Intelligent monitoring system and method for open channel flow

Abstract

The application provides an open channel flow intelligent monitoring system and method, which determines a continuous flow velocity field of a target open channel measurement section, divides the measurement section into a core hydraulic subzone and a transition zone hydraulic subzone according to the flow velocity gradient characteristics of each flow velocity distribution point in the continuous flow velocity field, determines a vertical projection line of the main flow velocity direction in the continuous flow velocity field, extracts the maximum possible detention flow of the water flow on the left side of the vertical projection line and the maximum possible detention flow of the water flow on the right side of the vertical projection line from the continuous flow velocity field according to a preset hydraulic detention flow condition, and further determines a detention flow influence coefficient of the measurement section; the dominant flow velocity of the water flow inertia force and the dominant flow velocity of the water flow resistance are jointly adjusted based on the detention flow influence coefficient to obtain a flow velocity adjustment value; and the flow monitoring data of the target open channel is determined according to the flow cross-sectional area of the current measurement section and the flow velocity adjustment value. The technical scheme provided by the application can accurately identify the asymmetric resistance characteristics in the water flow direction, and further reduce the calculation error of the overall flow at the measurement section.

Description

Technical Field

[0001] This application relates to the field of water channel flow monitoring technology, and more specifically, to an intelligent monitoring system and method for open channel flow. Background Technology

[0002] Water flow monitoring is a key technology in the fields of water resource management and water conservancy engineering. With the advancement of smart water conservancy construction, traditional manual measurement can no longer meet the requirements of real-time and accuracy. Currently, scenarios such as basin flood warning, agricultural irrigation optimization, and urban water supply and drainage scheduling all place higher demands on the dynamic acquisition of flow data. The development of sensing technologies such as ultrasonic, Doppler, and electromagnetic sensors has made non-contact flow monitoring possible, while the integration of the Internet of Things, big data, and edge computing has enabled remote transmission and intelligent analysis of monitoring data.

[0003] In existing canal flow monitoring, flow monitoring is usually based on a combination of fluid mechanics and sensing technology. For example, ultrasonic flow measurement calculates the flow velocity by measuring the time difference of sound wave propagation in the water flow (time difference method) or Doppler frequency shift (Doppler method) and then combines it with the cross-sectional area to obtain the flow rate. Open channel flow meters (such as Parshall flumes) measure the water level changes in the channel and convert the flow rate by combining the flume's geometric parameters. Pressure monitoring obtains the water depth through level sensors and estimates the flow rate by combining the channel shape and empirical formulas for flow velocity. However, in existing intelligent open channel flow monitoring, the flow monitoring methods cannot accurately identify the asymmetric hindrance characteristics in the direction of water flow, resulting in distortion of the flow velocity representativeness in the transition zone of the measurement section, which in turn causes calculation errors in the overall flow rate at the measurement section. Therefore, how to accurately identify the asymmetric hindrance characteristics in the direction of water flow and thus reduce the calculation error of the overall flow rate at the measurement section has become a challenge for the industry. Summary of the Invention

[0004] This application provides an intelligent monitoring system and method for open channel flow, which can accurately identify asymmetric obstruction characteristics in the direction of water flow, thereby reducing the calculation error of the overall flow at the measurement section.

[0005] In a first aspect, this application provides a method for intelligent monitoring of open channel flow, comprising the following steps:

[0006] The flow velocity distribution data of the target open channel is obtained by using intelligent monitoring sensors to conduct acoustic detection on the measurement section.

[0007] The velocity distribution data is interpolated and reconstructed to obtain the continuous velocity field of the measurement section. Then, the measurement section is partitioned according to the velocity gradient characteristics of each velocity distribution point in the continuous velocity field to obtain the core hydraulic zone and transition zone hydraulic zone corresponding to the measurement section.

[0008] Determine the vertical projection line of the main velocity direction in the continuous velocity field, extract the maximum possible flow rate of the water flow to the left and the maximum possible flow rate of the water flow to the right of the vertical projection line from the continuous velocity field according to the preset hydraulic stagnation conditions, and then determine the stagnation influence coefficient of the measurement section through the maximum possible flow rate of the water flow to the right and the maximum possible flow rate of the water flow to the left.

[0009] Based on the lagging influence coefficient, the dominant flow velocity of the inertial force of the water flow in the core hydraulic zone and the dominant flow velocity of the resistance of the water flow in the transition zone hydraulic zone are jointly tuned to obtain the flow velocity tuning value of the measurement section.

[0010] The flow monitoring data of the target open channel is obtained by measuring the cross-sectional area of ​​the current measurement section using the intelligent monitoring sensor and then calculating the cross-sectional area of ​​the water passage and the flow velocity setting value.

[0011] In some embodiments, interpolating and reconstructing the velocity distribution data to obtain the continuous velocity field of the measurement section specifically includes:

[0012] Kriging interpolation is used to perform preliminary interpolation on the velocity distribution data to obtain preliminary interpolated velocity distribution data;

[0013] The initial interpolated velocity distribution data is then gridded to construct a regular velocity grid.

[0014] The grid nodes in the velocity grid are interpolated twice to obtain the continuous velocity field of the measurement section.

[0015] In some embodiments, the measurement section is characterized by feature partitioning based on the velocity gradient characteristics of each velocity distribution point in the continuous velocity field, resulting in a core hydraulic partition and a transition zone hydraulic partition corresponding to the measurement section. Specifically, this includes:

[0016] Determine the velocity gradient components in the horizontal and vertical directions for each velocity distribution point within the continuous velocity field;

[0017] The velocity gradient characteristics of each velocity distribution point are calculated based on the velocity gradient components in the horizontal and vertical directions.

[0018] Velocity distribution points with velocity gradient characteristics greater than the velocity gradient characteristic threshold are classified as core hydraulic zones, and velocity distribution points with combined velocity gradient less than or equal to the velocity gradient characteristic threshold are classified as transition zone hydraulic zones, thus obtaining the core hydraulic zones and transition zone hydraulic zones corresponding to the measurement section.

