Three-dimensional ECT imaging method of integrated modeling seamless cutting sensitive field

Abstract

The invention discloses a three-dimensional ECT imaging method of an integrated modeling seamless cutting sensitive field. The method is used for eliminating the interference problem between adjacent three-dimensional ECT imaging systems. The method comprises the following steps: integrally modeling adjacent sub ECT sensors with electric field interference in a three-dimensional ECT imaging system, adopting a multi-electrode excitation mode of one excitation electrode for each adjacent sub ECT sensor, and calculating a total sensitive field matrix of an integrated model; the integrated total sensitive field matrix is seamlessly cut according to the electrode position and the imaging area attribution, the cut sensitive field is used for independent imaging of the corresponding sub ECT sensors, and images of the sub ECT sensors are spliced to form a complete ECT image. According to the invention, the complex gas-solid flow reactor is seamlessly segmented into a plurality of sub-ECT system images, and then the three-dimensional images of the sub-ECT systems are spliced, so that the three-dimensional imaging of a complex space is realized, and the imaging scale of the existing ECT can be greatly improved while the interference among the images is eliminated.

Description

Technical Field

[0001] The present invention relates to the technical field of circulating fluidized bed imaging, and in particular to a three-dimensional ECT imaging method with integrated multi-electrode seamless cutting sensitive field. Background Art

[0002] Electrical capacitance tomography (ECT) enables non-contact imaging of two-phase flows and measures particle flow characteristics within gas-solid reactors, such as solid concentration, particle velocity, and bubbling. It is an ideal technique for measuring gas-solid flow. However, current two-dimensional and three-dimensional ECT for fluidized beds also have certain limitations. Two-dimensional ECT can only image regular cross-sections, providing the average solid concentration distribution within a certain axial length of a local key section. Two-dimensional ECT requires minimal axial variation in fluid flow, meaning that actual three-dimensional flow can be treated as two-dimensional flow. It also requires that the electric field generated by the excitation signal from the detection circuit be uniform along the axial direction of the imaging region. This can be achieved by adding axial drive electrodes to increase axial uniformity and effectively reduce the impact of edge effects on two-dimensional ECT. Even without considering edge effects, the measurement result of two-dimensional ECT is the average concentration signal over the axial length of the measuring electrodes. Because gas-solid flow reactors, such as circulating fluidized beds, have irregular unit structures along the flow direction and cannot be treated as two-dimensional structures, three-dimensional imaging is necessary to image the entire fluidized bed. 3D ECT (also known as Electrical Capacitance Volume Tomography, or ECVT) can be used to image the interior of any three-dimensional object. Theoretically, it is not restricted by the object's shape and can measure 3D flow conditions at irregular locations within a fluidized bed. However, due to the complex structure of gas-solid reactors, the complexity of detection circuits, and the ill-posedness of imaging algorithms, 3D ECT systems are currently limited to localized locations within the fluidized bed. However, localized imaging cannot effectively reveal the overall flow characteristics within the reactor or the dynamic interactions between cells.

[0003] The prior patent publication number CN115356380B discloses a control method for a complex spatial distributed electrical capacitance tomography system, which regulates the synchronous acquisition between distributed electrical capacitance tomography and sub-ECT systems, and realizes full-cycle, three-dimensional, transient imaging of complex spaces or complex structures; as shown in the attached Figure 1As shown, the timing controller coordinates several ECT subsystems by sending unified frame numbers and frame start signals to synchronously acquire data from the fluidized bed and reconstruct three-dimensional images of each subregion without interfering with each other, ensuring that the overall imaging rate is not affected by the number of ECT subsystems. In actual experiments, this solution has found that when distributed ECT systems share a single signal source or when multiple excitation signal sources operate simultaneously, adjacent sensors can interfere with each other. The complex geometric structure of the circulating fluidized bed results in large capacitance differences, weak capacitance, a large number of electrodes, and a complex measurement system in the three-dimensional ECT subsystems. When two adjacent ECT subsystems are close together, the electric fields of some of the excitation electrodes in the different ECT subsystems will inevitably affect and interfere with each other, affecting the capacitance of some electrode pairs in the subsystems, thereby affecting image reconstruction and reducing imaging reliability. Summary of the Invention

[0004] 1. Technical problems to be solved: In response to the above technical problems, the present invention provides an integrated multi-electrode three-dimensional ECT imaging method with seamless cutting of the sensitive field. Based on the existing technology, it comprehensively solves the mutual interference problem between seamlessly connected adjacent sub-ECT systems from the aspects of sensor modeling, sensitive field calculation and segmentation, and data acquisition.

