CN113532598A - Online fault detection and regulation system of intelligent water meter - Google Patents
Online fault detection and regulation system of intelligent water meter Download PDFInfo
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Abstract
The invention discloses an intelligent water meter online fault detection and regulation system which comprises a fault analysis module, a fault recognition module, an operation detection module, a water meter detection module, a detection platform, a cloud database and a user login unit, wherein a signal input module is electrically connected with a signal processing module through a lead, the detection platform generates a fault signal and sends the fault signal to the fault analysis module after receiving a normal water meter, a corresponding operation detection coefficient, a normal water meter and a corresponding device detection coefficient, and the fault analysis module performs fault analysis on the water meter after receiving the fault signal. This online fault detection governing system of intelligent water gauge has solved and has detected governing system and when carrying out work, has the hysteresis quality, appears the problem of misreport and missing reporting easily, through inside fault identification and analysis module, can be better to the screening detection of trouble, reduce the condition that the wrong report appears, adopt the analysis of big data simultaneously, reduce the appearance of the condition of missing reporting.
Description
Technical Field
The invention relates to the technical field of intelligent water meters, in particular to an online fault detection and regulation system for an intelligent water meter.
Background
The intelligent water meter is a novel water meter which measures the water consumption by using the modern microelectronic technology, the modern sensing technology and the intelligent IC card technology and carries out water consumption data transmission and settlement transaction, compared with the traditional water meter which only has the functions of flow acquisition and mechanical pointer display of the water consumption, the intelligent water meter is a great progress, the water consumption can be controlled according to convention besides being recorded and electronically displayed, the water charge calculation of the step water price can be automatically completed, the water consumption data storage function can be carried out, the intelligent water meter fundamentally changes the traditional meter reading mode, the charging mode of card water consumption is realized, on the basis of saving a large amount of manpower, the problem of water charge default which puzzles the water supply industry for a long time is solved, and therefore, the novel water meter can directly bring huge economic benefits to the water supply industry.
In order to increase the protection to intelligent water gauge, need regularly overhaul it and maintain, but adopt the manual work to patrol and examine the cost higher, artificial speed is slower, accurate location can't be accomplished, when breaking down, can't make accurate judgement, simultaneously along with the continuous development of internet, more and more working methods can be accomplished through the internet, and common detection governing system is when carrying out work, be after equipment goes wrong, just indicate, not only there is certain hysteresis in the information, and the condition of reporting missing is reported to the wrong report appears easily, increase maintenance personal's work load, the result of use is not good.
Disclosure of Invention
The invention aims to provide an online fault detection and regulation system for an intelligent water meter, and aims to solve the problems that in the background technology, in order to increase the protection of the intelligent water meter, the intelligent water meter needs to be overhauled and maintained regularly, but the manual inspection cost is high, the manual inspection speed is low, the accurate positioning cannot be realized, when a fault occurs, the accurate judgment cannot be made, and along with the continuous development of the internet, more and more working modes can be completed through the internet, and when a common detection and regulation system works, the prompt is only carried out after the equipment has a problem, so that not only is the information lagged to a certain extent, but also the situations of misinformation and missing report easily occur, the workload of maintenance personnel is increased, and the using effect is not good.
