CN117309106B - Intelligent deviation rectifying method for water flow measurement data - Google Patents
Intelligent deviation rectifying method for water flow measurement data Download PDFInfo
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- CN117309106B CN117309106B CN202311291384.2A CN202311291384A CN117309106B CN 117309106 B CN117309106 B CN 117309106B CN 202311291384 A CN202311291384 A CN 202311291384A CN 117309106 B CN117309106 B CN 117309106B
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 532
- 238000005259 measurement Methods 0.000 title claims abstract description 148
- 238000000034 method Methods 0.000 title claims abstract description 47
- 238000004140 cleaning Methods 0.000 claims abstract description 307
- 239000003651 drinking water Substances 0.000 claims abstract description 146
- 235000020188 drinking water Nutrition 0.000 claims abstract description 140
- 238000007781 pre-processing Methods 0.000 claims abstract description 36
- 238000012937 correction Methods 0.000 claims abstract description 24
- 239000012530 fluid Substances 0.000 claims abstract description 17
- 230000008859 change Effects 0.000 claims abstract description 15
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- 238000010438 heat treatment Methods 0.000 claims description 70
- 230000002159 abnormal effect Effects 0.000 claims description 17
- 238000012360 testing method Methods 0.000 claims description 16
- 239000003814 drug Substances 0.000 claims description 13
- 238000011010 flushing procedure Methods 0.000 claims description 13
- 241000894006 Bacteria Species 0.000 claims description 12
- 244000005700 microbiome Species 0.000 claims description 12
- 238000001514 detection method Methods 0.000 claims description 11
- 239000000645 desinfectant Substances 0.000 claims description 9
- 230000008569 process Effects 0.000 claims description 9
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims description 8
- 239000007788 liquid Substances 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000004891 communication Methods 0.000 claims description 6
- 238000001223 reverse osmosis Methods 0.000 claims description 5
- 239000000126 substance Substances 0.000 claims description 5
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- 238000013450 outlier detection Methods 0.000 description 3
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 2
- 229910052799 carbon Inorganic materials 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 239000013618 particulate matter Substances 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- ZAMOUSCENKQFHK-UHFFFAOYSA-N Chlorine atom Chemical compound [Cl] ZAMOUSCENKQFHK-UHFFFAOYSA-N 0.000 description 1
- 241000588724 Escherichia coli Species 0.000 description 1
- 241000607142 Salmonella Species 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 229910052801 chlorine Inorganic materials 0.000 description 1
- 239000000460 chlorine Substances 0.000 description 1
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- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 229910052742 iron Inorganic materials 0.000 description 1
- WPBNNNQJVZRUHP-UHFFFAOYSA-L manganese(2+);methyl n-[[2-(methoxycarbonylcarbamothioylamino)phenyl]carbamothioyl]carbamate;n-[2-(sulfidocarbothioylamino)ethyl]carbamodithioate Chemical compound [Mn+2].[S-]C(=S)NCCNC([S-])=S.COC(=O)NC(=S)NC1=CC=CC=C1NC(=S)NC(=O)OC WPBNNNQJVZRUHP-UHFFFAOYSA-L 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F25/00—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume
- G01F25/10—Testing or calibration of apparatus for measuring volume, volume flow or liquid level or for metering by volume of flowmeters
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/10—Pre-processing; Data cleansing
- G06F18/15—Statistical pre-processing, e.g. techniques for normalisation or restoring missing data
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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
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/152—Water filtration
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- Bioinformatics & Computational Biology (AREA)
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Abstract
The invention relates to the technical field of data processing, and provides an intelligent deviation rectifying method for water flow measurement data, which comprises the following steps: acquiring water flow measurement data from a direct-drinking water fluid meter; setting a self-cleaning period of direct drinking water; preprocessing to obtain water flow measurement preprocessing data; primary correction data are obtained through primary correction; obtaining the replacement period of the direct drinking water filter element, and M sections of primary correction segmentation data; acquiring a cold and hot water flow data set; the cold and hot water flow data set is used as secondary deviation rectifying information, secondary deviation rectifying data are obtained through secondary correction, a water flow automatic deviation rectifying model is built, automatic deviation rectifying of water flow measurement data is achieved, the technical problem that accuracy of directly measured water flow measurement data is limited is solved, interference of various factors such as flow speed fluctuation and water temperature change is eliminated, accuracy of water flow measurement is improved, automatic analysis and processing of measurement data of the water flow automatic deviation rectifying model are built, and efficiency and operation convenience are improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an intelligent deviation rectifying method for water flow measurement data.
Background
Water flow measurement is a very important task in the fields of water resource management, industrial process control, environmental monitoring and the like, however, due to flow speed fluctuation, water temperature change and the like, flow speed fluctuation, namely the flow speed of water flow in a pipeline, may be unstable, so that certain deviation and fluctuation of measured data may exist, and flow speed fluctuation, namely the flow speed of water flow in the pipeline, may be unstable, so that the measured data may fluctuate; tube water temperature variations can lead to non-uniformity in flow rate, resulting in deviations in measured data.
In summary, the prior art has the technical problem that the accuracy of directly measured water flow measurement data is limited.
Disclosure of Invention
The application aims to solve the technical problem that the accuracy of directly measured water flow measurement data in the prior art is limited by providing an intelligent deviation rectifying method for water flow measurement data.
In view of the above problems, the present application provides an intelligent deviation rectifying method for water flow measurement data.
