Method, system and storage medium for sewer flow monitoring based on three-phase tomographic imaging

Abstract

The application provides a kind of sewer flow monitoring method, system and storage medium based on three-phase tomography, belongs to fluid measurement technical field.In the method, the boundary voltage vector and the capacitance vector of the radial section of the pipeline are synchronously acquired, the conductivity and dielectric constant distribution images are respectively reconstructed, and the phase distribution map is generated after fusion, according to which the cross-section content rate of gas, liquid and solid three phases is described;Based on the time sequence phase distribution map, different algorithms are used to calculate the flow rate of each phase, and the interface coupling, mass conservation and wall boundary constraint are introduced for physical correction, and finally the total flow is accurately calculated by combining the corrected flow rate, cross-section content rate and pipeline cross-sectional area.The application fuses the dual-mode information of electrical resistance and electrical capacitance tomography, realizes the independent and accurate measurement of the phase content rate and flow rate in complex multiphase flow, and has the advantages of non-invasive, no pressure loss and wide application flow type.

Description

Technical Field

[0001] This invention belongs to the field of fluid measurement technology, and in particular relates to a method, system and storage medium for monitoring the flow of drainage pipelines based on three-phase tomography. Background Technology

[0002] The fluids in urban drainage networks and industrial wastewater pipelines are typical gas-liquid-solid multiphase flows, exhibiting complex characteristics such as transient, non-uniform, and non-constant flow. Traditional flow monitoring equipment faces significant challenges under these conditions.

[0003] Electromagnetic flowmeters rely on the conductivity of the fluid, but when the fluid contains a large amount of gas or solid deposits, it severely interferes with the measuring magnetic field, causing the measured value to deviate significantly from the true value. Ultrasonic flowmeters experience severe scattering and attenuation of their acoustic signals when passing through fluids containing a large number of bubbles or solid particles, leading to a sharp drop in the signal-to-noise ratio and measurement failure. Resistance tomography is sensitive to conductive phases and has high imaging accuracy. However, when the gas content in the fluid is too high, forming a continuous gas phase, or when the conductivity changes drastically, the reconstructed image quality deteriorates significantly, and it is insensitive to non-conductive solids. Capacitance tomography is sensitive to media with large differences in dielectric constant. However, its sensitivity to highly conductive liquids is relatively low.

[0004] Therefore, existing technologies are unable to achieve independent and accurate measurement of the gas, liquid, and solid phases under the complex flow conditions of drainage pipe networks, and are even less able to obtain the flow velocity distribution on the cross section, which restricts the improvement of the level of precise control and safety management of drainage pipe networks. Summary of the Invention

[0005] This invention provides a method, system, and storage medium for monitoring the flow of drainage pipelines based on three-phase tomography, which can achieve independent and accurate measurement of the cross-sectional area content of the gas, liquid, and solid phases in the fluid to obtain the flow velocity distribution on the cross section, thereby further improving the level of precise control and safety management of drainage pipe networks.

[0006] In a first aspect, the present invention provides a method for monitoring the flow rate of drainage pipelines based on three-phase tomography, comprising:

[0007] Obtain the boundary voltage vector and capacitance vector of the radial section corresponding to the inner diameter of the target drainage pipe;

[0008] Construct a conductivity distribution image of the radial cross section based on the boundary voltage vector of the radial cross section;

[0009] Construct a dielectric constant distribution image of the radial section based on the capacitance vector of the radial section;

[0010] The conductivity distribution image and the dielectric constant distribution image are fused and classified to obtain the phase distribution map;

[0011] Determine the cross-sectional area content of the solid, liquid, and gas phases of the fluid in the target drainage pipe based on the phase distribution diagram;

[0012] Multiple phase distribution maps are continuously acquired at the target frequency to determine the flow velocities of the solid, liquid, and gas phases in the fluid based on two adjacent phase distribution maps;

[0013] The flow velocities of each phase in the fluid are corrected based on interface coupling constraints, mass conservation constraints, and wall boundary constraints.

[0014] The flow rate of the fluid in the target drainage pipe is determined based on the cross-sectional area content of each phase, the corrected flow velocity of each phase, and the area of ​​the radial cross section.

[0015] Optionally, constructing the conductivity distribution image of the radial cross-section based on the boundary voltage vector of the radial cross-section includes:

[0016] Construct the expression for the conductivity update equation of the radial cross section:

[0017] ;

[0018] in, The conductivity distribution after the k1th calculation The sensitivity matrix at point L; T denotes the transpose of the matrix; α is the regularization parameter; L is the regularization matrix; This represents the update amount for the conductivity distribution; V represents the voltage vector residual; σ0 represents the initial uniform conductivity distribution; V bnd The boundary voltage vector of the radial section; The conductivity distribution after the k1th calculation The corresponding voltage vector; C is the selection matrix; K is the global stiffness matrix;

[0019] The conductivity distribution calculated in the (k1+1)th iteration is calculated using the following formula. :

[0020] ;

[0021] If the update amount of conductivity distribution calculated in the iteration is less than the preset conductivity distribution threshold or the iteration reaches the maximum number of iterations, the obtained conductivity distribution will be used as the conductivity distribution image of the radial section.