[0005] 2. Technical solution: A three-dimensional ECT imaging method with integrated modeling and seamless cutting of sensitive fields is used to eliminate interference problems between adjacent three-dimensional ECT imaging systems. The method is characterized by: integrating adjacent sub-ECT sensors with electric field interference in the three-dimensional ECT imaging system into a model, adopting a multi-electrode excitation mode with one excitation electrode for each adjacent sub-ECT sensor, and calculating the total sensitive field matrix of the integrated model; seamlessly cutting the integrated total sensitive field matrix according to electrode position and imaging area affiliation, using the cut sensitive fields for independent imaging of the corresponding sub-ECT sensors, and splicing the images of the sub-ECTs to form a complete ECT image.

[0006] Furthermore, the method specifically includes the following steps: Step 1: Capacitive data is collected from the entire 3D ECT imaging system deployed in a complex space. The 3D ECT imaging system is composed of multiple sub-ECT sensors, each of which is equipped with multiple ECT electrodes arranged in an array. During the imaging process, one ECT electrode in each sub-ECT sensor serves as an excitation electrode, forming a capacitance pair with other electrodes in the sub-ECT sensor. Based on the capacitance values between each electrode pair and the sub-ECT sensor's sensitive field collected by the data acquisition system, the dielectric constant distribution of the enclosed 3D area is constructed, and the corresponding ECT image of the sub-ECT sensor is obtained. Step 2: Establish a finite element model of the ECT sensor and calculate the sensitive field of the integrated modeling multi-electrode excitation seamless cutting; obtain the position information of the adjacent ECT electrodes whose distance is less than the preset distance; if the adjacent ECT electrodes belong to different sub-ECT sensors, then determine that the adjacent sub-ECT sensors corresponding to the adjacent ECT electrodes are sub-ECT sensors that need to be spliced; merge all the sub-ECT sensors that need to be spliced and integrate them for simulation modeling; treat each sub-ECT sensor included in the integrated model as a unit, and each unit is equipped with an excitation electrode for multi-electrode excitation; calculate the total sensitive field matrix of the integrated model and each sub-ECT The sensitivity field process of the T sensor is as follows: first, the total sensitivity field matrix of adjacent sub-ECT sensors under multi-electrode excitation is calculated, and the total sensitivity field matrix is cut according to the position of the detection electrodes and the imaging area to obtain the sensitivity field of each sub-ECT sensor. The capacitance of the detection electrodes belonging to the same sub-ECT sensor is classified as the capacitance of the sub-ECT sensor, and the imaging pixels belonging to the area where the sub-ECT sensor is located are retained to form the sensitivity field of the sub-ECT sensor. This sensitive field takes into account the interaction between adjacent electrodes and is consistent with the excitation mode of data acquisition in step 1. It can avoid errors in image reconstruction and thus eliminate the problem of mutual interference between adjacent sub-ECT sensors. Step 3: During the imaging process, based on the capacitance data of each sub-ECT sensor collected in step 1 and the sensitive field of the sub-ECT sensor segmented in step 2, image reconstruction is performed on each adjacent sub-ECT sensor to obtain images of all sub-ECT sensors. When stitching images, the adjacent sub-ECT sensors are stitched into the ECT image of the entire system based on their locations.