According to a first aspect of the disclosure, an intelligent deviation rectifying method for water flow measurement data is provided, wherein the intelligent deviation rectifying method for water flow measurement data is applied to an intelligent deviation rectifying system for water flow measurement data, and the intelligent deviation rectifying system for water flow measurement data is in communication connection with a direct drinking water fluid meter, and the method comprises: acquiring water flow measurement data from the direct drinking water fluid meter, wherein the water flow measurement data comprises water inflow measurement data and water outflow measurement data; setting a self-cleaning period of direct drinking water, wherein in the self-cleaning period of the direct drinking water, the direct drinking water equipment performs automatic back flushing cleaning, and the self-cleaning period of the direct drinking water also comprises self-cleaning unit time length and self-cleaning unit water consumption, wherein the self-cleaning unit water consumption is used for representing the self-cleaning water consumption in unit time; performing data preprocessing on the water flow measurement data to obtain water flow measurement preprocessing data, wherein the data preprocessing comprises data cleaning and abnormal value detection, the data cleaning is used for removing noise, invalid or wrong data points, and the abnormal value detection can identify and process abnormal measurement data possibly existing; taking a water yield measurement data set corresponding to the self-cleaning period of the direct drinking water equipment as primary deviation rectifying information, and rectifying the water flow measurement pretreatment data to obtain primary deviation rectifying data; obtaining a direct drinking water filter element replacement period, segmenting the primary correction data through the direct drinking water filter element replacement period to obtain M segments of primary correction segmentation data, wherein M is more than or equal to N is more than or equal to 1, and N is the number of filter elements of the direct drinking water equipment; comparing the heating work log of the direct drinking water equipment to obtain a cold and hot water flow data set, wherein the cold and hot water flow data set comprises a cold water flow data set and a hot water flow data set; the cold and hot water flow data set is used as secondary deviation rectifying information, and the primary deviation rectifying data is rectified to obtain secondary deviation rectifying data; and constructing an automatic water flow deviation rectifying model based on the water flow measurement preprocessing data, the primary deviation rectifying data and the secondary deviation rectifying data, so as to realize automatic deviation rectifying of the water flow measurement data.
In another aspect of the present disclosure, an intelligent deviation rectifying system for water flow measurement data is provided, wherein the system comprises: the data acquisition module is used for acquiring water flow measurement data from the direct drinking water fluid meter, wherein the water flow measurement data comprise water inflow measurement data and water outflow measurement data; the automatic back-flushing cleaning module is used for setting a direct drinking water self-cleaning period, and in the direct drinking water self-cleaning period, the direct drinking water equipment carries out automatic back-flushing cleaning, and the direct drinking water self-cleaning period also comprises self-cleaning unit time length and self-cleaning unit water consumption, wherein the self-cleaning unit water consumption is used for representing the self-cleaning water consumption in unit time; the data preprocessing module is used for carrying out data preprocessing on the water flow measurement data to obtain water flow measurement preprocessing data, the data preprocessing comprises data cleaning and abnormal value detection, the data cleaning is used for removing data points with noise, invalidity or errors, and the abnormal value detection can identify and process abnormal measurement data possibly existing; the primary deviation rectifying module is used for taking a water yield measurement data set corresponding to the self-cleaning period of the direct drinking water equipment as primary deviation rectifying information, and rectifying the water flow measurement pretreatment data to obtain primary deviation rectifying data; the data segmentation module is used for obtaining a direct drinking water filter element replacement period, segmenting the primary deviation correction data through the direct drinking water filter element replacement period to obtain M segments of primary deviation correction segmented data, wherein M is more than or equal to N and more than or equal to 1, and N is the number of filter elements of the direct drinking water equipment; the cold and hot water flow data set acquisition module is used for acquiring a cold and hot water flow data set by comparing with a heating work log of the direct drinking water equipment, wherein the cold and hot water flow data set comprises a cold water flow data set and a hot water flow data set; the secondary deviation rectifying module is used for taking the cold and hot water flow data set as secondary deviation rectifying information, rectifying the primary deviation rectifying data and obtaining secondary deviation rectifying data; the automatic deviation measuring and correcting module is used for constructing an automatic deviation correcting model of the water flow based on the water flow measurement preprocessing data, the primary deviation correcting data and the secondary deviation correcting data, and realizing automatic deviation correction of the water flow measurement data.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
due to the adoption of the method, water flow measurement data are acquired from the direct drinking water fluid meter; setting a self-cleaning period of direct drinking water; carrying out data preprocessing on the water flow measurement data to obtain water flow measurement preprocessing data; correcting the water flow measurement pretreatment data to obtain primary correction data; obtaining the replacement period of the direct drinking water filter element, and M sections of primary correction segmentation data; acquiring a cold and hot water flow data set; and the cold and hot water flow data set is used as secondary deviation rectifying information, the primary deviation rectifying data is rectified to obtain secondary deviation rectifying data, a water flow automatic deviation rectifying model is built, automatic deviation rectifying of water flow measurement data is realized, interference of various factors such as flow speed fluctuation and water temperature change is eliminated, accuracy of water flow measurement is improved, automatic analysis and measurement data processing of the water flow automatic deviation rectifying model are built, and technical effects of efficiency and operation convenience are improved.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
Fig. 1 is a schematic flow chart of a possible intelligent deviation rectifying method for water flow measurement data according to an embodiment of the present application;
fig. 2 is a schematic flow chart of a possible process of setting a self-cleaning period of direct drinking water in an intelligent deviation rectifying method of water flow measurement data according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a possible flow chart of calculating a hot water flow data set in an intelligent deviation rectifying method of water flow measurement data according to an embodiment of the present application;
fig. 4 is a schematic diagram of a possible structure of an intelligent deviation rectifying system for water flow measurement data according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a data acquisition module 100, an automatic back flushing cleaning module 200, a data preprocessing module 300, a primary deviation rectifying module 400, a data segmentation module 500, a cold and hot water flow data set acquisition module 600, a secondary deviation rectifying module 700 and a measurement automatic deviation rectifying module 800.
