CN112325967A - Intelligent Internet of things water meter working state early warning method and system - Google Patents
Intelligent Internet of things water meter working state early warning method and system Download PDFInfo
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- CN112325967A CN112325967A CN202011242553.XA CN202011242553A CN112325967A CN 112325967 A CN112325967 A CN 112325967A CN 202011242553 A CN202011242553 A CN 202011242553A CN 112325967 A CN112325967 A CN 112325967A
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- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 873
- 238000000034 method Methods 0.000 title claims abstract description 24
- 230000005540 biological transmission Effects 0.000 claims abstract description 121
- 238000010992 reflux Methods 0.000 claims abstract description 29
- 238000005259 measurement Methods 0.000 claims description 25
- 230000035945 sensitivity Effects 0.000 claims description 18
- 238000005070 sampling Methods 0.000 claims description 16
- 230000002159 abnormal effect Effects 0.000 claims description 6
- 230000006855 networking Effects 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 4
- 239000000126 substance Substances 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 description 8
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F15/00—Details of, or accessories for, apparatus of groups G01F1/00 - G01F13/00 insofar as such details or appliances are not adapted to particular types of such apparatus
- G01F15/06—Indicating or recording devices
- G01F15/061—Indicating or recording devices for remote indication
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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
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Abstract
The invention provides an intelligent Internet of things water meter working state early warning method and system, which determine the water transmission reflux intensity state information in a water supply pipeline according to the water transmission state information so as to judge the water supply stability of the water supply pipeline, correspondingly adjust the water flow metering mode of the water meter and obtain water flow metering data, and finally early warn and adjust the working state of the water meter according to the water flow metering data.
Description
Technical Field
The invention relates to the technical field of Internet of things control, in particular to an intelligent Internet of things water meter working state early warning method and system.
Background
At present, the urban water supply system realizes stable water supply at constant pressure by laying a corresponding water supply pipeline network and performing water pressurization treatment on the water supply pipeline. Generally speaking, in order to measure the water consumption of a user timely and accurately, a corresponding water meter needs to be installed on a water supply pipeline for metering, but because the pipeline connection structure of a water supply pipeline network is complex and the water flow condition inside the pipeline changes many ends, the phenomenon of water flow disturbance inevitably exists inside the pipeline, the water flow disturbance can form water transmission backflow with certain intensity on the water meter, in order to avoid the influence of the water transmission backflow on the normal metering work of the water meter, when the water transmission backflow intensity inside the water supply pipeline exceeds a certain value, a certain pipe pressure can be generated on the water supply pipeline, and the normal metering of the water meter can be disturbed to cause the deviation of water flow metering data. It is therefore desirable in the art to provide a method and system for providing effective warning of the operating condition of a water meter based on the water transport reflux intensity status within the water supply pipeline.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides an intelligent Internet of things water meter working state early warning method and system, which judge the water supply stability of a water supply pipeline connected with a water meter by acquiring water flow transmission state information inside the water supply pipeline connected with the water meter, determining water transmission reflux intensity state information inside the water supply pipeline according to the water flow transmission state information, and judging the water supply stability of the water supply pipeline connected with the water meter according to the water supply stability judgment result, adjusting a water flow metering mode of the water meter to obtain corresponding water flow metering data, sending the water flow metering data to an Internet of things cloud for analysis and processing, so as to judge the accuracy of the water flow metering data, and early warning and adjusting the working state of the water meter according to the accuracy judgment result; therefore, the intelligent Internet of things water meter working state early warning method and system determine the water transmission backflow strength state information in the water supply pipeline according to the water transmission state information, judge the water supply stability of the water supply pipeline, correspondingly adjust the water flow metering mode of the water meter and obtain water flow metering data, and finally early warn and adjust the working state of the water meter according to the water flow metering data, and can timely and effectively early warn and adjust the working state of the water meter under the condition that the water transmission backflow in the water supply pipeline influences the normal metering work of the water meter, so that the reliability and the accuracy of water meter metering are improved to the maximum extent.
