Channel hopper opening flow determination method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of irrigation channel water flow measurement, in particular to a channel bucket opening flow determination method and device, electronic equipment and a storage medium. Determining a plurality of standard flow arrays according to a flow estimation model and the plurality of flow monitoring data sets; determining a plurality of roughness factors according to a plurality of water-passing section areas, a plurality of total flows and a plurality of standard flow arrays; and finally, determining the channel opening flow according to the roughness factor, the flow cross section area, the second bucket monitoring array and a bucket flow estimation model. According to the embodiment of the invention, the standard flow estimation is carried out through the plurality of flow monitoring data sets, the roughness of each flow is determined through the estimation of the total flow and the standard flow, and the roughness is an important factor influencing the flow measurement and is also the most difficult-to-determine factor, so that the flow measurement accuracy is improved after the accurate roughness is obtained. Therefore, the accurate metering flow can be obtained, and the metering result is more accurate and reliable.

Description

Technical Field

[0001] The invention relates to the technical field of irrigation canal water flow measurement, and in particular to a method, device, electronic equipment and storage medium for determining a channel bucket flow. Background Art

[0002] The canal system consists of a series of open channel sections and pumping stations. The open channel sections usually include a main channel that draws water from the river, multiple branch channels that draw water from the main channel, and multiple ditches that draw water from the branch channels. The location where the ditches connect to the branch channels is called the ditches. There are ditches at the ditches, and there are water gates downstream of the ditches on the branch channels. The ditches supply water to farmers to irrigate their farmland. The total flow at the ditches is usually measured according to a predetermined water supply flow and usage time.

[0003] However, in the actual water supply process, the actual water supply flow rate often does not match the planned water supply flow rate, resulting in large errors in irrigation water metering, reducing farmers' water use experience and causing water use conflicts.

[0004] The water supply stability formed by the control method used in traditional irrigation operation is poor. The flow at the bucket mouth is greatly affected by the water flow level height of the upper channel. The water depth of the main canal changes, which affects the water outflow at the bucket mouth.

[0005] Based on this, it is necessary to develop a method to determine the channel bucket flow rate. Summary of the invention

[0006] The embodiments of the present invention provide a method, device, electronic device and storage medium for determining the flow rate at a channel bucket mouth, which are used to solve the problem of inaccurate measurement of the flow rate at a channel bucket mouth in the prior art.

[0007] In a first aspect, an embodiment of the present invention provides a method for determining a channel bucket flow rate, comprising: Acquire a plurality of ditches monitoring data sets, wherein the ditches monitoring data sets include a plurality of first ditches monitoring arrays, each of the first ditches monitoring arrays corresponding to a ditches; Determining a plurality of standard flow arrays according to the ditches flow estimation model and the plurality of ditches monitoring data sets, wherein each flow array is obtained according to a ditches monitoring data set, and the standard flow array includes a plurality of standard flow estimates; Determine a plurality of roughnesses according to a plurality of water flow cross-sectional areas, a plurality of total flow rates and the plurality of standard flow arrays, wherein each ditches corresponds to a roughness and a water flow cross-sectional area, and the total flow rate is a total water flow rate of the plurality of ditches; The channel ditch mouth flow is determined based on the roughness, water flow cross-sectional area, the second ditch monitoring array and the ditch flow estimation model.

[0008] In a possible implementation, the step of obtaining a plurality of ditches monitoring data sets includes: Each ditch monitoring data set is obtained through the following steps: Randomly adjust the height of multiple bucket gates; For each ditch, multiple water level heights of the ditch are constructed into a water level monitoring array according to the order of preset water level positions, and added to the monitoring array queue; Determine the water level stability coefficients of multiple ditches based on multiple monitoring array arrays; If the water level stability coefficients of the plurality of ditches are all lower than the fluctuation threshold, constructing the water level monitoring arrays taken from the end of the plurality of monitoring array queues into a ditches monitoring data set; Otherwise, jump to the step of constructing a water level monitoring array of the multiple water level heights of the ditch according to the order of the preset water level positions; The method of determining the water level stability coefficients of multiple ditches according to multiple monitoring array queues includes: For each ditch, the water level stability coefficient is determined according to the first formula, wherein the first formula is:

[0009] In the formula, is the water level stability coefficient, To monitor the array queue The first data, To monitor the array queue The first data, is the total number of data in the water level monitoring array, To monitor the total number of arrays in the array queue.