[0007] Furthermore, the process of calculating the total sensitive field matrix of the integrated model and the sensitive field of each sub-ECT sensor in step 2 specifically includes: S21: The adjacent sub-ECT sensors are represented by ECTa and ECTb respectively; the space where ECTa and ECTb are located after being stimulated, i.e., the Q space, is represented by Qa and Qb respectively; the electrode of ECTa in the Q space i and ECTb electrodes i They are all excitation electrodes, and their electric field intensity distribution is represented by E i ( x , y , z ) represents; the total sensitive field matrix S of ECTa and ECTb is calculated according to the following formula: (1) In the above formula, represents the sensitive field strength formed by electrodes i and j at the (x, y, z) position in the Q space; Q(x, y, z) represents the (x, y, z) position in the Q space; V represents the excitation voltage; S22: Divide the 2K×2M-dimensional total sensitive field matrix S of the imaging areas of adjacent sub-ECT sensors obtained in S21 to obtain K×M-dimensional sensitive field matrices Sa and Sb of the sub-ECT sensors; where K is the number of capacitors of the sub-ECT sensor, and M is the number of imaging pixels in the sub-ECT sensor.

[0008] S23: The acquired sensitive field matrices of ECTa and ECTb are represented by Sa and Sb respectively, and the capacitance matrices of the sub-ECT sensors acquired by the data acquisition system are represented by λa and λb respectively; and the reconstructed image matrices ga and gb are obtained using the following imaging formula; (2) In the above formula, the superscript T represents the transposed matrix; S24: The obtained image matrices ga and gb are stitched together into a complete ECT image g according to the positions of their sub-ECT sensors.

[0009] Furthermore, the ECT image construction process of the entire system is as follows: the three-dimensional ECT imaging system uses a timing controller to send a unified excitation signal to each sub-ECT sensor. After receiving the start signal, the sub-ECT sensor reads the 12-bit frame number and performs electrode switching within the system. The electrode switching is such that each electrode in the sub-ECT sensor serves as an excitation electrode in turn, and the remaining electrodes serve as detection electrodes. During the data acquisition process, the capacitance array of all electrode combinations is combined with the seamlessly cut sensitive field to reconstruct a continuous three-dimensional image of each sub-ECT sensor. The imaging computer recognizes and matches data from different ECT subsystems in the same frame based on the data acquisition timestamp and the unified 12-bit frame number.

[0010] Furthermore, the image reconstruction algorithm is one of the LBP algorithm, Landweber algorithm, Tikhonov algorithm, and Newton–Raphson algorithm.

[0011] Furthermore, the sub-ECT sensor in the integrated simulation modeling includes at least two sub-ECT sensors.

[0012] 3.Beneficial effects: (1) This method discloses a three-dimensional ECT imaging method with integrated modeling and seamless cutting of sensitive fields. To address the electric field interference problem existing in the prior art, an integrated modeling and calculation of the sensitive field matrix is performed on all sub-ECT sensors with interference in the system, and the influence between adjacent sub-ECT sensors is included in the sensitive field of the integrated modeling. To ensure that each adjacent sub-ECT sensor can work independently after cutting, there is an excitation electrode in each adjacent sub-ECT at each moment. The total sensitive field matrix calculated by the integrated modeling is cut to obtain the independent sensitive fields of adjacent sub-ECT sensors containing mutual interference information, thereby achieving independent imaging of each sub-ECT sensor and eliminating interference between adjacent sub-ECT sensors.

[0013] (2) In a three-dimensional ECT imaging method for seamlessly cutting sensitive fields using integrated modeling, the total sensitive field matrix of adjacent sub-ECT sensors is seamlessly cut. The scale of the ECT system after cutting is significantly reduced, and the larger the number of cuts, the smaller the scale of each subsystem. This method can significantly reduce the computational complexity of image reconstruction; on the other hand, it can stitch together images of multiple sub-ECT systems to achieve ultra-large-scale three-dimensional imaging.

[0014] (3) In the three-dimensional ECT imaging method of an integrated multi-electrode seamless cutting sensitive field disclosed in this method, each sub-ECT sensor data acquisition instrument collects capacitance data in a distributed manner according to the modeled excitation pattern, ensuring that the collected data pattern is consistent with the sensitive field modeling pattern, and solving the mutual interference problem between adjacent sub-sensors.

