Image reconstruction method of non-contact electrical impedance tomography based on dual sensitive fields

Abstract

The present invention discloses a non-contact electrical impedance imaging technology image reconstruction method based on dual sensitive fields. The method simultaneously introduces a full-field sensitivity matrix and an empty-field sensitivity matrix, and uses a linear back projection (LBP) algorithm and a synchronous iterative reconstruction technology (SIRT) algorithm to carry out image reconstruction on the real and imaginary information of the electrical impedance acquired by the non-contact electrical impedance imaging sensor, and obtains a real reconstructed image under a full field and an imaginary reconstructed image under an empty field. In addition, the present invention adopts a hybrid image fusion strategy combining arithmetic mean fusion, subtraction fusion and logical filtering algorithm to carry out image fusion on the real reconstructed image and the imaginary reconstructed image, and obtain a final reconstructed image based on dual sensitive fields. Compared with the traditional electrical tomography technology image reconstruction method based on a single sensitive field, the present invention is more effective in mining and utilizing electrical impedance information, and can obtain a higher quality reconstructed image.

Description

Technical Field

[0001] The invention relates to an image reconstruction method of electrical tomography technology, and in particular to an image reconstruction method of non-contact electrical impedance tomography technology based on dual sensitive fields. Background Art

[0002] Electrical tomography (ET) is a non-invasive visualization technology with the advantages of simple structure, low cost, fast response, good safety and easy industrial application. It is one of the mainstream technologies for multiphase flow detection in industrial processes and has shown great development potential and application prospects in multiphase flow state monitoring and parameter measurement. However, ET technology is a developing technology and still cannot meet the growing needs of actual industrial applications.

[0003] Most of the existing ET technologies are based on a single sensitive field for image reconstruction. The commonly used sensitive fields mainly include full field and empty field. Among them, the full field is represented by the electrical resistance tomography (ERT) technology, which is mainly used to mine the real part of the electrical impedance or resistance information, and usually uses an array resistance sensor to obtain the phase distribution of conductive materials. The empty field is represented by the electrical capacitance tomography (ECT) technology, which is mainly used to mine the imaginary part of the electrical impedance or capacitance information. Generally, the phase distribution of non-conductive materials is reconstructed by an array capacitance sensor. Studies have shown that the actual multiphase fluid has both resistance characteristics (real part) and capacitance characteristics (imaginary part), so it should be regarded as an electrical impedance. This means that the existing ET technology based on a single sensitive field, which uses ERT or ECT to reconstruct the acquired resistance information or capacitance information, cannot fully utilize the fluid impedance information, thereby limiting its actual imaging performance. If the resistance and capacitance characteristics of fluid impedance can be explored and integrated by combining the field characteristics of full field and empty field, it is expected to provide an effective new way to improve the imaging performance of ET technology. However, there are still few reports on ET technology and image reconstruction methods based on dual sensitive fields, and related knowledge and experience are still relatively scarce, and more research is urgently needed. Summary of the invention

[0004] To solve the technical problem, the present invention provides a non-contact electrical impedance tomography (CIT) technology image reconstruction method based on dual sensitive fields. The method introduces dual sensitive fields, combines image reconstruction and image fusion, makes full use of the real and imaginary information of the electrical impedance, and obtains a higher quality reconstructed image. For image reconstruction, the present invention combines the Linear Back Projection (LBP) algorithm with the Simultaneous Iterative Reconstruction Technique (SIRT) algorithm, and reconstructs the real reconstructed image under the full field and the imaginary reconstructed image under the empty field based on the full field sensitivity matrix and the empty field sensitivity matrix respectively; for image fusion, the present invention provides a hybrid image fusion strategy combining arithmetic mean fusion, subtraction fusion and logical filtering algorithms, first obtains the arithmetic mean fusion image and subtraction fusion image of the real and imaginary reconstructed images respectively, and then fully mines and utilizes the commonality and difference information of the real and imaginary reconstructed images through the logical filtering algorithm to obtain the final reconstructed image based on the dual sensitive fields. Compared with the traditional electrical tomography image reconstruction method based on a single sensitive field, the present invention introduces a dual sensitive field to fully exploit the real and imaginary information of the electrical impedance, and further realizes the fusion of the real and imaginary information of the electrical impedance through image fusion, so that the obtained reconstructed image has better image quality.

