CN117367533A - Internet of things intelligent water meter fault diagnosis method, device and equipment - Google Patents
Internet of things intelligent water meter fault diagnosis method, device and equipment Download PDFInfo
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- 238000003745 diagnosis Methods 0.000 title claims abstract description 53
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- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
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Abstract
The application discloses a fault diagnosis method, device and equipment for an intelligent water meter of the Internet of things, wherein the method comprises the following steps: detecting whether the target water meter has abnormal information; if the abnormal information exists, identifying the abnormal type of the abnormal information; the abnormal type comprises a first abnormal type and a second abnormal type, wherein the first abnormal type is idle running of the water meter, and the second abnormal type is stalling of the water meter; if the first abnormal type is identified, first fault information corresponding to the first abnormal type is obtained; the first fault information comprises a first fault reason for causing the water meter to idle; if the first abnormal type is identified, obtaining second fault information corresponding to the first abnormal type; the second fault information comprises a second fault reason for causing the water meter to stop running; outputting a fault diagnosis report; the fault diagnosis report contains the first fault information or the second fault information, and the method has the advantages of effectively diagnosing the fault reason of the water meter and being beneficial to follow-up targeted maintenance.
Description
Technical Field
The application relates to the technical field of water meter fault detection, in particular to an intelligent water meter fault diagnosis method, device and equipment for the Internet of things.
Background
The intelligent water meter is a novel water meter which utilizes modern microelectronic technology, modern sensing technology and intelligent IC card technology to meter water consumption and conduct water consumption data transmission and settlement transaction, and has great progress compared with the traditional water meter which generally only has the functions of flow collection and mechanical pointer display of water consumption.
Various fault problems possibly occur in the use process of the intelligent water meter, so that the intelligent water meter needs to be monitored in real time, the existing monitoring method only can monitor whether the water meter has faults or not and then gives an alarm, but the effective diagnosis of the fault cause cannot be performed, and a worker or a user is required to check and diagnose by himself, so that the workload is increased, the working efficiency is low, the intelligent management is not facilitated, and the user experience is still to be further improved.
Disclosure of Invention
The main purpose of the application is to provide a fault diagnosis method, device and equipment for an intelligent water meter of the Internet of things, and aims to solve the technical problem that the existing fault monitoring method for the water meter cannot effectively diagnose the fault cause.
In order to achieve the above purpose, the present application provides a fault diagnosis method for an intelligent water meter of the internet of things, comprising the following steps:
detecting whether the target water meter has abnormal information;
if the abnormal information exists, identifying the abnormal type of the abnormal information; the abnormal type comprises a first abnormal type and a second abnormal type, wherein the first abnormal type is idle running of the water meter, and the second abnormal type is stalling of the water meter;
if the first abnormal type is identified, first fault information corresponding to the first abnormal type is obtained; the first fault information comprises a first fault reason for causing the water meter to idle;
if the first abnormal type is identified, obtaining second fault information corresponding to the first abnormal type; the second fault information comprises a second fault reason for causing the water meter to stop running;
outputting a fault diagnosis report; the fault diagnosis report contains first fault information or second fault information.
Optionally, the first fault information includes at least one of water pressure abnormality information and water leakage fault information, and the first fault cause includes at least one of water pressure abnormality and water leakage fault;
obtaining first fault information corresponding to a first abnormal type, including:
acquiring the local water pressure corresponding to the target water meter, and acquiring abnormal water pressure information if the local water pressure is greater than the preset standard water pressure; the standard water pressure is the water pressure range in which the target water meter can normally operate;
acquiring an instantaneous flow value corresponding to the target water meter, and acquiring water leakage fault information if the instantaneous flow value is greater than a preset dynamic flow threshold value; the dynamic flow threshold is a flow value set according to different time nodes.
Optionally, the first fault information further includes electromagnetic interference fault information, and the first fault cause further includes electromagnetic interference fault;
acquiring first fault information corresponding to the first abnormal type, and further comprising:
and acquiring the electromagnetic interference intensity of the surrounding environment of the target water meter, and acquiring electromagnetic interference fault information if the electromagnetic interference intensity is greater than the anti-interference intensity of the target water meter.