In order to achieve the purpose, the invention provides the following technical scheme: online fault detection governing system of intelligence water gauge, including fault analysis module, trouble recognition module, operation detection module, water gauge detection module, testing platform, high in the clouds database, user login unit, its characterized in that: the cloud database is internally provided with a signal input module and a signal processing module, the signal input module is electrically connected with the signal processing module through a wire, the signal processing module is electrically connected with the fault analysis module through a wire, the signal input module comprises a first signal input unit, a second signal input unit and a third signal input unit, the signal processing module comprises a first signal processing unit, a second signal processing unit and a third signal processing unit, the first signal processing unit is connected with the first signal input unit, the second signal processing unit is connected with the second signal input unit, and the third signal processing unit is connected with a plurality of third signal input units; the first signal processing unit, the second signal processing unit and the third signal processing unit are respectively connected with the fault analysis module, the detection platform generates a fault signal and sends the fault signal to the fault analysis module after receiving the normal water meter and the corresponding operation detection coefficient as well as the normal water meter and the corresponding device detection coefficient, the fault analysis module analyzes the fault of the water meter after receiving the fault signal,
the fault analysis module is used for carrying out fault judgment on the intelligent water meter, specifically, the fault analysis process is as follows, the intelligent water meter is marked as i, i =1, 2, … …, n and n are positive integers, a detection time period is set, the detection time period is marked as o, o =1, 2, … …, m and m are positive integers, and then the water supply pressure of the intelligent water meter in each time period is obtainedAnd marking the water supply pressure of the intelligent water meter in each time period as Vio, acquiring the water supply pressure of the intelligent water meter in each time period, marking the water supply pressure of the intelligent water meter in each time period as Iio, and calculating the water supply pressure of the intelligent water meter in each time period by using a formula
Obtaining the average pressure difference Xi of the intelligent water meter in the detection time period, wherein u is the rated water supply pressure and passes through the formula
Obtaining the average flow supply difference Ci in the detection time period of the intelligent water meter through a formula
2Obtaining the dispersion coefficient Di of the average pressure supply difference in the detection time period of the intelligent water meter through a formula
2Obtaining a discrete coefficient Fi of an average flow supply difference in an intelligent water meter detection time period, and comparing the average flow supply difference Xi and a corresponding discrete coefficient Di in the intelligent water meter detection time period, and the average flow supply difference Ci and a corresponding discrete coefficient Fi in the intelligent water meter detection time period with x, d, c and f respectively, wherein x is an average pressure supply difference threshold value, d is an average pressure supply difference discrete coefficient threshold value, c is an average flow supply difference threshold value, and f is an average flow supply difference discrete coefficient threshold value: if the average pressure supply difference Xi and the corresponding discrete coefficient Di in the detection time period of the intelligent water meter, the average flow supply difference Ci and the corresponding discrete coefficient Fi in the detection time period of the intelligent water meter are smaller than or equal to the corresponding threshold values x, d, c and f, judging that the intelligent water meter has no fault, if any coefficient of the average pressure supply difference Xi in the detection time period of the intelligent water meter and the average flow supply difference Ci in the detection time period of the intelligent water meter is larger than the corresponding threshold values x and c, judging that the intelligent water meter device has abnormity, generating a device detection signal and sending the device detection signal to a cloud detection platform, and if the average pressure supply difference in the detection time period of the intelligent water meter corresponds to the discrete coefficient Di and the average flow supply difference in the detection time period of the intelligent water meter is larger than the corresponding to the discrete coefficient DiAnd if any coefficient of the average flow supply difference corresponding to the discrete coefficient Fi is larger than the corresponding threshold values d and f, judging that the intelligent water meter is abnormal in operation, generating an operation detection signal and sending the operation detection signal to the detection platform.
Preferably, the specific detection method of the water meter detection module is as follows: acquiring energy consumption data of each water meter, wherein the energy consumption data comprise electricity consumption on the intelligent water meter and tap water consumption collected by the water meter, generating statistical data according to the consumption data, judging whether the energy consumption of each water meter is in a preset range or not according to a fault analysis module on a detection platform, outputting an alarm signal when the energy consumption data of the water meter exceeds the preset range, prompting a user of the intelligent water meter, generating a preset energy consumption curve of each water meter according to energy consumption equipment parameters, indicating the relation between the energy consumption of energy consumption equipment of the water meter and time in a preset time period according to the energy consumption data, generating an energy consumption statistical graph according to the energy consumption data, and judging whether the energy consumption is in the preset range or not according to the energy consumption statistical graph, wherein the steps of: and generating an actual energy consumption curve according to the energy consumption data, and comparing the actual energy consumption curve with a preset energy consumption curve to judge whether the energy consumption of each water meter is in a preset range.