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

[0006] The present invention provides a non-contact electrical impedance tomography image reconstruction method based on dual sensitive fields, which comprises the following steps:

[0007] 1) Establishing the full-field domain model and the empty-field domain model of the contactless electrical impedance imaging sensor respectively, and calculating the full-field sensitivity matrix and the empty-field sensitivity matrix respectively by the finite element method;

[0008] 2) Based on the full-field sensitivity matrix and the real part measurement value of the electrical impedance obtained by the actual non-contact electrical impedance imaging sensor, the real part projection vector is calculated, and the LBP algorithm and SIRT algorithm are used to reconstruct the real part reconstructed image under the full field;

[0009] 3) Based on the empty field sensitivity matrix and the imaginary part measurement value of the electrical impedance obtained by the actual non-contact electrical impedance imaging sensor, the imaginary part projection vector is calculated, and the LBP algorithm and SIRT algorithm are used to reconstruct the imaginary part reconstructed image under the empty field;

[0010] 4) The real part reconstructed image obtained under the full field and the imaginary part reconstructed image obtained under the empty field are fused to obtain the final reconstructed image based on the dual sensitive field.

[0011] Compared with the prior art, the present invention has the following beneficial effects:

[0012] 1) The present invention introduces dual sensitive fields, which realizes the mining and utilization of the real and imaginary parts of the multiphase flow electrical impedance under full field and empty field respectively, giving full play to the advantages of full field and empty field. Compared with the traditional ET technology image reconstruction method based on a single sensitive field, the utilization of electrical impedance information is more complete and effective.

[0013] 2) The present invention introduces image fusion technology and provides a hybrid image fusion strategy to fuse the real reconstructed image and the imaginary reconstructed image under dual sensitive fields, further optimizes the mining and utilization of electrical impedance information, and realizes the fusion and utilization of multi-phase flow resistance characteristics and capacitance characteristics. Compared with the existing technology, higher quality reconstructed images can be obtained.

[0014] 3) The present invention regards the multiphase fluid to be measured as electrical impedance, and simultaneously obtains its complete real and imaginary information of electrical impedance and the corresponding real and imaginary reconstructed images in a non-contact manner, which can avoid the problems of electrode polarization, electrochemical corrosion, electrode contamination, etc. caused by the contact measurement of traditional ERT technology, and has better industrial application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flowchart of an image reconstruction method of non-contact electrical impedance tomography technology based on dual sensitive fields;

[0016] Figure 2 It is a schematic diagram of the structure of a 12-electrode non-contact electrical impedance imaging sensor;

[0017] Figure 3 It is an equivalent circuit model of the excitation-detection electrode pair of a 12-electrode non-contact electrical impedance imaging sensor;

[0018] Figure 4 It is a full-field model of a 12-electrode contactless electrical impedance imaging sensor;

[0019] Figure 5 It is the empty field domain model of the 12-electrode non-contact electrical impedance imaging sensor;

[0020] Figure 6 It is the dual-sensitive field image reconstruction result based on the method of the present invention. DETAILED DESCRIPTION

[0021] The present invention is further described and illustrated below in conjunction with specific embodiments. The embodiments are merely exemplary of the present disclosure and do not define the scope of limitation. The technical features of each embodiment of the present invention may be combined accordingly without conflicting with each other.

