Intelligent cableway ADCP flow measurement method, system, equipment and medium

Abstract

The invention discloses an intelligent cableway ADCP flow measurement method, system and device and a medium. The method comprises the following steps that measurement parameters are obtained; wherein the measurement parameters comprise the initial water flow velocity, the propagation velocity of the measurement sound waves in the sand-containing water body and the volume sand content; inputting the initial water flow velocity and the volume sand content into a preset first flow measurement model to obtain a first water flow velocity; inputting the propagation velocity and the volume sand content into a preset second flow measurement model to obtain a second water flow velocity; obtaining a difference value between the first water flow speed measurement and the second water flow speed measurement, and judging whether the difference value is smaller than a preset threshold value or not; if yes, outputting the average value of the first water flow velocity and the second water flow velocity as the final water flow velocity; if not, the credibility of the first water flow velocity measurement and the credibility of the second water flow velocity measurement are obtained respectively, the first water flow velocity measurement or the second water flow velocity measurement with the high credibility is output as the final water flow velocity measurement, and the method and the device have the advantages of being reliable in data and improving the measurement precision.

Description

Technical Field

[0001] The present application relates to the field of ADCP flow measurement technology, and in particular to an intelligent cableway ADCP flow measurement method, system, equipment and medium. Background Art

[0002] The ADCP flow measurement system uses the Doppler effect of sound waves to measure water velocity and flow rate. When sound waves encounter a moving object, their frequency changes, a phenomenon known as the Doppler effect. The ADCP flow measurement system transmits sound waves and measures the speed and frequency of sound waves in water, thereby calculating water velocity and flow rate. Due to its superior principle, the ADCP breaks through traditional mechanical rotation-based sensing flowmeters. It uses an acoustic transducer as a sensor, emitting acoustic pulses. These pulses are then reflected by unevenly distributed counterscatterers such as sediment particles and plankton in the water column. The transducer receives the signal and measures the Doppler frequency shift to calculate flow rate.

[0003] The existing ADCP-based flow measurement method uses a single measurement model. When encountering an unevenly distributed sediment water environment, it is easy to cause single measurement data distortion, which ultimately affects the measurement results and has low measurement accuracy. Summary of the Invention

[0004] The main purpose of this application is to provide an intelligent cableway ADCP flow measurement method, system, equipment and medium, aiming to solve the technical problem that the existing ADCP flow measurement method has a single measurement data and leads to low measurement accuracy.

[0005] To achieve the above objectives, the present application provides an intelligent cableway ADCP flow measurement method, comprising the following steps: Obtain measurement parameters; the measurement parameters include the initial water flow velocity V0, the propagation velocity of the measured sound wave in the sand-laden water body C and the volumetric sand content C V , C V It indicates the percentage of sediment volume in the water body to the total volume; The initial water flow velocity V0 and volume sediment content C V Input into the preset first flow measurement model to obtain the first water flow velocity V1; The propagation velocity C and volumetric sand content C V Input into the preset second flow measurement model to obtain the second water flow velocity V2; Obtaining the difference between the first water flow velocity V1 and the second water flow velocity V2, and determining whether the difference is less than a preset threshold; If yes, the average value of the first water flow velocity V1 and the second water flow velocity V2 is output as the final water flow velocity; If not, the reliability of the first water flow speed measurement V1 and the second water flow speed measurement V2 are obtained respectively, and the first water flow speed measurement V1 or the second water flow speed measurement V2 with higher reliability is output as the final water flow speed measurement.

[0006] Optionally, respectively obtaining the trustworthiness of the first water flow velocity measurement V1 and the second water flow velocity measurement V2 includes: Obtain N groups of first water flow velocity measurements V1 and N groups of second water flow velocity measurements V2 respectively; Identify the number of abnormal data in the first water flow velocity measurement V1 of the N groups as n1; Identify the number of abnormal data in the N-group second water flow velocity measurement V2 as n2; The confidence level of the first water flow velocity measurement V1 is (N-n1) / N; The confidence level of the second water flow velocity measurement V2 is obtained as (N-n2) / N.

