A method for continuous monitoring of water level, flow velocity and flow rate

Abstract

The present invention relates to the field of water body video measurement, and is used to solve the problem that, during water area monitoring, multiple water body parameter monitoring systems are independent of each other and lack effective data interaction, thereby increasing measurement costs and reducing measurement accuracy. The present invention is specifically a method for integrated continuous monitoring of water level, flow rate and flow. In the present invention, rough measurement results are obtained through contact measurement to generate preconditions for auxiliary video image analysis, and then a non-contact measurement method of video images is used to further improve the accuracy of video image analysis and measurement, while reducing the difficulty of flow rate analysis of water bodies using video images and reducing monitoring costs. Multi-source synchronous acquisition and processing are performed by image acquisition equipment, thereby improving the accuracy and continuity of water level measurement. The flow rate can also be predicted by rationally utilizing water level and flow rate monitoring data, which can reduce the cost of performing flow rate measurement alone and improve data utilization.

Description

Technical Field

[0001] The present invention relates to the field of water body video measurement, and in particular to a method for continuously monitoring water level, flow velocity and flow integrated with each other. Background Art

[0002] With the rapid development of electronic technology and sensor technology, more and more instruments and equipment are being used to measure water velocity and flow at home and abroad. The most widely used ones are rotor velocimeters, Doppler velocimeters, particle graphic velocimeters, electromagnetic velocimeters, etc. The rotor velocimeter is the earliest river velocimeter used. It is an instrument that obtains flow velocity by rotating the mechanical rotor structure along with the movement of the water flow. From the technical indicators, the rotor velocimeter can adapt to the flow velocity and flow measurement tasks of most rivers. However, since its flow measurement component is a mechanical structure, it is easily affected by floating objects or aquatic plants in actual use, which can cause instrument failure. When facing extremely low flow rates, the impact of the water body is small, and the gap between the rotation of the rotor and the flow rate is large, which can cause large measurement errors.

[0003] Ultrasonic Doppler flowmeters mainly transmit ultrasonic waves through the flowing fluid in a certain way, convert them into electrical signals through the receiver, and calculate the corresponding two-dimensional or three-dimensional flow velocity components based on the Doppler frequency shift principle, thereby obtaining the flow velocity and flow direction. However, in water, the speed of sound is mainly a function of temperature and water salinity. Their changes will cause changes in the speed of sound, which in turn affects the measurement error. On the other hand, when the concentration of sand and gravel in the water flow is high, it will lead to the inability to measure the flow velocity and flow rate.

[0004] Therefore, when using a single flow velocity measurement component to measure flow velocity, there are uncertain measurement errors or conditional limitations, which affect the flow velocity measurement. At the same time, the existing flow velocity measurement component has a single function. When the regulatory conditions of the water area require multiple regulatory parameters, it is necessary to build multiple sets of flow velocity, flow, and water level monitoring systems. Since different systems are independent of each other, there is a lack of a complete interaction system between the multiple systems, which increases the complexity of water area monitoring and cannot use data interaction between multiple systems to reduce monitoring difficulty and monitoring costs.

[0005] In response to the above technical problems, this application proposes a solution. Summary of the Invention

[0006] In the present invention, rough measurement results are obtained through contact measurement, and quantitative analysis is performed based on the rough measurement results to obtain preconditions for auxiliary video image analysis. Then, a contactless measurement method of video images is used to further improve the accuracy of video image analysis and measurement, while reducing the difficulty of flow velocity analysis of water bodies using video images, reducing monitoring costs, performing multi-source synchronous acquisition through image acquisition equipment, and performing data verification and data refinement processing based on the acquired results, thereby improving the accuracy and continuity of water level measurement, and reasonably utilizing water level and flow velocity monitoring data to predict flow, which can reduce the cost of performing flow velocity measurement operations alone, improve data utilization, and solve the problem that multiple water parameter monitoring systems are independent of each other and lack effective data interaction during water area monitoring, thereby increasing measurement costs and reducing measurement accuracy. A method for integrated continuous monitoring of water level, flow velocity and flow is proposed.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A method for continuously monitoring water level, flow rate, and flow rate in an integrated manner includes a terminal acquisition control module connected to a terminal acquisition device and receiving acquisition results fed back by the terminal acquisition device, wherein the terminal acquisition device includes an image acquisition device, a flow rate monitoring device, and a terrain scanning device; the terminal acquisition module distributes the received acquisition results, wherein the flow rate monitoring device includes a conventional monitoring device and a video monitoring device;