[0010] In a possible implementation, the ditches flow estimation model includes a plurality of flow probability models, each probability model corresponds to a model flow, and the plurality of standard flow arrays are determined according to the ditches flow estimation model and the plurality of ditches monitoring data sets, including: For each canal monitoring data set, perform the following steps: traversally extracting a first ditch monitoring array from the ditch monitoring data set as an array to be input; Inputting the array to be input into multiple traffic probability models respectively to obtain multiple probability estimates; Determining a standard flow estimate based on the multiple probability estimates and the model flows of the multiple flow probability models, and adding the standard flow estimate to a standard flow array; If the traversal of the canal monitoring data set is not completed, jump to the step of traversing and taking out the first canal monitoring array from the canal monitoring data set as the array to be input; in, The determining of a standard flow estimate according to the plurality of probability estimates and the model flows of the plurality of flow probability models comprises: The standard flow estimate is determined according to a second formula, wherein the second formula is:

[0011] In the formula, is the standard flow estimate, For the A probability estimate, For the The model traffic corresponding to the traffic probability model is is the total number of traffic probability models.

[0012] In a possible implementation, the process of constructing the traffic probability model includes: Obtain multiple sample sets, wherein the sample set includes multiple sample ditches monitoring arrays, the Euclidean distances between the multiple sample ditches monitoring arrays in the sample set and the center of the sample set are less than a distance threshold, and each sample ditches monitoring array corresponds to a sample flow; The probability of the target sample appearing in each sample set is calculated respectively to obtain multiple sample probabilities, wherein the target sample is a sample ditches monitoring array whose model flow deviation value from the flow probability model is less than a threshold value; Substituting the multiple sample probabilities and the multiple sample set centers into the probability basic equation to obtain a first set of equations; Determining a plurality of coefficients in the probability basic model according to the first set of equations; Constructing a flow probability model according to the plurality of coefficients and the probability basic equation; Wherein, the probability basic equation is:

[0013] In the formula, is the sample probability, is a natural constant, is the weighted independent variable, For the The first coefficient, For the The sample set center, is the bias constant.

[0014] In a possible implementation, the determining of a plurality of roughnesses according to a plurality of water flow cross-sectional areas, a plurality of total flow rates, and a plurality of standard flow rate arrays includes: constructing the plurality of water flow cross-sectional areas into a water flow area matrix; constructing the plurality of total flows into a total flow column vector; constructing the plurality of standard flow arrays into a standard flow matrix; According to the relationship between the water flow cross-sectional area, the roughness, the standard flow array and the total flow, the water flow area matrix, the total flow column vector and the standard flow matrix are constructed into a second set of equations about the plurality of roughnesses; The second set of equations is solved to determine a plurality of roughnesses.

[0015] In a possible implementation, the second set of equations is:

[0016] In the formula, is the water area matrix, is the standard flow matrix, is the roughness column vector, is the total flow column vector, For the Doukoudi The cross-sectional area of ​​water flow, For the The first of the standard flow arrays Standard flow rate, For the The roughness of the mouth of the bucket, For the The total flow corresponding to the standard flow array.

[0017] In a possible implementation, the method of determining the channel ditch mouth flow rate according to the roughness, the water flow cross-sectional area, the second ditch monitoring array and the ditch flow rate estimation model includes: Inputting the second ditch monitoring array into the ditch flow estimation model, and determining the standard flow according to the output of the ditch flow estimation model; The product of the standard flow rate, the roughness and the water flow cross-sectional area is taken as the channel bucket flow rate.

[0018] In a second aspect, an embodiment of the present invention provides a channel bucket flow determination device, which is used to implement the channel bucket flow determination method described in the first aspect or any possible implementation of the first aspect, and the channel bucket flow determination device includes: A monitoring data acquisition module, used to acquire a plurality of ditches monitoring data sets, wherein the ditches monitoring data sets include a plurality of first ditches monitoring arrays, each of which corresponds to a ditches; A standard flow estimation module, configured to determine a plurality of standard flow arrays according to the ditches flow estimation model and the plurality of ditches monitoring data sets, wherein each flow array is obtained according to a ditches monitoring data set, and the standard flow array includes a plurality of standard flow estimates; A roughness determination module, used to determine a plurality of roughnesses according to a plurality of water flow cross-sectional areas, a plurality of total flow rates and the plurality of standard flow arrays, wherein each ditches corresponds to a roughness and a water flow cross-sectional area, and the total flow rate is a total water flow rate of the plurality of ditches; as well as, The bucket mouth flow determination module is used to determine the channel bucket mouth flow according to the roughness, water flow cross-sectional area, the second bucket channel monitoring array and the bucket channel flow estimation model.