[0015] In summary, this method uses integrated modeling, multi-electrode excitation, seamless cutting of sensitive fields, and distributed data acquisition to solve the mutual interference problem between seamlessly connected adjacent sub-ECT sensors in distributed ECT. It seamlessly cuts the complex and complete three-dimensional imaging space into multiple ECT sub-sensors, and synchronously collects capacitance data under the coordination of the timing controller, greatly expanding the imaging scale of three-dimensional ECT; it can realize the imaging of flows in any complex three-dimensional space. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is an overall schematic diagram of the three-dimensional ECT imaging system involved in this method; Figure 2 is a schematic diagram of two adjacent sub-ECT sensors in a specific embodiment; Figure 3 Schematic diagram of the total sensitive field matrix of two adjacent sub-ECT sensors in a specific embodiment; Figure 4 is a schematic diagram of stitching ECT images generated by two adjacent sub-ECT sensors in a specific embodiment; Figure 5It is the overall flow chart of the present invention. DETAILED DESCRIPTION

[0017] The present invention will be described in detail below with reference to the accompanying drawings.

[0018] As attached Figure 2 To the attached Figure 5 As shown, a three-dimensional ECT imaging method with integrated modeling and seamless cutting of sensitive fields is used to eliminate interference problems between adjacent three-dimensional ECT imaging systems. The method is characterized by: integrating adjacent sub-ECT sensors with electric field interference in the three-dimensional ECT imaging system into a model, adopting a multi-electrode excitation mode with one excitation electrode for each adjacent sub-ECT sensor, and calculating the total sensitive field matrix of the integrated model; seamlessly cutting the integrated total sensitive field matrix according to the electrode position and the imaging area affiliation, and using the cut sensitive fields for independent imaging of the corresponding sub-ECT sensors, and splicing the images of each sub-ECT to form a complete ECT image.

[0019] Furthermore, the method specifically includes the following steps: Step 1: Capacitive data is collected from the entire 3D ECT imaging system deployed in a complex space. The 3D ECT imaging system is composed of multiple sub-ECT sensors, each of which is equipped with multiple ECT electrodes arranged in an array. During the imaging process, one ECT electrode in each sub-ECT sensor serves as an excitation electrode, forming a capacitance pair with other electrodes in the sub-ECT sensor. Based on the capacitance values between each electrode pair and the sub-ECT sensor's sensitive field collected by the data acquisition system, the dielectric constant distribution of the enclosed 3D area is constructed, and the corresponding ECT image of the sub-ECT sensor is obtained. Step 2: Establish a finite element model of the ECT sensor and calculate the sensitive field of the integrated modeling multi-electrode excitation seamless cutting; obtain the position information of the adjacent ECT electrodes whose distance is less than the preset distance; if the adjacent ECT electrodes belong to different sub-ECT sensors, then determine that the adjacent sub-ECT sensors corresponding to the adjacent ECT electrodes are sub-ECT sensors that need to be spliced; merge all the sub-ECT sensors that need to be spliced and integrate them for simulation modeling; treat each sub-ECT sensor included in the integrated model as a unit, and each unit is equipped with an excitation electrode for multi-electrode excitation; calculate the total sensitive field matrix of the integrated model and each sub-ECT The sensitivity field process of the T sensor is as follows: first, the total sensitivity field matrix of adjacent sub-ECT sensors under multi-electrode excitation is calculated, and the total sensitivity field matrix is cut according to the position of the detection electrodes and the imaging area to obtain the sensitivity field of each sub-ECT sensor. The capacitance of the detection electrodes belonging to the same sub-ECT sensor is classified as the capacitance of the sub-ECT sensor, and the imaging pixels belonging to the area where the sub-ECT sensor is located are retained to form the sensitivity field of the sub-ECT sensor. This sensitive field takes into account the interaction between adjacent electrodes and is consistent with the excitation mode of data acquisition in step 1. It can avoid errors in image reconstruction and thus eliminate the problem of mutual interference between adjacent sub-ECT sensors. Step 3: During the imaging process, based on the capacitance data of each sub-ECT sensor collected in step 1 and the sensitive field of the sub-ECT sensor segmented in step 2, image reconstruction is performed on each adjacent sub-ECT sensor to obtain images of all sub-ECT sensors. When stitching images, the adjacent sub-ECT sensors are stitched into the ECT image of the entire system based on their locations.

