CN111551216B - Plain channel flow measurement equipment and method - Google Patents
Plain channel flow measurement equipment and method Download PDFInfo
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- CN111551216B CN111551216B CN202010494062.8A CN202010494062A CN111551216B CN 111551216 B CN111551216 B CN 111551216B CN 202010494062 A CN202010494062 A CN 202010494062A CN 111551216 B CN111551216 B CN 111551216B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F1/00—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow
- G01F1/002—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow wherein the flow is in an open channel
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- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02B—HYDRAULIC ENGINEERING
- E02B1/00—Equipment or apparatus for, or methods of, general hydraulic engineering, e.g. protection of constructions against ice-strains
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- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02B—HYDRAULIC ENGINEERING
- E02B5/00—Artificial water canals, e.g. irrigation canals
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F1/00—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow
- G01F1/66—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by measuring frequency, phase shift or propagation time of electromagnetic or other waves, e.g. using ultrasonic flowmeters
- G01F1/663—Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow by measuring frequency, phase shift or propagation time of electromagnetic or other waves, e.g. using ultrasonic flowmeters by measuring Doppler frequency shift
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
- G01F23/22—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by measuring physical variables, other than linear dimensions, pressure or weight, dependent on the level to be measured, e.g. by difference of heat transfer of steam or water
- G01F23/28—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm by measuring physical variables, other than linear dimensions, pressure or weight, dependent on the level to be measured, e.g. by difference of heat transfer of steam or water by measuring the variations of parameters of electromagnetic or acoustic waves applied directly to the liquid or fluent solid material
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
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Abstract
The embodiment of the invention discloses plain channel flow measurement equipment and a method, which are arranged on a channel and comprise the following steps: monitoring equipment and an informationized intelligent platform; the monitoring device includes: a radar current measurement master station; an upstream water level station, which is arranged upstream of the radar flow measurement master station; a downstream water level station disposed downstream of the radar flow measurement master station; the intelligent information platform is respectively in communication connection with the radar flow measurement master station, the upstream water level station and the downstream water level station, and is used for collecting data monitored by the radar flow measurement master station, the upstream water level station and the downstream water level station and calculating flow. The embodiment of the invention has the characteristics of calculating the flow according to the water head when the radar flow measurement enters the blind area, and compensating the defect of the radar flow measurement.
Description
Technical Field
The embodiment of the invention relates to the technical field of water resource engineering, in particular to plain channel flow measurement equipment and method.
Background
The plain ditch flow measurement is to set a flow measurement device at the front part of the ditch to monitor the water quantity. The ditch in the plain area has very slow gradient, generally cannot meet the conditions for building the water building, and only the flow rate and the water level are used for monitoring and calculating the water yield. The method is limited by investment factors, and the method is a good solution for measuring the flow rate and the water level by using a radar probe in a small branch canal and a remote automatic flow monitoring station, so that the method can avoid interference of sundries and siltation in water by non-contact measurement and has the advantages of less investment and no need of supervision. However, the radar flow rate probe has a larger starting flow rate (0.22 m/s), and when the flow rate is smaller than the starting flow rate, the monitored flow is zero, so that a blind area appears in flow calculation when the flow rate is slow, and the radar flow measurement method has the defect. Because plain canal, especially smaller canal has the function of retaining water and delivering water concurrently, the condition that the velocity of flow is slow also can appear in the time of the depth of water, if can not calculate the error that the flow caused can be bigger.
Disclosure of Invention
SPSS (Statistical Product and Service Solutions) referred to in this invention is "statistical product and service solution" software.
Therefore, the embodiment of the invention provides plain channel flow measurement equipment and a method thereof, which are used for solving the problem of flow measurement blind areas in the prior art when the flow rate is slow due to the radar flow measurement technology.
In order to achieve the above object, the embodiment of the present invention provides the following technical solutions:
according to a first aspect of an embodiment of the present invention, there is provided a plain channel flow measurement apparatus, installed on a channel, including: monitoring equipment and an informationized intelligent platform; the monitoring device includes:
a radar current measurement master station;
an upstream water level station, which is arranged upstream of the radar flow measurement master station;
a downstream water level station disposed downstream of the radar flow measurement master station;
the intelligent information platform is respectively in communication connection with the radar flow measurement master station, the upstream water level station and the downstream water level station, and is used for collecting data monitored by the radar flow measurement master station, the upstream water level station and the downstream water level station and calculating flow.