The invention provides an intelligent Internet of things water meter working state early warning method which is characterized by comprising the following steps:
step S1, acquiring water flow transmission state information inside a water supply pipeline connected with the water meter, and determining water transmission reflux intensity state information inside the water supply pipeline according to the water flow transmission state information;
step S2, according to the water transmission reflux intensity state information, judging the water supply stability of the water supply pipeline connected with the water meter, and according to the judgment result of the water supply stability, adjusting the water flow metering mode of the water meter to obtain corresponding water flow metering data;
step S3, sending the water flow metering data to an Internet of things cloud for analysis processing, so as to judge the accuracy of the water flow metering data, and carrying out early warning and adjustment on the working state of the water meter according to the judgment result of the accuracy;
further, in step S1, the acquiring water flow transmission state information inside a water supply pipeline connected to the water meter, and determining the water transmission backflow strength state information inside the water supply pipeline according to the water flow transmission state information specifically includes:
step S101, acquiring water flow velocity distribution state information and water flow direction distribution state information of the interior of the water supply pipeline along the pipeline cross section dimension of the water supply pipeline;
step S102, analyzing and processing the water flow direction distribution state information so as to determine the main flow direction of the water flow in the water supply pipeline, and analyzing and processing the water flow velocity distribution state information so as to determine the average flow velocity of the water flow of the water supply pipeline on the cross section dimension of the pipeline;
step S103, determining a water transmission backflow strength value inside the water supply pipeline along the length direction of the pipeline according to the main water flow direction and the average water flow speed;
further, in step S2, determining the water supply stability of the water supply pipeline connected to the water meter according to the water transmission backflow strength state information, and adjusting the water flow metering mode of the water meter according to the determination result of the water supply stability, so as to obtain corresponding water flow metering data specifically includes:
step S201, comparing the water transmission backflow strength value with the maximum water pressure strength value borne by the pipeline of the water supply pipeline, if the water transmission backflow strength value is less than or equal to the maximum water pressure strength value borne by the pipeline, determining that the water supply pipeline connected with the water meter is currently in a stable water supply state, otherwise, determining that the water supply pipeline connected with the water meter is currently in an unstable water supply state;
step S202, when the water supply pipeline connected with the water meter is determined to be in a stable water supply state currently, a mechanical water flow metering component of the water meter is instructed to carry out water flow metering operation, and an electronic water flow metering component of the water meter is instructed to stop carrying out water flow metering operation, so that corresponding water flow metering data are obtained;
step S203, when the water supply pipeline connected with the water meter is determined to be in the unstable water supply state at present, the electronic water flow metering component of the water meter is instructed to carry out water flow metering operation, the water flow metering sensitivity or the water flow metering sampling frequency of the electronic water flow metering component is improved, and meanwhile, the mechanical water flow metering component of the water meter is instructed to stop carrying out water flow operation, so that corresponding water flow metering data are obtained;
further, in step S3, the water flow measurement data is sent to the internet of things cloud for analysis processing, so as to determine the accuracy of the water flow measurement data, and according to the determination result of the accuracy, the early warning and the adjustment of the working state of the water meter specifically include:
step S301, the water flow metering data are sent to the Internet of things for operation and analysis processing, and therefore the water flow metering data are correspondingly divided into a plurality of water flow meter quantum data of a user in each hour in 24 hours a day;
step S302, comparing the water flow meter quantum data with a water flow metering average value obtained from a historical record, if the deviation between the water flow meter quantum data and the water flow metering average value is lower than a preset difference value, determining that the water flow metering data has accuracy, otherwise, determining that the water flow metering data does not have accuracy;
step S303, when it is determined that the water flow metering data does not have accuracy, indicating that the water meter is in an abnormal working state at present, and resetting the water flow metering sensitivity and/or the metering sampling frequency of the water meter to an initial factory state.
The invention also provides an intelligent Internet of things water meter working state early warning system which is characterized by comprising a water flow transmission state information acquisition module, a water transmission reflux intensity state information determination module, a water flow metering data acquisition module and a water meter working state early warning and adjusting module; wherein the content of the first and second substances,
the water flow transmission state information acquisition module is used for acquiring water flow transmission state information in a water supply pipeline connected with the water meter;
the water transmission reflux intensity state information determining module is used for determining water transmission reflux intensity state information in the water supply pipeline according to the water flow transmission state information;
the water flow metering data acquisition module is used for judging the water supply stability of a water supply pipeline connected with the water meter according to the water transmission backflow strength state information and adjusting a water flow metering mode of the water meter according to the judgment result of the water supply stability so as to acquire corresponding water flow metering data;
the water meter working state early warning and adjusting module is used for sending the water flow metering data to the cloud end of the Internet of things for analysis processing so as to judge the accuracy of the water flow metering data, and early warning and adjusting the working state of the water meter according to the judgment result of the accuracy;
further, the acquiring module of the water flow transmission state information specifically includes:
acquiring water flow velocity distribution state information and water flow direction distribution state information of the interior of the water supply pipeline along the pipeline cross section dimension of the water supply pipeline;
and the number of the first and second groups,
the water transmission backflow strength state information determining module is used for determining the water transmission backflow strength state information inside the water supply pipeline according to the water flow transmission state information, and specifically comprises the following steps:
analyzing the water flow direction distribution state information so as to determine the main flow direction of water flow in the water supply pipeline, and analyzing the water flow velocity distribution state information so as to determine the average water flow velocity of the water supply pipeline on the cross section dimension of the pipeline;
and determining the water transmission backflow strength value inside the water supply pipeline along the length direction of the pipeline according to the main water flow direction and the average water flow speed.