[0022] Optionally, constructing the dielectric constant distribution image of the radial cross-section based on the capacitance vector of the radial cross-section includes:

[0023] Construct the expression for the dielectric constant update equation of the radial section:

[0024] ;

[0025] in, The dielectric constant distribution after the k2th calculation The sensitivity matrix at point L; T denotes the transpose of the matrix; α is the regularization parameter; L is the regularization matrix; This represents the update amount of the dielectric constant distribution; The initial uniform dielectric constant distribution is used. For capacitance vector residuals; C meas The capacitance vector of the radial section; The dielectric constant distribution after the k2th calculation The corresponding capacitance vector; P(·) is the normalization operator; I(·) is the charge operator; K is the global stiffness matrix;

[0026] The dielectric constant distribution calculated in the (k2+1)th iteration is calculated using the following formula. :

[0027] ;

[0028] If the update amount of the dielectric constant distribution calculated in the iterative calculation is less than the preset dielectric constant distribution threshold or the maximum number of iterations is reached, the obtained dielectric constant distribution is used as the dielectric constant distribution image of the radial section.

[0029] Optionally, the process of fusing and classifying the conductivity distribution image and the dielectric constant distribution image to obtain a phase distribution map includes:

[0030] For conductivity distribution image I ERT Image I of (x,y) and dielectric constant distribution ECT The values ​​(x, y) are numerically normalized to ensure that the conductivity distribution image and the dielectric constant distribution image have the same numerical range, resulting in a normalized conductivity distribution image. Image of normalized permittivity distribution ;

[0031] The normalized conductivity distribution image and the normalized permittivity distribution image are fused according to the following formula:

[0032] ;

[0033] Among them, I fused (x, y) is the image obtained by fusing the normalized conductivity distribution image and the normalized permittivity distribution image; x is the x-axis coordinate value in the distribution image coordinate system; y is the y-axis coordinate value in the distribution image coordinate system; the origin of the distribution image coordinate system is the center of the radial section of the target drainage pipe, the x-axis direction is the radial direction of the target drainage pipe section and parallel to the horizontal plane, and the y-axis is perpendicular to the horizontal plane; ω is the weighting coefficient; 0 ≤ ω ≤ 1;

[0034] The fused images are classified and labeled to generate a phase distribution map.

[0035] Optionally, determining the cross-sectional area fractions of the solid, liquid, and gas phases of the fluid within the target drainage pipe based on the phase distribution diagram includes:

[0036] Obtain the total number of pixels in the phase distribution map, as well as the number of pixels in the solid phase, liquid phase, and gas phase;

[0037] The ratio of the number of pixels in each phase to the total number of pixels is used as the cross-sectional area content of the solid, liquid, and gas phases in the fluid, respectively.

[0038] Optionally, the step of continuously acquiring multiple phase distribution maps at a target frequency to determine the flow velocities of the solid, liquid, and gas phases in the fluid based on two adjacent phase distribution maps includes:

[0039] The flow velocity of the solid phase in the fluid is calculated using the cross-correlation method based on the distribution diagrams of two adjacent phases.

[0040] The flow velocity of the liquid phase in the fluid is calculated using the Lucas-Kanade optical flow method based on the distribution diagrams of two adjacent phases.

[0041] Identify independent gas masses in two adjacent phase distribution maps to extract the centroid coordinates of each gas mass;

[0042] By matching the centroid coordinates of each air mass, the displacement of the air mass between two adjacent phase distribution maps can be obtained;

[0043] The ratio of the displacement of the gas mass to the time interval between two adjacent phase distribution maps is used as the flow velocity of the gas phase in the fluid.

[0044] Optionally, the step of correcting the flow velocity of each phase in the fluid according to interface coupling constraints, mass conservation constraints, and wall boundary constraints includes:

[0045] Construct an objective function J that minimizes the deviation between the measured velocity and the physical constraints:

[0046] ;

[0047] Where λ1 is the interface coupling constraint term J interface The weighting coefficients; λ2 is the mass conservation constraint term J. mass The weighting coefficients; λ3 is the wall boundary constraint term J. wall Weighting coefficients; Γ gl For gas-liquid interface; V g V is the velocity of the gas phase in the fluid; l n represents the flow velocity of the liquid phase in the fluid. gl dS represents the unit normal vector of the gas-liquid interface; dS represents the area integral. The divergence sign is α.k V is the cross-sectional area fraction of the gas or liquid phase in a fluid; k Γ represents the flow velocity of the gas or liquid phase in the fluid; dV represents the volume integral; wall For wall surface; V m n represents the flow velocity of the solid, liquid, or gas phase in the fluid. wall t is the unit normal vector of the wall; wall The unit tangent vector of the wall;

[0048] The objective function is solved using the gradient descent method to obtain the corrected flow velocities of each phase.

[0049] Optionally, determining the flow rate of the fluid in the target drainage pipe based on the cross-sectional area fraction of each phase, the corrected flow velocity of each phase, and the area of ​​the radial cross section includes:

[0050] Calculate the flow rate Q of the fluid in the target drainage pipe using the following formula. total :

[0051] ;

[0052] Among them, V g_c The corrected gas phase flow rate; α g V is the cross-sectional area fraction of the gas phase in the fluid; l_c The corrected liquid flow rate; α l V is the cross-sectional area fraction of the liquid phase in the fluid; s_c The corrected solid flow rate; α s A represents the cross-sectional area fraction of the solid phase in the fluid; pipe This represents the area of ​​the radial cross-section.

[0053] Secondly, the present invention provides a drainage pipeline flow monitoring system based on three-phase tomography, comprising:

[0054] The acquisition module is used to acquire the boundary voltage vector and capacitance vector of the radial section corresponding to the inner diameter of the target drainage pipe;

[0055] The first construction module is used to construct a conductivity distribution image of the radial cross section based on the boundary voltage vector of the radial cross section;

[0056] The second construction module is used to construct a dielectric constant distribution image of the radial section based on the capacitance vector of the radial section;

[0057] The fusion and annotation module is used to fuse and classify the conductivity distribution image and the dielectric constant distribution image to obtain the phase distribution map;

[0058] The first determining module is used to determine the cross-sectional area content of the solid, liquid and gas phases of the fluid in the target drainage pipe based on the phase distribution diagram.