[0022] like Figure 1 As shown, the technical route of the present invention is firstly performed by using the LBP algorithm and the SIRT algorithm, based on the full-field sensitivity matrix calculated in advance under the full-field field model and the empty-field sensitivity matrix calculated in advance under the empty-field field model, to carry out image reconstruction on the real projection vector and the imaginary projection vector obtained by calculating the impedance measurement values ​​(real measurement values ​​and imaginary measurement values) obtained by the sensor, so as to obtain the real reconstructed image and the imaginary reconstructed image, and then adopt a hybrid image fusion strategy combining arithmetic mean fusion, subtraction fusion and logical filtering algorithm to fuse the real reconstructed image and the imaginary reconstructed image to obtain the final reconstructed image.

[0023] like Figure 2 As shown, the 12-electrode CIT sensor model established by the present invention is composed of an insulating pipe and 12 electrodes, wherein the 12 electrodes are marked as e1, e2, ..., e12 in sequence. The sensor adopts a 1-electrode excitation and 1-electrode detection mode, that is, a pair of excitation-detection electrode pairs is selected each time for electrical impedance measurement, wherein one electrode is used as an excitation electrode and one electrode is used as a detection electrode, and the electrodes other than the excitation-detection electrode pair are kept in a suspended state during the measurement process. The excitation-detection sequence is as follows: first, the e1 electrode is selected as the excitation electrode, and e2, ..., e12 are selected as detection electrodes in sequence; then, the e2 electrode is selected as the excitation electrode, and e3, ..., e12 are selected as detection electrodes in sequence; and the excitation electrode and the corresponding detection electrode are continuously changed in sequence until e11 is selected as the excitation electrode and e12 is selected as the detection electrode. Therefore, for the 12-electrode CIT sensor used in the present invention, a complete data acquisition can obtain 66 electrical impedance measurements, including 66 real impedance measurement values ​​and 66 imaginary impedance measurement values, which are used for subsequent real projection vector calculation, real image reconstruction and imaginary projection vector calculation, imaginary image reconstruction. Figure 3 The figure shows the equivalent circuit model of the excitation-detection electrode pair of the 12-electrode non-contact electrical impedance imaging sensor (taking the excitation-detection electrode pair e4-e10 as an example), where Z 4，10 is the equivalent electrical impedance of the fluid, C 4 , C 10 are the coupling capacitances formed by the tube wall, fluid and electrodes e4 and e10 respectively.

[0024] The field of the CIT sensor can be regarded as a quasi-static electromagnetic field. According to Maxwell's equations, the relationship between the distribution of the dielectric electrical properties (conductivity and dielectric constant) and the potential distribution in the field satisfies the following formula:

[0025]

[0026] Among them, γ(x, y) = σ(x, y) + jωε(x, y) is the complex conductivity distribution function of the medium in the CIT sensing field, σ(x, y), ε(x, y) and are the conductivity, dielectric constant and potential of the spatial point with coordinates (x, y) respectively. ω is the angular frequency of the AC excitation signal. is the Laplace operator. Ω is the sensing field of the CIT sensor. According to the above CIT excitation mode, the boundary condition of formula (1) is:

[0027]

[0028] Where U is the AC excitation voltage. e , Γ d and Γ f They represent the spatial regions where the excitation electrode, detection electrode and suspension electrode are located respectively. Represents the unit normal vector.

[0029] Studies have shown that real information can be better utilized by the full field, and imaginary information can be better utilized by the empty field. Considering that the actual multiphase fluid can be regarded as an electrical impedance, containing both real and imaginary information, the present invention introduces dual sensitive fields (full field and empty field) and calculates the full field sensitivity matrix and the empty field sensitivity matrix respectively, and uses them for subsequent image reconstruction of the real and imaginary information of the electrical impedance respectively. The present invention adopts the finite element method, and uses the simulation software COMSOL and MATLAB to calculate the sensitivity matrix under the dual sensitive field. The full field domain model and the empty field domain model of the CIT sensor are established in COMSOL, and the calculation of the full field sensitivity matrix and the empty field sensitivity matrix is ​​realized by co-simulation with MATLAB.