[0019] In some embodiments, determining the vertical projection line of the mainstream velocity direction in the continuous flow velocity field specifically includes:

[0020] Calculate the average direction of the velocity vector at each velocity distribution point in the continuous velocity field, and take this average direction as the main velocity direction;

[0021] Within the measurement cross-section, select the straight line whose angle with the main velocity direction is closest to 90 degrees as the vertical projection line of the main velocity direction.

[0022] In some embodiments, extracting the maximum possible flow rate of the water flow to the left and the maximum possible flow rate of the water flow to the right of the vertical projection line from the continuous velocity field according to preset hydraulic flow retention conditions specifically includes:

[0023] Using the vertical projection line as a reference, the continuous velocity field is divided into a left-side flow region and a right-side flow region;

[0024] Based on the preset hydraulic stagnation conditions, regions that meet the hydraulic stagnation conditions are determined in the left and right water flow regions as hydraulic stagnation zones, thereby obtaining the left and right hydraulic stagnation zones.

[0025] The maximum possible flow rate of the left-side flow is determined based on the distribution of all velocity points in the left-side hydraulic stagnation zone and the distribution of all velocity points in the left-side flow region.

[0026] The maximum possible flow rate of the right-side flow is determined based on the distribution of all velocity points in the right-side hydraulic stagnation zone and the distribution of all velocity points in the right-side flow region.

[0027] In some embodiments, the combined tuning of the dominant flow velocity of the inertial force in the core hydraulic zone and the dominant flow velocity of the flow resistance in the transition zone hydraulic zone, based on the laminar flow influence coefficient, to obtain the velocity tuning value of the measurement section specifically includes:

[0028] Extract the dominant flow velocity of inertial force in the core hydraulic zone and the dominant flow velocity of resistance in the transition zone hydraulic zone;

[0029] A flow velocity tuning model for the measurement section is constructed based on the hysteresis influence coefficient.

[0030] The dominant flow velocity of the inertial force in the core hydraulic zone and the dominant flow velocity of the resistance in the transition zone hydraulic zone are input into the velocity tuning model to obtain the velocity tuning value of the measurement section.

[0031] In some embodiments, the smart monitoring sensor includes a Doppler flow profiler and a pressure sensor.

[0032] Secondly, this application provides an intelligent monitoring system for open channel flow, comprising:

[0033] The detection module is used to perform acoustic wave detection on the measurement section of the target open channel through intelligent monitoring sensors to obtain the flow velocity distribution data of the measurement section;

[0034] The processing module is used to interpolate and reconstruct the velocity distribution data to obtain the continuous velocity field of the measurement section, and then to perform feature partitioning on the measurement section according to the velocity gradient characteristics of each velocity distribution point in the continuous velocity field to obtain the core hydraulic partition and transition zone hydraulic partition corresponding to the measurement section.

[0035] The processing module is also used to determine the vertical projection line of the main velocity direction in the continuous velocity field, extract the maximum possible flow rate of the water flow to the left and the maximum possible flow rate of the water flow to the right of the vertical projection line from the continuous velocity field according to the preset hydraulic stagnation conditions, and then determine the stagnation influence coefficient of the measurement section through the maximum possible flow rate of the water flow to the right and the maximum possible flow rate of the water flow to the left.

[0036] The processing module is also used to jointly tune the dominant flow velocity of the inertial force of the water flow in the core hydraulic zone and the dominant flow velocity of the resistance of the water flow in the transition zone hydraulic zone based on the lag influence coefficient, so as to obtain the flow velocity tuning value of the measurement section.

[0037] The execution module is used to measure the cross-sectional area of ​​the current measurement section based on the intelligent monitoring sensor, and then calculate the flow monitoring data of the target open channel through the cross-sectional area of ​​the water passage and the flow velocity setting value.

[0038] Thirdly, this application provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described intelligent monitoring method for open channel flow.

[0039] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described intelligent monitoring method for open channel flow.

[0040] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0041] The intelligent open channel flow monitoring system and method provided in this application firstly uses an intelligent monitoring sensor to perform acoustic wave detection on the measurement section of the target open channel to obtain the velocity distribution data of the measurement section; then, the velocity distribution data is interpolated and reconstructed to obtain the continuous velocity field of the measurement section; subsequently, the measurement section is characterized by partitioning based on the velocity gradient characteristics of each velocity distribution point in the continuous velocity field to obtain the core hydraulic partition and transition zone hydraulic partition corresponding to the measurement section; finally, the vertical projection line of the mainstream velocity direction in the continuous velocity field is determined, and the vertical projection line is extracted from the continuous velocity field according to preset hydraulic stagnation conditions. The maximum possible stagnant flow rate on the left and right sides of the shadow line are used to determine the stagnant flow influence coefficient of the measurement section. Based on the stagnant flow influence coefficient, the dominant flow velocity of the inertial force in the core hydraulic zone and the dominant flow velocity of the flow resistance in the transition zone hydraulic zone are jointly tuned to obtain the flow velocity tuning value of the measurement section. The cross-sectional area of ​​the current measurement section is measured by the intelligent monitoring sensor, and the flow monitoring data of the target open channel is calculated by the cross-sectional area and the flow velocity tuning value.