[0059] The second determining module is used to continuously acquire multiple phase distribution maps at a target frequency in order to determine the flow velocities of the solid, liquid and gas phases in the fluid based on two adjacent phase distribution maps.

[0060] The calibration module is used to correct the flow velocity of each phase in the fluid according to the interface coupling constraint, mass conservation constraint and wall boundary constraint respectively;

[0061] The third determining module is used to determine the flow rate of the fluid in the target drainage pipe based on the cross-sectional area content of each phase, the corrected flow velocity of each phase, and the area of ​​the radial cross section.

[0062] Thirdly, the present invention provides a computer-readable storage medium for storing a computer program; when the computer program is executed by a processor, it implements the steps of the drainage pipeline flow monitoring method based on three-phase tomography as described in the first aspect.

[0063] This invention provides a method, system, and storage medium for monitoring the flow of drainage pipelines based on three-phase tomography. The method fuses dual-modal information from conductivity imaging and dielectric constant imaging, enabling simultaneous response to differences in conductivity and dielectric properties. This overcomes the insufficient sensitivity of single-modal methods under continuous gas phase, highly conductive liquid, or non-conductive solid conditions, and significantly improves the identification accuracy and robustness of the three phases in complex multiphase flows.

[0064] Based on the time-series phase distribution diagram, the flow velocity of each phase can be calculated separately, enabling independent acquisition of the flow velocities of the gas, liquid, and solid phases. Furthermore, combined with the cross-sectional content of each phase, phase flow monitoring can be achieved, providing key data support for the dynamic process analysis of multiphase flow in drainage pipe networks.

[0065] By introducing interface coupling, mass conservation, and wall boundary constraints to physically correct the flow velocity, and combining the observation data with the basic laws of fluid mechanics, the distortion of flow velocity caused by image noise, algorithm errors, etc. is effectively reduced, and the physical rationality of the flow rate results and the overall measurement accuracy are improved. Attached Figure Description

[0066] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0067] Figure 1 A schematic flowchart of a drainage pipeline flow monitoring method based on three-phase tomography provided in an embodiment of the present invention;

[0068] Figure 2 This is a schematic cross-sectional view of the signal acquisition device provided in an embodiment of the present invention;

[0069] Figure 3 This is a three-dimensional structural diagram of the signal acquisition device provided in an embodiment of the present invention;

[0070] Figure 4 This is a schematic diagram of a drainage pipeline flow monitoring system based on three-phase tomography, provided as an embodiment of the present invention. Detailed Implementation

[0071] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0072] Example 1

[0073] like Figure 1 As shown, this embodiment provides a method for monitoring the flow rate of drainage pipelines based on three-phase tomography, including:

[0074] Step 101: Obtain the boundary voltage vector and capacitance vector of the radial section corresponding to the inner diameter of the target drainage pipe.

[0075] like Figure 2 and Figure 3 As shown, the inner wall of the target drainage pipe is embedded with an electrode array consisting of multiple alternating and uniformly arranged ERT electrodes C1 and ECT electrodes C2 for collecting signals within the pipe. Each electrode is wrapped with a grounded electromagnetic shielding layer C3 to suppress external electromagnetic interference. Each electrode is fixed to the inner wall of the pipe by fixing bolts C4 and connected to a flexible flow meter housing C10, which allows the flow meter to adapt to different pipe diameters. After the electrodes collect information, the information is transmitted to the image information processor C6 via a data transmission line C5. The image information processor C6 carries a processor that performs tomographic image reconstruction, converting the original signal into conductivity and dielectric constant values. The flow distribution image, based on the reconstructed tomographic image, performs information fusion and outputs a phase distribution map to the flow calculation device C7 and the result output display device C9. The flow calculation device C7 is equipped with a computing chip and integrates a flow velocity calculation algorithm. It adaptively selects the best algorithm combination according to the flow pattern, calculates the velocity of each phase and the total flow, and outputs it to the result output display device C9. The results are also uploaded to the data monitoring center via a wireless network. The result output display device C9 and the flow calculation device C7 are connected by a hinge C8, which makes the angle of the output display device C9 adjustable. At the same time, the result output display device can display the phase distribution results and the flow calculation results on the display device C9.

[0076] The aforementioned device is used to control the excitation of ERT and ECT in a time-sharing or simultaneous manner, and to acquire the boundary voltage vector and capacitance vector of the radial section corresponding to the inner diameter of the target drainage pipe. It should be noted that the radial section corresponding to the inner diameter is the radial section of the cavity of the target drainage pipe, i.e., the pipe wall thickness is not considered.

[0077] Step 102: Construct a conductivity distribution image of the radial cross section based on the boundary voltage vector of the radial cross section.

[0078] In this step, the Tikhonov regularized iterative algorithm is used to reconstruct the conductivity distribution image of the radial cross section based on the boundary voltage vector; for example, this step includes:

[0079] Construct the expression for the conductivity update equation of the radial cross section:

[0080] .

[0081] in, The conductivity distribution after the k1th calculation The sensitivity matrix at point L; T denotes the transpose of the matrix; α is the regularization parameter; L is the regularization matrix; This represents the update amount for the conductivity distribution; V represents the voltage vector residual; σ0 represents the initial uniform conductivity distribution; V bnd The boundary voltage vector of the radial section; The conductivity distribution after the k1th calculation The corresponding voltage vector; C is the selection matrix; K is the global stiffness matrix.