[0009] a water level confirmation module, which obtains water surface parameters acquired by an image acquisition device and terrain parameters acquired by a terrain scanning device, analyzes the water surface parameters and terrain parameters, and obtains a water level confirmation result and a terrain impact result based on the analysis results;

[0010] A flow velocity pre-order measurement module, which obtains the collection results of conventional monitoring equipment and analyzes the flow velocity based on the collection results to obtain a flow velocity fuzzy interval;

[0011] A flow rate precision measurement module, which generates an analysis duration based on the collection results of the video device and the flow rate fuzzy interval, and accurately analyzes the results collected by the video device according to the analysis duration to obtain an accurate flow rate result;

[0012] The flow prediction module obtains accurate flow velocity results and terrain impact results, and performs model analysis based on the accurate flow velocity results and terrain impact results to obtain flow prediction results.

[0013] As a preferred embodiment of the present invention, the collection results received by the terminal collection control module include:

[0014] The results collected by the image acquisition device include water surface images and slope images, wherein the water surface image is the area where the height measuring rod is located;

[0015] The results collected by terrain scanning equipment include ground contours and slope contours;

[0016] The results collected by conventional monitoring equipment in flow rate monitoring equipment include direct flow rate data, and the results collected by video monitoring equipment are continuous videos of the water surface.

[0017] As a preferred embodiment of the present invention, after the flow velocity pre-order measurement module obtains direct flow velocity data through conventional monitoring equipment, the direct flow velocity data is recorded and the number of direct flow velocity data is compared with a set sample number k. If the number of direct flow velocity data is greater than or equal to the set sample number k, flow velocity estimation is performed; if the number of direct flow velocity data is less than the set sample number k, statistics are continued;

[0018] When the flow velocity pre-order measurement module performs flow velocity estimation, a scatter plot is created with the flow velocity as the vertical axis, and a dispersion analysis is performed on the created scatter plot to obtain data dispersion. The flow velocity pre-order measurement module performs weight calculation on the data dispersion to obtain the flow velocity range width;

[0019] The flow velocity pre-order measurement module calculates the flow velocity average value in the scatter plot to obtain the flow velocity mean value, and simultaneously expands the flow velocity average value at both ends by the flow velocity range width to obtain the flow velocity fuzzy interval.

[0020] As a preferred embodiment of the present invention, after obtaining the flow velocity fuzzy interval, the flow velocity accurate measurement module performs unit conversion on the flow velocity fuzzy interval, converting the unit of the flow velocity fuzzy interval from m / s to cm / ms. The flow velocity accurate measurement module obtains a preset discrimination distance accuracy in cm, and calculates the ratio of the discrimination distance accuracy to the two end values ​​of the flow velocity fuzzy interval to obtain a time discrimination interval of X1ms to X2ms.

[0021] The flow velocity precise measurement module selects the integer closest to the median in the time discrimination interval X1-X2 and uses it as the analysis duration.

[0022] As a preferred embodiment of the present invention, the flow velocity accurate measurement module selects a frame of image from the video captured by the video device as a starting point, and selects a frame of image every analysis time interval after the starting point, thereby obtaining multiple image samples;

[0023] The flow velocity precision measurement module selects a reference point in the first frame of the image through an algorithm, selects the same reference point in subsequent images, calculates the moving distance of the reference point in two adjacent frames of the image, and calculates the precise flow velocity by the ratio of the moving distance and the analysis time.

[0024] The flow velocity precise measurement module performs arithmetic averaging on the multiple precise flow velocities obtained to obtain a precise flow velocity result, and outputs the precise flow velocity result through a network.