[0007] Optionally, if the trust levels of the first water flow velocity measurement V1 and the second water flow velocity measurement V2 are the same, the method further includes: Eliminate abnormal data from the N groups of first water flow velocity measurements V1 and the N groups of second water flow velocity measurements V2 respectively; Obtain a first average value of the remaining first water flow velocity V1; Obtain a second average value of the remaining second water flow velocity V2; Determine whether the difference between the first average value and the second average value is less than a preset threshold; If so, the average of the first average value and the second average value is output as the final water flow velocity measurement; If not, return to obtaining measurement parameters.

[0008] Optionally, the expression of the first flow measurement model is: V1=V0·(1+α·C V ); Where α is the compensation factor related to sediment particle size.

[0009] Optionally, the expression of the second flow measurement model is: V2=f d ·C / (2f0·cosθ); Where, f d is the Doppler frequency shift, f0 is the emission frequency of the measuring sound wave, and θ is the angle between the sound beam direction of the measuring sound wave and the target movement direction.

[0010] Alternatively, the expression for the propagation velocity C is: C=1449.2+4.6T-0.055T 2 +0.0003T 3 +(1.34-0.01T)(S-35)+0.016CV ; Where T is the water temperature and S is the water salinity. Optionally, the volumetric sand content C V The expression is:

[0011]

[0012] Zr=ω / Kμ; Where C(z) is the vertical sediment concentration distribution, z is the current water depth where the measuring instrument is located, a is the reference height, and C a is the sediment content at the reference height a, h is the total water depth, Zr is the suspension index of sediment, ω is the settling velocity of sediment particles, K is the Karman coefficient, and μ is the friction flow velocity‌.

[0013] To achieve the above objectives, the present application also provides an intelligent cableway ADCP flow measurement system, comprising: The parameter acquisition module is used to obtain the measurement parameters; the measurement parameters include the initial water flow velocity V0, the propagation velocity of the measured sound wave in the sand-laden water body C and the volumetric sand content C V , C V It indicates the percentage of sediment volume in the water body to the total volume; The first flow measurement calculation module is used to calculate the initial water flow velocity V0 and volume sediment content C V Input into the preset first flow measurement model to obtain the first water flow velocity V1; The second flow measurement calculation module is used to calculate the propagation velocity C and volume sediment content C V Input into the preset second flow measurement model to obtain the second water flow velocity V2; A judgment module, configured to obtain a difference between the first water flow velocity V1 and the second water flow velocity V2, and to determine whether the difference is less than a preset threshold; A first data processing module is configured to output an average of the first water flow velocity V1 and the second water flow velocity V2 as a final water flow velocity if yes; The second data processing module is configured to obtain the reliability of the first water flow speed measurement V1 and the second water flow speed measurement V2 respectively if no, and output the first water flow speed measurement V1 or the second water flow speed measurement V2 with higher reliability as the final water flow speed measurement.

[0014] To achieve the above objectives, the present application also provides a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above method.

[0015] To achieve the above objectives, the present application also provides a computer-readable storage medium, on which a computer program is stored. A processor executes the computer program to implement the above method.