Detailed Description
The embodiment of the application provides an intelligent deviation rectifying method for water flow measurement data, which solves the technical problem that the accuracy of directly measured water flow measurement data is limited, realizes the elimination of the interference of various factors such as flow velocity fluctuation and water temperature change, improves the accuracy of water flow measurement, constructs an automatic deviation rectifying model for water flow, automatically analyzes and processes measurement data, and improves the technical effects of efficiency and operation convenience.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Example 1
As shown in fig. 1, an embodiment of the present application provides an intelligent deviation rectifying method for water flow measurement data, where the intelligent deviation rectifying method for water flow measurement data is applied to an intelligent deviation rectifying system for water flow measurement data, and the intelligent deviation rectifying system for water flow measurement data is communicatively connected with a direct drinking water fluid meter, and the method includes:
s10: acquiring water flow measurement data from the direct drinking water fluid meter, wherein the water flow measurement data comprises water inflow measurement data and water outflow measurement data;
s20: setting a self-cleaning period of direct drinking water, wherein in the self-cleaning period of the direct drinking water, the direct drinking water equipment performs automatic back flushing cleaning, and the self-cleaning period of the direct drinking water also comprises self-cleaning unit time length and self-cleaning unit water consumption, wherein the self-cleaning unit water consumption is used for representing the self-cleaning water consumption in unit time;
as shown in fig. 2, step S20 includes the steps of:
s21: acquiring equipment type information of the direct drinking water equipment, wherein the equipment type information can be an activated carbon filter element and/or a reverse osmosis water purifier and/or an ultraviolet sterilizer;
S22: acquiring water quality information of a water source, wherein the water quality information of the water source comprises suspended matters, particulate matters, soluble matters, microorganisms, bacteria, pH values and medicine residues;
s23: and setting the self-cleaning period of the direct drinking water based on the water quality information of the water source and the equipment type information.
Specifically, the intelligent deviation correcting system of the water flow measurement data is in communication connection with the direct-drinking water fluid meter, the communication connection is simply through signal transmission interaction, a communication network is formed between the intelligent deviation correcting system of the water flow measurement data and the direct-drinking water fluid meter, and support is provided for water flow deviation correction;
acquiring water flow measurement data from a direct-drinking water fluid meter, wherein the water flow measurement data comprises water inflow measurement data and water outflow measurement data, the water flow measurement data can be acquired by communication connection with the direct-drinking water fluid meter, and a sensor is embedded in the direct-drinking water fluid meter, and can be a turbine flowmeter, an electromagnetic flowmeter and an ultrasonic flowmeter; setting a self-cleaning period of direct drinking water, wherein the self-cleaning period of direct drinking water is used for controlling the direct drinking water equipment to perform automatic back flushing cleaning;
Setting self-cleaning period of direct drinking water, wherein the self-cleaning period of direct drinking water comprises automatic back flushing cleaning of direct drinking water equipment, self-cleaning unit time length and self-cleaning unit water consumption, the self-cleaning unit water consumption is used for representing self-cleaning water consumption in unit time, the self-cleaning unit is often used for representing time required by one self-cleaning,
common equipment types comprise an active carbon filter element, a reverse osmosis water purifier and an ultraviolet sterilizer, wherein the active carbon filter element, the reverse osmosis water purifier and the ultraviolet sterilizer all have different working principles and cleaning requirements, and equipment type information and corresponding cleaning requirements of the direct drinking equipment are determined based on the use specification of the direct drinking equipment;
the suspended solids and the particulate matters are solid particulate matters such as sediment, dirt and the like which may exist in a water source; the soluble substances are chemical substances which can be dissolved in a water source, such as iron, manganese, chlorine and the like; microorganisms and bacteria that may be present in the water source, such as E.coli, salmonella, etc.; the pH value is the pH value of a water source and is generally expressed as the pH value of 0-14; the medicine residues are medicine or chemical substances possibly remained in the water source, so that water quality information of the water source is obtained; referring to the use instruction in the direct drinking water equipment, the direct drinking water self-cleaning period is set based on the water quality information of the water source and the type information of the equipment, and the direct drinking water self-cleaning period is set from the angles of the equipment type and the water source, so that the set direct drinking water self-cleaning period is suitable for the current scene.
Step S23 includes the steps of:
s231: acquiring water quality information of an applicable environment water source defined in a use instruction in the direct drinking water equipment, wherein the water quality information of the applicable environment water source comprises an applicable range of suspended matters and particles, an applicable range of soluble substances, an applicable range of microorganisms and bacteria, an applicable range of pH values and an applicable range of medicine residues;
s232: comparing the water quality information of the water source of the applicable environment with the water quality information of the water source;
s233: if the water quality information of the water source meets the water quality information of the water source of the applicable environment, setting the self-cleaning period of the direct drinking water as an initial self-cleaning period, wherein the initial self-cleaning period is 24 h/time.
Specifically, setting the self-cleaning cycle of the direct drinking water based on the water quality information of the water source and the type information of the equipment, wherein the self-cleaning cycle comprises the steps of consulting a use instruction of the direct drinking water equipment, finding a limit on water quality information of an applicable environment water source provided by a manufacturer, and taking the limit on water quality information of the applicable environment water source provided by the manufacturer as the water quality information of the applicable environment water source, wherein the limit comprises a suspended matter and particulate matter applicable section, a soluble matter applicable section, a microorganism and bacteria applicable section, a pH value applicable section and a medicine residue applicable section; comparing the water quality information of the water source with the water quality information of the water source of the applicable environment in the instruction of the direct drinking water equipment, and judging whether the water quality of the water source meets an applicable interval specified by a manufacturer;
If suspended matters and particulate matters, soluble matters, microorganisms and bacteria, pH values and medicine residues in the water quality information of the water source all meet the applicable ranges of the suspended matters and the particulate matters, the soluble matters, the microorganisms and bacteria, the pH values and the medicine residues in the water quality information of the water source applicable to the environment, the direct drinking water self-cleaning period is set as an initial self-cleaning period, and the initial self-cleaning period is 24 h/time;
if any one of suspended matters and particles, soluble matters, microorganisms and bacteria, pH values and medicine residues in the water quality information of the water source does not meet the applicable range of the suspended matters and the particles, the applicable range of the soluble matters, the applicable range of the microorganisms and the bacteria, the applicable range of the pH values and the applicable range of the medicine residues in the water quality information of the water source, namely, the water quality of the water source is too bad, the consumption corresponding to the self-cleaning period is too large, the direct drinking water equipment is not recommended to be used, and the direct drinking water equipment can be replaced.
