Speed measurement method based on intelligent flow measurement robot

Abstract

The invention relates to a speed measurement method based on an intelligent flow measurement robot, and belongs to the technical field of flow measurement. The method comprises the following steps: (1) an intelligent flow measurement robot advances along a flow channel and collects data; (2) when running to the end point of the flow channel, simulating the acquired image data, and performing equal-proportion optimal operation with the overall running distance to obtain three optimal flow measurement points; and (3) when the intelligent flow measurement robot returns from the flowing end point and runs to the three optimal flow measurement points, respectively measuring the water level depths of the corresponding flow measurement points, and calculating the regional average flow velocity and the section flow. The flow velocity is calculated based on the collected data of the existing intelligent flow measurement robot, the flow velocity calculation process is greatly shortened, the calculation amount is reduced, and the accuracy of the flow measurement result is improved.

Description

Technical Field

[0001] This invention relates to a speed measurement method based on an intelligent flow measurement robot, belonging to the field of flow measurement technology. Background Technology

[0002] Currently, the commonly used flow measurement method is fixed flow measurement. Fixed flow measurement involves installing multiple flow meters on a bridge and comprehensively processing and analyzing the data from these multiple flow meters to obtain the flow measurement result. However, multiple flow meters need to be installed on a single river cross-section, resulting in high measurement and maintenance costs. Furthermore, fixed flow measurement can only measure the surface velocity of the channel, resulting in low measurement accuracy. Moreover, it can only meet the flow measurement requirements of standard channel cross-sections, and its measurement accuracy is low for non-standard cross-sections.

[0003] Chinese patent document CN113280870A discloses a virtual two-line energy slope method for measuring river flow. Under non-uniform flow conditions, it measures two vertical velocities (one on each side of the central channel) in the cross-section of the water flow. Using the Chezy-Manning formula for uniform flow, a vertical velocity model is inversely calculated to obtain two virtual uniform flow energy slopes. These slopes are then substituted into the vertical velocity model to calculate a vertical velocity several times greater than the number of manually measured vertical lines. Finally, the flow rate is calculated using the partial velocity-area method. This method only uses the measured vertical velocities to calculate the flow rate, without considering factors such as channel shape and slope, resulting in certain deviations in the results. Therefore, this invention is proposed. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a velocity measurement method based on an intelligent flow measurement robot. By calculating the flow velocity based on the data collected by the existing intelligent flow measurement robot, the flow velocity calculation process is significantly reduced, the amount of computation is decreased, and the accuracy of the flow measurement results is improved.

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

[0006] A speed measurement method based on an intelligent flow measurement robot, comprising the following steps:

[0007] (1) The intelligent flow measurement robot moves along the flow channel and collects data;

[0008] (2) When the flow reaches the end of the flow channel, the collected image data is simulated and the optimal calculation is performed proportionally with the overall running distance to calculate the 3 optimal flow measurement points;

[0009] (3) When the intelligent flow measurement robot returns from the end of the flow and runs to the three optimal flow measurement points, it measures the water level depth at the corresponding flow measurement points and calculates the regional average flow velocity and cross-sectional flow rate.

[0010] Preferably according to the present invention, the data collected in step (1) includes shore image coordinates (used to compare shore coefficients and slope coefficients), surface velocity of water, height from the measurement point to the water surface, cross-sectional area, canal top width, canal bottom width, etc.

[0011] Preferably according to the present invention, in step (2), the calculation process of the 3 best flow measurement points is as follows:

[0012] According to the shore image coordinates, cross-sectional area, canal top width, and canal bottom width, calculate the areas of 4 regions. The areas of the 4 regions are S1, S2, S3, and S4 respectively, such that S2≈S3≈(S1 + S4), where S1 < S2 and S4 < S2 (S1, S2, S3, S4 are shown in the attached drawing). The points on the dividing line in the middle of the 4 regions are the best flow measurement points.

[0013] Preferably according to the present invention, in step (3), the calculation process of the regional velocity is as follows:

[0014] The velocity values of the 3 best flow measurement points are V1, V2, and V3 respectively. Let the average velocities of the 4 regions be Vs1, Vs2, Vs3, and Vs4. Then the calculation methods of the average velocities of the four regions are as follows:

[0015] Vs1 = V1 * A1;

[0016] Vs2 = (V1 + V2) / 2;

[0017] Vs3 = (V2 + V3) / 2;

[0018] Vs4 = V3 * A2;

[0019] In the formula, A1 is the starting shore coefficient, and A2 is the ending shore coefficient; the shore coefficient is a concept that describes the influence degree of the geographical features on the water boundary of waters such as rivers, lakes, or seas on the hydrological process. It is used to describe the interaction force between the river bank and the water area, helping researchers understand the interaction between the water body and the shore topography, vegetation, soil, etc. The shore coefficient is an important parameter in the river process, used to calculate the river erosion and deposition processes and the hydrodynamic characteristics of the river.