Preferably, the specific identification process of the fault identification module is as follows: obtaining respective working state data of a plurality of current intelligent water meters, determining difference data of the intelligent water meters and other intelligent water meters when the intelligent water meters and other intelligent water meters work according to the working state data of the intelligent water meters and the working state data of other intelligent water meters for each intelligent water meter, comparing the difference data with detection platform data to detect whether the intelligent water meters break down or not according to the difference data, determining that equipment breaks down if the difference data is larger than a set threshold, determining that the equipment does not break down if the difference data is not larger than the set threshold, obtaining respective comprehensive data of the plurality of intelligent water meters historically positioned in a preset area for each preset area, determining a difference value between respective comprehensive data results of the plurality of intelligent water meters currently positioned in the preset area and respective comprehensive data results of the plurality of intelligent water meters historically positioned in the preset area, and if the difference value is larger than the set threshold, and determining that the environment of the preset area is abnormal, and if the difference value is not greater than a set threshold value, determining that the environment of the preset area is normal.
Preferably, the fault analysis module includes a plurality of distributed probes, and the plurality of distributed probes are disposed in a link of the first signal processing unit, the second signal processing unit, and the third signal processing unit.
Compared with the prior art, the invention has the beneficial effects that: the intelligent water meter on-line fault detection and regulation system can better screen and detect faults through an internal fault identification and analysis module, reduce the situation of false alarm, better identify faults and reduce the situation of missed alarm by acquiring the energy consumption data of each water meter, wherein the energy consumption data comprises the electricity consumption on the intelligent water meter and the water consumption of tap water collected by the water meter, generate statistical data according to the consumption data, output an alarm signal when the energy consumption data of the water meter exceeds a preset range according to whether the energy consumption of each water meter is in the preset range or not through the fault analysis module on a detection platform, prompt a user of the intelligent water meter to acquire the current working state data of each intelligent water meter, and aim at each intelligent water meter according to the working state data of the intelligent water meter and the working state data of other intelligent water meters, determining difference data of the intelligent water meter and other intelligent water meters during working, comparing the difference data with detection platform data according to the difference data, detecting whether the intelligent water meter has a fault or not, if the difference data is larger than a set threshold, determining that the equipment has a fault, if the difference data is not larger than the set threshold, determining that the equipment does not have a fault, aiming at each preset area, obtaining respective comprehensive data of a plurality of intelligent water meters historically positioned in the preset area, determining a difference value between respective comprehensive data results of the plurality of intelligent water meters currently positioned in the preset area and respective comprehensive data results of the plurality of intelligent water meters historically positioned in the preset area, if the difference value is larger than the set threshold, determining that the environment of the preset area is abnormal, if the difference value is not larger than the set threshold, determining that the environment of the preset area is normal, and improving the use effect of the system.
Drawings
FIG. 1 is a schematic diagram of the overall architecture of the present invention;
FIG. 2 is a schematic structural diagram of a cloud database workflow of the present invention;
FIG. 3 is a schematic structural diagram of a fault identification module according to the present invention;
fig. 4 is a schematic structural diagram of a fault analysis module according to the present 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.
Referring to fig. 1-4, the present invention provides a technical solution: online fault detection governing system of intelligence water gauge, including fault analysis module, trouble recognition module, operation detection module, water gauge detection module, testing platform, high in the clouds database, user login unit, its characterized in that: the cloud database is internally provided with a signal input module and a signal processing module, the signal input module is electrically connected with the signal processing module through a wire, the signal processing module is electrically connected with the fault analysis module through a wire, the signal input module comprises a first signal input unit, a second signal input unit and a third signal input unit, the signal processing module comprises a first signal processing unit, a second signal processing unit and a third signal processing unit, the first signal processing unit is connected with the first signal input unit, the second signal processing unit is connected with the second signal input unit, and the third signal processing unit is connected with a plurality of third signal input units; the first signal processing unit, the second signal processing unit and the third signal processing unit are respectively connected with the fault analysis module, the detection platform generates a fault signal and sends the fault signal to the fault analysis module after receiving the normal water meter and the corresponding operation detection coefficient and the normal water meter and the corresponding device detection coefficient, the fault analysis module analyzes the fault of the water meter after receiving the fault signal,