[0016] The beneficial effects that this application can achieve are as follows: This application first collects the initial water flow velocity V0, measures the propagation velocity C of the sound wave in the sand-laden water body and the volumetric sand content C V The measurement parameters are the initial water velocity V0 and volume sediment content C V Input into the preset first flow measurement model, which can characterize the volumetric sediment content C V The influence of the initial water flow velocity V0 is used to correct the initial water flow velocity V0 to obtain the first water flow velocity V1, and the propagation velocity C and volume sediment content C are used to calculate the water flow velocity V1. V Input into the preset second flow measurement model, which is based on the ADCP measurement principle to collect basic data, that is, to measure the propagation speed C of sound waves in sandy water bodies, and combine it with the volumetric sand content C V Correct the measured value and finally obtain the second water flow velocity V2. Then calculate the difference between the first water flow velocity V1 and the second water flow velocity V2, and determine whether the difference is less than the preset threshold. If so, it means that the data collected by the two measurement methods are relatively true and reliable, and the measurement results are relatively close. At the same time, in order to further improve the accuracy of the measurement results, the average value of the first water flow velocity V1 and the second water flow velocity V2 is output as the final water flow velocity. If not, it means that the measurement data of one of the two measurement methods is distorted. At this time, the trust of the first water flow velocity V1 and the second water flow velocity V2 can be obtained respectively, and the first water flow velocity V1 or the second water flow velocity V2 with higher trust can be output as the final water flow velocity, thereby improving the accuracy of the measurement results. In summary, the present application can be based on multi-source data acquisition, and different measurement data can be fitted in combination with different flow measurement models. Finally, the measurement results obtained based on the two measurement methods are compared and analyzed, which reduces the risk of distortion of single measurement data, thereby obtaining a final water flow velocity with reliable calculation results and improving measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] To more clearly illustrate the specific embodiments of this application or the technical solutions in the prior art, the following briefly describes the drawings required for the specific embodiments or the description of the prior art. Similar elements or parts are generally identified by similar reference numerals throughout the drawings. Elements or parts in the drawings are not necessarily drawn to scale.

[0018] Figure 1 Schematic diagram of a flow chart of an intelligent cableway ADCP flow measurement method in an embodiment of the present application; Figure 2This is a schematic diagram of the framework structure of an intelligent cableway ADCP flow measurement system in an embodiment of the present application.

[0019] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0021] It should be noted that if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the fact that they can be implemented by ordinary technicians in this field. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0022] Example 1 Reference Figure 1 This embodiment provides an intelligent cableway ADCP flow measurement method, comprising the following steps: Obtain measurement parameters; the measurement parameters include the initial water flow velocity V0, the propagation velocity of the measured sound wave in the sand-laden water body C and the volumetric sand content C V , C V It indicates the percentage of sediment volume in the water body to the total volume; The initial water flow velocity V0 and volume sediment content C V Input into the preset first flow measurement model to obtain the first water flow velocity V1; The propagation velocity C and volumetric sand content C V Input into the preset second flow measurement model to obtain the second water flow velocity V2; Obtaining the difference between the first water flow velocity V1 and the second water flow velocity V2, and determining whether the difference is less than a preset threshold; If yes, the average value of the first water flow velocity V1 and the second water flow velocity V2 is output as the final water flow velocity; If not, the reliability of the first water flow speed measurement V1 and the second water flow speed measurement V2 are obtained respectively, and the first water flow speed measurement V1 or the second water flow speed measurement V2 with higher reliability is output as the final water flow speed measurement.

[0023] In this embodiment, the initial water flow velocity V0 is collected, the propagation velocity C of the sound wave in the sand-laden water body and the volumetric sand content C are measured. V The measurement parameters are the initial water velocity V0 and volume sediment content C V Input into the preset first flow measurement model, which can characterize the volumetric sediment content C V The influence of the initial water flow velocity V0 is used to correct the initial water flow velocity V0 to obtain the first water flow velocity V1, and the propagation velocity C and volume sediment content C are used to calculate the water flow velocity V1. V Input into the preset second flow measurement model, which is based on the ADCP measurement principle to collect basic data, that is, to measure the propagation speed C of sound waves in sandy water bodies, and combine it with the volumetric sand content C V Correct the measured value and finally obtain the second water flow velocity V2. Then calculate the difference between the first water flow velocity V1 and the second water flow velocity V2, and determine whether the difference is less than a preset threshold. If so, it means that the data collected by the two measurement methods are relatively true and reliable, and the measurement results are relatively close. At the same time, in order to further improve the accuracy of the measurement results, the average value of the first water flow velocity V1 and the second water flow velocity V2 is output as the final water flow velocity. If not, it means that the measurement data of one of the two measurement methods is distorted. At this time, the trustworthiness of the first water flow velocity V1 and the second water flow velocity V2 can be obtained respectively, and the first water flow velocity V1 or the second water flow velocity V2 with higher trustworthiness is output as the final water flow velocity, thereby improving the accuracy of the measurement results. In summary, this embodiment can be based on multi-source data acquisition and combined with different flow measurement models to fit different measurement data. Finally, the measurement results obtained based on the two measurement methods are compared and analyzed, reducing the risk of distortion of single measurement data, thereby obtaining a final water flow velocity with reliable calculation results and improving measurement accuracy.