Further, the water flow measurement data acquisition module judges the water supply stability of the water supply pipeline connected with the water meter according to the water transmission reflux intensity state information, and adjusts the water flow measurement mode of the water meter according to the judgment result of the water supply stability, so as to obtain corresponding water flow measurement data, and the water flow measurement data acquisition module specifically comprises:
comparing the water transmission backflow strength value with a maximum water pressure strength value borne by a pipeline of the water supply pipeline, if the water transmission backflow strength value is less than or equal to the maximum water pressure strength value borne by the pipeline, determining that the water supply pipeline connected with the water meter is currently in a stable water supply state, otherwise, determining that the water supply pipeline connected with the water meter is currently in an unstable water supply state;
when the water supply pipeline connected with the water meter is determined to be in a stable water supply state currently, indicating a mechanical water flow metering component of the water meter to perform water flow metering operation, and simultaneously indicating an electronic water flow metering component of the water meter to stop performing water flow metering operation, so as to obtain corresponding water flow metering data;
and when the water supply pipeline connected with the water meter is determined to be in an unstable water supply state at present, indicating an electronic water flow metering component of the water meter to perform water flow metering operation, improving the water flow metering sensitivity or water flow metering sampling frequency of the electronic water flow metering component, and simultaneously indicating a mechanical water flow metering component of the water meter to stop performing water flow operation so as to obtain corresponding water flow metering data.
Further, water gauge operating condition early warning and adjusting module will water flow measurement data send to the thing networking high in the clouds and carry out analysis processes to this judgement water flow measurement data's accuracy, and according to the judged result of accuracy, it is right the operating condition of water gauge carries out the early warning and adjusts and specifically includes:
sending the water flow metering data to an internet of things for operation and analysis processing, and correspondingly dividing the water flow metering data into a plurality of water flow meter quantum data of a user in each hour in 24 hours a day;
comparing the water flow meter quantum data with a water flow metering average value obtained by a historical record, if the deviation of the water flow meter quantum data and the water flow metering average value is lower than a preset difference value, determining that the water flow metering data has accuracy, otherwise, determining that the water flow metering data does not have accuracy;
and when the water flow metering data is determined to be inaccurate, indicating that the water meter is in an abnormal working state currently, and resetting the water flow metering sensitivity and/or the metering sampling frequency of the water meter to an initial factory state.
Compared with the prior art, the intelligent Internet of things water meter working state early warning method and system determine the water transmission reflux intensity state information inside the water supply pipeline connected with the water meter by acquiring the water transmission state information inside the water supply pipeline connected with the water meter, judge the water supply stability of the water supply pipeline connected with the water meter according to the water transmission reflux intensity state information, adjust the water flow metering mode of the water meter according to the judgment result of the water supply stability, acquire corresponding water flow metering data, send the water flow metering data to the cloud of the Internet of things for analysis and processing, judge the accuracy of the water flow metering data, and early warn and adjust the working state of the water meter according to the judgment result of the accuracy; therefore, the intelligent Internet of things water meter working state early warning method and system determine the water transmission backflow strength state information in the water supply pipeline according to the water transmission state information, judge the water supply stability of the water supply pipeline, correspondingly adjust the water flow metering mode of the water meter and obtain water flow metering data, and finally early warn and adjust the working state of the water meter according to the water flow metering data, and can timely and effectively early warn and adjust the working state of the water meter under the condition that the water transmission backflow in the water supply pipeline influences the normal metering work of the water meter, so that the reliability and the accuracy of water meter metering are improved to the maximum extent.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of an intelligent internet-of-things water meter working state early warning method provided by the invention.