[0082] The conductivity distribution calculated in the (k1+1)th iteration is calculated using the following formula. :

[0083] .

[0084] Solve the conductivity update equation to obtain the update amount of conductivity distribution. If the update amount of conductivity distribution calculated by iteration is less than the preset conductivity distribution threshold or the iteration reaches the maximum number of iterations, the obtained conductivity distribution is used as the conductivity distribution image of the radial section.

[0085] Step 103: Construct a dielectric constant distribution image of the radial section based on the capacitance vector of the radial section.

[0086] In this step, the dielectric constant distribution image of the radial cross section is reconstructed using the Tikhonov regularized iterative algorithm based on the capacitance vector; exemplarily, this step includes:

[0087] Construct the expression for the dielectric constant update equation of the radial section:

[0088] .

[0089] in, The dielectric constant distribution after the k2th calculation The sensitivity matrix at point L; T denotes the transpose of the matrix; α is the regularization parameter; L is the regularization matrix; This represents the update amount of the dielectric constant distribution; The initial uniform dielectric constant distribution is used. For capacitance vector residuals; C meas The capacitance vector of the radial section; The dielectric constant distribution after the k2th calculation The corresponding capacitance vector; P(·) is the normalization operator; I(·) is the charge operator; K is the global stiffness matrix.

[0090] The dielectric constant distribution calculated in the (k2+1)th iteration is calculated using the following formula. :

[0091] .

[0092] Solve the dielectric constant update equation to obtain the update amount of the dielectric constant distribution. If the update amount of the dielectric constant distribution is less than the preset dielectric constant distribution threshold or the iteration reaches the maximum number of iterations, the obtained dielectric constant distribution is used as the dielectric constant distribution image of the radial section.

[0093] Step 104: The conductivity distribution image and the dielectric constant distribution image are fused and classified to obtain the phase distribution map.

[0094] In this step, the conductivity distribution image I ERT Image I of (x,y) and dielectric constant distribution ECT Spatial unification is performed on (x,y) to make I ERT (x,y) and I ECT (x,y) have the same resolution and position.

[0095] For example, the Z-score normalization method is used to analyze the conductivity distribution image I. ERT Image I of (x,y) and dielectric constant distribution ECT The values ​​(x, y) are numerically normalized to ensure that the conductivity distribution image and the dielectric constant distribution image have the same numerical range, resulting in a normalized conductivity distribution image. Image of normalized permittivity distribution .

[0096] Using the linear weighting method to analyze I ERT (x,y) and I ECTPixel-level fusion is performed on (x,y), that is, the normalized conductivity distribution image and the normalized permittivity distribution image are fused according to the following formula:

[0097] .

[0098] Among them, I fused (x,y) is the image obtained by fusing the normalized conductivity distribution image and the normalized dielectric constant distribution image; x is the x-axis coordinate value in the distribution image coordinate system; y is the y-axis coordinate value in the distribution image coordinate system; the origin of the distribution image coordinate system is the center of the radial section of the target drainage pipe, the x-axis direction is the radial direction of the target drainage pipe section and parallel to the horizontal plane, and the y-axis is perpendicular to the horizontal plane; ω is the weighting coefficient; 0≤ω≤1.

[0099] For the fused image I fused (x,y) are classified and labeled to generate a high-precision phase distribution map M. phase (x, y); where the classification rules are as follows:

[0100] The region with high conductivity and medium dielectric constant is the liquid phase region.

[0101] The region with low electrical conductivity and low dielectric constant is the gas phase region.

[0102] Special combinations of electrical conductivity and dielectric properties (such as low electrical conductivity and high dielectric properties being non-conductive solids, and high electrical conductivity and unique morphology being conductive solids) constitute the solid phase region.

[0103] Among them, the conductivity value is less than 10. -6 Siemens / meter has low conductivity, at 10 -6 Siemens / Mi-10 6 Siemens / meter has medium conductivity, greater than 10. 6 Siemens / meter has high conductivity.

[0104] A dielectric constant value below 5.0 is considered low dielectric constant, between 5.0 and 20.0 is considered medium dielectric constant, and above 20.0 is considered high dielectric constant.

[0105] Step 105: Determine the cross-sectional area content of the solid, liquid and gas phases of the fluid in the target drainage pipe based on the phase distribution diagram.

[0106] For example, this step includes:

[0107] Obtain the total number of pixels in the phase distribution map, as well as the number of pixels in the solid phase, liquid phase, and gas phase.

[0108] The ratio of the number of pixels in each phase to the total number of pixels is used as the cross-sectional area content of the solid, liquid, and gas phases in the fluid, respectively; that is, the cross-sectional area content α of the solid phase. s=N 固 / N total N 固 N represents the number of pixels of the solid phase in the phase distribution diagram. total The total number of pixels in the phase distribution map; the cross-sectional area content α of the liquid phase. l =N 液 / N total N 液 The number of pixels in the liquid phase of the phase distribution diagram; the cross-sectional area content of the gas phase. N 气 This represents the number of pixels in the gas phase of the phase distribution map.

[0109] Step 106: Continuously acquire multiple phase distribution maps at the target frequency to determine the flow velocities of the solid, liquid, and gas phases in the fluid based on two adjacent phase distribution maps.

[0110] In this step, images are continuously acquired and reconstructed at high frequencies (typically 50Hz~1000Hz) to form a three-phase distribution image time series M=[M phase_1 (x,y), M phase_2 (x,y),…,M phase_n (x,y)]. Different methods are used to calculate the flow rate for different phases.

