Tri-axis fluxgate sensor measurement optimization method

Abstract

The application discloses a kind of three-axis magnetic flux sensor measurement optimization methods, comprising: S1. the three-axis output value of magnetic flux sensor is collected;S2. according to the three-axis output value, constructs input vector;S3. with the input vector as data basis, construct coefficient augmented matrix;S4. to coefficient augmented matrix is decomposed, obtains solution vector;S5. according to the solution vector, three-axis offset correction value and three-axis proportion correction value are calculated respectively;S6. according to the three-axis offset correction value and the three-axis proportion correction value, the three-axis output value is corrected, and the output value after correction is obtained.The application can effectively correct the output value of sensor, reduce measurement error, improve the measurement accuracy of sensor.

Description

Technical Field

[0001] The present invention relates to the field of sensor measurement, and in particular to a three-axis magnetic flux sensor measurement optimization method. Background Art

[0002] Due to factors such as equipment manufacturing, the three-axis flux sensor itself inevitably experiences magnetization issues, resulting in "hard magnetic interference." Furthermore, the various components and structures surrounding the flux sensor inevitably contain magnetizable materials. These materials are magnetized by the magnetic field being measured, and the resulting magnetic field in turn affects the measured field, creating "soft magnetic interference." All of this interference affects the flux sensor's output, leading to errors in the zero point and scale values ​​of each axis, resulting in inaccurate measurement data.

[0003] Therefore, a three-axis magnetic flux sensor measurement optimization method is needed to correct the output value of the sensor and reduce the measurement error. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to overcome the defects in the prior art and provide a three-axis magnetic flux sensor measurement optimization method, which can effectively correct the output value of the sensor, reduce the measurement error, and improve the measurement accuracy of the sensor.

[0005] The three-axis magnetic flux sensor measurement optimization method of the present invention comprises the following steps:

[0006] S1. Collect the three-axis output values ​​of the magnetic flux sensor;

[0007] S2. Construct an input vector based on the three-axis output values;

[0008] S3. Based on the input vector as the data basis, construct a coefficient augmentation matrix;

[0009] S4. Decompose the coefficient augmented matrix to obtain a solution vector;

[0010] S5. Calculate the three-axis offset correction value and the three-axis scale correction value according to the solution vector;

[0011] S6. Correct the three-axis output value according to the three-axis offset correction value and the three-axis ratio correction value to obtain a corrected output value.

[0012] Furthermore, the input vectors include vector I[0], vector I[1], vector I[2], vector I[3], vector I[4], vector I[5], and vector I[6];

[0013] I[0]=Y*Y; I[1]=Z*Z; I[2]=X; I[3]=Y; I[4]=Z; I[5]=1; I[6]=-X*X; wherein X is the output value of the x-axis in the three-axis output value, Y is the output value of the y-axis in the three-axis output value, and Z is the output value of the z-axis in the three-axis output value.

[0014] Furthermore, the coefficient augmentation matrix is ​​determined according to the following formula:

[0015] C[i][j]=I[j]*I[i];

[0016] Wherein, C[i][j] is an element in the coefficient augmentation matrix; the values ​​of i and j are both integers from 0 to 6.

[0017] Furthermore, the three-axis offset correction value is determined according to the following formula:

[0018] X_off=R[3] / 2;

[0019] Y_off = R[4] / (2*R[0]);

[0020] Z_off=R[5] / (2*R[1]);

[0021] Among them, X_off is the x-axis offset correction value, Y_off is the y-axis offset correction value, Z_off is the z-axis offset correction value, and R[0], R[1], R[3], R[4], and R[5] are all solution vectors.

[0022] Furthermore, the three-axis ratio correction value is determined according to the following formula:

[0023] X_scale = 1;

[0024] Y_scale = sqrt(R[1]);

[0025] Z_scale = sqrt(R[2]);

[0026] Where X_scale is the x-axis scale correction value, Y_scale is the y-axis scale correction value, Z_scale is the z-axis scale correction value, sqrt is the square root symbol; R[1] and R[2] are both solution vectors.

[0027] Furthermore, the corrected output value is determined according to the following formula:

[0028] X_res = X – X_off;

[0029] Y_res=(Y–Y_off) / Y_scale;

[0030] Z_res=(Z–Z_off) / Z_scale;

[0031] Among them, X_res is the corrected x-axis output value, Y_res is the corrected y-axis output value, and Z_res is the corrected z-axis output value.