Fig. 2 is a schematic structural diagram of an intelligent internet-of-things water meter working state early warning system provided by the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic flow chart of an intelligent internet-of-things water meter working state warning method according to an embodiment of the present invention. The intelligent Internet of things water meter working state early warning method comprises the following steps:
step S1, acquiring water flow transmission state information inside a water supply pipeline connected with the water meter, and determining water transmission reflux intensity state information inside the water supply pipeline according to the water flow transmission state information;
step S2, according to the water transmission reflux intensity status information, judging the water supply stability of the water supply pipeline connected with the water meter, and according to the judgment result of the water supply stability, adjusting the water flow metering mode of the water meter, so as to obtain the corresponding water flow metering data;
and S3, sending the water flow metering data to the Internet of things cloud for analysis processing, so as to judge the accuracy of the water flow metering data, and early warning and adjusting the working state of the water meter according to the judgment result of the accuracy.
The beneficial effects of the above technical scheme are: according to the intelligent Internet of things water meter working state early warning method, the water transmission backflow strength state information inside the water supply pipeline is determined according to the water flow transmission state information, so that the water supply stability of the water supply pipeline is judged, then the water flow metering mode of the water meter is correspondingly adjusted, water flow metering data is obtained, and finally early warning and adjustment are carried out on the working state of the water meter according to the water flow metering data.
Preferably, in the step S1, the acquiring the water flow transmission state information inside the water supply pipeline connected to the water meter, and the determining the water transmission backflow strength state information inside the water supply pipeline according to the water flow transmission state information specifically includes:
step S101, acquiring water flow velocity distribution state information and water flow direction distribution state information of the interior of the water supply pipeline along the pipeline cross section dimension of the water supply pipeline;
step S102, analyzing and processing the water flow direction distribution state information so as to determine the main flow direction of the water flow in the water supply pipeline, and analyzing and processing the water flow velocity distribution state information so as to determine the average flow velocity of the water flow of the water supply pipeline on the cross section dimension of the pipeline;
and step S103, determining a water transmission backflow strength value inside the water supply pipeline along the length direction of the pipeline according to the main flow direction of the water flow and the average flow velocity of the water flow.
The beneficial effects of the above technical scheme are: because the water transmission backward flow in the water supply pipeline is formed by rivers disturbance and the vortex that water in the water supply pipeline exists in the transmission course, and rivers disturbance and vortex are direct and water flow velocity and rivers direction relevant in the water supply pipeline, it is too high or rivers direction change too fast to work as the rivers velocity of flow, the inside water pressure change of water supply pipeline is also faster, then the water transmission backward flow intensity in the water supply pipeline is then higher, like this through obtaining water flow velocity distribution state information and the rivers direction distribution state information of water supply pipeline on the pipeline cross section dimension, can calculate the inside water transmission backward flow intensity value of water supply pipeline fast and accurately.
Preferably, in the step S2, the determining the water supply stability of the water supply pipeline connected to the water meter according to the water transmission backflow strength status information, and adjusting the water flow metering mode of the water meter according to the determination result of the water supply stability, so as to obtain the corresponding water flow metering data specifically includes:
step S201, comparing the water transmission reflux strength value with the maximum water pressure strength value borne by the pipeline of the water supply pipeline, if the water transmission reflux strength value is less than or equal to the maximum water pressure strength value borne by the pipeline, determining that the water supply pipeline connected with the water meter is currently in a stable water supply state, otherwise, determining that the water supply pipeline connected with the water meter is currently in an unstable water supply state;
step S202, when the water supply pipeline connected with the water meter is determined to be in a stable water supply state currently, a mechanical water flow metering component of the water meter is instructed to carry out water flow metering operation, and an electronic water flow metering component of the water meter is instructed to stop carrying out water flow metering operation, so that corresponding water flow metering data are obtained;
step S203, when it is determined that the water supply pipeline connected to the water meter is currently in a water supply unstable state, the electronic water flow metering component of the water meter is instructed to perform water flow metering operation, the water flow metering sensitivity or the water flow metering sampling frequency of the electronic water flow metering component is increased, and meanwhile, the mechanical water flow metering component of the water meter is instructed to stop performing water flow operation, so that corresponding water flow metering data is obtained.
The beneficial effects of the above technical scheme are: when the water transmission backflow strength value exceeds the maximum water pressure strength value which can be borne by the pipeline of the water supply pipeline, not only certain compression can be generated on the water supply pipeline to cause the deformation of the water supply pipeline, but also the normal water flow metering state of the water meter can be disturbed, because the mechanical water flow metering component and the electronic water flow metering component in the water meter respectively have different metering sensitivity and anti-interference performance, when the water supply pipeline connected with the water meter is determined to be in a stable water supply state, can only indicate the mechanical water flow metering component to perform metering work, otherwise, only indicate the electronic water flow metering component to perform metering work and improve the water flow metering sensitivity or the water flow metering sampling frequency of the electronic water flow metering component, therefore, the water meter can still carry out accurate water flow metering no matter in a stable or unstable water supply state.