Optionally, after obtaining the first fault information corresponding to the first anomaly type, the method further includes:
acquiring a water pressure anomaly coefficient delta 1 ，δ 1 ＝ε 1 *Δ 1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε 1 For the first conversion coefficient, if the local water pressure is within the standard water pressure range, epsilon 1 ＝0，Δ 1 Is the difference between the local water pressure and the standard water pressure;
obtaining a water leakage fault coefficient delta 2 ，δ 2 ＝ε 2 *Δ 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε 2 For the first conversion coefficient, ε if the instantaneous flow value is within the dynamic flow threshold 2 ＝0，Δ 2 Is the difference between the instantaneous flow value and the dynamic flow threshold;
acquiring electromagnetic interference fault coefficient delta 3 ，δ 3 ＝ε 3 *Δ 3 The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε 3 For the first conversion coefficient, if electromagneticThe interference strength is smaller than the anti-interference strength, epsilon 3 ＝0，Δ 3 Is the electromagnetic interference intensity;
obtaining fault level coefficients delta, delta=delta 1 +δ 2 +δ 3 ；
The fault level coefficient delta is added to the fault diagnosis report.
Optionally, the second fault information includes at least one of a blocking fault information and a counter operation fault information, and the second fault cause includes at least one of a blocking fault and a counter operation fault;
obtaining second fault information corresponding to a second abnormal type includes:
detecting the impurity content condition in a main pipeline connected with a target water meter to obtain blockage fault information;
and detecting the running condition of a counter in the target water meter to acquire the running fault information of the counter.
Optionally, if congestion fault information or counter operation fault information is obtained, the method further includes the following steps:
acquiring an operation video of a target water meter within a preset time;
decomposing the operation video frame by frame to obtain a plurality of water meter images;
extracting water meter reading information corresponding to a plurality of water meter images;
and identifying whether the plurality of water meter reading information has change, and if the plurality of water meter reading information has no change, judging that the second fault information exists.
Optionally, detecting a sundry content condition in a main pipeline connected to the target water meter to obtain blocking fault information, including:
acquiring initial water flow in a main pipeline;
obtaining the water outlet flow in the branch pipeline; wherein the branch pipeline is connected with the main pipeline;
and acquiring a flow difference value between the initial water flow and the outlet water flow, and acquiring blocking fault information if the flow difference value is larger than a preset flow standard threshold value.
Optionally, detecting whether the target water meter has abnormal information includes:
acquiring operation monitoring data of a target water meter;
acquiring operation standard data of a preset standard table;
comparing the operation monitoring data with the operation standard data and obtaining a comparison result;
if the comparison results are different, judging that the target water meter has abnormal information.
In order to achieve the above object, the present application further provides an intelligent water meter fault diagnosis device, including:
the abnormality detection module is used for detecting whether the target water meter has abnormality information or not;
the abnormal type identification module is used for identifying the abnormal type of the abnormal information if the abnormal information exists; the abnormal type comprises a first abnormal type and a second abnormal type, wherein the first abnormal type is idle running of the water meter, and the second abnormal type is stalling of the water meter;
the first acquisition module is used for acquiring first fault information corresponding to the first abnormal type if the first abnormal type is identified; the first fault information comprises a first fault reason for causing the water meter to idle;
the second acquisition module is used for acquiring second fault information corresponding to the second abnormal type if the second abnormal type is identified; the second fault information comprises a second fault reason for causing the water meter to stop running;
the output module is used for outputting a fault diagnosis report; the fault diagnosis report contains first fault information or second fault information.
To achieve the above object, the present application further provides a computer device, which includes a memory and a processor, where the memory stores a computer program, and the processor executes the computer program to implement the above method.
To achieve the above object, the present application further provides a computer readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement the above method.
The beneficial effects that this application can realize are as follows:
according to the method and the system, after abnormal information of the target water meter is detected, the abnormal types of the abnormal information are further screened and identified, the abnormal types mainly comprise two most common types of water meter idling and water meter stalling, if the abnormal types of the water meter idling are identified, the fault cause causing the water meter idling is further identified, corresponding first fault information can be generated, and similarly, if the abnormal types of the water meter stalling are identified, the fault cause causing the water meter stalling is further identified, corresponding second fault information can be generated, and the first fault information or the second fault information can generate a corresponding fault diagnosis report, so that effective diagnosis of the water meter fault cause is achieved, a follow-up manager or a user can quickly determine the water meter fault cause according to the fault diagnosis report, corresponding maintenance work is timely performed, and accordingly, the method and the system is high in pertinence, convenient to intelligent management and user experience is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are used in the description of the embodiments or the prior art will be briefly described below. Like elements or portions are generally identified by like reference numerals throughout the several figures. In the drawings, elements or portions thereof are not necessarily drawn to scale.