[0032] Furthermore, a coefficient augmentation matrix is ​​constructed, specifically including:

[0033] Construct n sets of input vectors;

[0034] Compute the elements of the coefficient augmented matrix:

[0035] C[i][j]=C[i][j] sum / n;

[0036] Among them, C[i][j] sum =C[i][j]0+C[i][j]1+...+C[i][j] k +...+C[i][j] n ; the C[i][j] k =I[j] k *I[i] k ; said I[j] k is the j-th input vector of the k-th group, the I[i] k is the i-th input vector of the k-th group; the values ​​of i and j are both integers from 0 to 6.

[0037] The beneficial effects of the present invention are as follows: a three-axis magnetic flux sensor measurement optimization method disclosed by the present invention effectively corrects the output value of the three-axis magnetic flux sensor by constructing a correction algorithm, making the output data of the three-axis magnetic flux sensor more accurate and reliable, thereby reducing the measurement or detection error of the three-axis magnetic flux sensor and improving the measurement accuracy of the three-axis magnetic flux sensor. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0039] Figure 1 Schematic diagram of the measurement optimization method of the present invention. DETAILED DESCRIPTION

[0040] The present invention will be further described below with reference to the accompanying drawings. Figure 1 As shown:

[0041] The three-axis magnetic flux sensor measurement optimization method of the present invention comprises the following steps:

[0042] S1. Collecting the three-axis output value of the magnetic flux sensor; wherein the three-axis output value includes the output value X of the x-axis, the output value Y of the y-axis, and the output value Z of the z-axis;

[0043] S2. Construct an input vector based on the three-axis output values;

[0044] S3. Based on the input vector as the data basis, construct a coefficient augmentation matrix;

[0045] S4. Decomposing the coefficient augmented matrix to obtain a solution vector; wherein the decomposition may adopt the existing LDU hierarchical or Gaussian decomposition, which will not be described in detail here;

[0046] S5. Calculate the three-axis offset correction value and the three-axis scale correction value according to the solution vector;

[0047] S6. Correct the three-axis output value according to the three-axis offset correction value and the three-axis ratio correction value to obtain a corrected output value.

[0048] In this embodiment, in step S2, the three-axis output values ​​are used as basic data to construct an input vector; the input vector includes vector I[0], vector I[1], vector I[2], vector I[3], vector I[4], vector I[5], and vector I[6];

[0049] I[0]=Y*Y; I[1]=Z*Z; I[2]=X; I[3]=Y; I[4]=Z; I[5]=1; I[6]=-X*X; wherein X is the output value of the x-axis in the three-axis output value, Y is the output value of the y-axis in the three-axis output value, and Z is the output value of the z-axis in the three-axis output value.

[0050] In this embodiment, in step S3, the input vector is used as basic data to construct a coefficient augmentation matrix; wherein, the elements in the coefficient augmentation matrix can be directly determined according to the following formula:

[0051] C[i][j]=I[j]*I[i];

[0052] Wherein, C[i][j] is an element in the coefficient augmentation matrix; the values ​​of i and j are both integers from 0 to 6.

[0053] Through the above method, a 6th-order coefficient augmented matrix can be formed.

[0054] Of course, in order to obtain a more accurate coefficient augmentation matrix, the coefficient augmentation matrix can also be constructed according to the following method, including:

[0055] Construct n groups of input vectors; wherein, in order to construct n groups of input vectors, the collected three-axis output values ​​should be data in as many directions as possible without data overflow. The more data collected, the higher the accuracy of the coefficient augmentation matrix constructed subsequently; each group of input vectors includes I[0]~I[6], a total of 7 vectors.

[0056] Compute the elements of the coefficient augmented matrix:

[0057] C[i][j]=C[i][j] sum / n;

[0058] Among them, C[i][j] sum =C[i][j]0+C[i][j]1+...+C[i][j] k +...+C[i][j] n ; the C[i][j] k =I[j] k *I[i] k ; said I[j] k is the j-th input vector of the k-th group, the I[i] k is the i-th input vector of the k-th group; the values ​​of i and j are both integers from 0 to 6.

