CN113987948B - Intelligent measuring and calculating method and system for outlet water flow of pump station - Google Patents

Intelligent measuring and calculating method and system for outlet water flow of pump station Download PDF

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CN113987948B
CN113987948B CN202111292159.1A CN202111292159A CN113987948B CN 113987948 B CN113987948 B CN 113987948B CN 202111292159 A CN202111292159 A CN 202111292159A CN 113987948 B CN113987948 B CN 113987948B
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施东海
赵兴磊
戴炜
周秋云
刘琳娟
沈旭
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Jiangsu Silian Water Technology Co ltd
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Abstract

The invention provides an intelligent measuring and calculating method for outlet water flow of a pump station, which comprises the following steps: obtaining a first water supply object; obtaining a first water quantity according to a first water supply object; obtaining a first water resource category according to the intelligent service system of the first pump station; determining first water purification equipment and a first conveying mode according to the first water resource category; obtaining a first purified water supply loss estimation value according to the first water purification equipment; obtaining a first estimated value of the loss of the supplied water for conveying according to the first conveying mode; inputting the first purified water supply loss estimation value and the first conveying water supply loss estimation value into a first outlet water flow measurement and calculation coefficient determination model to obtain a first pump station outlet water flow measurement and calculation coefficient; and calculating according to the water outlet flow measuring and calculating coefficient of the first pump station to obtain the water outlet flow of the first pump station. The method solves the technical problem that the measuring and calculating means with applicability to the self-specificity of each pump station is lack due to the fact that the measuring and calculating mode of the water yield of the pump station is low in individuation degree in the prior art.

Description

Intelligent measuring and calculating method and system for outlet water flow of pump station
Technical Field
The invention relates to the technical field of artificial intelligence correlation, in particular to a pump station water outlet flow intelligent measuring and calculating method and system.
Background
The water delivery and distribution pump station is an important engineering facility in the urban water supply industry, is a power source of water delivery and supply, plays a role in water supply for cities and regions, and the automation technology of the water supply pump station is gradually developed along with rapid development of machine learning and the proposal of the concept of the Internet of things in recent years. Distributed control is preliminarily realized at present, and basic realization is carried out on pump control, abnormal alarm, data acquisition, office automation and the like.
In the future, the automation of the pump station needs to develop towards the integration direction of measurement, control and management, wherein the monitoring of the water yield of the pump station is particularly important, and the reasonable water yield of the pump station is key data for determining whether the automatic control of the pump station can fall on the ground or not.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
in the prior art, the individual degree of the measuring and calculating mode of the water yield of the pump station is low, so that the technical problem of lack of measuring and calculating means with applicability to the self specificity of each pump station exists.
Disclosure of Invention
The embodiment of the application provides an intelligent measuring and calculating method and system for the outlet water flow of the pump station, and solves the technical problem that measuring and calculating means with applicability to the self-specificity of each pump station are lacked due to the fact that the measuring and calculating mode of the outlet water flow of the pump station is low in individuation degree in the prior art. The technical effects of the measuring and calculating mode of the pump station water yield with higher individuation degree are achieved by matching the conveying mode and the water purifying equipment according to the water resource category, respectively determining the water consumption degree obtained according to the actual condition of the pump station in the water purifying process and the conveying process, determining the water yield measuring and calculating coefficient through the intelligent model analysis according to the water consumption degree of the two steps, and finally determining the reasonable real-time pump station water yield according to the water yield measuring and calculating coefficient.
In view of the above problems, the embodiment of the application provides an intelligent measuring and calculating method and system for outlet water flow of a pump station.
In a first aspect, an embodiment of the present application provides an intelligent measuring and calculating method for outlet water flow of a pump station, where the method is applied to an intelligent management system of the pump station, and the method includes: obtaining a first water supply object; obtaining a first water resource category according to the intelligent service system of the first pump station; determining a first water purifying device and a first conveying mode according to the first water resource category and the first water supply object; obtaining a first purified water supply loss estimation value according to the first water purification equipment; obtaining a first estimated value of the loss of the water supply for conveying according to the first conveying mode; inputting the first purified water supply loss estimation value and the first conveying water supply loss estimation value into a first outlet water flow measurement and calculation coefficient determination model to obtain a first pump station outlet water flow measurement and calculation coefficient; and calculating according to the water outlet flow measuring and calculating coefficient of the first pump station to obtain the water outlet flow of the first pump station.
On the other hand, this application embodiment provides a pump station effluent discharge intelligent measurement and calculation system, wherein, the system includes: a first obtaining unit for obtaining a first water supply target; the second obtaining unit is used for obtaining a first water resource category according to the intelligent service system of the first pump station; the first determining unit is used for determining a first water purifying device and a first conveying mode according to the first water resource type and the first water supply object; a third obtaining unit, configured to obtain a first purified water supply loss estimation value according to the first water purification device; a fourth obtaining unit, configured to obtain a first estimated value of water supply loss for conveying according to the first conveying manner; a fifth obtaining unit, configured to input the first purified water supply loss estimation value and the first transport water supply loss estimation value into a first outlet flow measurement and calculation coefficient determination model, and obtain an outlet flow measurement and calculation coefficient of the first pump station; and the first calculating unit is used for measuring and calculating the coefficient according to the water outlet flow of the first pump station to obtain the water outlet flow of the first pump station through calculation.