[0025] As a preferred embodiment of the present invention, the flow velocity precision measurement module assists in calculating the moving distance between two reference points by determining the distance accuracy, thereby assisting in the selection of reference points.

[0026] As a preferred embodiment of the present invention, the water level confirmation module performs three-dimensional modeling of the terrain scanned by the terrain scanning device, and obtains the outline of the cross section in the three-dimensional modeling through algorithm software, and records it as the terrain influence result;

[0027] The flow prediction module obtains the water level confirmation result and the precise flow velocity result of the water level confirmation module, imports the precise flow velocity result, the water level confirmation result and the terrain influence result into the model, obtains the water level cross section through the cross-section profile and the water level confirmation result, and obtains the flow prediction result by multiplying the area of ​​the water level cross section and the precise flow velocity result.

[0028] As a preferred embodiment of the present invention, after acquiring the water surface image and the slope image, the water level confirmation module obtains the display scale on the height measuring rod in the water surface image, automatically marks the display scale through the image processing algorithm, records the number of display scales above the water surface, and calculates the scale water surface height through the preset total number of display scales;

[0029] The water level confirmation module processes the acquired slope image through an algorithm to obtain an image of the slope above the water surface, and compares the slope image above the water surface with a preset complete slope image to obtain the missing part in the slope image. The height of the missing part in the slope image is calculated through a three-dimensional model to obtain the water surface height of the slope.

[0030] As a preferred embodiment of the present invention, the water level confirmation module calculates the difference between the slope water surface height and the scale water surface height to obtain the height difference, and compares the height difference with the set error threshold. If the height difference is not greater than the error threshold, the slope water surface height and the scale water surface height are output as the actual water surface height. If the height difference is greater than the error threshold, a measurement abnormality warning is fed back through the network.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] In the present invention, when measuring the flow rate of a water body, a non-contact measurement method of a video image is adopted, thereby avoiding the disadvantage that the contact measurement method is disturbed by different conditions and different flow rates of the water body, and thus cannot always maintain continuous and stable measurement. At the same time, before the video image measurement, a rough measurement result is obtained through contact measurement, and a quantitative analysis is performed based on the rough measurement result to obtain the preconditions for assisting the video image analysis, thereby further improving the accuracy of the video image analysis measurement, while reducing the difficulty of the video image flow rate analysis of the water body and reducing the monitoring cost.

[0033] In the present invention, when measuring the water level, the height measuring rod and the water bank edge line are synchronously collected through image acquisition equipment, and the collected results are used for data verification and data refinement, which improves the accuracy of water level measurement and can maintain measurement continuity when one set of measurement methods fails.

[0034] In the present invention, the water area terrain contour is obtained by scanning equipment, and model calculation and analysis are performed based on the water area terrain contour, flow rate data and water level data, so as to reasonably predict the water area flow, which is more accurate than the traditional flow measurement method. At the same time, since the acquisition of water area terrain contour is generally used for riverbed and water body bottom terrain monitoring operations, the flow rate is predicted by reasonably utilizing the data generated by the water body bottom terrain monitoring operation, which can reduce the cost of performing flow rate measurement operations alone and improve data utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] To facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0036] Figure 1 is a system block diagram of the present invention;

[0037] Figure 2 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0038] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0039] Example 1: Please refer to Figure 1 - Figure 2As shown, a method for continuously monitoring water level, flow rate and flow rate in an integrated manner includes a terminal acquisition control module, a flow rate pre-measurement module, a flow rate precise measurement module, a water level confirmation module and a flow rate prediction module. The terminal acquisition control module is connected to a terminal acquisition device and receives acquisition results fed back by the terminal acquisition device, wherein the terminal acquisition device includes an image acquisition device, a flow rate monitoring device and a terrain scanning device, wherein the flow rate monitoring device includes a conventional monitoring device and a video monitoring device, wherein the conventional monitoring device can use a rotor tachometer, an electromagnetic tachometer, etc., and the video monitoring device uses a high-frame-rate high-definition camera device;

[0040] The collection results received by the terminal collection control module include:

[0041] The results collected by the image acquisition equipment include water surface images and slope images. The water surface image is the area where the height measuring rod is located. It can capture the basic requirements of the water surface and height measuring rod position at the same time.