the fault analysis module is used for carrying out fault judgment on the intelligent water meter, the specific judgment and analysis process is as follows, the intelligent water meter is marked as i, i =1, 2, … …, n and n are positive integers, a detection time period is set and marked as o, o =1, 2, … …, m and m are positive integers, then the water supply pressure of the intelligent water meter in each time period is obtained, the water supply pressure of the intelligent water meter in each time period is marked as Vio, the water supply pressure of the intelligent water meter in each time period is obtained, the water supply pressure of the intelligent water meter in each time period is marked as Iio, and the water supply pressure of the intelligent water meter in each time period is marked as Iio through a formula
Obtaining the average pressure difference Xi of the intelligent water meter in the detection time period, wherein u is the rated water supply pressure and passes through the formula
Obtaining the average flow supply difference Ci in the detection time period of the intelligent water meter through a formula
2Obtaining the dispersion coefficient Di of the average pressure supply difference in the detection time period of the intelligent water meter through a formula
2Obtaining a discrete coefficient Fi of an average flow supply difference in an intelligent water meter detection time period, and comparing the average flow supply difference Xi and a corresponding discrete coefficient Di in the intelligent water meter detection time period, and the average flow supply difference Ci and a corresponding discrete coefficient Fi in the intelligent water meter detection time period with x, d, c and f respectively, wherein x is an average pressure supply difference threshold value, d is an average pressure supply difference discrete coefficient threshold value, c is an average flow supply difference threshold value, and f is an average flow supply difference discrete coefficient threshold value: if the average pressure supply difference Xi and the corresponding discrete coefficient Di in the detection time period of the intelligent water meter, and the average flow supply difference Ci and the corresponding discrete coefficient Fi in the detection time period of the intelligent water meter are all smaller than or equal to the corresponding threshold values x, d, c and f, judging that the intelligent water meter is in a state of being used for measuring the flow rate of the waterIf any coefficient of the average pressure supply difference Xi in the detection time period of the intelligent water meter and the average flow supply difference Ci in the detection time period of the intelligent water meter is larger than the corresponding threshold values x and c, judging that the intelligent water meter device is abnormal, generating a device detection signal and sending the device detection signal to a cloud detection platform, and if any coefficient of the average pressure supply difference corresponding discrete coefficient Di in the detection time period of the intelligent water meter and the average flow supply difference corresponding discrete coefficient Fi in the detection time period of the intelligent water meter is larger than the corresponding threshold values d and f, judging that the intelligent water meter is abnormal in operation, generating an operation detection signal and sending the operation detection signal to the detection platform;
further, a specific detection method of the water meter detection module is as follows: acquiring energy consumption data of each water meter, wherein the energy consumption data comprises electricity consumption on the intelligent water meter and tap water consumption collected by the water meter, generating statistical data according to the consumption data, and judging whether the energy consumption of each water meter is in a preset range or not according to a fault analysis module on a detection platform, outputting an alarm signal when the energy consumption data of the water meter exceeds the preset range, prompting a user of the intelligent water meter, wherein the energy consumption data comprises electricity consumption parameters, water consumption parameters and a use time period of each water meter, generating a preset energy consumption curve of each water meter according to energy consumption equipment parameters, the preset energy consumption curve represents the relation between energy consumption equipment energy consumption and time of the water meter in a preset time period, generating an energy consumption statistical graph according to the energy consumption data, and judging whether the energy consumption is in the preset range or not according to the energy consumption statistical graph comprises the following steps: generating an actual energy consumption curve according to the energy consumption data, and comparing the actual energy consumption curve with a preset energy consumption curve to judge whether the energy consumption of each water meter is in a preset range;
further, the specific identification process of the fault identification module is as follows: obtaining respective working state data of a plurality of current intelligent water meters, determining difference data of the intelligent water meters and other intelligent water meters when the intelligent water meters and other intelligent water meters work according to the working state data of the intelligent water meters and the working state data of other intelligent water meters for each intelligent water meter, comparing the difference data with detection platform data to detect whether the intelligent water meters break down or not according to the difference data, determining that equipment breaks down if the difference data is larger than a set threshold, determining that the equipment does not break down if the difference data is not larger than the set threshold, obtaining respective comprehensive data of the plurality of intelligent water meters historically positioned in a preset area for each preset area, determining a difference value between respective comprehensive data results of the plurality of intelligent water meters currently positioned in the preset area and respective comprehensive data results of the plurality of intelligent water meters historically positioned in the preset area, and if the difference value is larger than the set threshold, determining that the environment of the preset area is abnormal, and if the difference value is not greater than a set threshold value, determining that the environment of the preset area is normal;
further, the fault analysis module comprises a plurality of distributed probes, and the plurality of distributed probes are arranged in a link of the first signal processing unit, the second signal processing unit and the third signal processing unit.