[0042] Therefore, this application can accurately identify asymmetric stagnation characteristics in the direction of water flow, thereby reducing the calculation error of the overall flow rate at the measurement section. First, by monitoring the velocity distribution data of the measurement section, the continuous velocity field of the measurement section is reconstructed from the velocity distribution data. Based on the velocity gradient characteristics of each velocity distribution point in the continuous velocity field, the measurement section is divided into characteristic partitions, resulting in the core hydraulic partition and transition zone hydraulic partition corresponding to the measurement section. This effectively identifies boundary effects and energy dissipation areas, provides constraint compensation for the tuning vertical velocity, and improves the accuracy and boundary consistency of the overall flow rate calculation. Second, the vertical projection line of the mainstream velocity direction in the continuous velocity field is determined. Based on the preset hydraulic stagnation conditions, the maximum possible stagnation flow rate to the left and right of the vertical projection line is extracted from the continuous velocity field to accurately identify asymmetric stagnation characteristics in the direction of water flow, and then quantitatively assess the degree of influence of this asymmetric stagnation effect on the overall water flow. Furthermore, the maximum possible stagnation flow rate of the right and left flows is used to determine... The stagnation influence coefficient of the measurement section can effectively reflect the impact of open channel boundary conditions and water flow state on flow transmission, providing an important basis for open channel design optimization, water conveyance efficiency assessment, and hydraulic model calibration, thereby effectively correcting the deviation between theoretical and actual flow rates. Then, based on the stagnation influence coefficient, the dominant flow velocity of the inertial force in the core hydraulic zone and the dominant flow velocity of the flow resistance in the transition zone hydraulic zone are jointly tuned to obtain the velocity tuning value of the measurement section. This effectively eliminates the interference of sidewall obstruction and water surface fluctuations on the velocity distribution, making the tuned velocity more consistent with the motion law of viscous fluids, resulting in a more representative flow rate at the measurement section, thus avoiding distortion of the velocity representation in the transition zone of the measurement section. Finally, the cross-sectional area of ​​the current measurement section is measured by intelligent monitoring sensors, and the flow monitoring data of the target open channel is calculated using the cross-sectional area and the velocity tuning value. In summary, the technical solution provided in this application can accurately identify asymmetric obstruction characteristics in the flow direction, thereby reducing the calculation error of the overall flow rate at the measurement section. Attached Figure Description

[0043] Figure 1 This is a schematic diagram of an application scenario architecture for an intelligent open channel flow monitoring method according to some embodiments of this application;

[0044] Figure 2 This is an exemplary flowchart of an intelligent open channel flow monitoring method according to some embodiments of this application;

[0045] Figure 3 This is an exemplary flowchart illustrating the determination of a continuous velocity field according to some embodiments of this application;

[0046] Figure 4 This is a schematic diagram of the structure of an intelligent open channel flow monitoring system according to some embodiments of this application;

[0047] Figure 5 This is a schematic diagram of the structure of a computer device for implementing an intelligent monitoring method for open channel flow, according to some embodiments of this application. Detailed Implementation

[0048] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0049] refer to Figure 1 This figure is a schematic diagram of an application scenario architecture for an intelligent open channel flow monitoring method according to some embodiments of this application. The application scenario architecture includes a data acquisition terminal, a communication network, and a server. The data acquisition terminal and the server are directly or indirectly connected through the communication network. The data acquisition terminal uses an intelligent monitoring sensor to perform acoustic wave detection on the measurement cross-section of the target open channel, obtains the flow velocity distribution data of the measurement cross-section, and uploads it to the server terminal. The server terminal interpolates and reconstructs the flow velocity distribution data to obtain the continuous flow velocity field of the measurement cross-section. Then, based on the flow velocity gradient characteristics of each flow velocity distribution point in the continuous flow velocity field, the measurement cross-section is partitioned into feature zones to obtain the corresponding core hydraulic zone and transition zone hydraulic zone; the continuous flow... The vertical projection line of the mainstream velocity direction in the velocity field is used to extract the maximum possible stagnant flow rate to the left and right of the vertical projection line from the continuous velocity field according to preset hydraulic stagnant flow conditions. Then, the stagnant flow influence coefficient of the measurement section is determined by the maximum possible stagnant flow rate to the right and left of the right. Based on the stagnant flow influence coefficient, the dominant flow velocity of the inertial force in the core hydraulic zone and the dominant flow velocity of the flow resistance in the transition zone hydraulic zone are jointly tuned to obtain the flow velocity tuning value of the measurement section. The cross-sectional area of ​​the current measurement section is measured by the intelligent monitoring sensor, and the flow monitoring data of the target open channel is calculated by the cross-sectional area and the flow velocity tuning value.

[0050] refer to Figure 2 The figure is an exemplary flowchart of an intelligent open channel flow monitoring method according to some embodiments of this application. The intelligent open channel flow monitoring method mainly includes the following steps:

[0051] In step 101, the flow velocity distribution data of the target open channel is obtained by using an intelligent monitoring sensor to conduct acoustic wave detection on the measurement section.

[0052] In practice, an acoustic pulse is emitted to the measurement section of the target open channel by a Doppler velocity profiler in the intelligent sensor, and the flow velocity value at the measurement section is calculated based on the Doppler frequency shift of the pulse echo to obtain the flow velocity values ​​at different locations of the measurement section. Then, the flow velocity distribution data of the measurement section is obtained by combining all the flow velocity values. The intelligent monitoring sensor includes a Doppler velocity profiler and a pressure sensor.

[0053] It should be noted that the measurement section in this application refers to a specific cross-section selected in the target open channel for flow monitoring. Specifically, the measurement section is a section perpendicular to the direction of water flow in the open channel, serving as the physical location and data acquisition area for flow monitoring. This provides a clear and quantifiable physical measurement unit for open channel flow monitoring, enabling scientific analysis and calculation based on specific cross-sectional data. The velocity distribution data in this application refers to data obtained by combining velocity values ​​at different locations of the measurement section.

[0054] In step 102, the velocity distribution data is interpolated and reconstructed to obtain the continuous velocity field of the measurement section. Then, the measurement section is partitioned according to the velocity gradient characteristics of each velocity distribution point in the continuous velocity field to obtain the core hydraulic partition and transition zone hydraulic partition corresponding to the measurement section.

[0055] In some embodiments, reference Figure 3 As shown in the figure, this is an exemplary flowchart of determining a continuous velocity field according to some embodiments of this application. In this embodiment, the continuous velocity field of the measurement section can be obtained by interpolating and reconstructing the velocity distribution data using the following steps:

[0056] First, in step 1021, Kriging interpolation is used to perform preliminary interpolation on the velocity distribution data to obtain the velocity distribution data after preliminary interpolation.