Preferably, in this step S3, send this water flow measurement data to the internet of things cloud for analysis processing, to this accuracy of judging this water flow measurement data, and according to the judged result of this accuracy, carry out early warning and adjustment to the operating condition of this water gauge specifically includes:
step S301, the water flow metering data are sent to the Internet of things for operation and analysis processing, and accordingly the water flow metering data are correspondingly divided into a plurality of water flow meter quantum data of a user in each hour in 24 hours a day;
step S302, comparing the water flow meter quantum data with the water flow metering average value obtained from the historical record, if the deviation between the water flow meter quantum data and the water flow metering average value is lower than a preset difference value, determining that the water flow metering data has accuracy, otherwise, determining that the water flow metering data does not have accuracy;
step S303, when it is determined that the water flow metering data does not have accuracy, indicating that the water meter is currently in an abnormal working state, and resetting the water flow metering sensitivity and/or the metering sampling frequency of the water meter to a factory initial state.
The beneficial effects of the above technical scheme are: the water flow metering average value is obtained by recording the historical water consumption of the user, so that the water flow metering average value can truly reflect the water consumption condition of the user at different time intervals in one day, and the water flow meter quantum data is compared with the water flow metering average value, so that whether the water flow metering data is accurate or not can be accurately determined, and the water flow metering sensitivity and/or the metering sampling frequency of the water meter can be conveniently reset subsequently.
Fig. 2 is a schematic structural diagram of an intelligent internet-of-things water meter working state early warning system according to an embodiment of the present invention. The intelligent Internet of things water meter working state early warning system comprises a water flow transmission state information acquisition module, a water transmission reflux intensity state information determination module, a water flow metering data acquisition module and a water meter working state early warning and adjusting module; wherein the content of the first and second substances,
the water flow transmission state information acquisition module is used for acquiring water flow transmission state information in a water supply pipeline connected with the water meter;
the water transmission reflux intensity state information determining module is used for determining water transmission reflux intensity state information in the water supply pipeline according to the water flow transmission state information;
the water flow metering data acquisition module is used for judging the water supply stability of a water supply pipeline connected with the water meter according to the water transmission reflux intensity state information and adjusting the water flow metering mode of the water meter according to the judgment result of the water supply stability so as to obtain corresponding water flow metering data;
this water gauge operating condition early warning and adjusting module is used for sending this water flow measurement data to the thing networking high in the clouds and carries out analysis processes to this accuracy of judging this water flow measurement data, and according to the judged result of this accuracy, carry out early warning and adjustment to the operating condition of this water gauge.
The beneficial effects of the above technical scheme are: the intelligent Internet of things water meter working state early warning system determines the water transmission backflow strength state information inside the water supply pipeline according to the water transmission state information, judges the water supply stability of the water supply pipeline, correspondingly adjusts the water flow metering mode of the water meter and obtains water flow metering data, and finally carries out early warning and adjustment on the working state of the water meter according to the water flow metering data.
Preferably, the acquiring of the water flow transmission state information in the water supply pipeline connected to the water meter by the water flow transmission state information acquiring module specifically includes:
acquiring water flow velocity distribution state information and water flow direction distribution state information of the interior of the water supply pipeline along the pipeline cross section dimension of the water supply pipeline;
and the number of the first and second groups,
the module for determining the water transmission reflux intensity state information determines the water transmission reflux intensity state information inside the water supply pipeline according to the water transmission state information, and specifically comprises the following steps:
analyzing the water flow direction distribution state information so as to determine the main flow direction of water flow in the water supply pipeline, and analyzing the water flow velocity distribution state information so as to determine the average water flow velocity of the water supply pipeline on the cross section dimension of the pipeline;
and determining the water transmission backflow strength value inside the water supply pipeline along the length direction of the pipeline according to the main flow direction of the water flow and the average flow velocity of the water flow.
The beneficial effects of the above technical scheme are: because the water transmission backward flow in the water supply pipeline is formed by rivers disturbance and the vortex that water in the water supply pipeline exists in the transmission course, and rivers disturbance and vortex are direct and water flow velocity and rivers direction relevant in the water supply pipeline, it is too high or rivers direction change too fast to work as the rivers velocity of flow, the inside water pressure change of water supply pipeline is also faster, then the water transmission backward flow intensity in the water supply pipeline is then higher, like this through obtaining water flow velocity distribution state information and the rivers direction distribution state information of water supply pipeline on the pipeline cross section dimension, can calculate the inside water transmission backward flow intensity value of water supply pipeline fast and accurately.