The embodiment of the application further comprises:
s234: acquiring self-cleaning mode information defined in a use specification of the direct drinking water equipment, wherein the self-cleaning mode information comprises high-efficiency self-cleaning mode information, medium-efficiency self-cleaning mode information and low-efficiency self-cleaning mode information;
S235-A: if the water quality information of the water source meets the water quality information of the water source of the applicable environment and meets the limitation of the low-efficiency self-cleaning mode information, acquiring low-efficiency self-cleaning duration and low-efficiency self-cleaning unit water consumption;
S235-B: if the water quality information of the water source meets the water quality information of the water source of the applicable environment and meets the limitation of the information of the medium-efficiency self-cleaning mode, acquiring medium-efficiency self-cleaning duration and medium-efficiency self-cleaning unit water consumption;
S235-C: if the water quality information of the water source meets the water quality information of the water source of the applicable environment and meets the limitation of the information of the high-efficiency self-cleaning mode, acquiring high-efficiency self-cleaning duration and high-efficiency self-cleaning unit water consumption;
s236: and determining the self-cleaning unit time length and the self-cleaning unit water consumption by the low-efficiency self-cleaning time length and the low-efficiency self-cleaning unit water consumption or the medium-efficiency self-cleaning time length and the medium-efficiency self-cleaning unit water consumption or the high-efficiency self-cleaning time length and the high-efficiency self-cleaning unit water consumption.
The embodiment of the application further comprises:
S237-A: setting a mode of cleaning only with water as a self-cleaning mode of the low-efficiency self-cleaning mode information;
S237-B: using a cleaning disinfectant, according to 1:40, obtaining a medium-efficiency cleaning solution, and setting a mode of using the medium-efficiency cleaning solution as a self-cleaning mode of the medium-efficiency self-cleaning mode information;
S237-C: using a cleaning disinfectant, according to 1:24, and setting a mode of using the efficient cleaning liquid as a self-cleaning mode of the efficient self-cleaning mode information.
Specifically, referring to a use specification of the direct drinking water equipment, acquiring self-cleaning mode information defined in the use specification of the direct drinking water equipment, wherein the self-cleaning mode information comprises high-efficiency self-cleaning mode information, medium-efficiency self-cleaning mode information and low-efficiency self-cleaning mode information;
if the water quality information of the water source meets the water quality information of the water source of the applicable environment and meets the limit of the information about the low-efficiency self-cleaning mode in the use instruction, acquiring low-efficiency self-cleaning duration and low-efficiency self-cleaning unit water consumption; if the water quality information of the water source meets the water quality information of the water source of the applicable environment and meets the limitation of the medium-efficiency self-cleaning mode information in the use specification, acquiring medium-efficiency self-cleaning duration and medium-efficiency self-cleaning unit water consumption; if the water quality information of the water source meets the water quality information of the water source of the applicable environment and meets the limit of the high-efficiency self-cleaning mode information in the use instruction, acquiring high-efficiency self-cleaning duration and high-efficiency self-cleaning unit water consumption;
Specifically, the low-efficiency self-cleaning mode is used for representing a mode of cleaning only by using water, and in the low-efficiency self-cleaning mode, the low-efficiency self-cleaning unit water consumption defaults to 500mL/min and the low-efficiency self-cleaning duration defaults to 3min, so that the method belongs to a general self-cleaning mode;
the medium-efficiency self-cleaning mode is used for characterization according to 1: the cleaning disinfectant diluted in the proportion of 40 is used as the medium-efficiency cleaning liquid, and in the medium-efficiency self-cleaning mode, the medium-efficiency cleaning liquid is relatively thick, the water consumption of the medium-efficiency self-cleaning unit is defaulted to 1000mL/min (1000 mL/min also comprises diluted cleaning disinfectant water), the medium-efficiency self-cleaning duration is defaulted to 4min, and the medium-efficiency self-cleaning mode belongs to a relatively thorough self-cleaning mode;
the efficient self-cleaning mode is used to characterize the usage according to 1: the cleaning disinfectant with the dilution ratio of 24 is used as the efficient cleaning liquid, and in the efficient self-cleaning mode, the efficient cleaning liquid is more concentrated than the medium-efficient cleaning liquid, the water consumption of the efficient self-cleaning unit defaults to 1500mL/min, and the time length of the efficient self-cleaning unit defaults to 6min, so that the efficient self-cleaning unit belongs to a more thorough self-cleaning mode;
meanwhile, the low-efficiency self-cleaning time length and the low-efficiency self-cleaning unit water consumption or the medium-efficiency self-cleaning time length and the medium-efficiency self-cleaning unit water consumption or the high-efficiency self-cleaning time length and the high-efficiency self-cleaning unit water consumption can be set by user definition, and the self-cleaning unit time length and the low-efficiency self-cleaning unit water consumption or the medium-efficiency self-cleaning time length and the medium-efficiency self-cleaning unit water consumption or the high-efficiency self-cleaning time length and the high-efficiency self-cleaning unit water consumption are determined;
The self-cleaning unit duration and the self-cleaning unit water consumption can be the low-efficiency self-cleaning duration and the low-efficiency self-cleaning unit water consumption or the medium-efficiency self-cleaning duration and the medium-efficiency self-cleaning unit water consumption or the high-efficiency self-cleaning unit water consumption or the self-cleaning self-defining duration which are set by a user in a self-defining way, and different self-cleaning modes are adopted to determine the self-cleaning unit duration and the self-cleaning unit water consumption, so that a foundation is provided for guaranteeing the accuracy of the self-cleaning unit water consumption.
S30: performing data preprocessing on the water flow measurement data to obtain water flow measurement preprocessing data, wherein the data preprocessing comprises data cleaning and abnormal value detection, the data cleaning is used for removing noise, invalid or wrong data points, and the abnormal value detection can identify and process abnormal measurement data possibly existing;
s40: taking a water yield measurement data set corresponding to the self-cleaning period of the direct drinking water equipment as primary deviation rectifying information, and rectifying the water flow measurement pretreatment data to obtain primary deviation rectifying data;
s50: obtaining a direct drinking water filter element replacement period, segmenting the primary correction data through the direct drinking water filter element replacement period to obtain M segments of primary correction segmentation data, wherein M is more than or equal to N is more than or equal to 1, and N is the number of filter elements of the direct drinking water equipment;
S60: comparing the heating work log of the direct drinking water equipment to obtain a cold and hot water flow data set, wherein the cold and hot water flow data set comprises a cold water flow data set and a hot water flow data set;
s70: the cold and hot water flow data set is used as secondary deviation rectifying information, and the primary deviation rectifying data is rectified to obtain secondary deviation rectifying data;
s80: and constructing an automatic water flow deviation rectifying model based on the water flow measurement preprocessing data, the primary deviation rectifying data and the secondary deviation rectifying data, so as to realize automatic deviation rectifying of the water flow measurement data.