The working principle is as follows: recording the intelligent water meter as i, i =1, 2, … …, n, n is a positive integer, setting a detection time period and marking the detection time period as o, o =1, 2, … …, m, m is a positive integer, then acquiring the water supply pressure of the intelligent water meter in each time period, marking the water supply pressure of the intelligent water meter in each time period as Vio, acquiring the water supply pressure of the intelligent water meter in each time period, marking the water supply pressure of the intelligent water meter in each time period as Iio, and calculating the water supply pressure of the intelligent water meter in each time period according to a formula
Obtaining the average pressure difference Xi of the intelligent water meter in the detection time period, wherein u is the rated water supply pressure and passes through the formula
Obtaining the average flow supply difference Ci in the detection time period of the intelligent water meter through a formula
2Obtaining the dispersion coefficient Di of the average pressure supply difference in the detection time period of the intelligent water meter through a formula
2Obtaining average in detection time period of intelligent water meterAnd comparing the average pressure supply difference Xi and the corresponding discrete coefficient Di in the detection time period of the intelligent water meter, and the average flow supply difference Ci and the corresponding discrete coefficient Fi in the detection time period of the intelligent water meter with x, d, c and f respectively, wherein x is an average pressure supply difference threshold value, d is an average pressure supply difference discrete coefficient threshold value, c is an average flow supply difference threshold value, and f is an average flow supply difference discrete coefficient threshold value: if the average pressure supply difference Xi and the corresponding discrete coefficient Di in the detection time period of the intelligent water meter, the average flow supply difference Ci and the corresponding discrete coefficient Fi in the detection time period of the intelligent water meter are less than or equal to the corresponding threshold values x, d, c and f, judging that the intelligent water meter has no fault, if any coefficient of the average pressure supply difference Xi in the detection time period of the intelligent water meter and the average flow supply difference Ci in the detection time period of the intelligent water meter is greater than the corresponding threshold values x and c, judging that the intelligent water meter has an abnormal device, generating a device detection signal and sending the device detection signal to a cloud detection platform, if any coefficient of the average pressure supply difference Di in the detection time period of the intelligent water meter and the average flow supply difference Fi in the detection time period of the intelligent water meter is greater than the corresponding threshold values d and f, judging that the intelligent water meter has an abnormal operation, generating an operation detection signal and sending the operation detection signal to the detection platform, acquiring energy consumption data of each water meter, wherein the energy consumption data comprises electricity consumption on the intelligent water meter and tap water consumption collected by the water meter, generating statistical data according to the consumption data, and judging whether the energy consumption of each water meter is in a preset range or not according to a fault analysis module on a detection platform, outputting an alarm signal when the energy consumption data of the water meter exceeds the preset range, prompting a user of the intelligent water meter, wherein the energy consumption data comprises electricity consumption parameters, water consumption parameters and a use time period of each water meter, generating a preset energy consumption curve of each water meter according to energy consumption equipment parameters, the preset energy consumption curve represents the relation between energy consumption equipment energy consumption and time of the water meter in a preset time period, generating an energy consumption statistical graph according to the energy consumption data, and judging whether the energy consumption is in the preset range or not according to the energy consumption statistical graph comprises the following steps: generating an actual energy consumption curve according to the energy consumption data, and comparing the actual energy consumption curve with a preset energy consumption curve to judge whether the energy consumption of each water meter is in a preset range to obtain a plurality of current water metersThe respective working state data of the intelligent water meters, aiming at each intelligent water meter, determining the difference data of the intelligent water meter and other intelligent water meters when the intelligent water meter and other intelligent water meters work according to the working state data of the intelligent water meter and the working state data of other intelligent water meters, comparing the difference data with the detection platform data according to the difference data to detect whether the intelligent water meter has a fault or not, if the difference data is larger than a set threshold value, determining that the equipment has no fault, if the difference data is not larger than the set threshold value, acquiring the respective comprehensive data of a plurality of intelligent water meters historically positioned in the preset area aiming at each preset area, determining the difference value between the respective comprehensive data result of the plurality of intelligent water meters currently positioned in the preset area and the respective comprehensive data result of the plurality of intelligent water meters historically positioned in the preset area, if the difference value is larger than the set threshold value, and determining that the environment of the preset area is abnormal, and if the difference value is not greater than a set threshold value, determining that the environment of the preset area is normal.