In a third aspect, an embodiment of the present application provides an intelligent measuring and calculating system for outlet water flow of a pump station, which includes a memory, a processor, and a computer program that is stored in the memory and can be run on the processor, wherein the processor implements the steps of the method according to any one of the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the first water supply object is obtained; obtaining a first water resource category according to the intelligent service system of the first pump station; determining a first water purifying device and a first conveying mode according to the first water resource category and the first water supply object; obtaining a first purified water supply loss estimated value according to the first water purification equipment; obtaining a first estimated value of the loss of the water supply for conveying according to the first conveying mode; inputting the first purified water supply loss estimated value and the first conveying water supply loss estimated value into a first outlet water flow measuring and calculating coefficient determining model to obtain a first pump station outlet water flow measuring and calculating coefficient; according to the technical scheme, the water outlet flow of the first pump station is obtained through calculation according to the water outlet flow measuring and calculating coefficient of the first pump station, the technical effects of matching a conveying mode and a water purifying device according to the water resource type, respectively determining the water consumption degree obtained according to the actual condition of the pump station in the water purifying process and the conveying process, determining a water outlet measuring and calculating coefficient through intelligent model analysis according to the water consumption degree of the two steps, finally determining reasonable real-time pump station water outlet according to the water supply object user quantity and the water using time and combining the water outlet measuring and calculating coefficient, and obtaining the individual pump station water outlet with higher degree in the measuring and calculating mode are achieved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
FIG. 1 is a schematic flow chart of an intelligent measuring and calculating method for pump station water outlet flow according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a method for determining a first water absorption coefficient based on the information on the first material;
FIG. 3 is a schematic flow chart of another intelligent measuring and calculating method for the outlet flow of the pump station according to the embodiment of the present application;
FIG. 4 is a schematic structural diagram of an intelligent measuring and calculating system for the outlet water flow of a pump station according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of the reference numerals: a first obtaining unit 11, a second obtaining unit 12, a first determining unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a fifth obtaining unit 16, a first calculating unit 17, an electronic device 300, a memory 301, a processor 302, a communication interface 303, and a bus architecture 304.
Detailed Description
The embodiment of the application provides an intelligent measuring and calculating method and system for the outlet water flow of the pump station, and solves the technical problem that measuring and calculating means with applicability to the self-specificity of each pump station are lacked due to the fact that the measuring and calculating mode of the outlet water flow of the pump station is low in individuation degree in the prior art. The technical effects of matching the conveying mode and the water purifying equipment according to the water resource type, respectively determining the water consumption degrees obtained according to the actual conditions of the pump station in the water purifying process and the conveying process, determining the water yield measuring and calculating coefficient through the intelligent model analysis according to the water consumption degrees in the two steps, and finally determining the reasonable real-time pump station water yield according to the water yield measuring and calculating coefficient, and the measuring and calculating mode of the pump station water yield with higher individuation degree are achieved.
Summary of the application
The water delivery and distribution pump station is an important engineering facility in the urban water supply industry, is a power source of water delivery and supply, plays a role in water supply for cities and regions, and gradually develops the automation technology of the water supply pump station along with rapid development of machine learning and the proposal of the concept of the Internet of things in recent years. Distributed control is preliminarily realized at present, and basic realization of pump control, abnormal alarm, data acquisition, office automation and the like is realized. In the future, the automation of the pump station needs to develop towards the integration direction of measurement, control and management, wherein the monitoring of the water yield of the pump station is particularly important, and the reasonable water yield of the pump station is key data for determining whether the automatic control of the pump station can fall on the ground or not. However, the individual degree of the measuring and calculating mode of the water yield of the pump station in the prior art is low, so that the technical problem that measuring and calculating means with applicability to the self specificity of each pump station is lacked exists.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides an intelligent measuring and calculating method for outlet water flow of a pump station, wherein the method is applied to an intelligent management system of the pump station, and the method comprises the following steps: obtaining a first water supply object; acquiring a first water resource category according to the intelligent service system of the first pump station; determining a first water purifying device and a first conveying mode according to the first water resource category and the first water supply object; obtaining a first purified water supply loss estimated value according to the first water purification equipment; obtaining a first estimated value of the loss of the water supply for conveying according to the first conveying mode; inputting the first purified water supply loss estimation value and the first conveying water supply loss estimation value into a first outlet water flow measurement and calculation coefficient determination model to obtain a first pump station outlet water flow measurement and calculation coefficient; and calculating to obtain the water outlet flow of the first pump station according to the water outlet flow measuring and calculating coefficient of the first pump station.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, an embodiment of the present application provides an intelligent measuring and calculating method for outlet water flow of a pump station, where the method is applied to an intelligent management system of the pump station, and the method includes:
s100: obtaining a first water supply object;
specifically, the first water supply object refers to a user who provides water resources for a pump station, and can be selected from residential water, public building water, industrial enterprise water, fire water and the like. One pump station may correspond to a plurality of water supply objects, and the first water supply object may be determined in an optional manner: the pump station is traversed and compared among a plurality of water supply objects, when the water supply object corresponding to the pump station appears, the pump station is marked immediately, the ratio of the daily water supply quantity of the water supply object to the total water supply quantity is collected and used as water supply weight and is recorded in identification information together with the water supply object, and when the comparison is finished, the identification information of the pump station represents the first water supply object. Different treatment modes can be adopted according to different water supply objects, and the water yield of the pump station is different due to different water consumption in different treatment processes, so that the water yield suitable for the specificity of the pump station can be calculated.
S200: acquiring a first water resource category according to the intelligent service system of the first pump station;
specifically, the first water resource category refers to that based on the first pumping station intelligent service system, the water resource source of the pumping station, such as the categories of surface water, underground water, etc., can be determined according to historical data in the system. The first water resource type selectable determining mode can be that a pump station is compared in the existing water resource type, and marking is carried out when the water resource type corresponding to the pump station appears according to historical data. Different water purification means and conveying processes can be determined by determining the first water resource type of the pump station, and further the water yield of the pump station with higher individuation degree can be calculated.