[0057] Then, in step 1022, the initially interpolated velocity distribution data is gridded to construct a regular velocity grid.

[0058] Finally, in step 1023, the grid nodes in the velocity grid are interpolated twice to obtain the continuous velocity field of the measurement section.

[0059] In specific implementation, firstly, Kriging interpolation is used to perform preliminary interpolation on the velocity distribution data to obtain the preliminary interpolated velocity distribution data, which will not be elaborated here. In addition, other interpolation methods can also be used to perform preliminary interpolation on the velocity distribution data, such as inverse distance weighted interpolation and bilinear interpolation, which are not limited here. Then, a two-dimensional grid structure (i.e., an equally spaced XY coordinate grid) is constructed based on the physical dimensions of the measurement section, and the preliminary interpolated velocity distribution data is mapped to the corresponding grid nodes to obtain a regular velocity grid. Finally, a second interpolation is performed on the grid nodes in the velocity grid to obtain the continuous velocity field of the measurement section. That is, cubic spline interpolation is used to perform cubic spline interpolation in the X and Y axes of the velocity grid, and the interpolation function is constructed from the velocity values ​​and partial derivatives of the 16 neighboring grid nodes around each grid node to achieve a high-order smooth estimation of the velocity values, thereby generating the continuous velocity field of the measurement section.

[0060] It should be noted that, in this embodiment, the velocity grid represents a regularized spatial data structure constructed on the open channel measurement cross section. The velocity grid divides the velocity data in a two-dimensional coordinate system according to a fixed spatial resolution, so that each grid node corresponds to a specific velocity value. In this embodiment, the continuous velocity field represents a two-dimensional vector field with definite velocity values ​​within the open channel measurement cross section. This continuous velocity field can reflect the local variation trend and overall distribution state of the water flow within the entire cross section, providing continuous, smooth, and physically meaningful basic data support for calculating the velocity gradient, identifying hydrodynamic characteristic areas, and performing hydraulic analyses such as head loss.

[0061] In some embodiments, the measurement section is characterized by feature partitioning based on the velocity gradient characteristics of each velocity distribution point in the continuous velocity field to obtain the core hydraulic partition and transition zone hydraulic partition corresponding to the measurement section. This can be achieved by the following steps:

[0062] Determine the velocity gradient components in the horizontal and vertical directions for each velocity distribution point within the continuous velocity field;

[0063] The velocity gradient characteristics of each velocity distribution point are calculated based on the velocity gradient components in the horizontal and vertical directions.

[0064] Velocity distribution points with velocity gradient characteristics greater than the velocity gradient characteristic threshold are classified as core hydraulic zones, and velocity distribution points with combined velocity gradient less than or equal to the velocity gradient characteristic threshold are classified as transition zone hydraulic zones, thus obtaining the core hydraulic zones and transition zone hydraulic zones corresponding to the measurement section.

[0065] In specific implementation, firstly, the partial derivatives of each horizontal distribution point in the main velocity direction and vertical direction are calculated using numerical differentiation methods (such as the central difference method) as the corresponding velocity gradient components. Then, the velocity gradient characteristics of each velocity distribution point are calculated based on the velocity gradient components in the horizontal and vertical directions. That is, for each velocity distribution point, the velocity gradient components in the horizontal and vertical directions are calculated using a modulo operation to obtain the velocity gradient characteristics of the velocity distribution point. Finally, the velocity distribution points with velocity gradient characteristics greater than the velocity gradient characteristic threshold are divided into core hydraulic zones, and the velocity distribution points with combined velocity gradients less than or equal to the velocity gradient characteristic threshold are divided into transition zone hydraulic zones. Thus, the core hydraulic zones and transition zone hydraulic zones corresponding to the measurement section are obtained. The velocity gradient characteristic threshold can be set based on the boundary layer theory and engineering experience of open channel fluid mechanics, and is not limited here.

[0066] It should be noted that, in this embodiment, the velocity gradient component represents the rate of change of the velocity vector in different spatial directions at the velocity distribution point in the continuous velocity field; the core hydraulic zoning table in this application refers to the mainstream region where the kinetic energy of the water flow velocity is concentrated in the measurement section of the open channel. The core hydraulic zoning is usually located at the central axis of the section or the mainstream channel. The water flow in the core hydraulic zoning has strong inertia and small disturbance, and has good representativeness and flow stability. Therefore, by determining the core hydraulic zoning, the accuracy and reliability of velocity estimation can be effectively improved; the transition zone hydraulic zoning in this application represents In the open channel measurement section, the region located at the edge of the core hydraulic zone with relatively low flow velocity is the transition zone hydraulic zone. This transition zone hydraulic zone is usually significantly affected by the boundary layer, backflow disturbance, or lateral flow, exhibiting unstable flow direction and complex momentum transfer. The transition zone hydraulic zone plays an important auxiliary correction role in open channel flow monitoring, effectively identifying boundary effects and energy dissipation areas, providing constraint compensation for the set vertical velocity, and improving the accuracy and boundary consistency of the overall flow calculation. In this embodiment, the velocity gradient feature represents the characteristic that measures the velocity change at the velocity distribution point of the measurement section.

[0067] In step 103, the vertical projection line of the main velocity direction in the continuous velocity field is determined. According to the preset hydraulic stagnation conditions, the maximum possible stagnation flow rate to the left and the maximum possible stagnation flow rate to the right of the vertical projection line are extracted from the continuous velocity field. Then, the stagnation influence coefficient of the measurement section is determined by the maximum possible stagnation flow rate to the right and the maximum possible stagnation flow rate to the left.