Optionally, the upstream water level station is provided with a first pressure type water level probe, a first cable pipe and a second collecting and transmitting device which are sequentially connected.
Optionally, the radar current measurement main station is provided with a radar probe, a second cable pipe and first acquisition and transmission equipment which are connected in sequence.
Optionally, the informationized intelligent platform comprises an automatic acquisition and uploading module, an internet of things database and an intelligent algorithm module, wherein the internet of things database is respectively in communication connection with the automatic acquisition and uploading module and the intelligent algorithm module, and the automatic acquisition and uploading module is respectively in communication connection with the first acquisition and transmission equipment and the second acquisition and transmission equipment.
Optionally, the automatic acquisition and uploading module includes an acquisition device, an internet of things protocol and a platform database, and the acquisition device transmits the acquired monitoring data to the platform database through the internet of things protocol.
Optionally, the intelligent algorithm module comprises a tracking learning unit, a historical data analysis unit and a data processing unit.
Optionally, the distance between the upstream water level station and the downstream water level station is greater than 300m.
Optionally, the distance between the radar probe and the water surface is greater than or equal to 2m.
Optionally, the radar probe includes a radar doppler flow rate probe and a radar water level probe, and the radar probe includes a doppler flow rate probe and a radar water level probe.
According to a second aspect of the embodiment of the present invention, there is provided a flow measurement method using the flow measurement device for plain channels, including the steps of:
a. when the water flow in the channel is at a normal flow rate, a radar Doppler flow rate probe and a radar water level probe are adopted to monitor the flow rate and the water level respectively; the second collecting and transmitting device collects the monitored flow rate and water level and transmits the flow rate and the water level to the automatic collecting and uploading module, the automatic collecting and uploading module collects the monitored flow rate and water level and uploads the flow rate and the water level to the internet of things database, and the intelligent algorithm module calculates flow Q1 through data of the internet of things database;
wherein Q1 i The flow is calculated by the flow rate and the water level of the radar station; x is X i Is the upstream-downstream water level difference; a. b is a regression parameter; c is a constant;
simultaneously monitoring the water levels at the upstream and downstream through a first pressure type water level probe and a second pressure type water level probe; the first collecting and transmitting device collects the monitored flow velocity and water level and transmits the flow velocity and water level to the automatic collecting and uploading module, and the automatic collecting and uploading module collects the monitored flow velocity and water level and uploads the flow velocity and water level to the database of the Internet of things;
b. repeating the step a every 30 minutes, gradually reducing the water flow in the channel to the starting flow speed, and obtaining a plurality of groups of flow-water head data; the intelligent algorithm module tracks the data change to carry out regression analysis in real time and updates the parameters of the function relation of flow and water level difference in real time;
c. in a radar speed measuring blind zone, according to the water level difference and the current water depth monitored by the upstream water level station and the downstream water level station, an intelligent algorithm module calculates flow Q2 by adopting a flow-water level difference function relation through data of an Internet of things database;
Q2=aX 2 +bX+c
and Q2 is the flow calculated according to the water level difference in the radar flow measurement blind area.
The embodiment of the invention has the following advantages:
the embodiment of the invention has the advantages of simple structure, low cost and novel design thought, and can make up the blind area of radar flow measurement, thereby improving the flow measurement precision and being beneficial to popularization and application in the remote automatic monitoring of the flow of plain channels. The radar flow measurement has a blind area, so that the flow measurement error is larger under the condition of low flow rate. The embodiment of the invention provides a method for measuring the upstream and downstream water levels by adding water level stations at the upstream and downstream of the water flow section to calculate the overflow when the flow speed is low, overcomes the defect of radar flow measurement, and improves the flow measurement precision on the premise of low cost. The intelligent algorithm module of the embodiment of the invention relies on the radar flow measurement master station to automatically fit regression parameters in real time, and is characterized in that the latest calibrated water level difference-flow relation is used for calculation every time radar flow measurement enters a blind zone, and the result is accurate.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those of ordinary skill in the art that the drawings in the following description are exemplary only and that other implementations can be obtained from the extensions of the drawings provided without inventive effort.
The structures, proportions, sizes, etc. shown in the present specification are shown only for the purposes of illustration and description, and are not intended to limit the scope of the invention, which is defined by the claims, so that any structural modifications, changes in proportions, or adjustments of sizes, which do not affect the efficacy or the achievement of the present invention, should fall within the scope of the invention.