[0042] The results collected by the terrain scanning equipment include ground contours and slope contours. The terrain scanning equipment can be an ultrasonic echo measurement device, a radar echo measurement device, a three-dimensional laser scanning device, or other existing technology capable of simultaneously collecting underwater and land terrain.

[0043] The results collected by conventional monitoring equipment in the flow rate monitoring equipment include direct flow rate data, and the results collected by the video monitoring equipment are continuous water surface video;

[0044] After obtaining the collected results, the terminal collection module directly distributes the received collection results.

[0045] The flow velocity pre-measurement module obtains the collection results of conventional monitoring equipment, analyzes the flow velocity based on the collection results, and obtains the flow velocity fuzzy interval. The specific steps are as follows:

[0046] Step 1: After the flow velocity pre-order measurement module obtains direct flow velocity data through conventional monitoring equipment, it records the direct flow velocity data and compares the number of direct flow velocity data with the set sample number k. If the number of direct flow velocity data is greater than or equal to the set sample number k, it proceeds to step 2 to estimate the flow velocity. If the number of direct flow velocity data is less than the set sample number k, it does not proceed to step 2 and continues to count until the number of direct flow velocity data counted is greater than the set sample number k.

[0047] Step 2: Flow velocity estimation. When the flow velocity pre-measurement module is estimating the flow velocity, a scatter plot is created with the flow velocity as the vertical axis, and a dispersion analysis is performed on the created scatter plot to obtain the data dispersion. The data dispersion is calculated as the standard deviation. That is, assuming that the flow velocity data is Vi, i=1, 2, 3, ..., n, the standard deviation V0 is calculated by the formula, , where Va is the average value of the flow velocity data. The flow velocity pre-order measurement module performs weighted calculation on the data discreteness to obtain the flow velocity range width Vc. ;

[0048] Step 3: The velocity pre-measurement module calculates the velocity average value in the scatter plot to obtain the velocity mean value. At the same time, the velocity average value is expanded at both ends by the velocity range width to obtain the velocity fuzzy interval Vmin~Vmax. .

[0049] The flow measurement module collects the results from the video device and generates an analysis time based on the flow rate fuzzy interval. The flow measurement module accurately analyzes the results collected by the video device based on the analysis time to obtain the accurate flow rate result. The specific steps are as follows:

[0050] S1: After obtaining the flow velocity fuzzy interval, the flow velocity precise measurement module converts the unit of the flow velocity fuzzy interval from m / s to cm / ms. The flow velocity precise measurement module obtains the preset discrimination distance accuracy in cm and calculates the ratio of the discrimination distance accuracy to the two end values ​​of the flow velocity fuzzy interval to obtain the time discrimination interval X1ms~X2ms;

[0051] S2: The flow velocity precision measurement module selects the integer closest to the median in the time discrimination interval X1 to X2 and uses it as the analysis duration;

[0052] S3: The flow velocity precision measurement module selects a frame of image from the video captured by the video device as the starting point, and selects a second frame of image after the starting point at an interval of one analysis time. Then, it selects a third frame of image after the second frame of image at an interval of one analysis time, and so on, selecting a frame of image every time an analysis time is passed.

[0053] S4: The flow velocity precision measurement module selects a reference point in the image of the first frame through an algorithm. The reference point is identified by a recognition algorithm during selection. The selected reference point can be a floating object in the water, a water feature point, etc. The same reference point is selected in subsequent images, and the moving distance of the reference point in two adjacent frames is calculated. The precise flow velocity is obtained by calculating the ratio of the moving distance and the analysis time. When calculating the moving distance of the two reference points, the flow velocity precision measurement module uses the discrimination distance accuracy as an aid. The position of the reference point on the first frame image is extended along the flow direction by a discrimination distance accuracy, and the reference point is identified nearby based on the end point of the extended discrimination distance accuracy, thereby assisting in the selection of the reference point.