[0030] The full-field model of the CIT sensor is as follows: Figure 4 As shown, the continuous phase (background) medium is liquid phase, and the conductivity is set to σ 1 =0.01S / m, the relative dielectric constant is set to ε 1 =78, the discrete phase (target) medium is gas phase, and the conductivity is set to σ 2 =0S / m, the relative dielectric constant is set to ε 2 = 1. The empty field model of the CIT sensor is as follows: Figure 5 As shown, the continuous phase (background) medium is gas phase, and the conductivity is set to σ 2 =0S / m, the dielectric constant is set to ε 2 =1, the discrete phase (target) medium is liquid phase, and the conductivity is set to σ 1 =0.01S / m, the dielectric constant is set to ε 1 =78.

[0031] For each pair of excitation-detection electrodes (ed), an AC voltage U is applied to the excitation electrode (e), and the full-field complex current and the empty-field complex current can be measured from the detection electrode (d) under full field and empty field, respectively, and the impedance measurement values ​​under full field and empty field can be calculated. and empty field complex current It can be calculated by formula (3) and formula (4) respectively:

[0032]

[0033]

[0034] in, and are the complex current densities calculated on the detection electrode (d) under full field and empty field, respectively.

[0035] The real part of the full-field impedance measurement R F and the imaginary part of the empty field impedance X E The calculation methods are shown in formula (5) and formula (6) respectively:

[0036]

[0037]

[0038] The full-field and empty-field sensitivity matrices are calculated using the finite element method, and the field is divided into 820 pixels, each of which can be filled with liquid or gas medium. Figure 4 As shown, for the full-field sensitivity matrix, all pixels are filled with liquid background to obtain the real background measurement value, and the pixels are changed from the background medium to the target medium (gas phase) in sequence. Each time, only one pixel is changed to the target medium, and the real measurement value of each pixel after the medium is changed is calculated in sequence. Then the full-field sensitivity matrix The calculation of is shown in formula (7):

[0039]

[0040] in, is an element in the full-field sensitivity matrix, n and m refer to the excitation-detection pair sequence number and the selected pixel sequence number, respectively. represents the real part of the measurement value obtained by the nth excitation-detection electrode pair when the medium of the mth pixel changes to the gas phase. It represents the real part measurement value obtained by the nth excitation-detection electrode pair when all pixels are filled with liquid background. M=820 is the number of pixels divided into fields, and N=66 is the number of electrical impedance measurement values ​​obtained by the measurement.

[0041] like Figure 5As shown, for the empty field sensitivity matrix, all pixels are filled with gas phase background to obtain the imaginary background measurement value, and the pixels are changed from the background medium to the target medium (liquid phase) in sequence. Each time, only one pixel is changed to the target medium, and the imaginary measurement value of each pixel after the medium is changed is calculated in sequence. Then the empty field sensitivity matrix The calculation is shown in formula (8):

[0042]

[0043] in, is an element in the empty field sensitivity matrix, n and m refer to the excitation-detection pair sequence number and the selected pixel sequence number, respectively. Represents the imaginary measurement value obtained by the nth excitation-detection electrode pair when the medium of the mth pixel changes to the liquid phase. and They represent the imaginary measurement values ​​obtained by the nth excitation-detection electrode pair when all pixels are filled with liquid background and gas background, respectively. Used to normalize the empty field sensitivity matrix.