S300: determining a first water purifying device and a first conveying mode according to the first water resource category and the first water supply object;
specifically, the first water purification equipment is water purification equipment with strong adaptability obtained by matching the first water resource type with the first water supply object, for example, if the first water supply object is residential water and the first water resource type is underground water, the water resource needs to be conveyed to the purification equipment at this time, and the water resource meeting the residential water standard is obtained by multi-level filtration and disinfection; the first conveying mode refers to a conveying process obtained by matching the first water resource type processing flow, for example, if the first water supply object is fire-fighting water, the first water resource type is surface water, and the selectable conveying mode is primary filtering, so that the first water resource type can be conveyed to each fire-fighting port to wait for use. According to different first water resource types and different first water supply objects, the first water purification equipment with higher applicability and the first conveying mode are matched, namely water resource processing information of all intermediate processes from a water outlet end to a water using end is stored, and an information basis is provided for measuring and calculating the water yield of a pump station with higher individuation degree.
S400: obtaining a first purified water supply loss estimated value according to the first water purification equipment;
s500: obtaining a first estimated value of the loss of the water supply for conveying according to the first conveying mode;
specifically, the first purified water supply loss estimation value refers to the loss estimation condition of the water resource in the purification process according to the matched actual conditions of the internal work flow and the material information of the first water purification equipment, the estimation cannot be independently judged according to the change trend of the difference value before and after entering the first water purification equipment in historical data, the change trend of the difference value is only the external expression form of the real-time change of the internal work flow and the material information, and the loss value of the water resource in the first water purification equipment can be accurately predicted by monitoring the actual conditions of the internal work flow and the material information in real time; similarly, the loss value of the water resource in the first water purifying equipment can be predicted according to the conveying flow of the first conveying mode and the actual condition of the conveying pipeline, and the estimated value of the loss of the first conveying water supply is obtained. And evaluating the water resource treatment loss water in all the intermediate processes from the water outlet end to the water using end to obtain the influence of the intermediate processes on water resources, and associating the first water supply object with the water yield of the pump station to provide an important information basis for further accurate measurement of the water yield of the pump station.
S600: inputting the first purified water supply loss estimated value and the first conveying water supply loss estimated value into a first outlet water flow measuring and calculating coefficient determining model to obtain a first pump station outlet water flow measuring and calculating coefficient;
s700: and calculating to obtain the water outlet flow of the first pump station according to the water outlet flow measuring and calculating coefficient of the first pump station.
Specifically, the first pump station water flow measurement coefficient information is an influence factor of an intermediate process obtained by inputting the first purified water supply loss estimation information and the first delivery water supply loss estimation information into the first water flow measurement coefficient determination model through intelligent analysis, the first water flow measurement coefficient determination model is established on the basis of a neural network model and has the characteristics of the neural network model, wherein the artificial neural network is an abstract mathematical model which is proposed and developed on the basis of modern neuroscience and aims to reflect the structure and the function of the human brain, the neural network is an operational model and is formed by connecting a large number of nodes (or called neurons), each node represents a specific output function called an excitation function, the connection between every two nodes represents a weighted value, called a weight, for a signal passing through the connection, which is equivalent to the memory of the artificial neural network, the output of the network is expressed by a logic strategy, the first water flow measurement coefficient determination model established on the basis of the neural network model can be accurately calculated by combining the water supply flow measurement coefficient with the first water flow measurement coefficient determination model, and the water supply loss measurement coefficient determination model can be accurately calculated by combining the first pump station.
Further, based on the estimated value of the loss of the first purified water supply and the estimated value of the loss of the first conveying water supply, a measurement and calculation coefficient of the flow rate of the outlet water of the first pump station is obtained, and the step S600 includes:
s610: inputting said first purified water supply loss estimate and said first delivery water supply loss estimate into a first effluent flow measurement coefficient determination model;
s620: the first effluent flow measurement coefficient determination model is obtained from a plurality of sets of training data, the plurality of sets of data including: the first purified water supply loss historical data, the first conveying water supply loss historical data and identification information for identifying the first pump station water outlet flow measurement and calculation coefficient.
S630: and obtaining a first output result, wherein the first output result comprises a water outlet flow measurement and calculation coefficient of the first pump station.
Specifically, the first effluent flow measurement coefficient determination model is a neural network model, which is a neural network model in machine learning, reflects many basic characteristics of human brain functions, and is a highly complex nonlinear dynamical learning system. Wherein, it can carry out continuous self-training study according to training data, each group of training data in the multiunit all includes: the first purified water supply loss historical data, the first conveying water supply loss historical data and identification information for identifying the first pump station water outlet flow measurement and calculation coefficient. And the first effluent flow measurement and calculation coefficient determination model is continuously corrected, and when the output information of the first effluent flow measurement and calculation coefficient determination model reaches a preset accuracy rate/convergence state, the supervised learning process is ended. By carrying out data training on the first outlet water flow measurement and calculation coefficient determination model, the first outlet water flow measurement and calculation coefficient determination model can process input data more accurately, and further the output first pump station outlet water flow measurement and calculation coefficient information is more accurate, so that the technical effects of accurately obtaining data information and improving the intellectualization of an evaluation result are achieved.
Further, based on the obtaining of the first purified water supply loss estimation value according to the first water purification device, the step S400 includes:
s410: according to the first water purification equipment, obtaining first water purification level information and first water purification duration information;
s420: obtaining first material information according to the first water purification level information;
s430: determining a first water absorption coefficient and first volume information according to the first material information;
s440: obtaining a first preset operation rule;
s450: and determining the first purified water supply loss estimation value according to the second preset operation rule through the first water absorption coefficient, the first purified water duration information and the first volume information.