FIG. 1 is a schematic diagram of a computer device architecture of a hardware operating environment involved in an embodiment of the present application;
fig. 2 is a schematic flow chart of a fault diagnosis method of an intelligent water meter of the internet of things in an embodiment of the application;
fig. 3 is a schematic frame diagram of an internet of things system according to an embodiment of the present application.
The realization, functional characteristics and advantages of the present application will be further described with reference to the embodiments, referring to the attached drawings.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that all directional indicators (such as up, down, left, right, front, and rear … …) in the embodiments of the present application are merely used to explain the relative positional relationship between the components, the movement condition, and the like in a specific posture, and if the specific posture is changed, the directional indicator is correspondingly changed.
In the present application, unless explicitly specified and limited otherwise, the terms "coupled," "secured," and the like are to be construed broadly, and for example, "secured" may be either permanently attached or removably attached, or integrally formed; can be mechanically or electrically connected; either directly or indirectly, through intermediaries, or both, may be in communication with each other or in interaction with each other, unless expressly defined otherwise. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art as the case may be.
In addition, if there is a description of "first", "second", etc. in the embodiments of the present application, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the meaning of "and/or" as it appears throughout includes three parallel schemes, for example "A and/or B", including the A scheme, or the B scheme, or the scheme where A and B are satisfied simultaneously. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be regarded as not exist and not within the protection scope of the present application.
Example 1
Referring to fig. 1, fig. 1 is a schematic structural diagram of a computer device of a hardware running environment according to an embodiment of the present invention, as shown in fig. 1, the computer device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a WIreless interface (e.g., a WIreless-FIdelity (WI-FI) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the architecture shown in fig. 1 is not limiting of a computer device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 1, an operating system, a data storage module, a network communication module, a user interface module, and an electronic program may be included in the memory 1005 as one type of storage medium.
In the computer device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the computer device of the present embodiment may be provided in the computer device, and the computer device calls the intelligent water meter fault diagnosis device stored in the memory 1005 through the processor 1001, and executes the intelligent water meter fault diagnosis method provided in the present embodiment.
Referring to fig. 2, based on the foregoing hardware environment, the embodiment provides a fault diagnosis method for an intelligent water meter of the internet of things, which includes the following steps:
step S100: detecting whether the target water meter has abnormal information;
step S200: if the abnormal information exists, identifying the abnormal type of the abnormal information; the abnormal type comprises a first abnormal type and a second abnormal type, wherein the first abnormal type is idle running of the water meter, and the second abnormal type is stalling of the water meter;
step S300: if the first abnormal type is identified, first fault information corresponding to the first abnormal type is obtained; the first fault information comprises a first fault reason for causing the water meter to idle;
step S400: if the first abnormal type is identified, obtaining second fault information corresponding to the first abnormal type; the second fault information comprises a second fault reason for causing the water meter to stop running;
step S500: outputting a fault diagnosis report; the fault diagnosis report contains first fault information or second fault information.
In this embodiment, the idle running of the water meter means that the water meter is still rotating under the condition that the water meter is not used by a user, and the stop running of the water meter means that the water meter stops rotating normally under the condition that the water meter is used by the user, and the fault reasons for the idle running of the water meter and the stop running of the water meter are various, so that specific fault reasons need to be analyzed in a targeted manner. Therefore, in this embodiment, after detecting that the target water meter has abnormal information, the abnormal types of the abnormal information are further screened and identified, where the abnormal types mainly include two most common types of water meter idling and water meter stalling, if the abnormal type of water meter idling is identified, then the fault cause causing water meter idling is further identified, the corresponding first fault information can be generated by the fault cause, and similarly, if the abnormal type of water meter stalling is identified, then the fault cause causing water meter stalling is further identified, the corresponding second fault information can be generated by the fault cause, and the first fault information or the second fault information can generate a corresponding fault diagnosis report, so that effective diagnosis of the water meter fault cause can be realized, a subsequent manager or a user can quickly determine the water meter fault cause according to the fault diagnosis report, and timely perform corresponding maintenance work.