Finally, it should be noted that the above-mentioned contents are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, and that the simple modifications or equivalent substitutions of the technical solutions of the present invention by those of ordinary skill in the art can be made without departing from the spirit and scope of the technical solutions of the present invention.
Claims (4)
1. Online fault detection governing system of intelligence water gauge, including fault analysis module, trouble recognition module, operation detection module, water gauge detection module, testing platform, high in the clouds database, user login unit, its characterized in that: the cloud database is internally provided with a signal input module and a signal processing module, the signal input module is electrically connected with the signal processing module through a wire, the signal processing module is electrically connected with the fault analysis module through a wire, the signal input module comprises a first signal input unit, a second signal input unit and a third signal input unit, the signal processing module comprises a first signal processing unit, a second signal processing unit and a third signal processing unit, the first signal processing unit is connected with the first signal input unit, the second signal processing unit is connected with the second signal input unit, and the third signal processing unit is connected with a plurality of third signal input units; the first signal processing unit, the second signal processing unit and the third signal processing unit are respectively connected with the fault analysis module, the detection platform generates a fault signal and sends the fault signal to the fault analysis module after receiving the normal water meter and the corresponding operation detection coefficient as well as the normal water meter and the corresponding device detection coefficient, the fault analysis module analyzes the fault of the water meter after receiving the fault signal,
the fault analysis module is used for carrying out fault judgment on the intelligent water meter, the specific judgment and analysis process is as follows, the intelligent water meter is recorded as i, i =1, 2, … …, n and n are positive integers, a detection time period is set, the detection time period is marked as o, o =1, 2, … … and m, and m is a positive integer, the water supply pressure of the intelligent water meter in each time period is obtained subsequently, the water supply pressure of the intelligent water meter in each time period is marked as Vio, the water supply pressure of the intelligent water meter in each time period is obtained, the water supply pressure of the intelligent water meter in each time period is marked as Iio, and the water supply pressure of the intelligent water meter in each time period is marked as Iio through a formula
Obtaining the average pressure difference Xi of the intelligent water meter in the detection time period, wherein u is the rated water supply pressure and passes through the formula
Obtaining the average flow supply difference Ci in the detection time period of the intelligent water meter through a formula
2Obtaining the dispersion coefficient Di of the average pressure supply difference in the detection time period of the intelligent water meter through a formula
2Obtaining a discrete coefficient Fi of an average flow supply difference in an intelligent water meter detection time period, and providing the average flow supply in the intelligent water meter detection time periodThe differential pressure Xi and the corresponding discrete coefficient Di, and the average flow supply difference Ci and the corresponding discrete coefficient Fi in the detection time period of the intelligent water meter are respectively and correspondingly compared with x, d, c and f, wherein x is an average differential pressure supply threshold value, d is an average differential pressure supply discrete coefficient threshold value, c is an average differential flow supply threshold value, and f is an average differential flow supply discrete coefficient threshold value: if the average pressure supply difference Xi and the corresponding discrete coefficient Di in the detection time period of the intelligent water meter, and the average flow supply difference Ci and the corresponding discrete coefficient Fi in the detection time period of the intelligent water meter are less than or equal to the corresponding threshold values x, d, c and f, judging that the intelligent water meter has no fault, if any coefficient of the average pressure difference Xi in the detection time period of the intelligent water meter and the average flow difference Ci in the detection time period of the intelligent water meter is larger than the corresponding threshold value x and c, judging that the intelligent water meter device is abnormal, generating a device detection signal and sending the device detection signal to the cloud detection platform, if any coefficient of the dispersion coefficient Di corresponding to the average supply pressure difference in the detection time period of the intelligent water meter and the dispersion coefficient Fi corresponding to the average supply flow difference in the detection time period of the intelligent water meter is larger than the corresponding threshold values d and f, and judging that the intelligent water meter is abnormal in operation, generating an operation detection signal and sending the operation detection signal to the detection platform.