[0019] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements the steps of the method described in the first aspect or any possible implementation method of the first aspect.

[0020] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect or any possible implementation of the first aspect are implemented.

[0021] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: The embodiment of the present invention discloses a method for determining the flow rate at the mouth of a channel. The method first obtains multiple ditch monitoring data sets, wherein the ditch monitoring data sets include multiple first ditch monitoring arrays, each of which corresponds to a ditch; then, multiple standard flow arrays are determined according to the ditch flow estimation model and the multiple ditch monitoring data sets, wherein each flow array is obtained according to a ditch monitoring data set, and the standard flow array includes multiple standard flow estimates; then, multiple roughness ratios are determined according to multiple water flow cross-sectional areas, multiple total flows, and the multiple standard flow arrays, wherein each ditch corresponds to a roughness ratio and a water flow cross-sectional area, and the total flow rate is the total water flow rate of multiple ditch channels; finally, the channel ditch flow rate is determined according to the roughness ratio, the water flow cross-sectional area, the second ditch monitoring array, and the ditch flow estimation model. The embodiment of the present invention estimates the standard flow rate through multiple ditch monitoring data sets, and then determines the roughness ratio of each ditch through the total flow rate and the standard flow rate estimation. Since the roughness ratio is an important factor affecting the flow metering and is also the most difficult factor to determine, after obtaining a relatively accurate roughness ratio, a relatively accurate metering flow rate can be obtained, and the metering result is more accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0023] Figure 1 is a flow chart of a method for determining a channel bucket flow rate provided by an embodiment of the present invention; Figure 2 is a schematic diagram of a standard flow estimation acquisition process provided by an embodiment of the present invention; Figure 3 It is a functional block diagram of a channel bucket flow determination device provided in an embodiment of the present invention; Figure 4 It is a functional block diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In the following description, specific details such as specific system structures and technologies are provided for the purpose of illustration rather than limitation so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, and methods are omitted so as not to obscure the description of the present invention with unnecessary details.

[0025] In order to make the purpose, technical solutions and advantages of the present invention more clear, a specific implementation method will be described below in conjunction with the accompanying drawings.

[0026] The following is a detailed description of an embodiment of the present invention. This example is implemented on the premise of the technical solution of the present invention, and a detailed implementation method and a specific operation process are given, but the protection scope of the present invention is not limited to the following embodiments.

[0027] Figure 1 A flow chart of a method for determining channel bucket flow rate provided in an embodiment of the present invention.

[0028] like Figure 1 As shown, it shows a flow chart of the implementation of the method for determining the channel bucket flow provided by an embodiment of the present invention, which is described in detail as follows: In step 101, a plurality of ditches monitoring data sets are obtained, wherein the ditches monitoring data sets include a plurality of first ditches monitoring arrays, each of which corresponds to a ditches.

[0029] In some embodiments, obtaining a plurality of ditches monitoring data sets includes: Each ditch monitoring data set is obtained through the following steps: Randomly adjust the height of multiple bucket gates; For each ditch, multiple water level heights of the ditch are constructed into a water level monitoring array according to the order of preset water level positions, and added to the monitoring array queue; Determine the water level stability coefficients of multiple ditches based on multiple monitoring array arrays; If the water level stability coefficients of the plurality of ditches are all lower than the fluctuation threshold, constructing the water level monitoring arrays taken from the end of the plurality of monitoring array queues into a ditches monitoring data set; Otherwise, jump to the step of constructing a water level monitoring array of the multiple water level heights of the ditch according to the order of the preset water level positions; The method of determining the water level stability coefficients of multiple ditches according to multiple monitoring array queues includes: For each ditch, the water level stability coefficient is determined according to the first formula, wherein the first formula is:

[0030] In the formula, is the water level stability coefficient, To monitor the array queue The first data, To monitor the array queue The first data, is the total number of data in the water level monitoring array, To monitor the total number of arrays in the array queue.