The target water meter mainly refers to an intelligent water meter which is easy to generate idle running or stalling faults, and comprises a card meter (an IC card and a radio frequency card water meter), a wireless remote water meter, a GPRS (general packet radio service) Internet of things water meter, a counting direct-reading remote water meter, a pulse water meter, a photoelectric direct-reading remote water meter and the like; the fault diagnosis report can be directly displayed on a user interface layer of the intelligent water meter to remind a user to check, and can also be sent to a background terminal, so that management personnel can process the fault diagnosis report in a centralized manner.
Thus, as an alternative embodiment, the first fault information includes at least one of water pressure abnormality information and water leakage fault information, and the first fault cause includes at least one of water pressure abnormality and water leakage fault;
in step S300, obtaining first fault information corresponding to the first anomaly type includes:
step S310: acquiring the local water pressure corresponding to the target water meter, and acquiring abnormal water pressure information if the local water pressure is greater than the preset standard water pressure; the standard water pressure is the water pressure range in which the target water meter can normally operate;
step S320: acquiring an instantaneous flow value corresponding to the target water meter, and acquiring water leakage fault information if the instantaneous flow value is greater than a preset dynamic flow threshold value; the dynamic flow threshold is a flow value set according to different time nodes.
In this embodiment, the first failure cause causing idle running of the water meter is more, the first failure cause is most common and typical, namely, unstable water pressure (namely, abnormal water pressure) and water leakage phenomenon (namely, water leakage failure), the unstable water pressure is that water in a pipeline can flow out of a water pump rapidly when being pressurized, a water valve can control a water switch, when being influenced by the air temperature or space fall and other environments, the pipeline can generate air to influence the water pressure, so that the water pressure fluctuation is larger, therefore, by detecting the local water pressure corresponding to the target water meter, if the water pressure fluctuation is larger, the local water pressure is larger than the range of the preset standard water pressure, at this time, water pressure abnormality information can be generated, and the water pressure abnormality information is added into a failure diagnosis report; when detecting whether water leakage exists, firstly detecting an instantaneous flow value corresponding to a target water meter, wherein the instantaneous flow value refers to the volume of water flowing through the water meter at a certain moment (usually in cubic meters), after calculating to obtain the instantaneous flow value, judging whether the instantaneous flow value of a certain time node is larger than a preset dynamic flow threshold value of a corresponding time node, if the instantaneous flow value is larger than the dynamic flow threshold value, directly judging that the water leakage condition occurs at the tail end of the water meter, generating water leakage fault information at the moment, adding the water leakage fault information into a fault diagnosis report, and if water pressure abnormal information and water leakage fault information are obtained at the same time, adding the two fault information into the fault diagnosis report, thereby realizing accurate and effective diagnosis of the water pressure abnormal information and the water leakage fault information respectively, and intuitively outputting diagnosis results.
It should be noted that the dynamic flow threshold may be set according to flow thresholds set by different time nodes, for example, 0-24h corresponds to 24 flow thresholds, and the flow thresholds are set according to historical water consumption data of the user.
As an alternative embodiment, the first fault information further includes electromagnetic interference fault information, and the first fault cause further includes electromagnetic interference fault;
in step S300, obtaining first fault information corresponding to the first anomaly type, further includes:
step S330: and acquiring the electromagnetic interference intensity of the surrounding environment of the target water meter, and acquiring electromagnetic interference fault information if the electromagnetic interference intensity is greater than the anti-interference intensity of the target water meter.
In this embodiment, since the part of the intelligent water meters are subjected to data acquisition, transmission and storage through the pulse signals, are easily interfered by external strong magnetic environments, which causes inaccurate water meter measurement and idle running, although the part of the intelligent water meters have certain anti-electromagnetic interference capability, the external electromagnetic interference intensity is too high and also causes certain influence, so that the embodiment also considers the influence factors of electromagnetic interference on the water meters, and the electromagnetic interference intensity of the surrounding environment of the target water meters is acquired, if the electromagnetic interference intensity is greater than the anti-interference intensity of the target water meters, electromagnetic interference fault information can be generated, and the electromagnetic interference fault information is added to the fault diagnosis report.