2. The intelligent water meter on-line fault detection and regulation system of claim 1, wherein: the specific detection method of the water meter detection module is as follows: acquiring energy consumption data of each water meter, wherein the energy consumption data comprise electricity consumption on the intelligent water meter and tap water consumption collected by the water meter, generating statistical data according to the consumption data, judging whether the energy consumption of each water meter is in a preset range or not according to a fault analysis module on a detection platform, outputting an alarm signal when the energy consumption data of the water meter exceeds the preset range, prompting a user of the intelligent water meter, generating a preset energy consumption curve of each water meter according to energy consumption equipment parameters, indicating the relation between the energy consumption of energy consumption equipment of the water meter and time in a preset time period according to the energy consumption data, generating an energy consumption statistical graph according to the energy consumption data, and judging whether the energy consumption is in the preset range or not according to the energy consumption statistical graph, wherein the steps of: and generating an actual energy consumption curve according to the energy consumption data, and comparing the actual energy consumption curve with a preset energy consumption curve to judge whether the energy consumption of each water meter is in a preset range.
3. The intelligent water meter on-line fault detection and regulation system of claim 1, wherein: the specific identification process of the fault identification module is as follows: obtaining respective working state data of a plurality of current intelligent water meters, determining difference data of the intelligent water meters and other intelligent water meters when the intelligent water meters and other intelligent water meters work according to the working state data of the intelligent water meters and the working state data of other intelligent water meters for each intelligent water meter, comparing the difference data with detection platform data to detect whether the intelligent water meters break down or not according to the difference data, determining that equipment breaks down if the difference data is larger than a set threshold, determining that the equipment does not break down if the difference data is not larger than the set threshold, obtaining respective comprehensive data of the plurality of intelligent water meters historically positioned in a preset area for each preset area, determining a difference value between respective comprehensive data results of the plurality of intelligent water meters currently positioned in the preset area and respective comprehensive data results of the plurality of intelligent water meters historically positioned in the preset area, and if the difference value is larger than the set threshold, and determining that the environment of the preset area is abnormal, and if the difference value is not greater than a set threshold value, determining that the environment of the preset area is normal.
4. The intelligent water meter on-line fault detection and regulation system of claim 1, wherein: the fault analysis module comprises a plurality of distributed probes, and the distributed probes are arranged in a link of the first signal processing unit, the second signal processing unit and the third signal processing unit.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117034044A (en) * | 2023-10-09 | 2023-11-10 | 山东朝启电子科技有限公司 | Intelligent meter management system based on data intelligence |
| CN117077058A (en) * | 2023-08-29 | 2023-11-17 | 广东青藤环境科技有限公司 | Intelligent business charge management system based on water consumption data analysis |
| CN117490810A (en) * | 2023-12-29 | 2024-02-02 | 浙江黄氏建设科技股份有限公司 | Water meter remote monitoring method and system based on positioning information |
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| CN117686068A (en) * | 2023-12-13 | 2024-03-12 | 京源中科科技股份有限公司 | Intelligent water meter communication abnormality detection method, device, equipment and storage medium |
| CN117490810A (en) * | 2023-12-29 | 2024-02-02 | 浙江黄氏建设科技股份有限公司 | Water meter remote monitoring method and system based on positioning information |
| CN117490810B (en) * | 2023-12-29 | 2024-03-22 | 浙江黄氏建设科技股份有限公司 | Water meter remote monitoring method and system based on positioning information |
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