[0024] As an optional implementation, respectively obtaining the trustworthiness of the first water flow velocity measurement V1 and the second water flow velocity measurement V2 includes: Obtain N groups of first water flow velocity measurements V1 and N groups of second water flow velocity measurements V2 respectively; Identify the number of abnormal data in the first water flow velocity measurement V1 of the N groups as n1; Identify the number of abnormal data in the N-group second water flow velocity measurement V2 as n2; The confidence level of the first water flow velocity measurement V1 is (N-n1) / N; The confidence level of the second water flow velocity measurement V2 is obtained as (N-n2) / N.

[0025] In this embodiment, when calculating the trust degree, N groups of measurement values ​​of the first water flow velocity V1 and N groups of measurement values ​​of the second water flow velocity V2 can be calculated and obtained respectively. Due to the influence of accidental errors and environmental factors, a small number of data may be distorted, and ultimately a small number of measurement values ​​may deviate significantly from the measurement values ​​of most of which are in the normal range. For example, taking 100 groups as an example, there are 10 groups of measurement values ​​that are obviously abnormal. Then, this part of the data can be marked as abnormal data, and the number of abnormal data in the first water flow velocity V1 and the number of abnormal data in the second water flow velocity V2 can be identified respectively, recorded as n1; and then the number of abnormal data can be calculated according to the number of abnormal data. The confidence level is calculated, that is, the confidence level of the first water flow velocity measurement V1 is (N-n1) / N, and the confidence level of the second water flow velocity measurement V2 is (N-n2) / N. The confidence level is based on the real-time measurement data on site as the judgment benchmark, rather than determining the confidence level of a certain measurement method based on fixed historical data. This is because the fixed historical data may be affected by the measurement environment on the day or various other factors, and there may be deviations in the reference and guidance. Therefore, here, the data measured on site is used as the latest historical data for big data training. Ultimately, the confidence levels of the two measurement methods can be calculated in real time and accurately, providing a prerequisite for improving measurement accuracy.

[0026] As an optional implementation, if the first water flow velocity measurement V1 and the second water flow velocity measurement V2 have the same reliability, the method further includes: Eliminate abnormal data from the N groups of first water flow velocity measurements V1 and the N groups of second water flow velocity measurements V2 respectively; Obtain a first average value of the remaining first water flow velocity V1; Obtain a second average value of the remaining second water flow velocity V2; Determine whether the difference between the first average value and the second average value is less than a preset threshold; If so, the average of the first average value and the second average value is output as the final water flow velocity measurement; If not, return to obtaining measurement parameters.

[0027] In this embodiment, taking into account the special case that the trust levels of the first water flow velocity measurement V1 and the second water flow velocity measurement V2 are the same, in order to ensure the accuracy of the final measurement results, the abnormal data in the N groups of first water flow velocity measurement V1 and the N groups of second water flow velocity measurement V2 are first eliminated respectively, and then the first average value of the remaining first water flow velocity measurement V1 and the second average value of the remaining second water flow velocity measurement V2 are calculated respectively. In order to further determine the reliability of the data, it is judged again whether the difference between the first average value and the second average value is less than the preset threshold value. If so, the average value of the first average value and the second average value is output as the final water flow velocity measurement. If not, it means that the overall data of one of the measurement methods is distorted, and the method returns to obtaining the measurement parameters and re-collects data for measurement, thereby improving the reliability of the calculation results.