As an optional implementation manner, after obtaining the first fault information corresponding to the first anomaly type in step S300, the method further includes:
step S340: acquiring a water pressure anomaly coefficient delta 1 ，δ 1 ＝ε 1 *Δ 1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε 1 For the first conversion coefficient, if the local water pressure is within the standard water pressure range, epsilon 1 ＝0，Δ 1 Is the difference between the local water pressure and the standard water pressure;
step S350: obtaining a water leakage fault coefficient delta 2 ，δ 2 ＝ε 2 *Δ 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε 2 For the first conversion coefficient, ε if the instantaneous flow value is within the dynamic flow threshold 2 ＝0，Δ 2 Is the difference between the instantaneous flow value and the dynamic flow threshold;
step S360: acquiring electromagnetic interference fault coefficient delta 3 ，δ 3 ＝ε 3 *Δ 3 The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε 3 For the first conversion coefficient, if the electromagnetic interference strength is smaller than the anti-interference strength, epsilon 3 ＝0，Δ 3 Is the electromagnetic interference intensity;
step S370: obtaining fault level coefficients delta, delta=delta 1 +δ 2 +δ 3 ；
Step S380: the fault level coefficient delta is added to the fault diagnosis report.
In this embodiment, since there may be more than one failure cause causing the water meter to idle, and the failure degree is inconsistent, and when there are a large number of failure types or a high failure degree, it may be difficult to handle the failure by the user alone, in this embodiment, the failure information corresponding to each failure cause is quantized, and the water pressure abnormality coefficient δ is set for each water pressure abnormality, water leakage condition, and electromagnetic interference is too high 1 Water leakage failure coefficient delta 2 And electromagnetic interference failure coefficient delta 3 Wherein whenWhen the ground water pressure is within the standard water pressure range, epsilon 1 =0, water pressure anomaly coefficient δ 1 =0, proving that there is no water pressure abnormality, otherwise ε 1 > 0, and similarly epsilon 2 When=0, i.e. leakage failure coefficient δ 2 =0, prove that there is no water leakage, otherwise ε 2 ＞0，ε 3 When=0, i.e. electromagnetic interference failure coefficient δ 3 =0, demonstrating lower electromagnetic interference, otherwise ε 3 More than 0, the water leakage fault, the electromagnetic interference fault and the electromagnetic interference fault belong to three different metering parameters, so the water leakage fault, the electromagnetic interference fault and the electromagnetic interference fault respectively pass through the corresponding conversion coefficient epsilon 1 、ε 2 And epsilon 3 The conversion coefficient can be set according to the system requirement to carry out parameter conversion on three different metering parameters so as to form three additively equal metering parameters, namely, the water pressure abnormality coefficient delta 1 Water leakage failure coefficient delta 2 And electromagnetic interference failure coefficient delta 3 The fault grade coefficient delta is finally calculated and obtained, the current fault degree of the water meter can be intuitively and quantitatively reflected, the fault grade coefficient delta is higher, and the fault degree is higher, so that when a first fault reason (mainly comprising abnormal water pressure, water leakage faults and electromagnetic interference faults) is detected and obtained, or the fault reason is that a user cannot process the fault reason (such as external electromagnetic interference is too strong), or the fault grade coefficient delta is calculated to exceed a preset safety grade, the target water meter can directly send a generated fault diagnosis report to a background terminal to remind a manager of processing the fault reason as soon as possible, and the fault reason is single or the fault reason can be processed by the user, the fault reason is directly displayed on a user interface layer of the target water meter to remind the user of processing the fault reason by the user, so that the fault diagnosis report is prevented from being sent to the background terminal to cause data congestion, and the data processing pressure is reduced.
The water pressure abnormality coefficient δ 1 Water leakage failure coefficient delta 2 Electromagnetic interference failure coefficient delta 3 And the failure level coefficient δ may each be displayed in a failure diagnosis report.
As an alternative embodiment, the second fault information includes at least one of a blocking fault information and a counter operation fault information, and the second fault cause includes at least one of a blocking fault and a counter operation fault;
in step S400, obtaining second fault information corresponding to a second anomaly type includes:
step S410: detecting the impurity content condition in a main pipeline connected with a target water meter to obtain blockage fault information;
step S420: and detecting the running condition of a counter in the target water meter to acquire the running fault information of the counter.