Specifically, the first water purification level information refers to information of different filter layers through which water is filtered in the process of purifying water by the first water purification apparatus, which is not limited by the following examples: for example, water is filtered through a cotton pad, coral ball, activated carbon, ceramic filter in sequence. The first water purification duration information refers to timing when water resources start to enter the first water purification equipment, and optionally, a time mark is made when filtering is performed at each level, and the timing is finished until the water resources exit the first water purification equipment, so that time data is obtained. Further, the first material information refers to material data corresponding to each level, such as arrangement information of materials, material type information, and the like, obtained according to the first water purification level information; the first water absorption coefficient refers to the capability of obtaining the absorption and loss of water according to the characteristics of the first material information, the first volume information refers to the space information occupied by the first material, and the larger the first volume information is, the more the water absorption capacity is likely to be. Further, the first preset operation rule refers to a formula for predicting the first purified water supply loss estimation value by using three items of data which are set after the first water absorption coefficient, the first purified water duration information and the first volume information are obtained. The optional implementation manner is as follows: the first water absorption coefficient is normalized to be the water absorption capacity of the first material in unit time and unit volume, the first water absorption coefficient, the first water purification time length information and the first volume information are linearly multiplied to obtain a final result, namely the first purification water supply loss estimation value, and the first purification water supply loss estimation value can be periodically updated in real time, so that the technical effect of the first purification water supply loss estimation value estimation result with higher individuation degree and instantaneity is achieved.
Further, based on the obtaining of the estimated value of the water supply loss for the first transportation mode, step S500 includes:
s510: according to the first conveying mode, second material information and first conveying duration information are obtained;
s520: determining a second water absorption coefficient and first conveying length information according to the second material information;
s530: obtaining a second preset operation rule;
s540: and determining the first conveying water supply loss estimated value according to the second preset operation rule and through the second water absorption coefficient, the first conveying time length information and the first conveying length information.
Specifically, the second material information refers to materials used by water resources through the transportation space used by the first transportation mode, such as different types of pipelines; the first conveying time length information refers to the time from the beginning of timing when different conveying materials are entered to the time when the conveying materials are discharged, the timing is finished until water resources are sent to the first water supply object, all the time is collected, and further, the second water absorption coefficient refers to the water absorption and loss capacity obtained according to the characteristic data of the second material information; the first conveying length information refers to length data of conveying pipelines, and the length information corresponding to different types of pipelines is different and is an information set corresponding to the first conveying duration information. Furthermore, the second preset operation rule refers to a formula for establishing a simultaneous data of the second water absorption coefficient, the first conveying time length information and the first conveying length information when the second water absorption coefficient, the first conveying time length information and the first conveying length information are acquired, so that the estimated value of the first conveying water supply loss can be confirmed. The optional implementation manner is as follows: and normalizing the second water absorption coefficient into the water absorption capacity of the second material in unit time and unit length, and linearly multiplying the data of the second water absorption coefficient, the second water absorption coefficient and the data of the second material in unit time and unit length to obtain a result, namely the first conveying water supply loss estimated value, wherein the first conveying water supply loss estimated value can be periodically updated in real time, so that the technical effect of the first conveying water supply loss estimated value estimation result with higher individualization degree and instantaneity is achieved.
Further, based on the determining the first water absorption coefficient according to the first material information, as shown in fig. 2, step S430 includes:
s431: acquiring the surface image information of the first material according to a first image acquisition device;
s432: performing convolution feature extraction on the first material surface image information to obtain first feature information, wherein the first feature information comprises a first pore size feature set and a first pore morphology feature set;
s433: inputting the first pore size characteristic set and the first pore morphology characteristic set into a first clustering model to obtain a first partition result;
s434: traversing the first pore size characteristic set and the first pore morphology characteristic set in the first partition result to obtain first partition characteristic information;
s435: acquiring a first subarea water absorption coefficient according to the first subarea characteristic information;
s436: collecting the water absorption coefficients of all the subareas to form a water absorption coefficient set;
s437: and taking the water absorption coefficient set as the first water absorption coefficient.
Specifically, the second water absorption coefficient and the first water absorption coefficient are determined in the same manner, and the determination of the first water absorption coefficient is taken as an example: the first image acquisition device is equipment for monitoring a water resource conveying and processing process, preferably miniature high-definition intelligent camera equipment, and the first material surface image information is an image data set formed by acquiring and storing the first material surface image through the first image acquisition device. Further, the first pore size feature set and the first pore morphology feature set refer to feature information obtained by performing convolution feature extraction on the first material surface image information, optionally, a feature extraction model based on convolution neural network training is selected for feature extraction, and convolution can be used as a feature extractor in machine learning, so that the extracted feature information has concentration and representativeness, and further convolution features of the first material surface image are obtained.
Further, the first clustering model is an intelligent model classified according to information features, and the first partition result is that the first clustering model is used for classifying the first pore size feature set and the first pore morphology feature set, materials with the first pore size or similar first pore morphology are classified into the same category, and regions on the materials correspondingly occupied by the same category are classified into partitions. The selectable characterization mode of the first partition result is as follows: and recording the data as a first partition, a second partition, a third partition and an Nth partition. And the Nth partition means that the first material is completely partitioned.
Furthermore, the first pore size characteristic set and the first pore morphology characteristic set are compared in the first partition result, and characteristic information which accords with the first partition result is added to obtain the first partition characteristic information, wherein the first partition characteristic information comprises characteristic information corresponding to the first partition, characteristic information corresponding to the second partition and characteristic information corresponding to the Nth partition.
Further, taking the determination of the water absorption coefficient of the first partition as an example, the determination of the water absorption coefficient of the second partition to the water absorption coefficient of the Nth partition is performed in the same manner as the determination of the water absorption coefficient of the first partition: through multiple sets of water absorption information in the history data in the process of passing through the first material, the following steps are used alternatively: the method comprises the steps of historical water yield, water consumption, purified water consumption = water absorption and time node information of a water purification device, constructing a function curve, wherein time nodes and function curves corresponding to different partitions are different, obtaining a function curve corresponding to a first partition according to the time nodes of the function curve, collecting multiple groups of water quantity information and time node information in the same mode to obtain a function curve corresponding to the first partition, and obtaining a data relation between a first material and the water absorption according to the function curve, namely the water absorption coefficient of the first partition. Furthermore, the first water absorption coefficient refers to a set of water absorption coefficients corresponding to all the zones in the first zone result. And (3) carrying out water absorption analysis on the first material subarea to obtain a water absorption coefficient set with higher individuation degree.