[0044] In actual measurement, after the CIT sensor obtains 66 real impedance measurement values ​​and 66 imaginary impedance measurement values, the real part projection vector and the imaginary part projection vector are calculated respectively, and image reconstruction is performed based on the obtained full field sensitive field matrix and empty field sensitive field matrix to obtain the real part and imaginary part reconstructed images of the impedance. The image reconstruction model of CIT can be expressed as the following formula:

[0045] P=SG (9)

[0046] Where P = [p 1 , p 2 , ..., p n , ..., p N ] T is the measured value projection vector, N = 66 is the number of projection values ​​in the projection vector, S = [s nm ] N×M is the sensitivity matrix, G=[g 1 , g 2 , ..., g m , ..., g M ] T is the grayscale vector of the reconstructed image. The real and imaginary projection vectors are calculated by the following formulas:

[0047]

[0048]

[0049] Among them, p R，n and p X，nRepresent the nth projection value in the real projection vector and the imaginary projection vector respectively. and They represent the real and imaginary measurement values ​​obtained by the nth excitation-detection electrode pair when the pipeline is filled with liquid background, is the imaginary measurement obtained by the nth excitation-detection electrode pair when the pipeline is filled with gas background. and They respectively represent the real measurement value and imaginary measurement value obtained by the nth excitation-detection electrode pair when the pipeline is the distribution to be measured.

[0050] The inverse problem of CIT image reconstruction can be transformed into an optimization problem for solution. The optimization objective function is as follows:

[0051]

[0052] in, It refers to the grayscale vector of the reconstructed image obtained by solving the optimization objective function. It refers to the value of vector G when {·} reaches its minimum value.

[0053] The present invention combines the LBP algorithm with the SIRT algorithm to solve the inverse problem of CIT. First, the LBP algorithm is used to calculate the initial image, and the image is reconstructed based on the full-field sensitivity matrix for the real part of the impedance, and based on the empty-field sensitivity matrix for the imaginary part of the impedance. The LBP algorithm formula is as follows:

[0054] Full Court:

[0055]

[0056] Empty venue:

[0057]

[0058] in, and are the grayscale values ​​of the mth pixel in the real initial image under full field and the imaginary initial image under empty field obtained by the LBP algorithm. Then, the grayscale vectors of the real initial image and the imaginary initial image obtained by the LBP algorithm are used as the initial iteration values ​​of the SIRT algorithm. The SIRT algorithm is used to iteratively solve the optimization objective function shown in formula (12), and the real reconstructed image and the imaginary reconstructed image are calculated based on the full field sensitivity matrix and the empty field sensitivity matrix, respectively. The formula of the SIRT algorithm is as follows:

[0059] Full Court:

[0060]

[0061] Empty venue:

[0062]

[0063] in, and are the grayscale value of the mth pixel in the real reconstructed image under full field and the imaginary reconstructed image under empty field obtained by the SIRT algorithm in the i-th iteration.

[0064] The present invention provides a hybrid image fusion strategy combining arithmetic mean fusion, subtraction fusion and logic filtering algorithm, which is used to fuse the acquired full-field real part reconstructed image and empty-field imaginary part reconstructed image. First, the arithmetic mean fusion image of the real part reconstructed image and the imaginary part reconstructed image is calculated according to the arithmetic mean fusion algorithm. Since the arithmetic mean fusion has the disadvantages of blurred image edges and inability to eliminate noise points, the present invention introduces a subtraction fusion algorithm on the basis of the arithmetic mean fusion algorithm, and uses the image difference information contained in the subtraction fusion image to remove the noise points of the arithmetic mean fusion image. In order to better utilize the arithmetic mean information and difference information of the real and imaginary part reconstructed images, the present invention introduces a logic filtering algorithm to improve the confidence of the fused image. The adopted hybrid image fusion strategy includes the following steps:

[0065] 1) Obtain the arithmetic mean fusion image of the real part reconstructed image under the full field and the imaginary part reconstructed image under the empty field through the arithmetic mean fusion algorithm:

[0066]

[0067] in, and They represent the gray value of the mth pixel in the arithmetic mean fused image, the real part reconstructed image under full field, and the imaginary part reconstructed image under empty field, respectively.

[0068] 2) Obtain the subtractive fusion image of the real part reconstructed image under full field and the imaginary part reconstructed image under empty field through the subtractive fusion algorithm:

[0069]

[0070] in, represents the gray value of the mth pixel in the subtractive fusion image, and |·| represents the absolute value.