[0031] Exemplarily, in the embodiment of the present invention, multiple water level depth sensors are provided in the ditch, and the water level height information of the ditch is obtained by using the multiple water level sensors in the ditch, and the water level height information collected at the same time is constructed into an array, and the array at the same time is collected as a ditch monitoring data set. The roughness of each ditch can be determined through the multiple ditch data sets and the flow of the branch canals corresponding to the multiple ditch canals (the ditch canals obtain water sources through the branch canals), and after the roughness is determined, the flow of the ditch can be determined according to the water level monitoring data.

[0032] To realize the above concept, in terms of constructing a ditch monitoring data set, the embodiment of the present invention verifies the stability of the water level gradient of each ditch, obtains water level monitoring data on the premise that the water level of each ditch is stable, and constructs a ditch monitoring data set.

[0033] Specifically, the heights of multiple sluice gates are randomly adjusted first, and then for each sluice, the multiple water level heights of the sluice are constructed into a water level monitoring array in the order of the preset water level monitoring point positions, and added to the monitoring array queue. Then, the water level stability coefficients of multiple sluices are determined according to the multiple monitoring array queues. If the water level stability coefficients of multiple sluices are all lower than the fluctuation threshold, the water level monitoring arrays taken from the end of the multiple monitoring array queues are constructed as the sluice monitoring data set. Otherwise, the above water level monitoring array collection steps are repeated. In this way, the obtained sluice monitoring data set is the water level monitoring data when the water level gradient of each sluice is stable, which provides data guarantee for determining the roughness of the sluice.

[0034] Regarding the water level stability coefficient, the embodiment of the present invention uses the following formula to determine it:

[0035] In the formula, is the water level stability coefficient, To monitor the array queue The first data, To monitor the array queue The first data, is the total number of data in the water level monitoring array, To monitor the total number of arrays in the array queue.

[0036] In step 102, a plurality of standard flow arrays are determined according to the ditches flow estimation model and the plurality of ditches monitoring data sets, wherein each flow array is obtained according to a ditches monitoring data set, and the standard flow array includes a plurality of standard flow estimates.

[0037] In some embodiments, the ditches flow estimation model includes a plurality of flow probability models, each probability model corresponds to a model flow, and the method of determining a plurality of standard flow arrays according to the ditches flow estimation model and the plurality of ditches monitoring data sets includes: For each canal monitoring data set, perform the following steps: traversally extracting a first ditch monitoring array from the ditch monitoring data set as an array to be input; Inputting the array to be input into multiple traffic probability models respectively to obtain multiple probability estimates; Determining a standard flow estimate based on the multiple probability estimates and the model flows of the multiple flow probability models, and adding the standard flow estimate to a standard flow array; If the traversal of the canal monitoring data set is not completed, jump to the step of traversing and taking out the first canal monitoring array from the canal monitoring data set as the array to be input; in, The determining of a standard flow estimate according to the plurality of probability estimates and the model flows of the plurality of flow probability models comprises: The standard flow estimate is determined according to a second formula, wherein the second formula is:

[0038] In the formula, is the standard flow estimate, For the A probability estimate, For the The model traffic corresponding to the traffic probability model is is the total number of traffic probability models.

[0039] In some implementations, the process of constructing the traffic probability model includes: Obtain multiple sample sets, wherein the sample set includes multiple sample ditches monitoring arrays, the Euclidean distances between the multiple sample ditches monitoring arrays in the sample set and the center of the sample set are less than a distance threshold, and each sample ditches monitoring array corresponds to a sample flow; The probability of the target sample appearing in each sample set is calculated respectively to obtain multiple sample probabilities, wherein the target sample is a sample ditches monitoring array whose model flow deviation value from the flow probability model is less than a threshold value; Substituting the multiple sample probabilities and the multiple sample set centers into the probability basic equation to obtain a first set of equations; Determining a plurality of coefficients in the probability basic model according to the first set of equations; Constructing a flow probability model according to the plurality of coefficients and the probability basic equation; Wherein, the probability basic equation is:

[0040] In the formula, is the sample probability, is a natural constant, is the weighted independent variable, For the The first coefficient, For the The sample set center, is the bias constant.