Specifically, the water flow measurement data is subjected to data preprocessing to obtain water flow measurement preprocessing data, wherein the data preprocessing generally comprises data cleaning and abnormal value detection, and the purpose of the data cleaning is to remove noise, invalid or wrong data points so as to ensure the accuracy and consistency of the data; the outlier detection may identify and process outlier measurement data that may be present, such as pipe leaks;
taking a water yield measurement data set corresponding to the self-cleaning period of the multi-section direct drinking water of the direct drinking water device as primary deviation rectifying information, for example, defaulting the water yield of the high-efficiency self-cleaning unit to 1500mL/min, defaulting the time length of the high-efficiency self-cleaning unit to 6min, and determining the water yield measurement data of the single default high-efficiency self-cleaning unit to 1500mL/min multiplied by 6 min=9000 mL, and correcting the water yield measurement pretreatment data to obtain primary deviation rectifying data based on the water yield measurement data set corresponding to the self-cleaning period of the multi-section direct drinking water of the known direct drinking water device;
The direct drinking water filter element is a key component for filtering and purifying water quality, the effective working time of the direct drinking water filter element is limited, and the filter element is replaced periodically by setting a filter element replacement period, so that the filtering effect and the water quality safety of direct drinking water equipment are ensured; obtaining a direct drinking water filter element replacement period (the direct drinking water filter element replacement period of the direct drinking water filter element is known), segmenting the primary correction data through the direct drinking water filter element replacement period to obtain M segments of primary correction segmentation data, wherein M=2 is verified to exist N 2 is a constant, M is not less than N is not less than 1, N is the number of filter elements of the direct drinking device, for example, N=3, the direct drinking device is provided with 3 filter elements, and if the replacement period of the filter element of the first model is three months, the replacement period of the filter element of the second model is one year, and the replacement period of the filter element of the third model is two years, M=2 3 =8；
The heating work log of the direct drinking water equipment is contrasted to obtain a cold water flow data set, wherein the cold water flow data set comprises a cold water flow data set and a hot water flow data set, the cold water flow data set is used as secondary deviation rectifying information, and the primary deviation rectifying data are rectified to obtain secondary deviation rectifying data;
Taking a bp network as a model basis, taking the water flow measurement pretreatment data, the primary deviation rectifying data and the secondary deviation rectifying data as retrieval contents, setting a retriever, summarizing and carrying out data retrieval on an intelligent deviation rectifying system of the water flow measurement data, obtaining water flow measurement pretreatment historical data, primary deviation rectifying historical data and secondary deviation rectifying historical data, adopting the water flow measurement pretreatment historical data as construction data, constructing new combination characteristics based on the water flow measurement pretreatment historical data, the primary deviation rectifying historical data and the secondary deviation rectifying historical data, taking the secondary deviation rectifying historical data as identification results, transmitting the identification results into the bp network for model convergence learning, constructing and training to obtain a water flow automatic deviation rectifying model, and carrying out M sections of primary deviation rectifying sectional data with the water flow automatic deviation rectifying model, wherein the water flow automatic deviation rectifying model is also divided into M water flow automatic deviation rectifying sub-models, and the water flow automatic deviation rectifying model is used for automatically rectifying the water flow measurement data, so that the accuracy and the reliability of the water flow automatic deviation rectifying are improved.
As shown in fig. 3, step S60 includes the steps of:
s61: acquiring a heating start instruction set and a heating end instruction set of the direct drinking water equipment through a heating work log of the direct drinking water equipment;
S62: determining a heating start hot water flow data set by comparing each time sequence node corresponding to the heating start instruction set;
s63: determining a heating end hot water flow data set by comparing each time sequence node corresponding to the heating end instruction set;
s64: and calculating the hot water flow data set based on the heating start hot water flow data set and the heating end hot water flow data set.
Specifically, a cold and hot water flow data set is acquired by comparing with a heating work log of the direct drinking water equipment, wherein the cold and hot water flow data set comprises a cold water flow data set and a hot water flow data set, the cold and hot water flow data set comprises a volume of water flowing through a certain cross section in unit time, and meanwhile, expansion and contraction exist in a hot water heating process; comparing the heating end instruction in the heating work log of the direct drinking water equipment to obtain a heating end instruction set of the direct drinking water equipment;
According to each time sequence node corresponding to the heating start instruction set, the heating start time of the heating start instruction can be determined, only hot water flow data is reserved, and a heating start hot water flow data set is determined; according to each time sequence node corresponding to the heating end instruction set, the heating end time of the heating end instruction can be determined, only the hot water flow data is reserved, and the heating end hot water flow data set is determined; and calculating the hot water flow data set based on the heating start hot water flow data set and the heating end hot water flow data set, and providing data support for hot water flow data calculation.
Step S64 includes the steps of:
s641: isolating a hot water output end of the direct drinking water equipment, performing water flow test on the hot water output end, and determining a hot water flow test data set;
s642: performing data combination calculation through each time sequence node corresponding to the hot water flow test data set, the heating start hot water flow data set and the heating end hot water flow data set to obtain a hot water flow time sequence change data set;
s643: and determining the hot water flow data set based on the hot water flow time sequence change data set.
Specifically, based on the heating start hot water flow data set and the heating end hot water flow data set, calculating the hot water flow data set, wherein the steps include isolating a hot water output end of the direct drinking water equipment, and performing water flow test of the hot water output end to obtain a hot water flow test data set; combining the hot water flow data of the heating start and the heating end at different moments according to each time sequence node corresponding to the hot water flow test data set, the heating start hot water flow data set and the heating end hot water flow data set to obtain a more complete hot water flow time sequence change data set;
and determining the hot water flow data set by adopting an interpolation method, wherein common interpolation methods comprise linear interpolation, polynomial interpolation, spline interpolation and the like. The interpolation processing can fill in missing values or smooth data in the hot water flow time sequence change data set, so that a more accurate hot water flow data set is obtained, and the hot water flow data set after the interpolation processing is ensured to have reasonable accuracy and reliability.