In this embodiment, the main second failure cause causing the stalling of the water meter is that the main pipeline of the target water meter is blocked due to too many sundries, or the second failure cause may be that the counter cannot operate due to the gear locking or the electronic failure of the counter, so by detecting the content of sundries and the operation condition of the counter, whether blocking failure information and/or counter operation failure information exist can be detected.
It should be noted that, when detecting the blocking fault information and the counter operation fault information, the method is effective only when the water consumption condition is generated, so that the water consumption information of the target water meter is detected before the second fault information corresponding to the second abnormal type is acquired, and when the water consumption information is detected, the detection step of the second fault information can be started.
As an alternative embodiment, if congestion fault information or counter operation fault information is obtained, the method further includes the following steps:
step S430: acquiring an operation video of a target water meter within a preset time;
step S440: decomposing the operation video frame by frame to obtain a plurality of water meter images;
step S450: extracting water meter reading information corresponding to a plurality of water meter images;
step S460: and identifying whether the plurality of water meter reading information has change, and if the plurality of water meter reading information has no change, judging that the second fault information exists.
In this embodiment, because the condition that the detection data is inaccurate is easy to exist in the detection of the blocking fault information and the counter operation fault information, when the blocking fault information and/or the counter operation fault information are detected, further detection is performed, in this embodiment, the operation video of the target water meter within the preset time (i.e. during water consumption) is acquired and acquired, the operation video is decomposed frame by frame to obtain a plurality of water meter images, the water meter reading information corresponding to the plurality of water meter images is extracted, whether the plurality of water meter reading information changes or not is identified, if no change exists, the water meter is proved to be not walked, and then the existence of the second fault information can be determined, at this time, the second fault information is added to the fault diagnosis report, and in this embodiment, by combining with the machine vision identification technology, the authenticity of the second fault information can be further confirmed through image processing, the accuracy of the data is ensured, and the generation of invalid data is avoided, and the data processing pressure is increased.
It should be noted that, here, a micro camera facing the water meter reading display interface may be disposed at a corresponding position around the target water meter, so that the operation video of the target water meter may be collected and stored conveniently when the operation video is needed, and the micro camera may not collect the operation video when the operation video is not needed (i.e. when no blocking fault information and/or counter operation fault information is detected).
As an optional embodiment, in step S410, detecting the impurity content condition in the main pipe connected to the target water meter to obtain the blockage fault information includes:
step S411: acquiring initial water flow in a main pipeline;
step S412: obtaining the water outlet flow in the branch pipeline; wherein the branch pipeline is connected with the main pipeline;
step S413: and acquiring a flow difference value between the initial water flow and the outlet water flow, and acquiring blocking fault information if the flow difference value is larger than a preset flow standard threshold value.
In this embodiment, when detecting the debris content condition, the flow difference between initial water flow in the main pipe and the outlet water flow in the lateral pipe is detected to the accessible, if debris piles up more, the flow difference can be bigger, when being greater than the standard threshold value of the flow of predetermineeing, proves that there is more debris to cause the rivers to be obstructed, can generate jam trouble information this moment, detects accurately effectively.
It should be noted that, the preset flow standard threshold is specifically set according to the specifications and the number of the main pipeline and the branch pipeline, and the use environment.
As an alternative embodiment, in step S100, detecting whether the target water meter has abnormal information includes:
step S110: acquiring operation monitoring data of a target water meter;
step S120: acquiring operation standard data of a preset standard table;
step S130: comparing the operation monitoring data with the operation standard data and obtaining a comparison result;
step S140: if the comparison results are different, judging that the target water meter has abnormal information.
In this embodiment, when detecting whether the target water meter has abnormal information, a standard meter (i.e. a mother meter) and the target water meter are connected together, and through water with a certain pressure, various tests are performed according to a rule, at this time, the readings of the two meters walk together, that is, operation monitoring data of the target water meter and operation standard data of the standard meter are respectively obtained, when the readings of the target water meter are consistent with those of the standard meter, that is, when the operation monitoring data are consistent with the operation standard data, the target water meter has no abnormal information, otherwise, if the comparison result has a difference, the existence of the abnormal information of the target water meter is judged, so that accurate detection of the abnormal information of the target water meter is realized, and when the abnormal information is detected, a next fault cause detection step is performed.