[0041] Exemplarily, the embodiment of the present invention estimates the flow rate of each ditch through a flow estimation model (standard flow estimation of the ditch).

[0042] like Figure 2As shown, the figure shows a schematic diagram of the standard flow estimation acquisition process. The flow estimation model of the embodiment of the present invention includes multiple flow probability models 202, and each probability model 202 corresponds to a model flow 203. For each ditch, the ditch monitoring array 201 is traversally taken out from the ditch monitoring data set and input into the multiple flow probability models 202 respectively to obtain multiple probability estimates 204. According to the multiple probability estimates 204 and the model flows 203 of the multiple flow probability models, the standard flow estimation 205 of the ditch is determined, and the standard flow estimation 205 of the ditch is added to the standard flow array. Repeating the above steps, the standard flow array is obtained. In other words, each ditch monitoring data set corresponds to a standard flow array.

[0043] Specifically, in determining the standard flow estimate 205 of the ditch based on the plurality of probability estimates 204 and the model flow 203 of the plurality of flow probability models, the embodiment of the present invention uses the following formula:

[0044] In the formula, is the standard flow estimate, For the A probability estimate, For the The model traffic corresponding to the traffic probability model is is the total number of traffic probability models.

[0045] In terms of constructing a flow probability model, an embodiment of the present invention is constructed based on multiple sample sets, the sample sets include multiple sample ditches monitoring arrays, the Euclidean distances between the multiple sample ditches monitoring arrays in the sample set and the center of the sample set are less than a distance threshold, and each sample ditches monitoring array corresponds to a sample flow. After obtaining multiple sample sets, firstly, the probability of the target sample appearing in each sample set is calculated respectively to obtain multiple sample probabilities, wherein the target sample is a sample ditches monitoring array whose model flow deviation value from the flow probability model is less than a threshold; then, the multiple sample probabilities and the multiple sample set centers are substituted into the probability basic equation to obtain a first set of equations; finally, multiple coefficients in the probability basic model are determined based on the first set of equations, and a flow probability model is constructed based on the multiple coefficients and the probability basic equation.

[0046] In one application scenario, the basic probability equation is:

[0047] In the formula, is the sample probability, is a natural constant, is the weighted independent variable, For the The first coefficient, For the The sample set center, is the bias constant.

[0048] In step 103, a plurality of roughnesses are determined according to a plurality of water flow cross-sectional areas, a plurality of total flow rates and the plurality of standard flow arrays, wherein each ditches corresponds to a roughness and a water flow cross-sectional area, and the total flow rate is the total water flow rate of the plurality of ditches.

[0049] In some embodiments, the determining of a plurality of roughnesses according to a plurality of water flow cross-sectional areas, a plurality of total flow rates, and a plurality of standard flow rate arrays comprises: constructing the plurality of water flow cross-sectional areas into a water flow area matrix; constructing the plurality of total flows into a total flow column vector; constructing the plurality of standard flow arrays into a standard flow matrix; According to the relationship between the water flow cross-sectional area, the roughness, the standard flow array and the total flow, the water flow area matrix, the total flow column vector and the standard flow matrix are constructed into a second set of equations about the plurality of roughnesses; The second set of equations is solved to determine a plurality of roughnesses.

[0050] In some embodiments, the second set of equations is:

[0051] In the formula, is the water area matrix, is the standard flow matrix, is the roughness column vector, is the total flow column vector, For the Doukoudi The cross-sectional area of ​​water flow, For the The first of the standard flow arrays Standard flow rate, For the The roughness of the mouth of the bucket, For the The total flow corresponding to the standard flow array.

[0052] Exemplarily, after obtaining multiple standard flow arrays, the embodiment of the present invention can determine the roughness based on the water-flowing cross-sectional area of ​​each ditches (in one application scenario, because the shape of the ditches is fixed, the water-flowing cross-sectional area of ​​the ditches can be determined based on the water level height at the ditches) and the total flow (in one application scenario, because the ditches are water sources obtained from branch channels, the flow of the branch channels is the total flow of multiple ditches).