[0068] In some embodiments, determining the vertical projection line of the mainstream velocity direction in the continuous flow velocity field can be achieved by the following steps:

[0069] Calculate the average direction of the velocity vector at each velocity distribution point in the continuous velocity field, and take this average direction as the main velocity direction;

[0070] Within the measurement cross-section, select the straight line whose angle with the main velocity direction is closest to 90 degrees as the vertical projection line of the main velocity direction.

[0071] In specific implementation, firstly, the average direction of the velocity vector at each velocity distribution point in the continuous velocity field is calculated using the data processing tool Python, and this average direction is taken as the mainstream velocity direction; then, the straight line within the measurement section that has the angle closest to 90 degrees with the mainstream velocity direction is selected as the vertical projection line of the mainstream velocity direction. That is, in the two-dimensional plane where the measurement section is located, a series of candidate straight lines (such as a family of equally spaced parallel straight lines) are preset, and the cosine value of the angle between the direction vector of each candidate straight line and the mainstream velocity direction is calculated using the vector dot product formula. The straight line whose cosine value is closest to 0 (i.e., the angle is closest to 90 degrees) is selected as the vertical projection line of the mainstream velocity direction.

[0072] It should be noted that in this embodiment, the mainstream velocity direction is the dominant direction of fluid motion in a continuous velocity field, used to reflect the main motion trend of the fluid on the measurement section, and is the dominant direction of water flow energy transmission and momentum distribution; in this application, the vertical projection line represents a characteristic straight line orthogonal to the mainstream velocity direction within the measurement section. The determination of the vertical projection line is to construct a characteristic profile perpendicular to the mainstream fluid motion direction, used to analyze the distribution law of flow velocity in the lateral direction, and is an important geometric reference line connecting the velocity field vector analysis and the cross-sectional flow calculation. In the open channel flow monitoring system, it serves as a reference axis for dividing measurement zones and deploying sensor arrays.

[0073] In some embodiments, extracting the maximum possible flow rate of the water flow to the left and the maximum possible flow rate of the water flow to the right of the vertical projection line from the continuous velocity field according to preset hydraulic flow conditions can be achieved by the following steps:

[0074] Using the vertical projection line as a reference, the continuous velocity field is divided into a left-side flow region and a right-side flow region;

[0075] Based on the preset hydraulic stagnation conditions, regions that meet the hydraulic stagnation conditions are determined in the left and right water flow regions as hydraulic stagnation zones, thereby obtaining the left and right hydraulic stagnation zones.

[0076] The maximum possible flow rate of the left-side flow is determined based on the distribution of all velocity points in the left-side hydraulic stagnation zone and the distribution of all velocity points in the left-side flow region.

[0077] The maximum possible flow rate of the right-side flow is determined based on the distribution of all velocity points in the right-side hydraulic stagnation zone and the distribution of all velocity points in the right-side flow region.

[0078] In specific implementation, firstly, the continuous velocity field is divided into two sub-regions, left and right, using the vertical projection line as the geometric boundary, resulting in a left flow region and a right flow region. Secondly, based on preset hydraulic stagnation conditions (which can be preset to define stagnation as the velocity at a velocity distribution point being less than 30% of the mainstream velocity), a point-by-point traversal algorithm is used to determine the velocity at each velocity distribution point in the left and right flow regions, filtering out the velocity distribution point set that meets the hydraulic stagnation conditions. Then, based on the velocity distribution point sets corresponding to the left and right flow regions respectively, a left hydraulic stagnation zone and a right hydraulic stagnation zone are constructed. Next, the quotient of the distribution values ​​of all velocity distribution points in the left hydraulic stagnation zone and the distribution values ​​of all velocity distribution points in the left flow region can be used as the maximum possible stagnation volume of the left flow. Finally, the quotient of the distribution values ​​of all velocity distribution points in the right hydraulic stagnation zone and the distribution values ​​of all velocity distribution points in the right flow region can be used as the maximum possible stagnation volume of the right flow.

[0079] It should be noted that, in this application, the hydraulic stagnation condition refers to the criterion used to define the transition of fluid motion from effective transport to stagnation. In this embodiment, the left hydraulic stagnation zone refers to the fluid region located to the left of the vertical projection line and satisfying the preset hydraulic stagnation condition, used to characterize the local stagnation region caused by boundary conditions (such as bank slope morphology, obstacles) or flow field structure (such as eddies, shear layers) on the left side of the vertical projection line. In this embodiment, the right hydraulic stagnation zone refers to the fluid region located to the right of the vertical projection line and satisfying the preset hydraulic stagnation condition, used to characterize the local stagnation region caused by boundary conditions (such as bank slope morphology, obstacles) or flow field structure (such as eddies, shear layers) on the right side of the vertical projection line. Slow-flowing regions; In this application, the maximum possible sluggish flow volume on the left side refers to the proportion of water body with a significantly reduced velocity on the left side of the vertical projection line. The maximum possible sluggish flow volume on the left side characterizes the degree of velocity reduction caused by factors such as boundary constraints and changes in flow regime on the left side, and can be used to quantify the flow sluggishness effect in the transverse direction of the cross section, reflecting the degree of influence of local resistance on the overall flow. In this application, the maximum possible sluggish flow volume on the right side refers to the proportion of water body with a significantly reduced velocity on the right side of the vertical projection line. The maximum possible sluggish flow volume on the right side characterizes the degree of velocity reduction caused by factors such as boundary constraints and changes in flow regime on the right side, and can be used to quantify the flow sluggishness effect in the transverse direction of the cross section, reflecting the degree of influence of local resistance on the overall flow.

[0080] In practice, the stagnation influence coefficient of the measurement section is determined by the maximum possible stagnation flow on the right side and the maximum possible stagnation flow on the left side. That is, the quotient of the maximum possible stagnation flow on the left side and the maximum possible stagnation flow on the right side can be used as the stagnation influence coefficient of the measurement section. The ratio of the maximum possible stagnation flow on the left and right sides is used as the stagnation influence coefficient because this ratio can intuitively reflect the distribution characteristics of the water flow stagnation effect on the cross section of the open channel. In natural water flow, due to the influence of factors such as sidewall conditions, river bends or local topography, different degrees of stagnation often occur on both sides of the channel. By comparing the relative magnitudes of the stagnation flow on both sides, it can be determined which side of the water flow is more severely obstructed, thereby quantitatively assessing the degree of influence of this asymmetric stagnation effect on the overall water flow.