[0111] For example, the flow velocity of the solid phase in the fluid is calculated using the cross-correlation method based on two adjacent phase distribution maps.

[0112] Solid particles are treated as natural tracer particles. Solid phase flow velocities are calculated using a cross-correlation algorithm by identifying the images of solid particles in two consecutive phase distribution maps.

[0113] Specifically, at two measurement sections (the first measurement section and the second measurement section) that are D apart along the direction of fluid flow, the cross-sectional content time series S1(t) of the solid phase at the first measurement section and the cross-sectional content time series S2(t) of the solid phase at the second measurement section are extracted.

[0114] Construct the cross-correlation function R of S1(t) and S2(t) 12 The expression for (τ):

[0115] .

[0116] Where τ is the time interval parameter.

[0117] Calculate R 12 (τ) The time interval parameter τ at which the maximum value is reached. max According to V s =D / τ max The average flow velocity V of the solid phase is obtained s .

[0118] The flow velocity V of the liquid phase in the fluid is calculated using the Lucas-Kanade optical flow method based on the distribution diagrams of two adjacent phases. l .

[0119] Specifically, the liquid phase velocity field is obtained by solving the optical flow equation over the entire liquid phase region. The optical flow equation is as follows:

[0120] .

[0121] in, I represents the spatial gradient of electrical conductivity. t denoted as the rate of change of electrical conductivity.

[0122] Identify independent gas masses in two adjacent phase distribution maps to extract the centroid coordinates of each gas mass.

[0123] By matching the centroid coordinates of each air mass, the displacement of the air mass between two adjacent phase distribution maps can be obtained. .

[0124] Displacement of air masses Time interval between two adjacent phase distribution diagrams The ratio of to is used as the velocity V of the gas phase in the fluid. g ,Right now, .

[0125] Step 107: Correct the flow velocity of each phase in the fluid according to the interface coupling constraint, mass conservation constraint and wall boundary constraint respectively.

[0126] In this step, an interface coupling constraint is introduced to ensure that the normal velocities of the two phases are continuous at the gas-liquid interface.

[0127] Mass conservation constraints are introduced to ensure that the velocities of each phase satisfy the continuity equation.

[0128] By introducing a no-slip condition on the wall, it is ensured that the normal components of the velocities of each phase are zero at the pipe wall.

[0129] For example, an objective function J is constructed to minimize the deviation between the measured velocity and the physical constraints:

[0130] .

[0131] Where λ1 is the interface coupling constraint term J interface The weighting coefficients; λ2 is the mass conservation constraint term J. mass The weighting coefficients; λ3 is the wall boundary constraint term J. wall Weighting coefficients; Γ gl For gas-liquid interface; V g V is the velocity of the gas phase in the fluid; l n represents the flow velocity of the liquid phase in the fluid.gl dS represents the unit normal vector of the gas-liquid interface; dS represents the area integral. The divergence sign is α. k V is the cross-sectional area fraction of the gas or liquid phase in a fluid; k Γ represents the flow velocity of the gas or liquid phase in the fluid; dV represents the volume integral; wall For wall surface; V m n represents the flow velocity of the solid, liquid, or gas phase in the fluid. wall t is the unit normal vector of the wall; wall This is the unit tangent vector of the wall.

[0132] The objective function is solved using the gradient descent method to obtain the corrected flow velocities of each phase.

[0133] Step 108: Determine the flow rate of the fluid in the target drainage pipe based on the cross-sectional area content of each phase, the corrected flow velocity of each phase, and the area of ​​the radial cross section.

[0134] For example, the flow rate Q of the fluid in the target drainage pipe is calculated according to the following formula. total :

[0135] .

[0136] Among them, V g_c The corrected gas phase flow rate; α g V is the cross-sectional area fraction of the gas phase in the fluid; l_c The corrected liquid flow rate; α l V is the cross-sectional area fraction of the liquid phase in the fluid; s_c The corrected solid flow rate; α s A represents the cross-sectional area fraction of the solid phase in the fluid; pipe This represents the area of ​​the radial cross-section.

[0137] This embodiment further discloses specific examples.

[0138] If the diameter of the pipe section measured by the equipment is 0.5m, then the cross-sectional area A is... pipe ≈0.196m 2 .

[0139] ERT and ECT electrode arrays are arranged on two cross-sections with a distance of D = 0.1 m. The electrode arrays collect data at a frequency of f = 200 Hz, i.e., the acquisition interval is... =0.005s.

[0140] Phase distribution identification map M obtained by data acquisition and fusion phase (x, y), the number of pixels in each phase is obtained as follows:

[0141] Total pixels .

[0142] Liquid phase pixel count .

[0143] Gas phase pixel count .

[0144] Number of solid phase pixels .

[0145] Calculate the cross-sectional area content of each phase:

[0146] .

[0147] Calculate the flow velocities of each phase:

[0148] Gas flow rate V g Displacement was measured by matching air masses using the Hungarian algorithm. .

[0149] .

[0150] Liquid flow rate V l The average flow velocity was calculated using the Lucas-Kanade optical flow method.

[0151] .

[0152] solid flow velocity V s The maximum cross-correlation time was measured using the cross-correlation method.

[0153] .

[0154] By introducing physical constraints such as interface coupling constraints, mass conservation constraints, and wall no-slip constraints, and using the gradient descent method for correction, the corrected three-phase flow velocities are obtained.

[0155] .

[0156] The total flow rate is calculated as follows:

[0157] .