[0054] The flow rate precision measurement module performs arithmetic averaging on the multiple precise flow rates obtained to obtain a precise flow rate result, and outputs the precise flow rate result through the network.

[0055] Example 2: Please refer to Figure 1 - Figure 2 As shown, the water level confirmation module obtains the water surface parameters collected by the image acquisition device and the terrain parameters obtained by the terrain scanning device, and analyzes the water surface parameters and the terrain parameters;

[0056] After acquiring the water surface image and the slope image, the water level confirmation module obtains the display scale on the height measuring rod in the water surface image, automatically marks the display scale through the image processing algorithm, records the number of display scales above the water surface, and calculates the scale water surface height through the preset total number of display scales;

[0057] The water level confirmation module processes the acquired slope image through an algorithm to obtain an image of the slope above the water surface. The module then compares the slope image above the water surface with a preset complete slope image to obtain the missing portion of the slope image. The module then calculates the height of the missing portion of the slope image using a three-dimensional model to obtain the water surface height of the slope.

[0058] The water level confirmation module calculates the difference between the slope water surface height and the scale water surface height to obtain the height difference, and compares the height difference with the set error threshold. If the height difference is not greater than the error threshold, the slope water surface height and the scale water surface height are weighted averaged and output as the actual water surface height. The weight values ​​are the credibility of the slope water surface height and the scale water surface height, respectively. The credibility is manually set by the management personnel. The credibility value is obtained after laboratory testing and big data analysis. If the height difference is greater than the error threshold, a measurement abnormality warning is fed back through the network.

[0059] The water level confirmation module uses the terrain scanned by the terrain scanning equipment to perform three-dimensional modeling, and obtains the outline of the cross section in the three-dimensional modeling through algorithm software, and records it as the terrain impact result;

[0060] The flow prediction module obtains the water level confirmation results and the precise flow velocity results of the water level confirmation module, imports the precise flow velocity results, water level confirmation results and terrain influence results into the model, obtains the water level cross section through the cross-sectional profile and the water level confirmation results, and obtains the flow prediction result by multiplying the area of ​​the water level cross section and the precise flow velocity result.

[0061] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for continuous monitoring of water level, flow rate and flow rate, characterized in that: The terminal acquisition control module is connected to the terminal acquisition device and receives the acquisition results fed back by the terminal acquisition device, wherein the terminal acquisition device includes an image acquisition device, a flow rate monitoring device and a terrain scanning device. The terminal acquisition control module distributes the received acquisition results, wherein the flow rate monitoring device includes a conventional monitoring device and a video monitoring device; a water level confirmation module, which obtains water surface parameters acquired by an image acquisition device and terrain parameters acquired by a terrain scanning device, analyzes the water surface parameters and terrain parameters, and obtains a water level confirmation result and a terrain impact result based on the analysis results; A flow velocity pre-order measurement module, which obtains the collection results of conventional monitoring equipment and analyzes the flow velocity based on the collection results to obtain a flow velocity fuzzy interval; A flow rate precision measurement module, which generates an analysis duration based on the collection results of the video device and the flow rate fuzzy interval, and accurately analyzes the results collected by the video device according to the analysis duration to obtain an accurate flow rate result; A flow prediction module, wherein the flow prediction module obtains an accurate result of flow velocity and a result of terrain influence, and performs model analysis based on the accurate result of flow velocity and the result of terrain influence to obtain a flow prediction result; After the flow velocity pre-order measurement module obtains direct flow velocity data through conventional monitoring equipment, it records the direct flow velocity data and compares the number of direct flow velocity data with the set sample number k. If the number of direct flow velocity data is greater than or equal to the set sample number k, the flow velocity is estimated; if the number of direct flow velocity data is less than the set sample number k, statistics are continued; When the flow velocity pre-order measurement module performs flow velocity estimation, a scatter plot is created with the flow velocity as the vertical axis, and a dispersion analysis is performed on the created scatter plot to obtain data dispersion. The flow velocity pre-order measurement module performs weight calculation on the data dispersion to obtain the flow velocity range width; The flow velocity pre-order measurement module calculates the flow velocity average value in the scatter plot to obtain the flow velocity mean value, and simultaneously expands the flow velocity average value at both ends by the flow velocity range width to obtain the flow velocity fuzzy interval; After obtaining the flow velocity fuzzy interval, the flow precision measurement module performs unit conversion on the flow velocity fuzzy interval, converting the unit of the flow velocity fuzzy interval from m / s to cm / ms. The flow precision measurement module obtains a preset discrimination distance accuracy in cm, and calculates the ratio of the discrimination distance accuracy to the two end values ​​of the flow velocity fuzzy interval to obtain a time discrimination interval of X1ms to X2ms. The flow rate accurate measurement module selects the integer closest to the median in the time discrimination interval X1ms~X2ms and uses it as the analysis duration, where X1 and X2 are two time values; The flow accurate measurement module selects a frame of image from the video captured by the video device as a starting point, and selects a frame of image every time an analysis time is interval after the starting point, thereby obtaining multiple image samples; The flow precision measurement module selects a reference point in the first frame of the image through an algorithm, and selects the same reference point in subsequent images, calculates the moving distance of the reference point in two adjacent frames of the image, and calculates the precise flow rate by the ratio of the moving distance and the analysis time. The flow rate precision measurement module performs arithmetic averaging on the multiple precise flow rates obtained to obtain a precise flow rate result, and outputs the precise flow rate result through a network.