[0081] It should be noted that the stagnation influence coefficient in this application represents a dimensionless parameter that measures the degree of asymmetry in the flow stagnation effect on the cross section of an open channel. Its core is to reflect the distribution characteristics of lateral momentum loss by comparing the relative differences in stagnation intensity on the left and right sides of the channel. This coefficient is based on the fundamental law in open channel fluid mechanics that "differences in sidewall resistance inevitably lead to asymmetric velocity distribution." When there are bends, uneven sidewall roughness, or local topographic obstacles in the channel, the scale of the stagnation zone formed on the left and right sides will show significant differences. By taking the ratio of the stagnation flow on both sides, the complexity of absolute flow rate calculation can be avoided, and the spatial bias of the stagnation effect can be intuitively characterized, providing a directional basis for subsequent velocity field correction and ensuring that the flow monitoring results accurately reflect the asymmetric motion characteristics of the actual water flow.

[0082] In step 104, the dominant flow velocity of the inertial force of the water flow in the core hydraulic zone and the dominant flow velocity of the resistance of the water flow in the transition zone hydraulic zone are jointly tuned based on the lag influence coefficient to obtain the flow velocity tuning value of the measurement section.

[0083] In some embodiments, the velocity tuning of the measurement section can be achieved by jointly tuning the dominant flow velocity of the inertial force in the core hydraulic zone and the dominant flow velocity of the flow resistance in the transition zone hydraulic zone based on the laminar flow influence coefficient, using the following steps:

[0084] Extract the dominant flow velocity of inertial force in the core hydraulic zone and the dominant flow velocity of resistance in the transition zone hydraulic zone;

[0085] A flow velocity tuning model for the measurement section is constructed based on the hysteresis influence coefficient.

[0086] The dominant flow velocity of the inertial force in the core hydraulic zone and the dominant flow velocity of the resistance in the transition zone hydraulic zone are input into the velocity tuning model to obtain the velocity tuning value of the measurement section.

[0087] In specific implementation, firstly, the dominant flow velocity of inertial force in the core hydraulic zone and the dominant flow velocity of resistance in the transition zone hydraulic zone are extracted. Specifically, the maximum flow velocity in the core hydraulic zone can be extracted as the dominant flow velocity of inertial force, and the minimum flow velocity in the transition zone hydraulic zone can be extracted as the dominant flow velocity of resistance. In open channels, the flow characteristics of the core hydraulic zone are dominated by inertial force, and the viscous effect is negligible. According to boundary layer theory, the velocity distribution in this core hydraulic zone conforms to potential flow characteristics. The velocity value at the maximum velocity point best reflects the dynamic equilibrium state of inertial force. The velocity at this point is not affected by the wall resistance effect and can directly characterize the limiting capacity of inertial motion. Therefore, the maximum flow velocity in the core hydraulic zone can be extracted as the dominant flow velocity of inertial force. In the transition zone hydraulic zone, the minimum velocity point usually appears in the viscous sublayer or in areas with significant surface wave resistance. According to Prandtl boundary layer theory, the velocity at this point directly reflects the cumulative effect of wall shear stress, and its magnitude is related to local resistance loss. Power exhibits a linear correlation and is a direct measure of resistance. Therefore, the minimum flow velocity in the transition zone hydraulic section can be extracted as the dominant flow velocity for flow resistance. Then, based on the stagnation influence coefficient, a velocity tuning model for the measurement section is constructed. The velocity tuning model is: Velocity tuning model = Dominant flow velocity of inertial force in the core hydraulic section - (Dominant flow velocity of inertial force in the core hydraulic section - Dominant flow velocity of flow resistance in the transition zone hydraulic section) × Stagnation influence coefficient. This velocity tuning model... The quality is achieved by converting energy loss into velocity correction through the stagnation influence coefficient, and coupling the competitive relationship between inertial force and resistance in a linear weighted manner to realize the mapping from theoretical velocity (inertia-dominated) to actual velocity (considering resistance loss), which will not be elaborated here; finally, the dominant velocity of inertial force in the core hydraulic zone and the dominant velocity of resistance in the transition zone hydraulic zone are input into the velocity tuning model, and the output of the velocity tuning model is used as the velocity tuning value of the measurement section.

[0088] It should be noted that, in this application, the dominant flow velocity of inertial force represents the characteristic flow velocity in the core hydraulic zone of the measurement section, which characterizes the intensity of inertial force; its essence is to reflect the fluid's ability to move under the control of inertial force. In this application, the dominant flow velocity of flow resistance represents the characteristic flow velocity in the transition zone hydraulic zone of the measurement section, which characterizes the intensity of viscous resistance; its essence is to reflect the degree of momentum dissipation caused by viscous effects and boundary friction. In this embodiment, the velocity tuning model refers to a mathematical model that couples the hysteresis influence coefficient with the velocity distribution characteristics, used for... The flow velocity in the core area and the transition zone is adjusted in a coordinated manner. In this application, the flow velocity set value represents the equivalent flow velocity that reflects the dynamic balance between inertial force and resistance. Specifically, it is the characteristic flow velocity value after joint tuning of the dominant flow velocity of inertial force in the core hydraulic zone of the open channel section and the dominant flow velocity of resistance in the transition zone hydraulic zone through the flow velocity tuning model. By determining the flow velocity set value, the interference of sidewall obstruction and water surface fluctuation on the flow velocity distribution can be effectively eliminated, making the tuned flow velocity more consistent with the motion law of viscous fluid and obtaining a more representative flow rate at the measurement section.