[0158] In summary, the drainage pipeline flow monitoring method based on three-phase tomography provided in this embodiment effectively overcomes the inherent defects of single-mode technology by complementing dual-modal imaging (conductivity distribution image and dielectric constant distribution image), enabling the drainage pipeline to maintain extremely high measurement accuracy and stability even in complex multiphase flows containing a large number of bubbles and solid particles.

[0159] This embodiment is not limited by flow pattern. It can effectively identify and accurately measure bubbly flow, slug flow, stratified flow, or annular flow, solving the industry problem of traditional flow meters experiencing drastic performance deterioration or even failure under specific flow patterns.

[0160] Signal acquisition is achieved based on a wall-mounted electrode array, which eliminates the need to insert measuring elements or change the flow field structure. It has the advantages of being non-invasive, pressure loss-free, and wear-free, and is suitable for long-term, high-reliability monitoring of complex media such as municipal drainage and industrial wastewater.

[0161] A velocity correction based on physical constraints (interface coupling, mass conservation, wall boundary) is introduced, which deeply integrates observation data with the basic laws of fluid mechanics, effectively correcting errors and physical contradictions that may be introduced by a single algorithm.

[0162] In this embodiment, solid flow monitoring can be used to provide early warning of pipeline sedimentation, and comprehensive analysis of liquid level and flow rate can be used to provide early warning of overflow risk.

[0163] Example 2

[0164] Based on the same inventive concept as Embodiment 1, this embodiment provides a drainage pipeline flow monitoring system based on three-phase tomography. Since the principle of this system in solving the problem is similar to that of the drainage pipeline flow monitoring method based on three-phase tomography described in Embodiment 1, the implementation of this system can refer to the implementation of the drainage pipeline flow monitoring method based on three-phase tomography.

[0165] like Figure 4 As shown, this embodiment provides a drainage pipeline flow monitoring system based on three-phase tomography, including:

[0166] The acquisition module 10 is used to acquire the boundary voltage vector and capacitance vector of the radial section corresponding to the inner diameter of the target drainage pipe.

[0167] The first construction module 20 is used to construct a conductivity distribution image of the radial section based on the boundary voltage vector of the radial section.

[0168] The second construction module 30 is used to construct a dielectric constant distribution image of the radial section based on the capacitance vector of the radial section.

[0169] The fusion annotation module 40 is used to fuse and classify the conductivity distribution image and the dielectric constant distribution image to obtain the phase distribution map.

[0170] The first determining module 50 is used to determine the cross-sectional area content of the solid, liquid and gas phases of the fluid in the target drainage pipe based on the phase distribution diagram.

[0171] The second determining module 60 is used to continuously acquire multiple phase distribution maps at a target frequency in order to determine the flow velocities of the solid phase, liquid phase and gas phase in the fluid based on two adjacent phase distribution maps.

[0172] The calibration module 70 is used to correct the flow velocity of each phase in the fluid according to the interface coupling constraint, mass conservation constraint and wall boundary constraint.

[0173] The third determining module 80 is used to determine the flow rate of the fluid in the target drainage pipe based on the cross-sectional area content of each phase, the corrected flow velocity of each phase, and the area of ​​the radial cross section.

[0174] For more detailed information on the working process of each of the above modules, please refer to the relevant content disclosed in Example 1, which will not be repeated here.

[0175] Example 3

[0176] This embodiment provides a computer device, including a processor and a memory; wherein, when the processor executes the computer program stored in the memory, it implements the steps of the drainage pipeline flow monitoring method based on three-phase tomography as described in Embodiment 1.

[0177] For a more detailed explanation of the above method, please refer to the relevant content disclosed in Example 1, which will not be repeated here.

[0178] Example 4

[0179] This embodiment provides a computer-readable storage medium for storing a computer program; when the computer program is executed by a processor, it implements the steps of the drainage pipeline flow monitoring method based on three-phase tomography described in Embodiment 1.

[0180] For a more detailed explanation of the above method, please refer to the relevant content disclosed in Example 1, which will not be repeated here.

[0181] Example 5

[0182] This embodiment provides a computer program product, including computer-executable instructions or a computer program. When the computer-executable instructions or the computer program are executed by a processor, they implement the steps of the drainage pipeline flow monitoring method based on three-phase tomography described in Embodiment 1.

[0183] For a more detailed explanation of the above method, please refer to the relevant content disclosed in Example 1, which will not be repeated here.

[0184] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems, devices, storage media, and computer program products disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple, and relevant parts can be referred to the method section.

[0185] Those skilled in the art will clearly understand that the techniques in the embodiments of the present invention can be implemented using software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments of the present invention.

[0186] In some embodiments, computer-executable instructions may take the form of programs, software, software modules, scripts, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as stand-alone programs or as modules, components, subroutines, or other units suitable for use in a computing environment.

[0187] As an example, computer-executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple co-located files (e.g., files that store one or more modules, subroutines, or code sections).

[0188] As an example, computer-executable instructions can be deployed to execute on a single electronic device, or on multiple electronic devices located at one location, or on multiple electronic devices distributed across multiple locations and interconnected via a communication network.

[0189] The present invention has been described in detail above with reference to specific embodiments and exemplary examples; however, these descriptions should not be construed as limiting the present invention. Those skilled in the art will understand that various equivalent substitutions, modifications, or improvements can be made to the technical solutions and embodiments of the present invention without departing from the spirit and scope of the invention, and all such modifications and improvements fall within the scope of the present invention. The scope of protection of the present invention is defined by the appended claims.