Example 2
Based on the same inventive concept as the foregoing embodiment, this embodiment further provides an intelligent water meter fault diagnosis device, including:
the abnormality detection module is used for detecting whether the target water meter has abnormality information or not;
the abnormal type identification module is used for identifying the abnormal type of the abnormal information if the abnormal information exists; the abnormal type comprises a first abnormal type and a second abnormal type, wherein the first abnormal type is idle running of the water meter, and the second abnormal type is stalling of the water meter;
the first acquisition module is used for acquiring first fault information corresponding to the first abnormal type if the first abnormal type is identified; the first fault information comprises a first fault reason for causing the water meter to idle;
the second acquisition module is used for acquiring second fault information corresponding to the second abnormal type if the second abnormal type is identified; the second fault information comprises a second fault reason for causing the water meter to stop running;
the output module is used for outputting a fault diagnosis report; the fault diagnosis report contains first fault information or second fault information.
The explanation and examples of each module in the apparatus of this embodiment may refer to the method of the foregoing embodiment, and will not be repeated here.
It should be noted that, the intelligent water meter fault diagnosis device in this embodiment may be connected to an internet of things system, where the internet of things system includes a user platform, a service platform, a management platform, a sensor network platform and an intelligent water meter object platform that interact in sequence, so as to form a standard internet of things five-platform structure. The user platform comprises user terminals such as personal users, government users, supervisory users and the like, and the physical entity of the user platform comprises various user terminals such as mobile phones, computers, special terminals and the like, and the user terminals are served by combining with user information system software.
The service platform is a functional platform for realizing service communication. In some embodiments, the service platform may include a server such as a water service, an operation service, and a security service.
The management platform is a functional platform for realizing operation management of the Internet of things system, and comprises a device management sub-platform, a service management sub-platform and a data center module; the device management sub-platform can comprise a device running state monitoring management module, a fault data monitoring management module, a device parameter management module, a device life cycle management module and the like, and can manage and monitor various index data of the intelligent water meter through each functional module; the service management sub-platform can comprise a revenue management module, a business and commercial tenant management module, a report management module, a message management module, a scheduling management module, a purchase and sale difference management module, an operation analysis management module and a comprehensive service management module, and can realize interaction and processing of service data through the cooperation of the functional modules.
The sensing network platform is a functional platform for realizing sensing communication, and comprises a device management module and a data transmission management module, wherein the device management module comprises a network management module, an instruction management module and a device state management module, and the data transmission management module comprises a data protocol management module, a data analysis module, a data classification module, a data transmission monitoring module and a data transmission safety module.
The intelligent water meter object platform is a functional platform for realizing perception control. In some embodiments, the smart meter object platform may include a plurality of smart meters, each corresponding to one of the anomaly detection module, one of the anomaly type identification modules, one of the first acquisition modules, one of the second acquisition modules, and one of the output modules, respectively.
In some embodiments, the intelligent water meter object platform not only comprises the abnormality detection module, the abnormality type identification module, the first acquisition module, the second acquisition module and the output module, but also comprises an MCU control module, a communication module and an alarm module. Therefore, through the synergistic effect of the functional modules, the interactive Internet of things five-platform structure of the Internet of things is realized, and a frame foundation is provided for the intelligent water meter fault diagnosis device.
Example 3
Based on the same inventive concept as the previous embodiments, this embodiment provides a computer device, which includes a memory and a processor, where the memory stores a computer program, and the processor executes the computer program to implement the above method.
Example 4
Based on the same inventive concept as the previous embodiments, this embodiment provides a computer readable storage medium, on which a computer program is stored, and a processor executes the computer program to implement the above method.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the claims, and all equivalent structures or equivalent processes using the descriptions and drawings of the present application, or direct or indirect application in other related technical fields are included in the scope of the claims of the present application.
