polarized light along the Y axis through the gas cell is used to obtain the voltage value of the Y-axis photoelectric acquisition module output .

7. The rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device according to claim 1, characterized in that, In step 1, the ultra-high sensitivity three-axis magnetic field measuring device comprises a beam splitter connected with a first laser, a first detection light barrel module, a first detection light barrel channel, a gas chamber, a first detection light barrel channel, a first mirror, a first detection light barrel module and a first photoelectric collection module connected in sequence at the first split output end of the beam splitter, a second detection light barrel module, a second detection light barrel channel, a gas chamber, a second detection light barrel channel, a second mirror, a second detection light barrel module, a second photoelectric collection module and an upper computer connected in sequence at the second split output end of the beam splitter, and the upper computer is connected with a sample feeding system through a sample feeding system driver. The sample feeding system comprises a dovetail slot sliding table and a rotating shaft connected with a motor respectively, one end of the rotating shaft is connected with the dovetail slot sliding table, and the other end is connected with a sample groove and extends into the measurement area.

8. The rock magnetic measurement method based on the ultra-high sensitivity three-axis magnetic field measurement device according to claim 1, characterized in that, In step 1, the ultra-high sensitivity three-axis magnetic field measuring device comprises a second laser, a pump light barrel module, a pump light barrel channel, a gas chamber, a pump light barrel channel, a third mirror and a third photoelectric collection module connected in sequence. The gas chamber is located in an oven, the oven is located in a coil, the coil comprises a Y-axis magnetic compensation coil, a Z-axis magnetic compensation coil and an X-axis magnetic compensation coil, the coil is located in an amorphous magnetic shielding barrel, the amorphous magnetic shielding barrel is located in a five-layer permalloy magnetic shielding barrel, and the coil is connected with a signal generator.

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