Preferably, the water flow measurement data obtaining module determines the water supply stability of the water supply pipeline connected to the water meter according to the water transmission reflux strength state information, and adjusts the water flow measurement mode of the water meter according to the determination result of the water supply stability, so as to obtain the corresponding water flow measurement data specifically includes:
comparing the water transmission backflow strength value with the maximum water pressure strength value borne by the pipeline of the water supply pipeline, if the water transmission backflow strength value is smaller than or equal to the maximum water pressure strength value borne by the pipeline, determining that the water supply pipeline connected with the water meter is currently in a stable water supply state, and otherwise, determining that the water supply pipeline connected with the water meter is currently in an unstable water supply state;
when the water supply pipeline connected with the water meter is determined to be in a stable water supply state currently, indicating a mechanical water flow metering component of the water meter to perform water flow metering operation, and simultaneously indicating an electronic water flow metering component of the water meter to stop performing water flow metering operation, so as to obtain corresponding water flow metering data;
and when the water supply pipeline connected with the water meter is determined to be in an unstable water supply state at present, indicating the electronic water flow metering component of the water meter to carry out water flow metering operation, improving the water flow metering sensitivity or water flow metering sampling frequency of the electronic water flow metering component, and simultaneously indicating the mechanical water flow metering component of the water meter to stop carrying out water flow operation so as to obtain corresponding water flow metering data.
The beneficial effects of the above technical scheme are: when the water transmission backflow strength value exceeds the maximum water pressure strength value which can be borne by the pipeline of the water supply pipeline, not only certain compression can be generated on the water supply pipeline to cause the deformation of the water supply pipeline, but also the normal water flow metering state of the water meter can be disturbed, because the mechanical water flow metering component and the electronic water flow metering component in the water meter respectively have different metering sensitivity and anti-interference performance, when the water supply pipeline connected with the water meter is determined to be in a stable water supply state, can only indicate the mechanical water flow metering component to perform metering work, otherwise, only indicate the electronic water flow metering component to perform metering work and improve the water flow metering sensitivity or the water flow metering sampling frequency of the electronic water flow metering component, therefore, the water meter can still carry out accurate water flow metering no matter in a stable or unstable water supply state.
Preferably, this water gauge operating condition early warning and adjusting module sends this water flow measurement data to the thing networking high in the clouds and carries out analysis processes to this accuracy of judging this water flow measurement data, and according to the judged result of this accuracy, carry out the early warning and adjust the operating condition of this water gauge and specifically include:
sending the water flow metering data to an internet of things for operation and analysis processing, and correspondingly dividing the water flow metering data into a plurality of water flow meter quantum data of a user in each hour in 24 hours a day;
comparing the water flow meter quantum data with the water flow metering average value obtained from the historical record, if the deviation of the water flow meter quantum data and the water flow metering average value is lower than a preset difference value, determining that the water flow metering data has accuracy, otherwise, determining that the water flow metering data does not have accuracy;
when the water flow metering data is determined to be inaccurate, indicating that the water meter is in an abnormal working state currently, and resetting the water flow metering sensitivity and/or the metering sampling frequency of the water meter to a factory initial state.
The beneficial effects of the above technical scheme are: the water flow metering average value is obtained by recording the historical water consumption of the user, so that the water flow metering average value can truly reflect the water consumption condition of the user at different time intervals in one day, and the water flow meter quantum data is compared with the water flow metering average value, so that whether the water flow metering data is accurate or not can be accurately determined, and the water flow metering sensitivity and/or the metering sampling frequency of the water meter can be conveniently reset subsequently.