Claims

1. A sewer flow monitoring method based on three-phase tomography, characterized by, The method comprises the following steps: obtaining a boundary voltage vector and a capacitance vector of a radial section corresponding to an inner diameter of a target drainage pipe; constructing an electrical conductivity distribution image of the radial section according to the boundary voltage vector of the radial section; constructing a dielectric constant distribution image of the radial section according to the capacitance vector of the radial section; fusing and classifying the electrical conductivity distribution image and the dielectric constant distribution image to obtain a phase distribution image; determining the cross-sectional area content rates of the solid phase, the liquid phase and the gas phase of the fluid in the target drainage pipe according to the phase distribution image; continuously obtaining a plurality of phase distribution images at a target frequency, and determining the flow rates of the solid phase, the liquid phase and the gas phase in the fluid according to adjacent two phase distribution images; correcting the flow rates of each phase in the fluid according to interface coupling constraints, mass conservation constraints and wall boundary constraints respectively; determining the flow rate of the fluid in the target drainage pipe according to the cross-sectional area content rates of each phase, the corrected flow rates of each phase and the area of the radial section; wherein the continuously obtaining a plurality of phase distribution images at a target frequency, and determining the flow rates of the solid phase, the liquid phase and the gas phase in the fluid according to adjacent two phase distribution images comprises: calculating the flow rate of the solid phase in the fluid by using a cross-correlation method based on adjacent two phase distribution images; calculating the flow rate of the liquid phase in the fluid by using a Lucas-Kanade optical flow method based on adjacent two phase distribution images; identifying independent air masses in adjacent two phase distribution images to extract the centroid coordinates of each air mass; performing air mass matching on the centroid coordinates of each air mass to obtain the displacement of the air mass between adjacent two phase distribution images; taking the ratio of the displacement of the air mass to the time interval of adjacent two phase distribution images as the flow rate of the gas phase in the fluid; the correcting the flow rates of each phase in the fluid according to interface coupling constraints, mass conservation constraints and wall boundary constraints respectively comprises: constructing a target function J that aims to minimize the deviation between the measured velocity and the physical constraints: ； wherein λ1 is the weight coefficient of the interface coupling constraint term J interface ; λ2 is the weight coefficient of the mass conservation constraint term J mass ; λ3 is the weight coefficient of the wall boundary constraint term J wall ; Γ gl is the gas-liquid interface; V g is the flow rate of the gas phase in the fluid; V l is the flow rate of the liquid phase in the fluid; n gl is the unit normal vector of the gas-liquid interface; dS represents the area integral; is the divergence symbol; α k is the cross-sectional area fraction of the gas phase or the liquid phase in the fluid; V k is the flow rate of the gas phase or the liquid phase in the fluid; dV represents the volume integral; Γ wall is the wall surface; V m is the flow rate of the solid phase, the liquid phase or the gas phase in the fluid; n wall is the unit normal vector of the wall surface; t wall is the unit tangent vector of the wall surface; solving the target function by using a gradient descent method to obtain the corrected flow rates of each phase; the determining the flow rate of the fluid in the target drainage pipe according to the cross-sectional area content rates of each phase, the corrected flow rates of each phase and the area of the radial section comprises: The flow rate Q of the fluid in the target sewer pipe is calculated according to the following formula total : ； where V g_c is the corrected gas phase flow rate; a g is the cross-sectional area fraction of the gas phase in the fluid; V l_c is the corrected liquid phase flow rate; a l is the cross-sectional area fraction of the liquid phase in the fluid; V s_c is the corrected solid phase flow rate; a s is the cross-sectional area fraction of the solid phase in the fluid; A pipe is the area of the radial cross-section.

2. The sewer flow monitoring method according to claim 1, characterized in that, the constructing the electrical conductivity distribution image of the radial section according to the boundary voltage vector of the radial section comprises: constructing an expression of an electrical conductivity update equation of the radial section: ； wherein, is the sensitivity matrix at the conductivity distribution after the k1th computation; T denotes the transpose of a matrix; a is a regularization parameter; L is a regularization matrix; is the update of the conductivity distribution; is the update of the conductivity distribution; is the voltage vector residual; a0is the initial uniform conductivity distribution; V bnd is the boundary voltage vector of the radial cross-section; is the conductivity distribution after the k1th computation is the corresponding voltage vector; C is a selection matrix; K is the global stiffness matrix; The conductivity distribution for the k1+1th calculation is calculated according to the following equation : ； in the case of iterative calculation until the update amount of the electrical conductivity distribution is less than a preset electrical conductivity distribution threshold or the iteration reaches a maximum number, taking the obtained electrical conductivity distribution as the electrical conductivity distribution image of the radial section.

3. The sewer flow monitoring method according to claim 1, characterized in that, the constructing the dielectric constant distribution image of the radial section according to the capacitance vector of the radial section comprises: constructing an expression of a dielectric constant update equation of the radial section: ； wherein, is the sensitivity matrix at the dielectric constant distribution after the k2 computation T denotes the transpose of the matrix; a is a regularization parameter; L is a regularization matrix; is the update of the dielectric constant distribution; is the initial uniform dielectric constant distribution; is the capacitance vector residual; C meas is the capacitance vector of the radial section; is the dielectric constant distribution after the k2 computation is the corresponding capacitance vector; P(·) is a normalization operator; I(·) is a charge operator; K is a global stiffness matrix; The dielectric constant distribution of the k2+1th calculation is calculated according to the following formula : ； in the case of iterative calculation until the update amount of the dielectric constant distribution is less than a preset dielectric constant distribution threshold or the iteration reaches a maximum number, taking the obtained dielectric constant distribution as the dielectric constant distribution image of the radial section.