In summary, the intelligent deviation rectifying method for water flow measurement data provided by the embodiment of the application has the following technical effects:
1. Due to the adoption of the method, water flow measurement data are acquired from the direct drinking water fluid meter; setting a self-cleaning period of direct drinking water; carrying out data preprocessing on the water flow measurement data to obtain water flow measurement preprocessing data; correcting the water flow measurement pretreatment data to obtain primary correction data; obtaining the replacement period of the direct drinking water filter element, and M sections of primary correction segmentation data; acquiring a cold and hot water flow data set; the intelligent deviation rectifying method for the water flow measurement data has the advantages that interference of various factors such as flow speed fluctuation and water temperature change is eliminated, accuracy of water flow measurement is improved, automatic analysis and processing of the water flow automatic deviation rectifying model are constructed, and technical effects of efficiency and operation convenience are improved.
2. Because the hot water output end of the isolated direct drinking water equipment is adopted, the hot water output end is subjected to water flow test, and a hot water flow test data set is determined; and carrying out data combination calculation through each time sequence node corresponding to the hot water flow test data set, the heating start hot water flow data set and the heating end hot water flow data set to obtain a hot water flow time sequence change data set, determining the hot water flow data set by adopting an interpolation method, filling missing values or smooth data in the hot water flow time sequence change data set, thereby obtaining a more accurate hot water flow data set, and ensuring that the hot water flow data set after interpolation processing has reasonable accuracy and reliability.
Example two
Based on the same inventive concept as the intelligent deviation rectifying method of water flow measurement data in the foregoing embodiment, as shown in fig. 4, an embodiment of the present application provides an intelligent deviation rectifying system of water flow measurement data, where the system includes:
the data acquisition module 100 is used for acquiring water flow measurement data from the direct drinking water fluid meter, wherein the water flow measurement data comprises water inflow measurement data and water outflow measurement data;
the automatic back-flushing cleaning module 200 is used for setting a direct drinking water self-cleaning period, and in the direct drinking water self-cleaning period, the direct drinking water equipment performs automatic back-flushing cleaning, and the direct drinking water self-cleaning period also comprises a self-cleaning unit time length and a self-cleaning unit water consumption, wherein the self-cleaning unit water consumption is used for representing the self-cleaning water consumption in unit time;
the data preprocessing module 300 is configured to perform data preprocessing on the water flow measurement data to obtain water flow measurement preprocessed data, where the data preprocessing includes data cleaning and outlier detection, the data cleaning is used to remove noise, invalid or erroneous data points, and the outlier detection can identify and process possible abnormal measurement data;
The primary deviation rectifying module 400 is configured to take a water output measurement data set corresponding to the self-cleaning period of the direct drinking water of the multiple segments of the direct drinking water equipment as primary deviation rectifying information, and rectify the water flow measurement pretreatment data to obtain primary deviation rectifying data;
the data segmentation module 500 is used for obtaining a direct drinking water filter element replacement period, segmenting the primary deviation rectifying data through the direct drinking water filter element replacement period to obtain M segments of primary deviation rectifying segmented data, wherein M is more than or equal to N is more than or equal to 1, and N is the number of filter elements of the direct drinking water equipment;
the cold and hot water flow data set acquisition module 600 is configured to acquire a cold and hot water flow data set by comparing with a heating log of the direct drinking water device, where the cold and hot water flow data set includes a cold water flow data set and a hot water flow data set;
the secondary deviation rectifying module 700 is configured to take the cold and hot water flow data set as secondary deviation rectifying information, and rectify the primary deviation rectifying data to obtain secondary deviation rectifying data;
the automatic deviation-correcting measurement module 800 is configured to construct an automatic deviation-correcting water flow model based on the water flow measurement preprocessing data, the primary deviation-correcting data and the secondary deviation-correcting data, so as to realize automatic deviation correction of the water flow measurement data.
Further, the system includes:
the equipment type information acquisition module is used for acquiring equipment type information of the direct drinking water equipment, wherein the equipment type information can be an activated carbon filter element and/or a reverse osmosis water purifier and/or an ultraviolet sterilizer;
the water source water quality information acquisition module is used for acquiring water source water quality information, wherein the water source water quality information comprises suspended matters, particulate matters, soluble matters, microorganisms, bacteria, pH values and medicine residues;
the direct drinking water self-cleaning period acquisition module is used for setting the direct drinking water self-cleaning period based on the water quality information of the water source and the equipment type information.
Further, the system includes:
the applicable environment water source water quality information acquisition module is used for acquiring applicable environment water source water quality information defined in a use instruction in the direct drinking water equipment, wherein the applicable environment water source water quality information comprises a suspended matter and particulate matter applicable range, a soluble matter applicable range, a microorganism and bacteria applicable range, a pH value applicable range and a medicine residue applicable range;
the comparison module is used for comparing the water quality information of the applicable environment water source and the water quality information of the water source;
the direct drinking water self-cleaning period setting module is used for setting the direct drinking water self-cleaning period as an initial self-cleaning period if the water quality information of the water source meets the water quality information of the water source of the applicable environment, and the initial self-cleaning period is 24 h/time.
Further, the system includes:
the self-cleaning mode information acquisition module is used for acquiring self-cleaning mode information defined in the use specification of the direct drinking water equipment, wherein the self-cleaning mode information comprises high-efficiency self-cleaning mode information, medium-efficiency self-cleaning mode information and low-efficiency self-cleaning mode information;
the low-efficiency self-cleaning duration and low-efficiency self-cleaning unit water consumption acquisition module is used for acquiring low-efficiency self-cleaning duration and low-efficiency self-cleaning unit water consumption if the water quality information of the water source meets the water quality information of the water source of the applicable environment and accords with the limitation of the low-efficiency self-cleaning mode information;
the medium-efficiency self-cleaning duration and medium-efficiency self-cleaning unit water consumption acquisition module is used for acquiring medium-efficiency self-cleaning duration and medium-efficiency self-cleaning unit water consumption if the water quality information of the water source meets the water quality information of the water source of the applicable environment and accords with the limitation of the medium-efficiency self-cleaning mode information;
the high-efficiency self-cleaning duration and high-efficiency self-cleaning unit water consumption acquisition module is used for acquiring high-efficiency self-cleaning duration and high-efficiency self-cleaning unit water consumption if the water quality information of the water source meets the water quality information of the water source of the applicable environment and accords with the limit of the high-efficiency self-cleaning mode information;
The self-cleaning unit duration and self-cleaning unit water consumption acquisition module is used for determining the self-cleaning unit duration and self-cleaning unit water consumption through the low-efficiency self-cleaning duration and low-efficiency self-cleaning unit water consumption or the medium-efficiency self-cleaning duration and medium-efficiency self-cleaning unit water consumption or the high-efficiency self-cleaning duration and high-efficiency self-cleaning unit water consumption.