FIG. 1 is a schematic diagram of a plain channel flow measurement device layout according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an informationized intelligent platform of a plain channel flow measurement device according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a radar flow measurement master station of a plain channel flow measurement device according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a water level station of a plain channel flow measurement device according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of functional units and interrelationships of an intelligent algorithm module of a plain channel flow measurement device according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of regression curves of the relationship between the upstream and downstream water level elevation differences and the flow of a plain channel flow measurement device according to an embodiment of the present invention;
fig. 7 is a schematic diagram of a process of time variation of the water depth and the upstream-downstream water level difference of a radar station of a plain channel flow measurement device according to an embodiment of the present invention;
fig. 8 is a schematic diagram of a water head-flow data processing process of radar measured data of a plain channel flow measurement device according to an embodiment of the present invention;
fig. 9 is a schematic diagram of a water level difference-flow data processing process under the condition of small water level difference (radar current measurement is in a dead zone and no radar measured data) of a plain channel current measurement device provided by the embodiment of the invention;
in the figure: 1-an upstream water level station; 11-a first cable duct; 12-a second acquisition and transmission device; 13-a sand filter tank; 14-a first pressure type water level probe; 2-a radar current measurement master station; 21-a radar probe; 211-radar doppler flow rate probe; 212-radar water level probe; 22-a first acquisition and transmission device; 3-a downstream water level station; 4-water surface; 5-channel; 6-an informationized intelligent platform; 61-an automatic acquisition and uploading module; 62-an internet of things database; 63-an intelligent algorithm module; 631-a tracking learning unit; 632-a historical data analysis unit; 633-a data processing unit; 7-water flow section.
Detailed Description
Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1 to 9, an embodiment of the present invention provides a plain channel flow measurement device, which is installed on a side wall of a channel 5, and includes: monitoring equipment and an intelligent information platform; the monitoring device includes:
a radar current measurement master station 2;
an upstream water level station 1, wherein the upstream water level station 1 is arranged upstream of the radar flow measurement main station 2;
the downstream water level station 3 is arranged at the downstream of the radar flow measurement main station 2;
the informationized intelligent platform 6 is respectively in communication connection with the radar current measurement main station 2, the upstream water level station 1 and the downstream water level station 3, and the informationized intelligent platform 6 is used for collecting data monitored by the radar current measurement main station 2, the upstream water level station 1 and the downstream water level station 3 and calculating flow.
The radar flow measurement device is simple in structure, low in cost and novel in design thought, can improve the measurement accuracy of radar flow measurement, and is beneficial to popularization and application in the remote automatic flow monitoring of plain channels. The radar flow measurement of the plain channel has a blind area, so that the flow measurement error is larger under the condition of low flow velocity. For example, when the flow rate is 0.15m/s and the water flow section 7 is 1m 2 The water content per day is 7000m 3 By radar alone measuring flow, this flowIs undetectable. Aiming at the problem, the invention provides a method for measuring the upstream and downstream water levels by adding water level stations at the upstream and downstream of the water flow section 7 to calculate the overflow when the flow speed is low, so that the defect of radar flow measurement is overcome, and the accuracy of flow measurement is improved on the premise of low cost.
While the flow is calculated by the upstream and downstream water level difference alone, the relationship is quite limited in theory, the relationship of water level difference and flow is unstable, and the data discreteness is quite high. The intelligent algorithm module 63 of the invention relies on the radar flow measurement master station 2 to automatically fit regression parameters in real time, and is characterized in that the latest calibrated water level difference-flow relation is used for calculation every time radar flow measurement enters a blind zone, and the result is accurate.
As an alternative embodiment of the invention, as shown in fig. 3, the radar flow measurement main station 2 is provided with a radar probe 21, and the radar probe 21 is as close to the water surface 4 as possible and is higher than the highest water level by 2m, thereby being beneficial to obtaining better radar Doppler signals; in cross section, the probe should be as close to the center as possible, ensuring that the maximum surface flow rate is achieved.
As an alternative embodiment of the present invention, as shown in fig. 3, the radar probe 21 includes a radar doppler flow rate probe 211 and a radar water level probe 212, and the radar probe 21 includes a doppler flow rate probe 211 and a radar water level probe 212, and can detect the flow rate and the water level of the water surface 4 for the calculation of the flow rate; the automatic acquisition and reporting is accomplished by the first acquisition and transmission device 22.