[0028] It should be noted that if no calculation results can be obtained after multiple rounds of measurements, it means that there is an abnormality in one of the measurement methods (such as sensor failure, etc.). Here, a threshold for the number of iterations can be set. When the threshold is exceeded, an alarm message is sent to remind the background management personnel to conduct troubleshooting in time.

[0029] As an optional implementation, the expression of the first flow measurement model is: V1=V0·(1+α·C V ); Where α is the compensation factor related to sediment particle size.

[0030] In this embodiment, since the flow velocity of a river is closely related to its sediment content, generally speaking, the faster the flow velocity of a river, the greater its sediment content. When the water flow velocity is low, its erosion capacity is weak, and the erosion effect on the riverbed and riverbank is small, so the river sediment content is low. When the water flow velocity increases, its erosion capacity increases, the erosion effect on the riverbed and riverbank is strengthened, and the river sediment content increases. Therefore, when calculating the actual flow velocity, an initial water flow velocity V0 is first calculated, and then based on the volumetric sediment content C V The initial water flow velocity V0 is corrected and compensated by multiplying it by the compensation factor α, and finally the first water flow velocity V1 can be calculated. The compensation factor α related to the sediment particle size can be obtained by inversion based on historical measurement data.

[0031] As an optional implementation, the expression of the second flow measurement model is: V2=f d ·C / (2f0·cosθ); Where, f d is the Doppler frequency shift, f0 is the emission frequency of the measuring sound wave, and θ is the angle between the sound beam direction of the measuring sound wave and the target movement direction.

[0032] In this embodiment, the difference between the transmitted and received frequencies caused by the Doppler effect is called the Doppler shift, which reveals the law of how the properties of waves change during motion. The Doppler shift f can be obtained based on the hydrographic lead fish equipped with ADCP. d , measure the emission frequency f0 of the sound wave, and the angle θ between the sound beam direction of the measuring sound wave and the target movement direction (i.e., the water flow direction), and calculate the propagation speed C of the measuring sound wave in the sandy water body. By inputting the above formula, the second water flow velocity V2 can be accurately calculated.

[0033] As an optional implementation, the expression of the propagation velocity C is: C=1449.2+4.6T-0.055T 2 +0.0003T 3+(1.34-0.01T)(S-35)+0.016C V ; Where T is the water temperature and S is the water salinity. In this embodiment, the existing calculation model for measuring the propagation velocity C of sound waves in water bodies is mainly based on clear water environments or environments with a small amount of sand, and therefore basically only considers the influence of water temperature and water salinity. However, this embodiment is aimed at the measurement environment of high-silt water bodies. Therefore, in order to improve the calculation accuracy, 0.016C is used here. V As a correction term, the propagation velocity C is compensated, that is, the volumetric sand content C is taken into account. V The influence on the propagation velocity C, thereby improving the reliability of the calculation results of the propagation velocity C. After testing, combined with 0.016C V After compensation as a correction term, the calculation accuracy can be improved by 6%.

[0034] As an optional embodiment, the volumetric sand content C V The expression is:

[0035]

[0036] Zr=ω / Kμ; Where C(z) is the vertical sediment concentration distribution, z is the current water depth where the measuring instrument (i.e., the hydrographic lead fish equipped with ADCP) is located, a is the reference height, and C a is the sediment content at the reference height a, h is the total water depth, Zr is the suspension index of sediment, ω is the settling velocity of sediment particles, K is the Karman coefficient, and μ is the friction flow velocity‌.