Further, based on the coefficient measured and calculated according to the outlet flow of the first pump station, the outlet flow of the first pump station is calculated, and the step S700 includes:
s710: obtaining a first water quantity according to the first water supply object;
s720: according to the intelligent management system of the first pump station, obtaining first working time, wherein the first working time and the first water consumption have a one-to-one correspondence relationship;
specifically, taking one of a plurality of water supply objects in the first water supply object as an example, calculating the water output of the pump station, wherein the first water amount refers to the water consumption corresponding to the first water supply object, preferably the maximum daily water consumption between seven days, and optionally adjusting the first water amount in real time with seven days as a period; the first working duration refers to the sum of time consumed in each working link in the process of providing the first water supply object with the first water amount from the intelligent management system of the first pump station. One water supply object corresponds to one working time length, the working time length and the working time length form a group of numerical values in a one-to-one correspondence mode, and the numerical values can be stored in a list mode optionally. The water consumption of the water supply object in a set period is monitored and updated in real time, so that an information basis can be provided for regulating and controlling the accurate pump station water yield.
S730: determining a first pump station water outlet flow measurement formula according to the first pump station water outlet flow measurement coefficient:
Figure GDA0003758820220000161
q: the water outlet flow of the first pump station; k: measuring and calculating a coefficient of the water outlet flow of the first pump station; q 1 : a first amount of water; t: a first operating time period.
S740: and inputting various data according to the measuring and calculating formula of the water outlet flow of the first pump station, and calculating the water outlet flow of the first pump station.
Further, as shown in fig. 3, the method step S800 further includes:
s810: obtaining first damage information according to the second material surface image information;
s820: obtaining first damage degree information according to the first damage information;
s830: obtaining a first damage degree threshold;
s840: determining whether the first damage level is within the first damage level threshold;
s850: marking the first damage information of which the first damage degree is within the first damage degree threshold value to obtain first marking information;
s860: obtaining a first correction coefficient according to the first mark information;
s870: and correcting the outlet water flow measuring and calculating coefficient of the first pump station according to the first correction coefficient to obtain an outlet water flow measuring and calculating coefficient of a second pump station.
Specifically, the first damage information refers to a conveying position where damage is present in the first conveying manner, which is determined after the evaluation of the second material surface image information; the first damage degree information refers to the damage degree of the damaged conveying position, and the length and the width of a crack and the abrasion thickness of a material can be used for representing optionally; the first breakage threshold refers to a preset maximum breakage that the second material can withstand, such as a maximum value that the length and width of a crack can withstand. Further, comparing all the collected first damage degree information with the first damage degree threshold, marking damage positions of which the first damage degree information is greater than or equal to the first damage degree threshold, namely damage positions of which the first damage degree is within the first damage degree threshold, optionally evaluating the water loss amount of the first damage degree information corresponding to the damage positions according to historical data, and storing the first damage degree information and the water loss amount into the first marking information. Furthermore, the first correction coefficient refers to that the partition water absorption coefficient corresponding to the partition is modified according to the water loss amount of the first damage degree information corresponding to the damage position in the first mark information, which obtains the partition information corresponding to the damage position of the second material. And further, obtaining a new outlet water flow measurement coefficient, namely the outlet water flow measurement coefficient of the second pump station. Because in the conveying process, the conveying pipeline can be damaged inevitably, the first mark information representation is used according to the water resource loss condition caused by the damage factor, the water absorption coefficient of the corresponding partition is corrected, the water outlet flow measuring and calculating coefficient of the second pump station with stronger adaptability is obtained, and the water outlet flow of the pump station with higher individuation degree can be measured and calculated.
To sum up, the pump station water outlet flow intelligent measuring and calculating method and system provided by the embodiment of the application have the following technical effects:
1. the first water supply object is obtained; obtaining a first water resource category according to the intelligent service system of the first pump station; determining first water purification equipment and a first conveying mode according to the first water resource category; obtaining a first purified water supply loss estimation value according to the first water purification equipment; obtaining a first estimated value of the loss of the water supply for conveying according to the first conveying mode; inputting the first purified water supply loss estimation value and the first conveying water supply loss estimation value into a first outlet water flow measurement and calculation coefficient determination model to obtain a first pump station outlet water flow measurement and calculation coefficient; according to the technical scheme, the water outlet flow of the first pump station is obtained through calculation according to the water outlet flow measuring and calculating coefficient of the first pump station, the technical effects of matching a conveying mode and a water purifying device according to the water resource type, respectively determining the water consumption degree obtained according to the actual condition of the pump station in the water purifying process and the conveying process, determining a water outlet measuring and calculating coefficient through intelligent model analysis according to the water consumption degree of the two steps, finally determining reasonable real-time pump station water outlet according to the water supply object user quantity and the water using time and combining the water outlet measuring and calculating coefficient, and obtaining the individual pump station water outlet with higher degree in the measuring and calculating mode are achieved.
2. And (3) carrying out water absorption analysis on the first material subarea to obtain a water absorption coefficient set with higher individuation degree.
3. Because in the conveying process, the conveying pipeline can be damaged inevitably, the first mark information representation is used according to the water resource loss condition caused by the damage factor, the water absorption coefficient of the corresponding partition is corrected, the water outlet flow measuring and calculating coefficient of the second pump station with stronger adaptability is obtained, and the water outlet flow of the pump station with higher individuation degree can be measured and calculated.