As an alternative embodiment of the present invention, as shown in fig. 4, the upstream water level station 1 is provided with a first pressure type water level probe 14, a first cable pipe and a second collecting and transmitting device 12 which are connected in sequence; the radar flow measurement main station 2 is provided with a radar probe 21, a second cable pipe and first acquisition and transmission equipment 22 which are connected in sequence; the first pressure type water level probe 14 and the second pressure type water level probe are used for sensing water depth, and complete automatic acquisition and reporting through the acquisition and transmission equipment 12, and synchronously report to the automatic acquisition and uploading module 61 of the informationized intelligent platform 6. The first pressure type water level probe 14 and the second pressure type water level probe are buried below the ground of the side slope of the channel 5 and are not interfered by water level flushing and sundry blockage; the first pressure type water level probe 14 and the second pressure type water level probe are 50cm lower than the bottom of the canal, so that the monitoring of the lowest water level is ensured; the sand and stone filter tank 13 with the cross section of not less than 100cm is upwards arranged along the side slope of the channel 5 from the first pressure type water level probe 14 and the second pressure type water level probe, the cross section of the sand and stone filter tank 13 is 40 x 50cm, sand and stone are filled in the sand and stone filter tank 13, the water permeability is good, and the filtering effect is achieved, so that the induction of the water level is ensured; the level measurement is used by the upstream and downstream water stations to determine the relative elevation.
As an alternative embodiment of the present invention, as shown in fig. 2, the informationized intelligent platform 6 includes an automatic acquisition and uploading module 61, an internet of things database 62 and an intelligent algorithm module 63, where the internet of things database 62 is respectively in communication connection with the automatic acquisition and uploading module 61 and the intelligent algorithm module 63, and the automatic acquisition and uploading module 61 is respectively in communication connection with the first acquisition and transmission device 22 and the second acquisition and transmission device 12.
As an optional embodiment of the present invention, the automatic acquisition and uploading module 61 includes an acquisition device, an internet of things protocol and a platform database, where the acquisition device remotely performs synchronous acquisition on the data monitored by the upstream water level station 1, the downstream water level station 3 and the radar current measurement master station 2, and transmits the data to the platform database through the internet of things protocol.
As an alternative embodiment of the present invention, the internet of things database 62 is used to monitor the storage and access services of data, and may be invoked by the informationized intelligent platform 6.
As an alternative embodiment of the present invention, as shown in fig. 4 and 5, the intelligent algorithm module 63 includes a tracking learning unit 631, a history data analysis unit 632, and a data processing unit 633; the tracking learning unit 631 is the core of the intelligent algorithm module 63, tracks radar flow measurement and upstream and downstream water level data in real time, and the automatic learning function can calculate the correlation parameter of flow-water level difference in real time according to the measured data. The historical data analysis unit 632 is used for analyzing the historical monitoring data to determine the qualitative relationship of flow-water head under different water levels. The tracking learning unit 631 generates parameters of a "flow rate-water head" function relationship by tracking the monitoring data. The data processing unit 633 selects different calculation methods to calculate the flow according to the current radar flow measurement state and the current water depth.
As an alternative embodiment of the invention, as shown in fig. 1, there can be no pumping station water intake facility between the upstream water level station 1 and the downstream water level station 3, and there can be branching channels 5, and the distance between the upstream water level station 1 and the downstream water level station 3 is greater than 300m.
As shown in fig. 1 to 5, the embodiment of the present invention further provides a flow measurement method using the flow measurement device of the plain channel, including the following steps:
a. when the water flow in the channel is at a normal flow rate, a radar Doppler flow rate probe 211 and a radar water level probe 212 are adopted to monitor the flow rate and the water level respectively; the second collecting and transmitting device 12 collects the monitored flow rate and water level and transmits the flow rate and water level to the automatic collecting and uploading module 61, the automatic collecting and uploading module 61 collects the monitored flow rate and water level and uploads the flow rate and water level to the internet of things database 62, and the intelligent algorithm module 63 calculates the flow rate Q1 according to the data of the internet of things database 62; specifically: the tracking learning unit 631 tracks radar current measurement and upstream and downstream water level data in real time, and the automatic learning function calculates a correlation parameter of "flow-water level difference" in real time according to the measured data. The historical data analysis unit 632 determines the qualitative relationship of "flow-head" for different water levels. The tracking learning unit 631 generates parameters of a "flow rate-water head" function relationship by tracking the monitoring data. The data processing unit 633 performs state recognition according to the current radar flow measurement state and the current water depth, and selects different calculation methods to calculate the flow according to different states such as whether the current radar flow measurement state is greater than the starting flow rate, the deep water state, the shallow water state, the MR mark state and the like;
according to the conditionsC=0 is introduced into the SPSS fitting module to obtain a and b; the data array of the fitting condition is continuously updated along with the radar current measurement data, and the data '0, 0' represents that the flow is zero when the water head difference is zero. The regression parameters a, b track changes as radar data is updated.