Further, the system includes:
the low-efficiency self-cleaning mode setting module is used for setting a mode of cleaning only by water as a self-cleaning mode of the low-efficiency self-cleaning mode information;
the medium-efficiency self-cleaning mode setting module is used for using cleaning disinfectant according to the following steps of 1:40, obtaining a medium-efficiency cleaning solution, and setting a mode of using the medium-efficiency cleaning solution as a self-cleaning mode of the medium-efficiency self-cleaning mode information;
the high-efficiency self-cleaning mode setting module is used for using cleaning disinfectant according to the following steps of 1:24, and setting a mode of using the efficient cleaning liquid as a self-cleaning mode of the efficient self-cleaning mode information.
Further, the system includes:
the heating start instruction set and heating end instruction set acquisition module is used for acquiring a heating start instruction set and a heating end instruction set of the direct drinking water equipment through the heating work log of the direct drinking water equipment;
The heating start hot water flow data set determining module is used for determining a heating start hot water flow data set by comparing each time sequence node corresponding to the heating start instruction set;
the heating end hot water flow data set determining module is used for determining a heating end hot water flow data set by comparing each time sequence node corresponding to the heating end instruction set;
and the hot water flow data set calculation module is used for calculating the hot water flow data set based on the heating start hot water flow data set and the heating end hot water flow data set.
Further, the system includes:
the hot water flow test data set determining module is used for isolating a hot water output end of the direct drinking water equipment, carrying out water flow test on the hot water output end and determining a hot water flow test data set;
the data combination calculation module is used for carrying out data combination calculation through each time sequence node corresponding to the hot water flow test data set, the heating start hot water flow data set and the heating end hot water flow data set to obtain a hot water flow time sequence change data set;
and the hot water flow data set determining module is used for determining the hot water flow data set based on the hot water flow time sequence change data set.
Any of the steps of the methods described above may be stored as computer instructions or programs in a non-limiting computer memory and may be called by a non-limiting computer processor to identify any of the methods to implement embodiments of the present application, without unnecessary limitations.
Further, the first or second element may not only represent a sequential relationship, but may also represent a particular concept, and/or may be selected individually or in whole among a plurality of elements. It will be apparent to those skilled in the art that various modifications and variations can 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 present application and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (8)
1. The intelligent deviation rectifying method for the water flow measurement data is characterized in that the intelligent deviation rectifying method for the water flow measurement data is applied to an intelligent deviation rectifying system for the water flow measurement data, and the intelligent deviation rectifying system for the water flow measurement data is in communication connection with a direct drinking water fluid meter, and the method comprises the following steps:
acquiring water flow measurement data from the direct drinking water fluid meter, wherein the water flow measurement data comprises water inflow measurement data and water outflow measurement data;
Setting a self-cleaning period of direct drinking water, wherein in the self-cleaning period of the direct drinking water, the direct drinking water equipment performs automatic back flushing cleaning, and the self-cleaning period of the direct drinking water also comprises self-cleaning unit time length and self-cleaning unit water consumption, wherein the self-cleaning unit water consumption is used for representing the self-cleaning water consumption in unit time;
performing data preprocessing on the water flow measurement data to obtain water flow measurement preprocessing data, wherein the data preprocessing comprises data cleaning and abnormal value detection, the data cleaning is used for removing noise, invalid or wrong data points, and the abnormal value detection can identify and process abnormal measurement data possibly existing;
taking a water yield measurement data set corresponding to the self-cleaning period of the direct drinking water equipment as primary deviation rectifying information, and rectifying the water flow measurement pretreatment data to obtain primary deviation rectifying data;
obtaining a direct drinking water filter element replacement period, segmenting the primary correction data through the direct drinking water filter element replacement period to obtain M segments of primary correction segmentation data, wherein M is more than or equal to N is more than or equal to 1, and N is the number of filter elements of the direct drinking water equipment;
comparing the heating work log of the direct drinking water equipment to obtain a cold and hot water flow data set, wherein the cold and hot water flow data set comprises a cold water flow data set and a hot water flow data set;
The cold and hot water flow data set is used as secondary deviation rectifying information, and the primary deviation rectifying data is rectified to obtain secondary deviation rectifying data;
and constructing an automatic water flow deviation rectifying model based on the water flow measurement preprocessing data, the primary deviation rectifying data and the secondary deviation rectifying data, so as to realize automatic deviation rectifying of the water flow measurement data.
2. The intelligent deviation correcting method of water flow measurement data according to claim 1, wherein the setting of a self-cleaning period of direct drinking water, in which the direct drinking water equipment performs automatic back flushing cleaning, the self-cleaning period of direct drinking water further includes a self-cleaning unit duration and a self-cleaning unit water consumption, wherein the self-cleaning unit water consumption is used for representing the self-cleaning water consumption in unit time, includes:
acquiring equipment type information of the direct drinking water equipment, wherein the equipment type information can be an activated carbon filter element and/or a reverse osmosis water purifier and/or an ultraviolet sterilizer;
acquiring water quality information of a water source, wherein the water quality information of the water source comprises suspended matters, particulate matters, soluble matters, microorganisms, bacteria, pH values and medicine residues;
and setting the self-cleaning period of the direct drinking water based on the water quality information of the water source and the equipment type information.