[0089] In step 105, the cross-sectional area of ​​the water passage at the current measurement section is measured by the intelligent monitoring sensor, and then the flow monitoring data of the target open channel is calculated by the cross-sectional area of ​​the water passage and the flow velocity setting value.

[0090] In some embodiments, measuring the cross-sectional area of ​​the water passage at the current measurement section based on the intelligent monitoring sensor can be achieved by the following steps:

[0091] The intelligent monitoring sensor collects the water level elevation of the measurement section and simultaneously acquires the pre-stored channel geometric parameters.

[0092] Based on the water level elevation data and channel geometric parameters, the cross-sectional area of ​​the current measurement section is calculated using the composite cross-sectional area integration method.

[0093] In practice, firstly, the water level elevation of the measurement section is collected by the pressure sensor in the intelligent monitoring sensor, and the pre-stored channel geometric parameters are retrieved synchronously. The channel geometric parameters are the bottom width of the open channel. Then, based on the water level elevation and the channel geometric parameters, the cross-sectional area of ​​the current measurement section is calculated using the composite cross-sectional area integration method. That is, the measurement section is divided into several vertical strips by the Simpson numerical integration method in the composite cross-sectional area integration method, and the cross-sectional area of ​​the current measurement section is obtained by multiplying and summing the water level elevation and the corresponding bottom width of each vertical strip.

[0094] It should be noted that, in this application, the cross-sectional area of ​​the water passage represents the effective cross-sectional area through which the water actually passes at the measurement section of the open channel.

[0095] In practice, the flow monitoring data of the target open channel is calculated by the cross-sectional area of ​​the water passage and the flow velocity setting value. That is, the flow monitoring data of the target open channel is determined by the product of the cross-sectional area of ​​the water passage and the flow velocity setting value.

[0096] In this application, the flow monitoring data refers to the flow values ​​obtained from the measurement section of the target open channel.

[0097] In another aspect, in some embodiments, this application provides an intelligent monitoring system for open channel flow, with reference to... Figure 4 The figure is a schematic diagram of the structure of an intelligent open channel flow monitoring system according to some embodiments of this application. The intelligent open channel flow monitoring system includes: a detection module 201, a processing module 202, and an execution module 203, which are described below:

[0098] The detection module 201 in this application is mainly used to perform acoustic wave detection on the measurement section of the target open channel through an intelligent monitoring sensor to obtain the flow velocity distribution data of the measurement section.

[0099] Processing module 202, in this application, is mainly used to interpolate and reconstruct the velocity distribution data to obtain the continuous velocity field of the measurement section, and then to perform feature partitioning on the measurement section according to the velocity gradient characteristics of each velocity distribution point in the continuous velocity field to obtain the core hydraulic partition and transition zone hydraulic partition corresponding to the measurement section.

[0100] The processing module 202 is further configured to determine the vertical projection line of the main velocity direction in the continuous velocity field, extract the maximum possible flow rate of the water flow to the left and the maximum possible flow rate of the water flow to the right of the vertical projection line from the continuous velocity field according to the preset hydraulic stagnation conditions, and then determine the stagnation influence coefficient of the measurement section through the maximum possible flow rate of the water flow to the right and the maximum possible flow rate of the water flow to the left.

[0101] In addition, the processing module 202 is also used to jointly tune the dominant flow velocity of the inertial force of the water flow in the core hydraulic zone and the dominant flow velocity of the resistance of the water flow in the transition zone hydraulic zone based on the lag influence coefficient, so as to obtain the flow velocity tuning value of the measurement section.

[0102] The execution module 203 in this application is mainly used to measure the cross-sectional area of ​​the current measurement section according to the intelligent monitoring sensor, and then calculate the flow monitoring data of the target open channel through the cross-sectional area of ​​the water passage and the flow velocity setting value.

[0103] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described intelligent monitoring method for open channel flow.

[0104] In some embodiments, reference Figure 5 The figure is a schematic diagram of the structure of a computer device for implementing an intelligent open channel flow monitoring method according to some embodiments of this application. The intelligent open channel flow monitoring method in the above embodiments can... Figure 5 The computer device shown is used to implement this, and the computer device includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.

[0105] The processor 301 can be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more devices used to control the execution of the open channel flow intelligent monitoring method in this application.

[0106] The communication bus 302 can be used to transmit information between the aforementioned components.

[0107] The memory 303 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CDROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 303 may exist independently and be connected to the processor 301 via the communication bus 302. The memory 303 may also be integrated with the processor 301.

[0108] The memory 303 stores program code for executing the scheme of this application, and its execution is controlled by the processor 301. The processor 301 executes the program code stored in the memory 303. The program code may include one or more software modules. In the above embodiments, the determination of the intelligent monitoring method for open channel flow can be achieved through the processor 301 and one or more software modules in the program code in the memory 303.

[0109] Communication interface 304 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0110] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single CPU) processor or a multi-core (multi CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0111] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0112] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described intelligent monitoring method for open channel flow.