Wherein Q1 i Unit m 3 /s,The flow is calculated by the flow rate and the water level of the radar station; x is X i =L1 i -L2 i Units of cm, L1 i 、L2 i The water level elevations measured by the upstream water level station 3 and the downstream water level station 3 are respectively;
is the upstream-downstream water level difference; a. b is a regression parameter; c is a constant;
simultaneously monitoring the water levels at the upstream and downstream through the first pressure type water level probe 14 and the second pressure type water level probe; the first collecting and transmitting device 22 collects the monitored flow rate and water level and transmits the flow rate and water level to the automatic collecting and uploading module 61, and the automatic collecting and uploading module 61 collects the monitored flow rate and water level and uploads the flow rate and water level to the internet of things database 62;
b. repeating the step a every 30 minutes, gradually reducing the water flow in the channel to the starting flow speed, and obtaining a plurality of groups of flow-water head data; the intelligent algorithm module 63 tracks the data change to perform regression analysis in real time and updates the parameters of the function relationship of flow and water level difference in real time;
c. in the radar speed measuring blind area, according to the water level difference and the current water depth monitored by the upstream water level station and the downstream water level station, an intelligent algorithm module 63 calculates the flow Q2 by adopting a flow-water level difference function relation through the data of an Internet of things database 62;
Q2=aX 2 +bX+c
wherein Q2, unit m 3 And/s is the flow calculated according to the water level difference in the radar flow measurement blind area.
Specifically, as shown in fig. 7 and 8, in the drawings:
h1, unit m is the water depth of the radar station;
t, unit h, which is the time from the monitoring record to the monitoring start, wherein the monitoring frequency is one half hour, and a part of records are selected to describe the calculation processing process;
q3, unit m 3 If the current water diversion process does not have the latest radar flow measurement data, as shown as A-U in FIG. 7 (1), the flow calculated by the regression parameters of the same water depth in the database last time is selected;
q, unit m 3 S, analyzing and sorting the flow measurement result;
MR, recursion calculation and water level difference reset mark, 2-bit character, M-0 is normal, 1 is waiting for "recursion" calculation, R-0 is normal, 1 is water level difference reverts to zero.
As shown in fig. 7 (1), the method is summarized as "water level difference reset-blind area-radar actual measurement-blind area-water level difference reset", wherein a-U, D-B is a blind area, and U-D is a radar normal flow measurement area; as shown in fig. 7 (2), the method is summarized as "water level difference reset-dead zone-water level difference reset", the water diversion amount of the channel 5 is small, the water level difference is gradually increased, the flow rate does not reach the starting flow rate of the radar doppler flow rate probe 211, then the water level difference is gradually zeroed, and all the points from the point a to the point B run in the radar dead zone.
As shown in the A-U section of FIG. 7 (1), the water head starts to increase but is in the dead zone, the flow calculated by the regression parameters of the same water depth in the database last time is selected, and the MR is marked as '10'.
The water level difference is increased, the flow enters a U-D section, as shown in fig. 7 (1) and fig. 8 (2), the flow Q is directly radar flow Q1, and regression parameters a and b are calculated one by one from radar flow measurement data more than 3 times; the flow Q is then calculated for the preceding a-U segment with the newly obtained regression parameters, simply referred to as the "recursive algorithm", and MR is labeled "00".
As shown in the section D-B in fig. 7 (1) and fig. 8 (2), the flow Q2 is calculated by using the regression parameters a, B recorded in the last piece of the data table, and directly written into Q, where "real-time calibration real-time regression calculation flow".
As shown in fig. 7 (2) and fig. 9 (1), the whole flow measurement is located in a dead zone, the flow calculated by the regression parameter of the same water depth in the database last time is selected, and the MR is marked as '10'; as shown in fig. 9 (2), when the water head is reset again, the flow measurement data is processed such that q=q3 and MR is marked "00".