4. The sewer flow monitoring method according to claim 1, characterized in that, the fusing and classifying the electrical conductivity distribution image and the dielectric constant distribution image to obtain the phase distribution image comprises: to the conductivity distribution image I ERT (x,y) and the dielectric constant distribution image I ECT (x,y) are numerically normalized so that the conductivity distribution image and the dielectric constant distribution image have the same numerical range, to obtain a normalized conductivity distribution image with the normalized dielectric constant distribution image ; fusing the normalized electrical conductivity distribution image and the normalized dielectric constant distribution image according to the following formula: ； wherein I fused (x,y) is the image after fusion of the normalized conductivity distribution image and the normalized permittivity distribution image; x is the x-axis coordinate value on the distribution image coordinate system; y is the y-axis coordinate value on the distribution image coordinate system; the origin of the distribution image coordinate system is the center of the target drainage pipeline radial cross section, the x-axis direction is the radial direction of the target drainage pipeline cross section and parallel to the horizontal direction, and the y-axis is perpendicular to the horizontal direction; ω is a weight coefficient; 0≤ω≤1; performing classification labeling on the fused image to generate the phase distribution image.

5. The sewer flow monitoring method of claim 1, wherein, The method comprises the following steps of: acquiring the total number of pixels in the phase distribution map and the number of pixels in the solid phase, the number of pixels in the liquid phase and the number of pixels in the gas phase; taking the ratio of the number of pixels in each phase to the total number of pixels as the cross-sectional area content rate of the solid phase, the liquid phase and the gas phase in the fluid.

6. A sewer flow monitoring system based on three-phase tomography, characterized by The method comprises the following steps of: an acquisition module, configured to acquire the boundary voltage vector and the capacitance vector of the radial cross section corresponding to the inner diameter of the target drainage pipeline; a first construction module, configured to construct an electrical conductivity distribution image of the radial cross section according to the boundary voltage vector of the radial cross section; a second construction module, configured to construct a dielectric constant distribution image of the radial cross section according to the capacitance vector of the radial cross section; a fusion and labeling module, configured to fuse and classify the electrical conductivity distribution image and the dielectric constant distribution image to obtain a phase distribution map; a first determination module, configured to determine the cross-sectional area content rate of the solid phase, the liquid phase and the gas phase in the fluid in the target drainage pipeline according to the phase distribution map; a second determination module, configured to continuously acquire a plurality of phase distribution maps at a target frequency, and to determine the flow rate of the solid phase, the liquid phase and the gas phase in the fluid according to adjacent two phase distribution maps; a correction module, configured to correct the flow rate of each phase in the fluid according to the interface coupling constraint, the mass conservation constraint and the wall boundary constraint; a third determination module, configured to determine the flow rate of the fluid in the target drainage pipeline according to the cross-sectional area content rate of each phase, the corrected flow rate of each phase and the area of the radial cross section; wherein the continuously acquiring a plurality of phase distribution maps at a target frequency and determining the flow rate of the solid phase, the liquid phase and the gas phase in the fluid according to adjacent two phase distribution maps comprises the following steps of: calculating the flow rate of the solid phase in the fluid by using the cross-correlation method based on adjacent two phase distribution maps; calculating the flow rate of the liquid phase in the fluid by using the Lucas-Kanade optical flow method based on adjacent two phase distribution maps; identifying independent air masses in adjacent two phase distribution maps to extract the centroid coordinates of each air mass; performing air mass matching on the centroid coordinates of each air mass to obtain the displacement of the air mass between adjacent two phase distribution maps; taking the ratio of the displacement of the air mass to the time interval of adjacent two phase distribution maps as the flow rate of the gas phase in the fluid; the correction module, configured to correct the flow rate of each phase in the fluid according to the interface coupling constraint, the mass conservation constraint and the wall boundary constraint, comprises the following steps of: constructing a target function J that aims to minimize the deviation between the measured velocity and the physical constraint; ； where λ1 is the weight coefficient of the interface coupling constraint term J interface ; λ2 is the weight coefficient of the mass conservation constraint term J mass ; λ3 is the weight coefficient of the wall boundary constraint term J wall ; Γ gl is the gas-liquid interface; V g is the flow rate of the gas phase in the fluid; V l is the flow rate of the liquid phase in the fluid; n gl is the unit normal vector of the gas-liquid interface; dS represents the area integral; is the divergence symbol; α k is the cross-sectional area fraction of the gas phase or the liquid phase in the fluid; V k is the flow rate of the gas phase or the liquid phase in the fluid; dV represents the volume integral; Γ wall is the wall surface; V m is the flow rate of the solid phase, the liquid phase or the gas phase in the fluid; n wall is the unit normal vector of the wall surface; t wall is the unit tangent vector of the wall surface; solving the target function by using the gradient descent method to obtain the corrected flow rate of each phase; the third determination module, configured to determine the flow rate of the fluid in the target drainage pipeline according to the cross-sectional area content rate of each phase, the corrected flow rate of each phase and the area of the radial cross section, comprises the following steps of: The flow rate Q of the fluid in the target sewer pipe is calculated according to the following formula total : ； wherein V g_c is the corrected gas phase flow rate; a g is the cross-sectional area fraction of the gas phase in the fluid; V l_c is the corrected liquid phase flow rate; a l is the cross-sectional area fraction of the liquid phase in the fluid; V s_c is the corrected solid phase flow rate; a s is the cross-sectional area fraction of the solid phase in the fluid; A pipe is the area of the radial cross-section.

7. A computer-readable storage medium, characterized in that, a computer program storage unit, configured to store a computer program; the computer program is executed by a processor to implement the steps of the drainage pipeline flow monitoring method based on three-phase tomography in any one of claims 1-5.

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