[0020] Furthermore, the process of calculating the total sensitive field matrix of the integrated model and the sensitive field of each sub-ECT sensor in step 2 specifically includes: S21: The adjacent sub-ECT sensors are represented by ECTa and ECTb respectively; the space where ECTa and ECTb are located after being stimulated, i.e., the Q space, is represented by Qa and Qb respectively; the electrode of ECTa in the Q space i and ECTb electrodes i They are all excitation electrodes, and their electric field intensity distribution is represented by E i ( x , y , z ) represents; the total sensitive field matrix S of ECTa and ECTb is calculated according to the following formula: (1) In the above formula, represents the sensitive field strength formed by electrodes i and j at the (x, y, z) position in the Q space; Q(x, y, z) represents the (x, y, z) position in the Q space; V represents the excitation voltage; S22: Divide the 2K×2M-dimensional total sensitive field matrix S of the imaging areas of adjacent sub-ECT sensors obtained in S21 to obtain K×M-dimensional sensitive field matrices Sa and Sb of the sub-ECT sensors; where K is the number of capacitors of the sub-ECT sensor, and M is the number of imaging pixels in the sub-ECT sensor.

[0021] S23: The acquired sensitive field matrices of ECTa and ECTb are represented by Sa and Sb respectively, and the capacitance matrices of the sub-ECT sensors acquired by the data acquisition system are represented by λa and λb respectively; and the reconstructed image matrices ga and gb are obtained using the following imaging formula; (2) In the above formula, the superscript T represents the transposed matrix; S24: The obtained image matrices ga and gb are stitched together into a complete ECT image g according to the positions of their sub-ECT sensors.

[0022] Furthermore, the ECT image construction process of the entire system is as follows: the three-dimensional ECT imaging system uses a timing controller to send a unified excitation signal to each sub-ECT sensor. After receiving the start signal, the sub-ECT sensor reads the 12-bit frame number and performs electrode switching within the system. The electrode switching is such that each electrode in the sub-ECT sensor serves as an excitation electrode in turn, and the remaining electrodes serve as detection electrodes. During the data acquisition process, the capacitance array of all electrode combinations is combined with the seamlessly cut sensitive field to reconstruct a continuous three-dimensional image of each sub-ECT sensor. The imaging computer recognizes and matches data from different ECT subsystems in the same frame based on the data acquisition timestamp and the unified 12-bit frame number.

[0023] Furthermore, the image reconstruction algorithm is one of the LBP algorithm, Landweber algorithm, Tikhonov algorithm, and Newton–Raphson algorithm.

[0024] Furthermore, the sub-ECT sensor in the integrated simulation modeling includes at least two sub-ECT sensors. Specific embodiment: As attached Figure 2In this embodiment, two sub-ECT sensors, ECTa and ECTb, are used as examples. Each sub-sensor in this embodiment has 32 electrodes. The bottom four electrodes of sensor ECTa (labeled 1 and 2, with two unnumbered electrodes 3 and 4 on the back) and the top four electrodes of sensor ECTb (labeled 29 and 30, with two unnumbered electrodes 31 and 32 on the back) are seamlessly arranged. When electrode 1 of ECTa, which is located near the top of ECTb, is used as the excitation electrode, it simultaneously excites ECTb. This causes the measured capacitance between electrode 1 and electrode 29, the farthest electrodes in ECTb, to become abnormally large, resulting in the complete inability of the measurement system to perform imaging properly.