2. The method for continuous monitoring of water level, flow rate and flow rate according to claim 1, characterized in that: The acquisition results received by the terminal acquisition control module include: The results collected by the image acquisition device include water surface images and slope images, wherein the water surface image is the area where the height measuring rod is located; The results collected by terrain scanning equipment include ground contours and slope contours; The results collected by conventional monitoring equipment in flow rate monitoring equipment include direct flow rate data, and the results collected by video monitoring equipment are continuous videos of the water surface.

3. The method for continuous monitoring of water level, flow rate and flow rate according to claim 1, characterized in that: The flow rate precision measurement module assists in calculating the moving distance between two reference points by determining the distance accuracy, thereby assisting in the selection of reference points.

4. The method for continuous monitoring of water level, flow rate and flow rate according to claim 1, characterized in that: The water level confirmation module performs three-dimensional modeling on the terrain scanned by the terrain scanning device, and obtains the outline of the cross section in the three-dimensional modeling through the algorithm software, and records it as the terrain influence result; The flow prediction module obtains the water level confirmation result and the precise flow velocity result of the water level confirmation module, imports the precise flow velocity result, the water level confirmation result and the terrain influence result into the model, obtains the water level cross section through the cross-section profile and the water level confirmation result, and obtains the flow prediction result by multiplying the area of ​​the water level cross section and the precise flow velocity result.

5. The method for continuous monitoring of water level, flow rate and flow rate according to claim 1, characterized in that: After acquiring the water surface image and the slope image, the water level confirmation module obtains the display scale on the height measuring rod in the water surface image, automatically marks the display scale through the image processing algorithm, records the number of display scales above the water surface, and calculates the scale water surface height through the preset total number of display scales; The water level confirmation module processes the acquired slope image through an algorithm to obtain an image of the slope above the water surface, and compares the slope image above the water surface with a preset complete slope image to obtain the missing part in the slope image. The height of the missing part in the slope image is calculated through a three-dimensional model to obtain the water surface height of the slope.

6. The method for continuous monitoring of water level, flow rate and flow rate according to claim 5, characterized in that: The water level confirmation module calculates the difference between the slope water surface height and the scale water surface height to obtain the height difference, and compares the height difference with the set error threshold. If the height difference is not greater than the error threshold, the slope water surface height and the scale water surface height are output as the water level confirmation result. If the height difference is greater than the error threshold, a measurement abnormality warning is fed back through the network.

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