[0071] 3) Through the logical filtering algorithm, according to the real part reconstructed image under the full field and the imaginary part reconstructed image under the empty field, combined with the arithmetic mean fusion image and the subtraction fusion image obtained by the above calculation, the final reconstructed image based on the dual sensitive field is obtained:

[0072]

[0073] in, Represents the gray value of the mth pixel in the final reconstructed image based on the dual sensitive field. max(x, y) represents the maximum value of the number x and the number y. h and λ l are the thresholds of the logic filter, respectively and λ is a parameter that determines the degree to which the difference information represented by the subtractive fusion image is removed, which is λ h and λ l and λ are empirical parameters, determined based on preliminary experiments.

[0074] In order to verify the effectiveness of this method, image reconstruction experiments were carried out under six groups of gas-liquid two-phase flow distributions, including annular distribution, bubbling distribution and laminar distribution. The results are shown in Figure 2. Figure 6 As shown. The experimental results show that the image reconstruction method of non-contact electrical impedance imaging technology based on dual sensitive fields proposed in the present invention is effective, and the reconstructed image based on dual sensitive fields obtained by this method is basically consistent with the real distribution image. Compared with the real part reconstructed image under a single full field and the imaginary part reconstructed image under a single empty field, the reconstructed image based on dual sensitive fields in the present invention has fewer artifacts, higher image quality, and is more consistent with the real distribution. This conclusion further verifies the effectiveness of the image reconstruction method based on dual sensitive fields in the present invention, indicating that it has obvious advantages and better development potential than the traditional image reconstruction method based on a single sensitive field.

[0075] The above-mentioned embodiments only express several implementation methods of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the present invention. For ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention.

Claims

1. A non-contact electrical impedance tomography image reconstruction method based on dual sensitive fields, characterized in that: The steps include: 1) Based on the non-contact electrical impedance imaging sensor, a full-field domain model and an empty-field domain model of the non-contact electrical impedance imaging sensor are established respectively; and the full-field sensitivity matrix and the empty-field sensitivity matrix are calculated respectively by the finite element method; 2) Based on the full-field sensitivity matrix and the real part measurement value of the electrical impedance obtained by the actual non-contact electrical impedance imaging sensor, the real part projection vector is calculated, and the LBP algorithm and SIRT algorithm are used to reconstruct the real part reconstructed image under the full field; 3) Based on the empty field sensitivity matrix and the imaginary part measurement value of the electrical impedance obtained by the actual non-contact electrical impedance imaging sensor, the imaginary part projection vector is calculated, and the LBP algorithm and SIRT algorithm are used to reconstruct the imaginary part reconstructed image under the empty field; 4) Fusing the real part reconstructed image obtained under the full field and the imaginary part reconstructed image obtained under the empty field to obtain the final reconstructed image based on the dual sensitive field; In the step 4), a hybrid image fusion method combining arithmetic mean fusion, subtraction fusion and logic filtering algorithm is used to fuse the real part reconstructed image obtained under the full field and the imaginary part reconstructed image obtained under the empty field; Among them, the arithmetic mean fusion algorithm and the subtraction fusion algorithm are used to calculate the arithmetic mean fusion image and the subtraction fusion image respectively, and on this basis, the final reconstructed image based on the dual sensitive field is obtained by the logical filtering algorithm; The step 4) comprises the following steps: 4.1) Obtaining the arithmetic mean fusion image of the real part reconstructed image under the full field and the imaginary part reconstructed image under the empty field by the arithmetic mean fusion algorithm; 4.2) Obtaining a subtractive fusion image of the real part reconstructed image under full field and the imaginary part reconstructed image under empty field by using a subtractive fusion algorithm; 4.3) Through the logical filtering algorithm, according to the real part reconstructed image under the full field and the imaginary part reconstructed image under the empty field, the final reconstructed image based on the dual sensitive field is obtained by combining the calculated arithmetic mean fusion image and subtraction fusion image.