[0037] In this embodiment, based on the above integral relationship, C v is the volume-weighted average of C(z) in the vertical direction, and C(z) is the vertical sediment concentration distribution function, which represents the suspended sediment concentration at the water depth z (unit: kg / m³), which can be calculated by the dynamic sediment compensation equation. The sediment concentration C at the reference height a in the equation is a The measured or empirical reference sediment content at 0.05h-0.1h above the riverbed is usually taken; the total water depth h represents the vertical distance from the water surface to the riverbed, determines the vertical distribution scale, and can be measured by a pressure sensor; Zr is used as a dynamic adjustment factor and can be calculated by the formula Zr=ω / Kμ, where the sediment settling velocity ω refers to the speed at which sediment particles sink at a uniform speed in still water. This speed is related to the particle diameter (d), shape, and viscosity of the water flow. In the laminar flow area, the sedimentation velocity ω is proportional to the square of the particle diameter (d 2 ) is proportional to the particle diameter. In the turbulent region, the settling velocity ω is proportional to the 0.5 power of the particle diameter (d0.5 ) is proportional to the turbulent mixing intensity; the Karman coefficient K reflects the turbulent mixing intensity and can be taken as 0.2-0.3 in high sand content water bodies; the friction velocity μ reflects the shear force of the water flow and can be obtained by inverting the near-bottom velocity profile.

[0038] The comparison of the measurement errors of this embodiment and the prior art is shown in Table 1: Table 1 Measurement error comparison table

[0039] As can be seen from the above table, the measurement error of the solution of this embodiment is significantly reduced and improved based on the prior art, thereby effectively improving the measurement accuracy.

[0040] Example 2 Reference Figure 2 Based on the same inventive concept as the above embodiment, this embodiment further provides an intelligent cableway ADCP flow measurement system, comprising: The parameter acquisition module is used to obtain the measurement parameters; the measurement parameters include the initial water flow velocity V0, the propagation velocity of the measured sound wave in the sand-laden water body C and the volumetric sand content C V , C V It indicates the percentage of sediment volume in the water body to the total volume; The first flow measurement calculation module is used to calculate the initial water flow velocity V0 and volume sediment content C V Input into the preset first flow measurement model to obtain the first water flow velocity V1; The second flow measurement calculation module is used to calculate the propagation velocity C and volume sediment content C V Input into the preset second flow measurement model to obtain the second water flow velocity V2; A judgment module, configured to obtain a difference between the first water flow velocity V1 and the second water flow velocity V2, and to determine whether the difference is less than a preset threshold; A first data processing module is configured to output an average of the first water flow velocity V1 and the second water flow velocity V2 as a final water flow velocity if yes; The second data processing module is configured to obtain the reliability of the first water flow speed measurement V1 and the second water flow speed measurement V2 respectively if no, and output the first water flow speed measurement V1 or the second water flow speed measurement V2 with higher reliability as the final water flow speed measurement.

[0041] The relevant explanations and examples of each module in the system of this embodiment can refer to the methods of the aforementioned embodiments and will not be repeated here.

[0042] Example 3 Based on the same inventive concept as the above embodiment, this embodiment provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above method.

[0043] Example 4 Based on the same inventive concept as the above embodiment, this embodiment provides a computer-readable storage medium, on which a computer program is stored. A processor executes the computer program to implement the above method.

[0044] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. An intelligent cableway ADCP flow measurement method, characterized in that: The following steps are involved: Obtain measurement parameters; the measurement parameters include the initial water flow velocity V0, the propagation velocity of the measured sound wave in the sand-laden water body C and the volumetric sand content C V , C V It indicates the percentage of sediment volume in the water body to the total volume; The initial water flow velocity V0 and volume sediment content C V Input into the preset first flow measurement model to obtain the first water flow velocity V1; The propagation velocity C and volumetric sand content C V Input into the preset second flow measurement model to obtain the second water flow velocity V2; Obtaining the difference between the first water flow velocity V1 and the second water flow velocity V2, and determining whether the difference is less than a preset threshold; If yes, the average value of the first water flow velocity V1 and the second water flow velocity V2 is output as the final water flow velocity; If not, the reliability of the first water flow speed measurement V1 and the second water flow speed measurement V2 are obtained respectively, and the first water flow speed measurement V1 or the second water flow speed measurement V2 with higher reliability is output as the final water flow speed measurement.