[0020] The cross-sectional flow formula is:

[0021]

[0022] In the formula, Q is the cross-sectional flow, m³ / s; A is the cross-sectional area of the flowing water, m²; R is the hydraulic radius, m; n is the roughness coefficient; I is the water surface slope; K is the correction coefficient.

[0023] Further preferably according to the present invention, in the cross-sectional flow formula, the calculation formula of the cross-sectional area of the flowing water is as follows:

[0024]

[0025] In the formula, B is the width of the channel bottom; m is the slope coefficient; and h is the water depth.

[0026]

[0027] In the formula, b is the width of the channel bottom; H ​​is the height of the channel top.

[0028] According to a preferred embodiment of the present invention, the hydraulic radius calculation formula in the cross-sectional flow calculation formula is as follows:

[0029]

[0030] In the formula, x is the wetted perimeter; B is the width of the channel bottom; h is the water depth; and m is the slope coefficient.

[0031] According to a preferred embodiment of the present invention, based on the above formula, the cross-sectional flow rate is proportional to the water depth. The cross-sectional flow rate can be estimated based on the water depth. Through calculation, the cross-sectional flow rate at different water levels at each measuring point can be further obtained.

[0032] The formula for calculating cross-sectional flow rate is simplified to: Q = k * v * A

[0033] In the formula: v is the flow velocity, which is the average flow velocity value of the corresponding region, Vs1, Vs2, Vs3 or Vs4.

[0034] The beneficial effects of this invention are as follows:

[0035] This invention provides a velocity measurement method based on an intelligent flow measurement robot. The flow velocity is calculated based on the data collected by the existing intelligent flow measurement robot, which greatly reduces the flow velocity calculation process, reduces the amount of calculation, and improves the accuracy of the flow measurement results. Attached Figure Description

[0036] Figure 1 This is a schematic diagram of the process of the present invention;

[0037] Figure 2 This is a schematic diagram of the optimal flow measurement point distribution for this invention;

[0038] Figure 3 This is a schematic diagram illustrating the optimal flow measurement point division for this invention. Detailed Implementation

[0039] The present invention will be further described below with reference to the embodiments and accompanying drawings, but is not limited thereto.

[0040] Example 1:

[0041] like Figure 1 As shown in the figure, this embodiment provides a speed measurement method based on an intelligent flow measurement robot, the steps of which are as follows:

[0042] (1) The intelligent flow measurement robot advances along the flow channel and collects data, including shore image coordinates (used to compare shore coefficients and slope coefficients), surface velocity of water, height from the measurement point to the water surface, cross-sectional area, canal top width, and canal bottom width, etc.;

[0043] (2) When it runs to the end of the flow channel, it simulates the collected image data and performs an equal-proportion optimal operation with the overall running distance to calculate 3 optimal flow measurement points. The calculation process is as follows:

[0044] Based on the shore image coordinates, cross-sectional area, canal top width, and canal bottom width, calculate the areas of 4 regions. The areas of the 4 regions are S1, S2, S3, and S4 respectively, such that S2≈S3≈(S1 + S4), where S1 < S2 and S4 < S2 (S1, S2, S3, S4 are shown in the attached figure). The points on the dividing lines in the middle of the 4 regions are the optimal flow measurement points.

[0045] (3) The intelligent flow measurement robot returns from the flow end. When it runs to the 3 optimal flow measurement points, it measures the water depth at the corresponding flow measurement points respectively and calculates the regional average velocity and cross-sectional flow rate;

[0046] The calculation process of the regional velocity is as follows:

[0047] The velocity values at the 3 optimal flow measurement points are V1, V2, and V3 respectively. Let the average velocities of the 4 regions be Vs1, Vs2, Vs3, and Vs4. Then the calculation methods of the average velocities of the four regions are as follows:

[0048] Vs1 = V1 * A1;

[0049] Vs2 = (V1 + V2) / 2;

[0050] Vs3 = (V2 + V3) / 2;

[0051] Vs4 = V3 * A2;

[0052] In the formula, A1 is the starting shore coefficient and A2 is the ending shore coefficient; the shore coefficient is a concept that describes the influence degree of geographical features on the water boundary of water areas such as rivers, lakes, or seas on the hydrological process. It is used to describe the interaction force between the river bank and the water area, helping researchers understand the interaction between the water body and the river bank topography, vegetation, soil, etc. The shore coefficient is an important parameter in the river process, used to calculate the river erosion and deposition processes and the hydrodynamic characteristics of the river.