[0053] Specifically, the multiple water flow cross-sectional areas are constructed into a water flow area matrix, the multiple total flows are constructed into a total flow column vector (each total flow corresponds to a time node, that is, corresponds to a ditch monitoring data set), and the multiple standard flow arrays are constructed into a standard flow matrix. According to the relationship between the water flow cross-sectional area, the roughness, and the standard flow array and the total flow, the row vector, the column vector, and the matrix are constructed into a second set of equations about multiple roughnesses. By solving the second set of equations, multiple roughnesses are determined. In an application scenario, the second set of equations:

[0054] In the formula, is the water area matrix, is the standard flow matrix, is the roughness column vector, is the total flow column vector, For the Doukoudi The cross-sectional area of ​​water flow, For the The first of the standard flow arrays Standard flow rate, For the The roughness of the mouth of the bucket, For the The total flow corresponding to the standard flow array.

[0055] In step 104, the flow rate at the channel ditch mouth is determined according to the roughness, the water flow cross-sectional area, the second ditch monitoring array and the ditch flow estimation model.

[0056] In some implementations, determining the channel ditches flow rate according to the roughness, the water flow cross-sectional area, the second ditches monitoring array, and the ditches flow rate estimation model includes: Inputting the second ditch monitoring array into the ditch flow estimation model, and determining the standard flow according to the output of the ditch flow estimation model; The product of the standard flow rate, the roughness and the water flow cross-sectional area is taken as the channel bucket flow rate.

[0057] For example, after the roughness is determined, the channel hopper flow rate can be determined based on the roughness, the hopper water-passing cross-sectional area and the standard flow rate. Specifically, for each hopper channel, its multiple water level monitoring information is constructed into an array and input into multiple flow probability models to obtain multiple probability values. The standard flow rate is determined based on the multiple probability values ​​and the flow rates of multiple flow probability models. The product of the standard flow rate, the roughness and the hopper water-passing cross-sectional area is the channel hopper flow rate.

[0058] The embodiment of the method for determining the flow at the mouth of a channel of the present invention first obtains a plurality of ditch monitoring data sets, wherein the ditch monitoring data set includes a plurality of first ditch monitoring arrays, each of which corresponds to a ditch; then, according to the ditch flow estimation model and the plurality of ditch monitoring data sets, a plurality of standard flow arrays are determined, wherein each flow array is obtained according to a ditch monitoring data set, and the standard flow array includes a plurality of standard flow estimates; then, according to a plurality of water-passing cross-sectional areas, a plurality of total flows, and the plurality of standard flow arrays, a plurality of roughnesses are determined, wherein each ditch corresponds to a roughness and a water-passing cross-sectional area, and the total flow is the total water flow of the plurality of ditches; finally, according to the roughness, the water-passing cross-sectional area, the second ditch monitoring array, and the ditch flow estimation model, the flow at the mouth of the channel is determined. The embodiment of the present invention estimates the standard flow through a plurality of ditch monitoring data sets, and then determines the roughness of each ditch through the total flow and the standard flow estimation. Since the roughness is an important factor affecting the flow metering and is also the most difficult factor to determine, after obtaining a relatively accurate roughness, a relatively accurate metering flow can be obtained, and the metering result is more accurate and reliable.

[0059] It should be understood that the size of the serial numbers of the steps in the above implementation does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the implementation method of the present invention.

[0060] The following is an implementation of the device of the present invention. For details not described in detail, reference may be made to the corresponding method implementation described above.

[0061] Figure 3 is a functional block diagram of a channel bucket flow determination device provided in an embodiment of the present invention, referring to Figure 3 The channel bucket flow determination device includes: a monitoring data acquisition module 301, a standard flow estimation module 302, a roughness determination module 303 and a bucket flow determination module 304, wherein: The monitoring data acquisition module 301 is used to acquire a plurality of ditches monitoring data sets, wherein the ditches monitoring data sets include a plurality of first ditches monitoring arrays, each of which corresponds to a ditches; A standard flow estimation module 302 is used to determine a plurality of standard flow arrays according to the ditches flow estimation model and the plurality of ditches monitoring data sets, wherein each flow array is obtained according to a ditches monitoring data set, and the standard flow array includes a plurality of standard flow estimates; A roughness determination module 303 is used to determine a plurality of roughnesses according to a plurality of water flow cross-sectional areas, a plurality of total flow rates and the plurality of standard flow arrays, wherein each ditches corresponds to a roughness and a water flow cross-sectional area, and the total flow rate is a total water flow rate of the plurality of ditches; The channel mouth flow determination module 304 is used to determine the channel mouth flow according to the roughness, the water flow cross-sectional area, the second channel monitoring array and the channel flow estimation model.