Example two
Based on the same inventive concept as the pump station water outlet flow intelligent measuring and calculating method in the foregoing embodiment, as shown in fig. 4, the embodiment of the present application provides an intelligent measuring and calculating system for the pump station water outlet flow, wherein the system includes:
a first obtaining unit 11, the first obtaining unit 11 being configured to obtain a first water supply target;
the second obtaining unit 12 is configured to obtain a first water resource category according to the intelligent service system of the first pump station, where the second obtaining unit 12 is configured to obtain a second water resource category according to the first pump station intelligent service system;
a first determination unit 13, wherein the first determination unit 13 is used for determining a first water purification unit and a first conveying mode according to the first water resource type and the first water supply object;
a third obtaining unit 14, wherein the third obtaining unit 14 is configured to obtain a first purified water supply loss estimation value according to the first water purification device;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain a first estimated value of the water supply loss for the transportation according to the first transportation mode;
a fifth obtaining unit 16, where the fifth obtaining unit 16 is configured to input the first purified water supply loss estimation value and the first transport water supply loss estimation value into a first outlet flow measurement coefficient determination model, so as to obtain a first pump station outlet flow measurement coefficient;
and the first calculating unit 17 is used for calculating the water outlet flow of the first pump station according to the water outlet flow measuring and calculating coefficient of the first pump station.
Further, the system comprises:
a first input unit for inputting the first purified water supply loss estimate and the first delivery water supply loss estimate into a first effluent flow measurement coefficient determination model;
a first training unit for obtaining the first effluent flow measurement coefficient determination model from a plurality of sets of training data, the plurality of sets of data comprising: the first purified water supply loss historical data, the first conveying water supply loss historical data and identification information for identifying the first pump station water outlet flow measurement and calculation coefficient.
And the first output unit is used for obtaining a first output result, and the first output result comprises a water outlet flow measurement and calculation coefficient of the first pump station.
Further, the system comprises:
a sixth obtaining unit, configured to obtain, according to the first water purification apparatus, first water purification level information and first water purification time length information;
a seventh obtaining unit for obtaining first material information according to the first water purification level information;
a second determination unit configured to determine a first water absorption coefficient and first volume information based on the first material information;
an eighth obtaining unit, configured to obtain a first preset operation rule;
and the third determining unit is used for determining the first purified water supply loss estimation value according to the second preset operation rule through the first water absorption coefficient, the first purified water time length information and the first volume information.
Further, the system comprises:
a ninth obtaining unit configured to obtain second material information and first conveyance time length information according to the first conveyance manner;
a fourth determination unit configured to determine a second water absorption coefficient and first conveyance length information based on the second material information;
a tenth obtaining unit, configured to obtain a second preset operation rule;
and the fifth determining unit is used for determining the first conveying water supply loss estimation value according to the second preset operation rule and through the second water absorption coefficient, the first conveying time length information and the first conveying length information.
Further, the system comprises:
an eleventh obtaining unit, configured to obtain the first material surface image information according to a first image acquisition device;
a twelfth obtaining unit, configured to perform convolution feature extraction on the first material surface image information to obtain first feature information, where the first feature information includes a first pore size feature set and a first pore morphology feature set;
a thirteenth obtaining unit, configured to input the first pore size feature set and the first pore morphology feature set into a first clustering model, and obtain a first segmentation result;
a fourteenth obtaining unit, configured to traverse the first pore size feature set and the first pore morphology feature set in the first segmentation result, so as to obtain first segmentation feature information;
a fifteenth obtaining unit, configured to obtain a first partition water absorption coefficient according to the first partition characteristic information;
the first acquisition unit is used for acquiring the water absorption coefficients of all the partitions to form a water absorption coefficient set;
a first setting unit configured to set the water absorption coefficient as the first water absorption coefficient.
Further, the system comprises:
a sixteenth obtaining unit configured to obtain a first amount of water according to the first water supply target;
a seventeenth obtaining unit, configured to obtain a first working duration according to the intelligent management system of the first pump station, where the first working duration and the first water usage amount have a one-to-one correspondence relationship;
a sixth determining unit, configured to determine a first pump station water outflow measurement formula according to the first pump station water outflow measurement coefficient:
Figure GDA0003758820220000221
q: the water outlet flow of the first pump station; k: measuring and calculating the coefficient of the water outlet flow of the first pump station; q 1 : a first amount of water; t: a first operating time period.
And the second calculation unit is used for inputting various data according to the first pump station water outlet flow measurement and calculation formula and calculating the water outlet flow of the first pump station.
Further, the system further comprises:
an eighteenth obtaining unit, configured to obtain first damage information according to the second material surface image information;
a nineteenth obtaining unit configured to obtain first breakage degree information based on the first breakage information;
a twentieth obtaining unit for obtaining a first breakage degree threshold value;
a first judging unit, configured to judge whether the first damage degree is within the first damage degree threshold;
a twenty-first obtaining unit, configured to mark the first damage information of which the first damage degree is within the first damage degree threshold value, and obtain first mark information;
a twenty-second obtaining unit configured to obtain a first correction coefficient according to the first flag information;
and the twenty-third obtaining unit is used for correcting the water outlet flow measuring and calculating coefficient of the first pump station according to the first correction coefficient to obtain a water outlet flow measuring and calculating coefficient of the second pump station.
Exemplary embodiments of the inventionElectronic device
The electronic device of the embodiment of the present application is described below with reference to fig. 5:
based on the same inventive concept as the pump station water outlet flow intelligent measuring and calculating method in the foregoing embodiment, the embodiment of the present application further provides a pump station water outlet flow intelligent measuring and calculating system, which includes: a processor coupled to a memory, the memory for storing a program that, when executed by the processor, causes a system to perform the method of any of the first aspects.
The electronic device 300 includes: processor 302, communication interface 303, memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. Wherein, the communication interface 303, the processor 302 and the memory 301 may be connected to each other through a bus architecture 304; the bus architecture 304 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.
Processor 302 may be a CPU, microprocessor, ASIC, or one or more integrated circuits configured to control the execution of the programs of the present application.