As can be seen from the content of the above embodiment, the method and system for early warning the working state of the intelligent internet of things water meter determine the water transmission backflow strength state information inside the water supply pipeline according to the water transmission state information by acquiring the water transmission state information inside the water supply pipeline connected to the water meter, determine the water supply stability of the water supply pipeline connected to the water meter according to the water transmission backflow strength state information, adjust the water flow metering mode of the water meter according to the determination result of the water supply stability, thereby obtaining the corresponding water flow metering data, send the water flow metering data to the cloud of the internet of things for analysis and processing, thereby determining the accuracy of the water flow metering data, and early warning and adjusting the working state of the water meter according to the determination result of the accuracy; therefore, the intelligent Internet of things water meter working state early warning method and system determine the water transmission backflow strength state information in the water supply pipeline according to the water transmission state information, judge the water supply stability of the water supply pipeline, correspondingly adjust the water flow metering mode of the water meter and obtain water flow metering data, and finally early warn and adjust the working state of the water meter according to the water flow metering data, and can timely and effectively early warn and adjust the working state of the water meter under the condition that the water transmission backflow in the water supply pipeline influences the normal metering work of the water meter, so that the reliability and the accuracy of water meter metering are improved to the maximum extent.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. The intelligent Internet of things water meter working state early warning method is characterized by comprising the following steps:
step S1, acquiring water flow transmission state information inside a water supply pipeline connected with the water meter, and determining water transmission reflux intensity state information inside the water supply pipeline according to the water flow transmission state information;
step S2, according to the water transmission reflux intensity state information, judging the water supply stability of the water supply pipeline connected with the water meter, and according to the judgment result of the water supply stability, adjusting the water flow metering mode of the water meter to obtain corresponding water flow metering data;
and S3, sending the water flow metering data to an Internet of things cloud for analysis processing, so as to judge the accuracy of the water flow metering data, and carrying out early warning and adjustment on the working state of the water meter according to the judgment result of the accuracy.
2. The intelligent internet-of-things water meter working state early warning method as claimed in claim 1, characterized in that: in step S1, the acquiring water flow transmission state information inside a water supply pipeline connected to the water meter, and determining the water transmission backflow strength state information inside the water supply pipeline according to the water flow transmission state information specifically includes:
step S101, acquiring water flow velocity distribution state information and water flow direction distribution state information of the interior of the water supply pipeline along the pipeline cross section dimension of the water supply pipeline;
step S102, analyzing and processing the water flow direction distribution state information so as to determine the main flow direction of the water flow in the water supply pipeline, and analyzing and processing the water flow velocity distribution state information so as to determine the average flow velocity of the water flow of the water supply pipeline on the cross section dimension of the pipeline;
and S103, determining a water transmission backflow strength value inside the water supply pipeline along the length direction of the pipeline according to the main water flow direction and the average water flow speed.
3. The intelligent internet-of-things water meter working state early warning method as claimed in claim 2, characterized in that: in step S2, determining the water supply stability of the water supply pipeline connected to the water meter according to the water transmission reflux intensity status information, and adjusting the water flow metering mode of the water meter according to the determination result of the water supply stability, so as to obtain corresponding water flow metering data specifically includes:
step S201, comparing the water transmission backflow strength value with the maximum water pressure strength value borne by the pipeline of the water supply pipeline, if the water transmission backflow strength value is less than or equal to the maximum water pressure strength value borne by the pipeline, determining that the water supply pipeline connected with the water meter is currently in a stable water supply state, otherwise, determining that the water supply pipeline connected with the water meter is currently in an unstable water supply state;
step S202, when the water supply pipeline connected with the water meter is determined to be in a stable water supply state currently, a mechanical water flow metering component of the water meter is instructed to carry out water flow metering operation, and an electronic water flow metering component of the water meter is instructed to stop carrying out water flow metering operation, so that corresponding water flow metering data are obtained;
step S203, when it is determined that the water supply pipeline connected with the water meter is in the unstable water supply state at present, the electronic water flow metering component of the water meter is instructed to perform water flow metering operation, the water flow metering sensitivity or the water flow metering sampling frequency of the electronic water flow metering component is improved, and meanwhile, the mechanical water flow metering component of the water meter is instructed to stop performing water flow operation, so that corresponding water flow metering data are obtained.
4. The intelligent internet-of-things water meter working state early warning method as claimed in claim 3, wherein: in step S3, the water flow measurement data is sent to the internet of things cloud for analysis processing, so as to determine the accuracy of the water flow measurement data, and according to the determination result of the accuracy, the early warning and adjustment of the working state of the water meter specifically include:
step S301, the water flow metering data are sent to the Internet of things for operation and analysis processing, and therefore the water flow metering data are correspondingly divided into a plurality of water flow meter quantum data of a user in each hour in 24 hours a day;
step S302, comparing the water flow meter quantum data with a water flow metering average value obtained from a historical record, if the deviation between the water flow meter quantum data and the water flow metering average value is lower than a preset difference value, determining that the water flow metering data has accuracy, otherwise, determining that the water flow metering data does not have accuracy;
step S303, when it is determined that the water flow metering data does not have accuracy, indicating that the water meter is in an abnormal working state at present, and resetting the water flow metering sensitivity and/or the metering sampling frequency of the water meter to an initial factory state.