[0062] Figure 4 is a functional block diagram of an electronic device provided by an embodiment of the present invention. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 400 and a memory 401, wherein the memory 401 stores a computer program 402 that can be run on the processor 400. When the processor 400 executes the computer program 402, the steps in the above-mentioned channel bucket flow determination method and the embodiment are implemented, for example Figure 1 Steps 101 to 104 are shown.

[0063] Exemplarily, the computer program 402 may be divided into one or more modules / units, and the one or more modules / units are stored in the memory 401 and executed by the processor 400 to implement the present invention.

[0064] The electronic device 4 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device 4 may include, but is not limited to, a processor 400 and a memory 401. Those skilled in the art will appreciate that Figure 4 It is only an example of the electronic device 4 and does not constitute a limitation of the electronic device 4. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device 4 may also include input and output devices, network access devices, buses, etc.

[0065] The processor 400 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0066] The memory 401 may be an internal storage unit of the electronic device 4, such as a hard disk or memory of the electronic device 4. The memory 401 may also be an external storage device of the electronic device 4, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 4. Further, the memory 401 may also include both an internal storage unit and an external storage device of the electronic device 4. The memory 401 is used to store the computer program 402 and other programs and data required by the electronic device 4. The memory 401 may also be used to temporarily store data that has been output or is to be output.

[0067] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the implementation method can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method implementation method, which will not be repeated here.

[0068] In the above-mentioned embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0069] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0070] In the embodiments provided by the present invention, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0071] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0072] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0073] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the processes in the above-mentioned implementation method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various methods and device implementation methods can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device that can carry the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium.

[0074] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for determining the flow rate at a channel outlet, characterized in that: include: Acquire a plurality of ditches monitoring data sets, wherein the ditches monitoring data sets include a plurality of first ditches monitoring arrays, each of the first ditches monitoring arrays corresponding to a ditches; Determining a plurality of standard flow arrays according to the ditches flow estimation model and the plurality of ditches monitoring data sets, wherein each flow array is obtained according to a ditches monitoring data set, and the standard flow array includes a plurality of standard flow estimates; Determine a plurality of roughnesses according to a plurality of water flow cross-sectional areas, a plurality of total flow rates and the plurality of standard flow arrays, wherein each ditches corresponds to a roughness and a water flow cross-sectional area, and the total flow rate is the total water flow rate of the plurality of ditches; The channel ditch mouth flow is determined based on the roughness, water flow cross-sectional area, the second ditch monitoring array and the ditch flow estimation model.

2. The method for determining the channel hopper flow rate according to claim 1, characterized in that: The obtaining of multiple ditches monitoring data sets includes: Each ditch monitoring data set is obtained through the following steps: Randomly adjust the height of multiple bucket gates; For each ditch, multiple water level heights of the ditch are constructed into a water level monitoring array according to the order of preset water level positions, and added to the monitoring array queue; Determine the water level stability coefficients of multiple ditches based on multiple monitoring array arrays; If the water level stability coefficients of the plurality of ditches are all lower than the fluctuation threshold, constructing the water level monitoring arrays taken from the end of the plurality of monitoring array queues into a ditches monitoring data set; Otherwise, jump to the step of constructing a water level monitoring array of the multiple water level heights of the ditch according to the order of the preset water level positions; The method of determining the water level stability coefficients of multiple ditches according to multiple monitoring array queues includes: For each ditch, the water level stability coefficient is determined according to the first formula, wherein the first formula is: In the formula, is the water level stability coefficient, To monitor the array queue The first data, To monitor the array queue The first data, is the total number of data in the water level monitoring array, To monitor the total number of arrays in the array queue.

3. The method for determining the channel hopper flow rate according to claim 1, characterized in that: The ditches flow estimation model includes a plurality of flow probability models, each probability model corresponds to a model flow, and the plurality of standard flow arrays are determined according to the ditches flow estimation model and the plurality of ditches monitoring data sets, including: For each canal monitoring data set, perform the following steps: traversally extracting a first ditch monitoring array from the ditch monitoring data set as an array to be input; Inputting the array to be input into multiple traffic probability models respectively to obtain multiple probability estimates; Determining a standard flow estimate based on the multiple probability estimates and the model flows of the multiple flow probability models, and adding the standard flow estimate to a standard flow array; If the traversal of the ditch monitoring data set is not completed, jump to the step of traversing and taking out the first ditch monitoring array from the ditch monitoring data set as the array to be input; in, The determining of a standard flow estimate according to the plurality of probability estimates and the model flows of the plurality of flow probability models comprises: The standard flow estimate is determined according to a second formula, wherein the second formula is: In the formula, is the standard flow estimate, For the A probability estimate, For the The model traffic corresponding to the traffic probability model is is the total number of traffic probability models.