[0059] According to the above method, a coefficient augmentation matrix with high accuracy can be formed.

[0060] By performing LDU grading or Gaussian decomposition on the coefficient augmentation matrix constructed above, we can obtain R[0], R[1], R[2], R[3], R[4], and R[5], a total of 6 solution vectors.

[0061] In this embodiment, the three-axis offset correction value is determined according to the following formula:

[0062] X_off=R[3] / 2;

[0063] Y_off = R[4] / (2*R[0]);

[0064] Z_off=R[5] / (2*R[1]);

[0065] Among them, X_off is the x-axis offset correction value, Y_off is the y-axis offset correction value, Z_off is the z-axis offset correction value, and R[0], R[1], R[3], R[4], and R[5] are all solution vectors.

[0066] Determine the three-axis ratio correction value according to the following formula:

[0067] X_scale = 1;

[0068] Y_scale = sqrt(R[1]);

[0069] Z_scale = sqrt(R[2]);

[0070] Where X_scale is the x-axis scale correction value, Y_scale is the y-axis scale correction value, Z_scale is the z-axis scale correction value, sqrt is the square root symbol; R[1] and R[2] are both solution vectors.

[0071] The corrected output value is determined according to the following formula:

[0072] X_res = X – X_off;

[0073] Y_res=(Y–Y_off) / Y_scale;

[0074] Z_res=(Z–Z_off) / Z_scale;

[0075] Among them, X_res is the corrected x-axis output value, Y_res is the corrected y-axis output value, and Z_res is the corrected z-axis output value.

[0076] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the purpose and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A three-axis magnetic flux sensor measurement optimization method, characterized by: The steps include: S1. Collect the three-axis output values ​​of the magnetic flux sensor; S2. Construct an input vector based on the three-axis output values; S3. Based on the input vector as the data basis, construct a coefficient augmentation matrix; Construct the coefficient augmentation matrix, including: Construct n groups of input vectors; the input vectors include vector I[0], vector I[1], vector I[2], vector I[3], vector I[4], vector I[5], and vector I[6]; I[0]=Y*Y; I[1]=Z*Z; I[2]=X; I[3]=Y; I[4]=Z; I[5]=1; I[6]=-X*X; wherein X is the output value of the x-axis in the three-axis output value, Y is the output value of the y-axis in the three-axis output value, and Z is the output value of the z-axis in the three-axis output value; Compute the elements of the coefficient augmented matrix: C[i][j]=C[i][j] sum / n; Among them, C[i][j] sum =C[i][j]0+C[i][j]1+...+C[i][j] k +...+C[i][j] n ; the C[i][j] k =I[j] k *I[i] k ; said I[j] k is the j-th input vector of the k-th group, the I[i] k is the i-th input vector of the k-th group; the values ​​of i and j are both integers from 0 to 6; S4. Decompose the coefficient augmented matrix to obtain a solution vector; S5. Calculate the three-axis offset correction value and the three-axis scale correction value according to the solution vector; Determine the three-axis offset correction value according to the following formula: X_off=R[3] / 2; Y_off = R[4] / (2*R[0]); Z_off=R[5] / (2*R[1]); Among them, X_off is the x-axis offset correction value, Y_off is the y-axis offset correction value, Z_off is the z-axis offset correction value, R[0], R[1], R[3], R[4], and R[5] are all solution vectors; Determine the three-axis ratio correction value according to the following formula: X_scale = 1; Y_scale = sqrt(R[1]); Z_scale = sqrt(R[2]); Where X_scale is the x-axis scale correction value, Y_scale is the y-axis scale correction value, Z_scale is the z-axis scale correction value, sqrt is the square root symbol; R[1] and R[2] are both solution vectors; S6. Correct the three-axis output value according to the three-axis offset correction value and the three-axis ratio correction value to obtain a corrected output value.

2. The three-axis magnetic flux sensor measurement optimization method according to claim 1, characterized in that: The corrected output value is determined according to the following formula: X_res = X – X_off; Y_res=(Y–Y_off) / Y_scale; Z_res=(Z–Z_off) / Z_scale; Among them, X_res is the corrected x-axis output value, Y_res is the corrected y-axis output value, and Z_res is the corrected z-axis output value.

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