While the invention has been described in detail in the foregoing general description and specific examples, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
Claims (5)
1. Plain channel flow measurement equipment installs on the channel, and a serial communication port, include: monitoring equipment and an informationized intelligent platform; the monitoring device includes:
a radar current measurement master station;
an upstream water level station, which is arranged upstream of the radar flow measurement master station;
a downstream water level station disposed downstream of the radar flow measurement master station;
the information intelligent platform is respectively in communication connection with the radar flow measurement master station, the upstream water level station and the downstream water level station, and is used for collecting data monitored by the radar flow measurement master station, the upstream water level station and the downstream water level station and calculating flow;
the upstream water level station is provided with a first pressure type water level probe, a first cable pipe and a second acquisition and transmission device which are connected in sequence;
the radar flow measurement main station is provided with a radar probe, a second cable pipe and first acquisition and transmission equipment which are connected in sequence, wherein the radar probe comprises a radar Doppler flow velocity probe and a radar water level probe;
the information intelligent platform comprises an automatic acquisition and uploading module, an Internet of things database and an intelligent algorithm module, wherein the Internet of things database is respectively in communication connection with the automatic acquisition and uploading module and the intelligent algorithm module, and the automatic acquisition and uploading module is respectively in communication connection with the first acquisition and transmission equipment and the second acquisition and transmission equipment;
the intelligent algorithm module comprises a tracking learning unit, a historical data analysis unit and a data processing unit; the tracking learning unit tracks radar flow measurement and upstream and downstream water level data in real time, and calculates correlation parameters of flow-water level difference in real time according to measured data; the historical data analysis unit analyzes the historical monitoring data and determines qualitative relations of flow-water head under different water levels; the tracking learning unit generates parameters of a 'flow-water head' function relation through tracking the monitoring data; and the data processing unit performs state identification tracking according to the current radar flow measurement state and the current water depth, and selects different calculation methods to calculate the flow according to different states of whether the current radar flow measurement state is larger than the starting flow rate.
2. The plain channel flow measurement apparatus according to claim 1, wherein: the automatic acquisition and uploading module comprises acquisition equipment, an internet of things protocol and a platform database, wherein the acquisition equipment transmits acquired monitoring data to the platform database through the internet of things protocol.
3. The plain channel flow measurement apparatus according to claim 1, wherein: the distance between the upstream water level station and the downstream water level station is greater than 300m.
4. The plain channel flow measurement apparatus according to claim 1, wherein: the distance between the radar probe and the water surface is more than or equal to 2m.
5. A flow measuring method using the plain channel flow measuring device according to any one of claims 1 to 4, characterized in that,
the method comprises the following steps:
a. when the water flow in the channel is normal flow velocity, a radar Doppler flow velocity probe and a radar water level probe are adopted to monitor respectively
Flow rate and water level; the second collecting and transmitting device collects the monitored flow speed and water level and transmits the flow speed and water level to the automatic collecting and uploading die
The intelligent algorithm module is used for automatically acquiring and uploading the monitored flow rate and water level to the database of the Internet of things
Calculating flow Q1 through data of database of Internet of things
wherein Q1i is the flow calculated by the flow rate and the water level of the radar station; x is X i Is the upstream-downstream water level difference;
a. b is a regression parameter; c is a constant;
simultaneously monitoring the water levels at the upstream and downstream through a first pressure type water level probe and a second pressure type water level probe; the first collecting and transmitting device collects the monitored flow velocity and water level and transmits the flow velocity and water level to the automatic collecting and uploading module, and the automatic collecting and uploading module collects the monitored flow velocity and water level and uploads the flow velocity and water level to the database of the Internet of things;
b. repeating the step a every 30 minutes, gradually reducing the water flow in the channel to the starting flow speed, and obtaining a plurality of groups of flow-water head data; the intelligent algorithm module tracks the data change to carry out regression analysis in real time and updates the parameters of the function relation of flow and water level difference in real time;
c. in a radar speed measuring blind zone, according to the water level difference and the current water depth monitored by the upstream water level station and the downstream water level station, an intelligent algorithm module calculates flow Q2 by adopting a flow-water level difference function relation through data of an Internet of things database;
Q2=aX 2 +bX+c
and Q2 is the flow calculated according to the water level difference in the radar speed measurement blind area.
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