2. The intelligent cableway ADCP flow measurement according to claim 1, characterized in that: Obtaining the trustworthiness of the first water flow velocity V1 and the second water flow velocity V2 respectively includes: Obtain N groups of first water flow velocity measurements V1 and N groups of second water flow velocity measurements V2 respectively; Identify the number of abnormal data in the first water flow velocity measurement V1 of the N groups as n1; Identify the number of abnormal data in the N-group second water flow velocity measurement V2 as n2; The confidence level of the first water flow velocity measurement V1 is (N-n1) / N; The confidence level of the second water flow velocity measurement V2 is obtained as (N-n2) / N.

3. The intelligent cableway ADCP flow measurement method according to claim 2, characterized in that: If the trust levels of the first water flow velocity measurement V1 and the second water flow velocity measurement V2 are the same, the method further includes: Eliminate abnormal data from the N groups of first water flow velocity measurements V1 and the N groups of second water flow velocity measurements V2 respectively; Obtain a first average value of the remaining first water flow velocity V1; Obtain a second average value of the remaining second water flow velocity V2; Determine whether the difference between the first average value and the second average value is less than a preset threshold; If so, the average of the first average value and the second average value is output as the final water flow velocity measurement; If not, return to obtaining measurement parameters.

4. An intelligent cableway ADCP flow measurement method according to any one of claims 1 to 3, characterized in that: The expression of the first flow measurement model is: V1=V0·(1+α·C V ); Where α is the compensation factor related to sediment particle size.

5. An intelligent cableway ADCP flow measurement method according to any one of claims 1 to 3, characterized in that: The expression of the second flow measurement model is: V2=f d ·C / (2f0·cosθ); Where, f d is the Doppler frequency shift, f0 is the emission frequency of the measuring sound wave, and θ is the angle between the sound beam direction of the measuring sound wave and the target movement direction.

6. The intelligent cableway ADCP flow measurement method according to claim 5, characterized in that: The expression of propagation velocity C is: C=1449.2+4.6T-0.055T 2 +0.0003T 3 +(1.34-0.01T)(S-35)+0.016C V ; Where T is the water temperature and S is the water salinity.

7. The intelligent cableway ADCP flow measurement method according to claim 6, characterized in that: Volumetric sand content C V The expression is: Zr=ω / Kμ; Where C(z) is the vertical sediment concentration distribution, z is the current water depth where the measuring instrument is located, a is the reference height, and C a is the sediment content at the reference height a, h is the total water depth, Zr is the suspension index of sediment, ω is the settling velocity of sediment particles, K is the Karman coefficient, and μ is the friction flow velocity‌.

8. An intelligent cableway ADCP flow measurement system, characterized in that: include: The parameter acquisition module is used to obtain the measurement parameters; the measurement parameters include the initial water flow velocity V0, the propagation velocity of the measured sound wave in the sand-laden water body C and the volumetric sand content C V , C V It indicates the percentage of sediment volume in the water body to the total volume; The first flow measurement calculation module is used to calculate the initial water flow velocity V0 and volume sediment content C V Input into the preset first flow measurement model to obtain the first water flow velocity V1; The second flow measurement calculation module is used to calculate the propagation velocity C and volume sediment content C V Input into the preset second flow measurement model to obtain the second water flow velocity V2; A judgment module, configured to obtain a difference between the first water flow velocity V1 and the second water flow velocity V2, and to determine whether the difference is less than a preset threshold; A first data processing module is configured to output an average of the first water flow velocity V1 and the second water flow velocity V2 as a final water flow velocity if yes; The second data processing module is configured to obtain the reliability of the first water flow speed measurement V1 and the second water flow speed measurement V2 respectively if no, and output the first water flow speed measurement V1 or the second water flow speed measurement V2 with higher reliability as the final water flow speed measurement.

9. A computer device, characterized in that: The computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the processor executes the computer program to implement the method according to any one of claims 1 to 7.

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