3. The intelligent deviation rectifying method for water flow measurement data according to claim 2, wherein said setting said self-cleaning period of drinking water based on said water quality information of water source and said equipment type information comprises:
acquiring water quality information of an applicable environment water source defined in a use instruction in the direct drinking water equipment, wherein the water quality information of the applicable environment water source comprises an applicable range of suspended matters and particles, an applicable range of soluble substances, an applicable range of microorganisms and bacteria, an applicable range of pH values and an applicable range of medicine residues;
comparing the water quality information of the water source of the applicable environment with the water quality information of the water source;
if the water quality information of the water source meets the water quality information of the water source of the applicable environment, setting the self-cleaning period of the direct drinking water as an initial self-cleaning period, wherein the initial self-cleaning period is 24 h/time.
4. The intelligent deviation rectifying method of water flow measurement data according to claim 3, wherein the self-cleaning period of the direct drinking water further comprises self-cleaning unit duration and self-cleaning unit water consumption, and further comprises:
acquiring self-cleaning mode information defined in a use specification of the direct drinking water equipment, wherein the self-cleaning mode information comprises high-efficiency self-cleaning mode information, medium-efficiency self-cleaning mode information and low-efficiency self-cleaning mode information;
If the water quality information of the water source meets the water quality information of the water source of the applicable environment and meets the limitation of the low-efficiency self-cleaning mode information, acquiring low-efficiency self-cleaning duration and low-efficiency self-cleaning unit water consumption;
if the water quality information of the water source meets the water quality information of the water source of the applicable environment and meets the limitation of the information of the medium-efficiency self-cleaning mode, acquiring medium-efficiency self-cleaning duration and medium-efficiency self-cleaning unit water consumption;
if the water quality information of the water source meets the water quality information of the water source of the applicable environment and meets the limitation of the information of the high-efficiency self-cleaning mode, acquiring high-efficiency self-cleaning duration and high-efficiency self-cleaning unit water consumption;
and determining the self-cleaning unit time length and the self-cleaning unit water consumption by the low-efficiency self-cleaning time length and the low-efficiency self-cleaning unit water consumption or the medium-efficiency self-cleaning time length and the medium-efficiency self-cleaning unit water consumption or the high-efficiency self-cleaning time length and the high-efficiency self-cleaning unit water consumption.
5. The intelligent deviation rectifying method of water flow measurement data according to claim 4, further comprising:
setting a mode of cleaning only with water as a self-cleaning mode of the low-efficiency self-cleaning mode information;
Using a cleaning disinfectant, according to 1:40, obtaining a medium-efficiency cleaning solution, and setting a mode of using the medium-efficiency cleaning solution as a self-cleaning mode of the medium-efficiency self-cleaning mode information;
using a cleaning disinfectant, according to 1:24, and setting a mode of using the efficient cleaning liquid as a self-cleaning mode of the efficient self-cleaning mode information.
6. The intelligent deviation rectifying method of water flow measurement data according to claim 1, wherein the step of obtaining a cold and hot water flow data set by comparing the heating work log of the direct drinking water equipment, wherein the cold and hot water flow data set comprises a cold water flow data set and a hot water flow data set, and the method comprises the steps of:
acquiring a heating start instruction set and a heating end instruction set of the direct drinking water equipment through a heating work log of the direct drinking water equipment;
determining a heating start hot water flow data set by comparing each time sequence node corresponding to the heating start instruction set;
determining a heating end hot water flow data set by comparing each time sequence node corresponding to the heating end instruction set;
and calculating the hot water flow data set based on the heating start hot water flow data set and the heating end hot water flow data set.
7. The intelligent deviation rectifying method of water flow measurement data according to claim 6, wherein said calculating said hot water flow data set based on said heating start hot water flow data set and said heating end hot water flow data set comprises:
isolating a hot water output end of the direct drinking water equipment, performing water flow test on the hot water output end, and determining a hot water flow test data set;
performing data combination calculation through each time sequence node corresponding to the hot water flow test data set, the heating start hot water flow data set and the heating end hot water flow data set to obtain a hot water flow time sequence change data set;
and determining the hot water flow data set based on the hot water flow time sequence change data set.
8. An intelligent deviation rectifying system for water flow measurement data, characterized in that the intelligent deviation rectifying method for implementing the water flow measurement data according to any one of claims 1-7 comprises the following steps:
the data acquisition module is used for acquiring water flow measurement data from the direct drinking water fluid meter, wherein the water flow measurement data comprise water inflow measurement data and water outflow measurement data;
The automatic back-flushing cleaning module is used for setting a direct drinking water self-cleaning period, and in the direct drinking water self-cleaning period, the direct drinking water equipment carries out automatic back-flushing cleaning, and the direct drinking water self-cleaning period also comprises self-cleaning unit time length and self-cleaning unit water consumption, wherein the self-cleaning unit water consumption is used for representing the self-cleaning water consumption in unit time;
the data preprocessing module is used for carrying out data preprocessing on the water flow measurement data to obtain water flow measurement preprocessing data, the data preprocessing comprises data cleaning and abnormal value detection, the data cleaning is used for removing data points with noise, invalidity or errors, and the abnormal value detection can identify and process abnormal measurement data possibly existing;
the primary deviation rectifying module is used for taking a water yield measurement data set corresponding to the self-cleaning period of the direct drinking water equipment as primary deviation rectifying information, and rectifying the water flow measurement pretreatment data to obtain primary deviation rectifying data;
the data segmentation module is used for obtaining a direct drinking water filter element replacement period, segmenting the primary deviation correction data through the direct drinking water filter element replacement period to obtain M segments of primary deviation correction segmented data, wherein M is more than or equal to N and more than or equal to 1, and N is the number of filter elements of the direct drinking water equipment;
The cold and hot water flow data set acquisition module is used for acquiring a cold and hot water flow data set by comparing with a heating work log of the direct drinking water equipment, wherein the cold and hot water flow data set comprises a cold water flow data set and a hot water flow data set;
the secondary deviation rectifying module is used for taking the cold and hot water flow data set as secondary deviation rectifying information, rectifying the primary deviation rectifying data and obtaining secondary deviation rectifying data;
the automatic deviation measuring and correcting module is used for constructing an automatic deviation correcting model of the water flow based on the water flow measurement preprocessing data, the primary deviation correcting data and the secondary deviation correcting data, and realizing automatic deviation correction of the water flow measurement data.
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