[0113] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0114] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for intelligent monitoring of open channel flow, characterized in that, Includes the following steps: The flow velocity distribution data of the target open channel is obtained by using intelligent monitoring sensors to conduct acoustic detection on the measurement section. The velocity distribution data is interpolated and reconstructed to obtain the continuous velocity field of the measurement section. Then, the measurement section is partitioned according to the velocity gradient characteristics of each velocity distribution point in the continuous velocity field to obtain the core hydraulic zone and transition zone hydraulic zone corresponding to the measurement section. Determine the vertical projection line of the main velocity direction in the continuous velocity field, extract the maximum possible flow rate of the water flow to the left and the maximum possible flow rate of the water flow to the right of the vertical projection line from the continuous velocity field according to the preset hydraulic stagnation conditions, and then determine the stagnation influence coefficient of the water flow at the measurement section through the maximum possible flow rate of the water flow to the right and the maximum possible flow rate of the water flow to the left. Based on the lagging influence coefficient, the dominant flow velocity of the inertial force of the water flow in the core hydraulic zone and the dominant flow velocity of the resistance of the water flow in the transition zone hydraulic zone are jointly tuned to obtain the flow velocity tuning value of the measurement section. The flow monitoring data of the target open channel is obtained by measuring the cross-sectional area of ​​the current measurement section based on the intelligent monitoring sensor and then calculating the cross-sectional area of ​​the water flow and the flow velocity setting value. Specifically, extracting the maximum possible flow rate of the water flow to the left and right of the vertical projection line from the continuous velocity field according to preset hydraulic flow conditions includes: Using the vertical projection line as a reference, the continuous velocity field is divided into a left-side flow region and a right-side flow region; Based on the preset hydraulic stagnation conditions, regions that meet the hydraulic stagnation conditions are determined in the left and right water flow regions as hydraulic stagnation zones, thereby obtaining the left and right hydraulic stagnation zones. The maximum possible flow rate of the left-side flow is determined by the distribution of all velocity distribution points in the left-side hydraulic stagnation zone and the distribution of all velocity distribution points in the left-side flow region. The quotient of the distribution of all velocity distribution points in the left-side hydraulic stagnation zone and the distribution of all velocity distribution points in the left-side flow region is taken as the maximum possible flow rate of the left-side flow. The maximum possible flow rate of the right-side flow is determined by the distribution of all velocity points in the right-side hydraulic stagnation zone and the distribution of all velocity points in the right-side flow region. The quotient of the distribution of all velocity points in the right-side hydraulic stagnation zone and the distribution of all velocity points in the right-side flow region is taken as the maximum possible flow rate of the right-side flow.

2. The method as described in claim 1, characterized in that, The process of interpolating and reconstructing the velocity distribution data to obtain the continuous velocity field of the measurement section specifically includes: Kriging interpolation is used to perform preliminary interpolation on the velocity distribution data to obtain preliminary interpolated velocity distribution data; The initial interpolated velocity distribution data is then gridded to construct a regular velocity grid. The grid nodes in the velocity grid are interpolated twice to obtain the continuous velocity field of the measurement section.

3. The method as described in claim 1, characterized in that, Based on the velocity gradient characteristics of each velocity distribution point in the continuous velocity field, the measurement section is divided into feature partitions to obtain the core hydraulic partition and transition zone hydraulic partition corresponding to the measurement section. Specifically, these include: Determine the velocity gradient components in the horizontal and vertical directions for each velocity distribution point within the continuous velocity field; The velocity gradient characteristics of each velocity distribution point are calculated based on the velocity gradient components in the horizontal and vertical directions. Velocity distribution points with velocity gradient characteristics greater than the velocity gradient characteristic threshold are classified as core hydraulic zones, and velocity distribution points with velocity gradient characteristics less than or equal to the velocity gradient characteristic threshold are classified as transition zone hydraulic zones, thus obtaining the core hydraulic zones and transition zone hydraulic zones corresponding to the measurement section.

4. The method as described in claim 1, characterized in that, Determining the perpendicular projection line of the mainstream velocity direction in the continuous flow velocity field specifically includes: Calculate the average direction of the velocity vector at each velocity distribution point in the continuous velocity field, and take this average direction as the main velocity direction; Within the measurement cross-section, select the straight line whose angle with the main velocity direction is closest to 90 degrees as the vertical projection line of the main velocity direction.

5. The method as described in claim 1, characterized in that, Based on the lagging influence coefficient, the dominant flow velocity of the inertial force in the core hydraulic zone and the dominant flow velocity of the resistance in the transition zone hydraulic zone are jointly tuned to obtain the flow velocity tuning value of the measurement section, specifically including: Extract the dominant flow velocity of inertial force in the core hydraulic zone and the dominant flow velocity of resistance in the transition zone hydraulic zone; A flow velocity tuning model for the measurement section is constructed based on the hysteresis influence coefficient. The dominant flow velocity of the inertial force in the core hydraulic zone and the dominant flow velocity of the resistance in the transition zone hydraulic zone are input into the velocity tuning model to obtain the velocity tuning value of the measurement section.

6. The method as described in claim 1, characterized in that, The intelligent monitoring sensor includes a Doppler flow profiler and a pressure sensor.

7. An intelligent open channel flow monitoring system, which uses the method described in any one of claims 1 to 6 to monitor open channel flow, characterized in that, The system includes: The detection module is used to perform acoustic wave detection on the measurement section of the target open channel through intelligent monitoring sensors to obtain the flow velocity distribution data of the measurement section; The processing module is used to interpolate and reconstruct the velocity distribution data to obtain the continuous velocity field of the measurement section, and then to perform feature partitioning on the measurement section according to the velocity gradient characteristics of each velocity distribution point in the continuous velocity field to obtain the core hydraulic partition and transition zone hydraulic partition corresponding to the measurement section. The processing module is also used to determine the vertical projection line of the main velocity direction in the continuous velocity field, extract the maximum possible flow rate of the water flow to the left and the maximum possible flow rate of the water flow to the right of the vertical projection line from the continuous velocity field according to the preset hydraulic stagnation conditions, and then determine the stagnation influence coefficient of the measurement section through the maximum possible flow rate of the water flow to the right and the maximum possible flow rate of the water flow to the left. The processing module is also used to jointly tune the dominant flow velocity of the inertial force of the water flow in the core hydraulic zone and the dominant flow velocity of the resistance of the water flow in the transition zone hydraulic zone based on the lag influence coefficient, so as to obtain the flow velocity tuning value of the measurement section. The execution module is used to measure the cross-sectional area of ​​the current measurement section based on the intelligent monitoring sensor, and then calculate the flow monitoring data of the target open channel through the cross-sectional area of ​​the water passage and the flow velocity setting value.

8. A computer device, characterized in that, The computer device includes a memory and a processor, the memory storing code, and the processor being configured to retrieve the code and execute the open channel flow intelligent monitoring method as described in any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the intelligent monitoring method for open channel flow as described in any one of claims 1 to 6.

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