[0053] The cross-sectional flow rate calculation formula is:

[0054]

[0055] In the formula, Q is the cross-sectional flow rate, m3 / s; A is the cross-sectional area of ​​the water passage, m2; R is the hydraulic radius, m; n is the roughness coefficient; I is the water surface gradient; and K is the correction coefficient.

[0056] The formula for calculating the cross-sectional area of ​​water flow is as follows:

[0057]

[0058] In the formula, B is the width of the channel bottom; m is the slope coefficient; and h is the water depth.

[0059]

[0060] In the formula, b is the width of the channel bottom; H ​​is the height of the channel top.

[0061] In the formula for calculating cross-sectional flow, the formula for calculating the hydraulic radius is:

[0062]

[0063] In the formula, x is the wetted perimeter; B is the width of the channel bottom; h is the water depth; and m is the slope coefficient.

[0064] Based on the above formula, it can be concluded that the cross-sectional flow rate is proportional to the water depth. The cross-sectional flow rate can be estimated based on the water depth. Through calculation, the cross-sectional flow rate at different water levels at each measuring point can be further obtained.

[0065] The formula for calculating cross-sectional flow rate is simplified to: Q = k * v * A

[0066] In the formula: v is the flow velocity, which is the average flow velocity value of the corresponding region, Vs1, Vs2, Vs3 or Vs4.

[0067] The above description is merely an embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A speed measurement method based on an intelligent flow measurement robot, characterized in that, The steps are as follows: (1) The intelligent flow measurement robot advances along the flow channel to collect data; (2) When it runs to the end of the flow channel, it simulates the collected image data and performs a proportional best operation with the overall running distance to calculate 3 optimal flow measurement points; (3) The intelligent flow measurement robot returns from the flow end point. When it runs to the 3 optimal flow measurement points, it measures the water depth at the corresponding flow measurement points respectively, and calculates the regional average flow velocity and cross-sectional flow rate.

2. The speed measurement method based on an intelligent flow measurement robot as described in claim 1, characterized in that, The data collected in step (1) includes shore image coordinates, surface flow velocity of water, height from the measurement point to the water surface, cross-sectional area, canal top width, and canal bottom width.

3. The speed measurement method based on an intelligent flow measurement robot as described in claim 2, characterized in that, In step (2), the calculation process of the 3 optimal flow measurement points is as follows: According to the shore image coordinates, cross-sectional area, canal top width, and canal bottom width, calculate the areas of 4 regions. The areas of the 4 regions are S1, S2, S3, and S4 respectively, such that S2≈S3≈(S1 + S4), where S1 < S2, S4 < S2, and the points on the dividing lines in the middle of the 4 regions are the optimal flow measurement points.

4. The speed measurement method based on an intelligent flow measurement robot as described in claim 3, characterized in that, In step (3), the calculation process of the regional flow velocity is as follows: The flow velocity values of the 3 optimal flow measurement points are V1, V2, and V3 respectively. Let the average flow velocities of the 4 regions be Vs1, Vs2, Vs3, and Vs4. Then the calculation methods of the average flow velocities of the four regions are as follows: Vs = V1 * A1; Vs2 = (V1 + V2) / 2; Vs3 = (V2 + V3) / 2; Vs4 = V3 * A2; In the formula, A1 is the starting shore coefficient, and A2 is the ending shore coefficient; The cross-sectional flow rate calculation formula is: In the formula, Q is the cross-sectional flow rate, m³ / s; A is the cross-sectional area of the flowing water, m²; R is the hydraulic radius, m; n is the roughness coefficient; I is the water surface slope; K is the correction coefficient.

5. The speed measurement method based on an intelligent flow measurement robot as described in claim 4, characterized in that, In the cross-sectional flow rate calculation formula, the cross-sectional area calculation formula is as follows: In the formula, B is the canal bottom width; m is the side slope coefficient; h is the water depth; In the formula, b is the canal bottom width; H is the canal top height.

6. The speed measurement method based on an intelligent flow measurement robot as described in claim 5, characterized in that, In the cross-sectional flow rate calculation formula, the hydraulic radius calculation formula is: In the formula, x is the wetted perimeter; B is the canal bottom width; h is the water depth; m is the side slope coefficient.

7. The speed measurement method based on an intelligent flow measurement robot as described in claim 6, characterized in that, In step (3), The cross-sectional flow rate calculation formula is simplified to: Q = k * v * A In the formula: v is the flow velocity, taking the average flow velocity values Vs1, Vs2, Vs3, or Vs4 of the corresponding region.

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