2. The image reconstruction method of non-contact electrical impedance tomography technology based on dual sensitive fields according to claim 1 is characterized in that: In the step 1), the full-field domain model uses the liquid medium as the continuous phase and the gas medium as the discrete phase; the empty-field domain model uses the gas medium as the continuous phase and the liquid medium as the discrete phase.

3. The image reconstruction method of non-contact electrical impedance tomography technology based on dual sensitive fields according to claim 1, characterized in that: In step 1), the full-field sensitivity matrix and the empty-field sensitivity matrix are calculated by the finite element method, specifically: For each pair of excitation-detection electrodes of the contactless electrical impedance imaging sensor, an AC voltage U is applied to the excitation electrodes, a full-field complex current and a no-field complex current are measured from the detection electrodes under a full field and an empty field, respectively, and an electrical impedance measurement value under a full field and an electrical impedance measurement value under an empty field are calculated; Divide the field into a number of pixels, each of which can be filled with a liquid medium or a gas medium; For the full-field sensitivity matrix, all pixels are filled with liquid background to obtain the real background measurement value, and the pixels are changed from the background medium to the gas phase medium in sequence, with only one pixel being changed to the gas phase medium each time, and the real impedance measurement value of each pixel after the medium is changed is calculated in sequence, and then the full-field sensitivity matrix is ​​constructed; For the empty-field sensitivity matrix, all pixels are filled with gas background to obtain the imaginary background measurement value, and the pixels are changed from the background medium to the liquid medium in turn. Each time, only one pixel is changed to the liquid medium, and the imaginary impedance measurement value of each pixel after the medium is changed is calculated in turn, and then the empty-field sensitivity matrix is ​​constructed.

4. The image reconstruction method of non-contact electrical impedance tomography technology based on dual sensitive fields according to claim 1, characterized in that: The step 2) is: for the real part measurement value of the impedance obtained by the non-contact impedance imaging sensor, calculate the real part projection vector, reconstruct the real part initial image based on the full-field sensitivity matrix and the real part projection vector, and then use the LBP algorithm to reconstruct the real part of the initial image, and then use the grayscale vector of the initial image as the iterative initial value of the SIRT algorithm, and again based on the full-field sensitivity matrix, use the SIRT algorithm to obtain the real part reconstructed image under the full field.

5. The image reconstruction method of non-contact electrical impedance tomography technology based on dual sensitive fields according to claim 1, characterized in that: The step 3) is: for the imaginary part measurement value of the impedance obtained by the non-contact impedance imaging sensor, calculate the imaginary part projection vector, reconstruct the imaginary part initial image based on the empty field sensitivity matrix and the imaginary part projection vector, and then use the LBP algorithm to reconstruct the imaginary part initial image, and then use the grayscale vector of the initial image as the iterative initial value of the SIRT algorithm, and again based on the empty field sensitivity matrix, use the SIRT algorithm to obtain the imaginary part reconstructed image under the empty field.

6. The image reconstruction method of non-contact electrical impedance tomography technology based on dual sensitive fields according to claim 1, characterized in that: The step 4.3) comprises the following steps: For each pixel in the image, if the grayscale value of the pixel in both the real and imaginary reconstructed images is greater than or equal to the threshold λ h , then the pixel is calculated as a gas phase pixel, that is, the gray value is 1; if the gray value of the pixel in the real part reconstructed image and the imaginary part reconstructed image is less than or equal to the threshold λ l , the pixel is calculated as a liquid pixel, that is, the gray value is 0; if the pixel does not meet the above conditions, it is considered that the pixel is an artifact, and the gray value of the pixel in the arithmetic mean fusion image is subtracted from the gray value of the pixel in the subtraction fusion image and the set removal degree parameter λ. If the result is a non-negative value, the non-negative value is directly used as the gray value of the pixel. If the result is a negative value, the pixel is calculated as a liquid pixel, that is, the gray value is set to 0.

Images