[0026] In this method, all adjacent sensors are modeled as a whole, using multi-electrode excitation. Each adjacent sub-ECT sensor has one electrode in the excitation state. For a distributed ECT system with N adjacent sub-ECT sensors, N electrodes are excited simultaneously. The total sensitive field matrix is shown in the attached figure. Figure 3 As shown in the figure (N=2), the sensitive field of each subsystem is kept consistent with the electrode excitation mode, that is, the sensor integration model under simulation is completely consistent with the data acquisition mode in the experiment, solving the interference problem between adjacent sub-ECT sensors.

[0027] Each ECT subsystem Figure 1 Under the control of the timing controller shown, all K (K=32*(32-1) / 2=496) pairs of capacitance are distributedly collected according to the excitation and detection relationship in the table below to form the capacitance matrices λa and λb of each sub-sensor. The symbol "->" in the table indicates the formation of capacitance pairs, and the left side is the excitation electrode number, and the right side is the detection electrode number. Figure 4 Based on Figure 2 The sensitive fields Sa, Sb and capacitance matrices λa, λb calculated by the integrated modeling method are used to reconstruct the image matrices ga and gb of each subsystem using the imaging algorithm, and then spliced together to form a complete g according to the positional relationship of each ECT subsystem.

[0028] Table 1. Sub-ECT sensor capacitor numbers Excitation electrode 1 1﹣>2 1﹣>3 1﹣>4 … 1﹣>32 2 / 2﹣>3 2﹣>4 … 2﹣>32 3 / / 3﹣>4 … 3﹣>32 … … … … … … 31 / / / … 31﹣>32 Although the present invention has been disclosed above in terms of preferred embodiments, they are not intended to limit the present invention. Anyone skilled in the art can make various changes or modifications without departing from the spirit and scope of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection defined by the claims of this application.

Claims

1. A 3D ECT imaging method with integrated modeling and seamlessly cut sensitive fields, used to eliminate interference between adjacent 3D ECT imaging systems; characterized by: Adjacent sub-ECT sensors with electric field interference in a three-dimensional ECT imaging system are integrated into a model. A multi-electrode excitation mode with one excitation electrode is used for each adjacent sub-ECT sensor, and the total sensitivity field matrix of the integrated model is calculated. The integrated total sensitivity field matrix is seamlessly segmented according to electrode position and imaging area affiliation. The segmented sensitivity field is used for independent imaging of the corresponding sub-ECT sensors, and the images of each sub-ECT are stitched together to form a complete ECT image.

2. The three-dimensional ECT imaging method with integrated modeling and seamless cutting of the sensitive field according to claim 1, characterized in that: The specific steps include: Step 1: Capacitive data is collected from the entire 3D ECT imaging system deployed in a complex space. The 3D ECT imaging system is composed of multiple sub-ECT sensors, each of which is equipped with multiple ECT electrodes arranged in an array. During the imaging process, one ECT electrode in each sub-ECT sensor serves as an excitation electrode, forming a capacitance pair with other electrodes in the sub-ECT sensor. Based on the capacitance values between each electrode pair and the sub-ECT sensor's sensitive field collected by the data acquisition system, the dielectric constant distribution of the enclosed 3D area is constructed, and the corresponding ECT image of the sub-ECT sensor is obtained. Step 2: Establish a finite element model of the ECT sensor and calculate the sensitive field of the integrated modeling multi-electrode excitation seamless cutting; obtain the position information of the adjacent ECT electrodes whose distance is less than the preset distance; if the adjacent ECT electrodes belong to different sub-ECT sensors, then determine that the adjacent sub-ECT sensors corresponding to the adjacent ECT electrodes are sub-ECT sensors that need to be spliced; merge all the sub-ECT sensors that need to be spliced and integrate them for simulation modeling; treat each sub-ECT sensor included in the integrated model as a unit, and each unit is equipped with an excitation electrode for multi-electrode excitation; calculate the total sensitive field matrix of the integrated model and each sub-ECT The sensitivity field process of the T sensor is as follows: first, the total sensitivity field matrix of adjacent sub-ECT sensors under multi-electrode excitation is calculated, and the total sensitivity field matrix is cut according to the position of the detection electrodes and the imaging area to obtain the sensitivity field of each sub-ECT sensor. The capacitance of the detection electrodes belonging to the same sub-ECT sensor is classified as the capacitance of the sub-ECT sensor, and the imaging pixels belonging to the area where the sub-ECT sensor is located are retained to form the sensitivity field of the sub-ECT sensor. This sensitive field takes into account the interaction between adjacent electrodes and is consistent with the excitation mode of data acquisition in step 1. It can avoid errors in image reconstruction and thus eliminate the problem of mutual interference between adjacent sub-ECT sensors. Step 3: During the imaging process, based on the capacitance data of each sub-ECT sensor collected in step 1 and the sensitive field of the sub-ECT sensor segmented in step 2, image reconstruction is performed on each adjacent sub-ECT sensor to obtain images of all sub-ECT sensors. When stitching images, the adjacent sub-ECT sensors are stitched into the ECT image of the entire system based on their locations.