The communication interface 303 may be any device, such as a transceiver, for communicating with other devices or communication networks, such as an ethernet, a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a wired access network, and the like.
The memory 301 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an electrically erasable Programmable read-only memory (EEPROM), a compact-read-only-memory (CD-ROM) or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor through a bus architecture 304. The memory may also be integral to the processor.
The memory 301 is used for storing computer-executable instructions for executing the present application, and is controlled by the processor 302 to execute. The processor 302 is configured to execute a computer execution instruction stored in the memory 301, so as to implement the intelligent measuring and calculating method for the outlet water flow of the pumping station provided in the above embodiment of the present application.
Optionally, the computer-executable instructions in this embodiment may also be referred to as application program codes, which is not specifically limited in this embodiment.
The embodiment of the application provides an intelligent measuring and calculating method for outlet water flow of a pump station, wherein the method is applied to an intelligent management system of the pump station, and the method comprises the following steps: obtaining a first water supply object; obtaining a first water resource category according to the intelligent service system of the first pump station; determining a first water purifying device and a first conveying mode according to the first water resource type and the first water supply object; obtaining a first purified water supply loss estimation value according to the first water purification equipment; obtaining a first conveying water supply loss estimation value according to the first conveying mode; inputting the first purified water supply loss estimated value and the first conveying water supply loss estimated value into a first outlet water flow measuring and calculating coefficient determining model to obtain a first pump station outlet water flow measuring and calculating coefficient; and calculating to obtain the water outlet flow of the first pump station according to the water outlet flow measuring and calculating coefficient of the first pump station. The technical effects of the measuring and calculating mode of the pump station water yield with higher individuation degree are achieved by matching the conveying mode and the water purifying equipment according to the water resource category, respectively determining the water consumption degree obtained according to the actual condition of the pump station in the water purifying process and the conveying process, determining the water yield measuring and calculating coefficient through the intelligent model analysis according to the water consumption degree of the two steps, and finally determining the reasonable real-time pump station water yield according to the water yield measuring and calculating coefficient.
Those of ordinary skill in the art will understand that: the various numbers of the first, second, etc. mentioned in this application are only used for the convenience of description and are not used to limit the scope of the embodiments of this application, nor to indicate the order of precedence. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any," or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one (one ) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions described in accordance with the embodiments of the application are all or partially generated when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), among others.
The various illustrative logical units and circuits described in this application may be implemented or operated upon by design of a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in the embodiments herein may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software cells may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be disposed in a terminal. In the alternative, the processor and the storage medium may reside in different components within the terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary of the present application as defined in the appended claims and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations.

Claims (7)

1. An intelligent measuring and calculating method for outlet water flow of a pump station is applied to an intelligent management system of a first pump station, and comprises the following steps:
obtaining a first water supply object;
obtaining a first water resource category according to the first pump station intelligent management system;
determining a first water purifying device and a first conveying mode according to the first water resource category and the first water supply object;
obtaining a first purified water supply loss estimation value according to the first water purification equipment;
obtaining a first estimated value of the loss of the water supply for conveying according to the first conveying mode;
inputting the first purified water supply loss estimation value and the first conveying water supply loss estimation value into a first outlet water flow measurement and calculation coefficient determination model to obtain a first pump station outlet water flow measurement and calculation coefficient;
calculating according to the water outlet flow measuring and calculating coefficient of the first pump station to obtain the water outlet flow of the first pump station;
wherein, according to the first purification water supply loss estimation value and the first transmission water supply loss estimation value, obtaining a first pump station water flow measurement and calculation coefficient, including:
inputting said first purified water supply loss estimate and said first delivered water supply loss estimate into a first outlet flow measurement coefficient determination model;
the first effluent flow measurement coefficient determination model is obtained from a plurality of sets of training data, the plurality of sets of training data comprising: the first pump station water supply loss historical data, the first conveying water supply loss historical data and identification information for identifying the first pump station water outlet flow measurement coefficient;
obtaining a first output result, wherein the first output result comprises a water outlet flow measurement and calculation coefficient of the first pump station;
wherein, according to the first pump station effluent flow measurement and calculation coefficient, calculating to obtain the first pump station effluent flow, including:
obtaining a first water quantity according to the first water supply object;
according to the intelligent management system of the first pump station, obtaining a first working time length, wherein the first working time length and the first water consumption have a one-to-one correspondence relationship;
determining a first pump station water outlet flow measurement formula according to the first pump station water outlet flow measurement coefficient:
Figure FDA0003771780110000021
q: the water outlet flow of the first pump station; k: measuring and calculating the coefficient of the water outlet flow of the first pump station; q 1 : a first amount of water; t: a first operating time period;
and inputting various data according to the measuring and calculating formula of the water outlet flow of the first pump station, and calculating the water outlet flow of the first pump station.
2. The method of claim 1, wherein said obtaining a first purified water supply loss estimate based on said first water purification plant comprises:
according to the first water purification equipment, first water purification level information and first water purification duration information are obtained;
obtaining first material information according to the first water purification level information;
determining a first water absorption coefficient and first volume information according to the first material information;
obtaining a first preset operation rule;
and determining the first purified water supply loss estimation value according to the first preset operation rule through the first water absorption coefficient, the first purified water duration information and the first volume information.
3. The method of claim 1, wherein said obtaining a first delivery supply water loss estimate based on said first delivery mode comprises:
according to the first conveying mode, second material information and first conveying time length information are obtained;
determining a second water absorption coefficient and first conveying length information according to the second material information;
obtaining a second preset operation rule;
and determining the estimated value of the first conveying water supply loss according to the second preset operation rule and through the second water absorption coefficient, the first conveying time length information and the first conveying length information.