5. The intelligent Internet of things water meter working state early warning system is characterized by comprising a water flow transmission state information acquisition module, a water transmission reflux intensity state information determination module, a water flow metering data acquisition module and a water meter working state early warning and adjusting module; wherein the content of the first and second substances,
the water flow transmission state information acquisition module is used for acquiring water flow transmission state information in a water supply pipeline connected with the water meter;
the water transmission reflux intensity state information determining module is used for determining water transmission reflux intensity state information in the water supply pipeline according to the water flow transmission state information;
the water flow metering data acquisition module is used for judging the water supply stability of a water supply pipeline connected with the water meter according to the water transmission backflow strength state information and adjusting a water flow metering mode of the water meter according to the judgment result of the water supply stability so as to acquire corresponding water flow metering data;
the water meter working state early warning and adjusting module is used for sending the water flow metering data to the Internet of things cloud end for analysis processing, so that the accuracy of the water flow metering data is judged, and according to the judgment result of the accuracy, the working state of the water meter is early warned and adjusted.
6. The intelligent internet-of-things water meter working state early warning system as claimed in claim 5, wherein: the water flow transmission state information acquisition module acquires water flow transmission state information inside a water supply pipeline connected with the water meter, and specifically comprises:
acquiring water flow velocity distribution state information and water flow direction distribution state information of the interior of the water supply pipeline along the pipeline cross section dimension of the water supply pipeline;
and the number of the first and second groups,
the water transmission backflow strength state information determining module is used for determining the water transmission backflow strength state information inside the water supply pipeline according to the water flow transmission state information, and specifically comprises the following steps:
analyzing the water flow direction distribution state information so as to determine the main flow direction of water flow in the water supply pipeline, and analyzing the water flow velocity distribution state information so as to determine the average water flow velocity of the water supply pipeline on the cross section dimension of the pipeline;
and determining the water transmission backflow strength value inside the water supply pipeline along the length direction of the pipeline according to the main water flow direction and the average water flow speed.
7. The intelligent internet-of-things water meter working state early warning system as claimed in claim 6, wherein: the water flow measurement data acquisition module judges the water supply stability of a water supply pipeline connected with the water meter according to the water transmission reflux intensity state information, and adjusts the water flow measurement mode of the water meter according to the judgment result of the water supply stability, so as to obtain corresponding water flow measurement data, and the water flow measurement data acquisition module specifically comprises:
comparing the water transmission backflow strength value with a maximum water pressure strength value borne by a pipeline of the water supply pipeline, if the water transmission backflow strength value is less than or equal to the maximum water pressure strength value borne by the pipeline, determining that the water supply pipeline connected with the water meter is currently in a stable water supply state, otherwise, determining that the water supply pipeline connected with the water meter is currently in an unstable water supply state;
when the water supply pipeline connected with the water meter is determined to be in a stable water supply state currently, indicating a mechanical water flow metering component of the water meter to perform water flow metering operation, and simultaneously indicating an electronic water flow metering component of the water meter to stop performing water flow metering operation, so as to obtain corresponding water flow metering data;
and when the water supply pipeline connected with the water meter is determined to be in an unstable water supply state at present, indicating an electronic water flow metering component of the water meter to perform water flow metering operation, improving the water flow metering sensitivity or water flow metering sampling frequency of the electronic water flow metering component, and simultaneously indicating a mechanical water flow metering component of the water meter to stop performing water flow operation so as to obtain corresponding water flow metering data.
8. The intelligent internet-of-things water meter working state early warning system as claimed in claim 7, wherein: the water gauge operating condition early warning and adjusting module will water flow measurement data send to the thing networking high in the clouds and carry out analysis processes to this judgement water flow measurement data's accuracy, and according to the judged result of accuracy, it is right the operating condition of water gauge carries out the early warning and adjusts and specifically includes:
sending the water flow metering data to an internet of things for operation and analysis processing, and correspondingly dividing the water flow metering data into a plurality of water flow meter quantum data of a user in each hour in 24 hours a day;
comparing the water flow meter quantum data with a water flow metering average value obtained by a historical record, if the deviation of the water flow meter quantum data and the water flow metering average value is lower than a preset difference value, determining that the water flow metering data has accuracy, otherwise, determining that the water flow metering data does not have accuracy;
and when the water flow metering data is determined to be inaccurate, indicating that the water meter is in an abnormal working state currently, and resetting the water flow metering sensitivity and/or the metering sampling frequency of the water meter to an initial factory state.
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