3. The three-dimensional ECT imaging method with integrated modeling and seamless cutting of the sensitive field according to claim 2, characterized in that: The process of calculating the total sensitive field matrix of the integrated model and the sensitive field of each sub-ECT sensor in step 2 specifically includes: S21: The adjacent sub-ECT sensors are represented by ECTa and ECTb respectively; the space where ECTa and ECTb are located after being stimulated, i.e., the Q space, is represented by Qa and Qb respectively; the electrodes of ECTa in the Q space i and ECTb electrodes i They are all excitation electrodes, and their electric field intensity distribution is represented by E i ( x , y , z ) represents; the total sensitive field matrix S of ECTa and ECTb is calculated according to the following formula: In the above formula, represents the sensitive field strength formed by electrodes i and j at the (x, y, z) position in the Q space; Q(x, y, z) represents the (x, y, z) position in the Q space; V represents the excitation voltage; S22: Divide the 2K×2M-dimensional total sensitive field matrix S of the imaging areas of adjacent sub-ECT sensors obtained in S21 to obtain K×M-dimensional sensitive field matrices Sa and Sb of the sub-ECT sensors; where K is the number of capacitors of the sub-ECT sensor, and M is the number of imaging pixels in the sub-ECT sensor; S23: The acquired sensitive field matrices of ECTa and ECTb are represented by Sa and Sb respectively, and the capacitance matrices of the sub-ECT sensors acquired by the data acquisition system are represented by λa and λb respectively; and the reconstructed image matrices ga and gb are obtained using the following imaging formula; （2） In the above formula, the superscript T represents the transposed matrix; S24: The obtained image matrices ga and gb are stitched together into a complete ECT image g according to the positions of their sub-ECT sensors.

4. The 3D ECT imaging method with integrated modeling and seamless cutting of the sensitive field according to claim 2, characterized in that: The ECT image construction process of the entire system is as follows: the 3D ECT imaging system uses a timing controller to send a unified excitation signal to each sub-ECT sensor. After receiving the start signal, the sub-ECT sensor reads the 12-bit frame number and performs electrode switching within the system. The electrode switching is such that each electrode in the sub-ECT sensor acts as an excitation electrode in turn, and the remaining electrodes serve as detection electrodes. During the data acquisition process, the capacitance array of all electrode combinations is combined with the seamlessly cut sensitive field to reconstruct a continuous 3D image of each sub-ECT sensor. The imaging computer recognizes and matches data from different ECT subsystems in the same frame based on the data acquisition timestamp and the unified 12-bit frame number.

5. The three-dimensional ECT imaging method with integrated modeling and seamless cutting of the sensitive field according to claim 1 is characterized by: The image reconstruction algorithm is one of the LBP algorithm, Landweber algorithm, Tikhonov algorithm, and Newton–Raphson algorithm.

6. The three-dimensional ECT imaging method with integrated modeling and seamless cutting of the sensitive field according to claim 1 is characterized by: The sub-ECT sensors in the integrated simulation modeling include at least two sub-ECT sensors.

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