4. The method for determining the channel hopper flow rate according to claim 3, characterized in that: The construction process of the traffic probability model includes: Obtain multiple sample sets, wherein the sample set includes multiple sample ditches monitoring arrays, the Euclidean distances between the multiple sample ditches monitoring arrays in the sample set and the center of the sample set are less than a distance threshold, and each sample ditches monitoring array corresponds to a sample flow; The probability of the target sample appearing in each sample set is calculated respectively to obtain multiple sample probabilities, wherein the target sample is a sample ditches monitoring array whose model flow deviation value from the flow probability model is less than a threshold value; Substituting the multiple sample probabilities and the multiple sample set centers into the probability basic equation to obtain a first set of equations; Determining a plurality of coefficients in the probability basic model according to the first set of equations; Constructing a flow probability model according to the plurality of coefficients and the probability basic equation; Wherein, the probability basic equation is: In the formula, is the sample probability, is a natural constant, is the weighted independent variable, For the The first coefficient, For the The sample set center, is the bias constant.

5. The method for determining the channel hopper flow rate according to claim 1, characterized in that: The method of determining a plurality of roughnesses according to a plurality of water flow cross-sectional areas, a plurality of total flow rates and a plurality of standard flow rate arrays comprises: constructing the plurality of water flow cross-sectional areas into a water flow area matrix; constructing the plurality of total flows into a total flow column vector; constructing the plurality of standard flow arrays into a standard flow matrix; According to the relationship between the water flow cross-sectional area, the roughness, the standard flow array and the total flow, the water flow area matrix, the total flow column vector and the standard flow matrix are constructed into a second set of equations about the plurality of roughnesses; The second set of equations is solved to determine a plurality of roughnesses.

6. The method for determining the channel hopper flow rate according to claim 5, characterized in that: The second set of equations is: In the formula, is the water area matrix, is the standard flow matrix, is the roughness column vector, is the total flow column vector, For the Doukoudi The cross-sectional area of ​​water flow, For the The first of the standard flow arrays Standard flow rate, For the The roughness of the mouth of the bucket, For the The total flow corresponding to the standard flow array.

7. The method for determining the channel outlet flow rate according to any one of claims 1 to 6, characterized in that: The method of determining the channel hopper flow rate according to the roughness, the water flow cross-sectional area, the second hopper monitoring array and the hopper flow rate estimation model includes: Inputting the second ditch monitoring array into the ditch flow estimation model, and determining the standard flow according to the output of the ditch flow estimation model; The product of the standard flow rate, the roughness and the water flow cross-sectional area is taken as the channel bucket flow rate.

8. A device for determining the flow rate at a channel hopper, characterized in that: Used to implement the channel bucket flow determination method according to any one of claims 1 to 7, the channel bucket flow determination device comprises: A monitoring data acquisition module, used to acquire a plurality of ditches monitoring data sets, wherein the ditches monitoring data sets include a plurality of first ditches monitoring arrays, each of which corresponds to a ditches; A standard flow estimation module, configured to determine a plurality of standard flow arrays according to the ditches flow estimation model and the plurality of ditches monitoring data sets, wherein each flow array is obtained according to a ditches monitoring data set, and the standard flow array includes a plurality of standard flow estimates; A roughness determination module, used to determine a plurality of roughnesses according to a plurality of water flow cross-sectional areas, a plurality of total flow rates and the plurality of standard flow arrays, wherein each ditches corresponds to a roughness and a water flow cross-sectional area, and the total flow rate is a total water flow rate of the plurality of ditches; as well as, The bucket mouth flow determination module is used to determine the channel bucket mouth flow according to the roughness, water flow cross-sectional area, the second bucket channel monitoring array and the bucket channel flow estimation model.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method as claimed in any one of claims 1 to 7 are implemented.

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