4. The method of claim 2, wherein said determining a first water absorption coefficient based on said first material information comprises:
acquiring surface image information of a first material according to a first image acquisition device;
performing convolution feature extraction on the first material surface image information to obtain first feature information, wherein the first feature information comprises a first pore size feature set and a first pore morphology feature set;
inputting the first pore size characteristic set and the first pore morphology characteristic set into a first clustering model to obtain a first partition result;
traversing the first pore size characteristic set and the first pore morphology characteristic set in the first partition result to obtain first partition characteristic information;
acquiring a first subarea water absorption coefficient according to the first subarea characteristic information;
collecting the water absorption coefficients of all the subareas to form a water absorption coefficient set;
and taking the water absorption coefficient as the first water absorption coefficient.
5. The method of claim 4, wherein the method further comprises:
obtaining first damage information according to the first material surface image information;
obtaining first damage degree information according to the first damage information;
obtaining a first damage degree threshold;
determining whether the first damage level is within the first damage level threshold;
marking the first damage information of which the first damage degree is within the first damage degree threshold value to obtain first marking information;
obtaining a first correction coefficient according to the first mark information;
and correcting the outlet water flow measuring and calculating coefficient of the first pump station according to the first correction coefficient to obtain an outlet water flow measuring and calculating coefficient of the second pump station.
6. The utility model provides a pump station effluent discharge intelligent measurement and calculation system, wherein, the system includes:
a first obtaining unit for obtaining a first water supply target;
the second obtaining unit is used for obtaining a first water resource category according to the intelligent management system of the first pump station;
the first determining unit is used for determining a first water purifying device and a first conveying mode according to the first water resource type and the first water supply object;
a third obtaining unit, configured to obtain a first purified water supply loss estimation value according to the first water purification device;
a fourth obtaining unit, configured to obtain a first estimated value of water supply loss for transportation according to the first transportation mode;
a fifth obtaining unit, configured to input the first purified water supply loss estimate and the first transport water supply loss estimate to a first outlet flow measurement coefficient determination model, and obtain an outlet flow measurement coefficient of a first pump station;
the first calculating unit is used for calculating the water outlet flow of the first pump station according to the water outlet flow measuring and calculating coefficient of the first pump station;
a first input unit for inputting the first purified water supply loss estimate and the first delivery water supply loss estimate into a first effluent flow measurement coefficient determination model;
a first training unit, wherein the first training unit is used for obtaining the first effluent flow measurement coefficient determination model by multiple sets of training data, and the multiple sets of training data comprise: the first pump station water supply loss historical data, the first conveying water supply loss historical data and identification information for identifying the first pump station water outlet flow measurement coefficient;
the first output unit is used for obtaining a first output result, and the first output result comprises a water outlet flow measurement and calculation coefficient of the first pump station;
a sixteenth obtaining unit configured to obtain a first amount of water according to the first water supply target;
a seventeenth obtaining unit, configured to obtain a first working duration according to the intelligent management system of the first pump station, where the first working duration and the first water usage amount have a one-to-one correspondence relationship;
a sixth determining unit, configured to determine a first pump station water outflow measurement formula according to the first pump station water outflow measurement coefficient:
Figure FDA0003771780110000061
q: the water outlet flow of the first pump station; k: measuring and calculating a coefficient of the water outlet flow of the first pump station; q 1 : a first amount of water; t: a first operating time period;
and the second calculation unit is used for inputting various data according to the measuring and calculating formula of the water outlet flow of the first pump station and calculating the water outlet flow of the first pump station.
7. The utility model provides a pump station effluent discharge intelligent measurement and calculation system, includes: a processor coupled with a memory for storing a program that, when executed by the processor, causes a system to perform the method of any of claims 1 to 5.
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CN117130280B (en) * 2023-09-25 2024-03-15 南栖仙策(南京)高新技术有限公司 Pump room control method and device, electronic equipment and storage medium
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Family Cites Families (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FI118486B (en) * 2004-03-16 2007-11-30 Abb Oy A method for controlling a pump station and an inverter for powering the pump station
JP4799168B2 (en) * 2005-12-21 2011-10-26 株式会社東芝 Water distribution and pipeline information analysis system
US7606636B2 (en) * 2007-01-31 2009-10-20 Halliburton Energy Services, Inc. Methods for managing flow control valves in process systems
JP2010037803A (en) * 2008-08-05 2010-02-18 Sayama Seisakusho:Kk Pump direct water supply system and pump direct water supply method
CN102033969B (en) * 2009-09-29 2013-01-30 Sgi工程有限公司 Water supply network management system and method
JP5932466B2 (en) * 2012-04-27 2016-06-08 株式会社日立製作所 Water distribution operation control device
CN102930480B (en) * 2012-11-19 2015-07-15 国家电网公司 System and method for comprehensive energy efficiency evaluation of hydraulic power plant
CN203930457U (en) * 2014-02-19 2014-11-05 中国能源建设集团广东省电力设计研究院 Power plant water total digitalization monitoring system and self-equilibrating water utilities system
CN103899599B (en) * 2014-04-24 2016-04-27 徐州重型机械有限公司 A kind of controlling method of instant flow matches, system and hoist
CN104533806B (en) * 2014-11-04 2016-09-28 合肥工业大学 A kind of high-power photovoltaic water pump system team control water yield maximizes control algolithm
CN106094903B (en) * 2016-08-26 2023-11-03 魏斯瓦瑟环境技术（嘉兴）有限公司 Water purifier water outlet flow control system
CN106503313B (en) * 2016-10-10 2019-11-12 济南大学 Series-parallel cascade pumping station water-carriage system operational efficiency calculation method and system
CN109345044A (en) * 2018-11-27 2019-02-15 广东工业大学 A kind of Optimal Operation of Pumping Stations method based on variable length Gene hepatitis B vaccine
CN109657327B (en) * 2018-12-13 2019-10-29 扬州大学 The evaluation method of pump installation outlet passage comprehensive performance

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