Claims (10)
1. The fault diagnosis method of the intelligent water meter of the Internet of things is characterized by comprising the following steps of:
detecting whether the target water meter has abnormal information;
if the abnormality information exists, identifying the abnormality type of the abnormality information; the abnormal type comprises a first abnormal type and a second abnormal type, wherein the first abnormal type is idle running of the water meter, and the second abnormal type is stalling of the water meter;
if the first abnormal type is identified, first fault information corresponding to the first abnormal type is obtained; wherein, the first fault information comprises a first fault reason for causing the water meter to idle;
if the second abnormal type is identified, second fault information corresponding to the second abnormal type is acquired; wherein the second fault information comprises a second fault cause causing the water meter to stop running;
outputting a fault diagnosis report; wherein the fault diagnosis report includes the first fault information or the second fault information.
2. The method for diagnosing faults of the intelligent water meter of the internet of things according to claim 1, wherein the first fault information comprises at least one of water pressure abnormality information and water leakage fault information, and the first fault cause comprises at least one of water pressure abnormality and water leakage fault;
the obtaining the first fault information corresponding to the first abnormal type includes:
acquiring the local water pressure corresponding to the target water meter, and acquiring the water pressure abnormality information if the local water pressure is greater than a preset standard water pressure; the standard water pressure is a water pressure range in which the target water meter can normally operate;
acquiring an instantaneous flow value corresponding to the target water meter, and acquiring the water leakage fault information if the instantaneous flow value is larger than a preset dynamic flow threshold; wherein the dynamic flow threshold is a flow value set according to different time nodes.
3. The method for diagnosing faults of the intelligent water meter of the internet of things according to claim 2, wherein the first fault information further comprises electromagnetic interference fault information, and the first fault cause further comprises electromagnetic interference faults;
the obtaining the first fault information corresponding to the first abnormal type further includes:
and acquiring the electromagnetic interference intensity of the surrounding environment of the target water meter, and acquiring the electromagnetic interference fault information if the electromagnetic interference intensity is larger than the anti-interference intensity of the target water meter.
4. The method for diagnosing faults of the intelligent water meter of the internet of things according to claim 3, wherein after the first fault information corresponding to the first abnormality type is obtained, the method further comprises:
acquiring a water pressure anomaly coefficient delta 1 ，δ 1 ＝ε 1 *Δ 1 The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε 1 For the first conversion coefficient, if the local water pressure is within the standard water pressure range, epsilon 1 ＝0，Δ 1 Is the difference between the local water pressure and the standard water pressure;
obtaining a water leakage fault coefficient delta 2 ，δ 2 ＝ε 2 *Δ 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε 2 For a first conversion factor, ε if the instantaneous flow value is within the dynamic flow threshold 2 ＝0，Δ 2 A difference value between the instantaneous flow value and the dynamic flow threshold;
acquiring electromagnetic interference fault coefficient delta 3 ，δ 3 ＝ε 3 *Δ 3 The method comprises the steps of carrying out a first treatment on the surface of the Wherein ε 3 For the first conversion coefficient, if the electromagnetic interference strength is smaller than the anti-interference strength, epsilon 3 ＝0，Δ 3 Is the electromagnetic interference intensity;
obtaining fault level coefficients delta, delta=delta 1 +δ 2 +δ 3 ；
The fault level coefficient delta is added to the fault diagnosis report.
5. The method for diagnosing faults of an intelligent water meter for the internet of things according to any of claims 1 to 4, wherein the second fault information comprises at least one of blocking fault information and counter operation fault information, and the second fault cause comprises at least one of blocking fault and counter operation fault;
the obtaining the second fault information corresponding to the second abnormal type includes:
detecting the impurity content condition in a main pipeline connected with the target water meter so as to acquire the blockage fault information;
and detecting the running condition of a counter in the target water meter to acquire the running fault information of the counter.
6. The method for diagnosing faults of an intelligent water meter of the internet of things according to claim 5, wherein if the blocking fault information or the counter operation fault information is obtained, the method further comprises the following steps:
acquiring an operation video of the target water meter within a preset time;
decomposing the operation video frame by frame to obtain a plurality of water meter images;
extracting water meter reading information corresponding to a plurality of water meter images;
and identifying whether the plurality of water meter reading information changes, if so, judging that the second fault information exists, and adding the second fault information to the fault diagnosis report.
7. The method for diagnosing faults of an intelligent water meter of the internet of things according to claim 5, wherein the detecting the impurity content condition in the main pipeline connected with the target water meter to obtain the blocking fault information comprises:
acquiring initial water flow in the main pipeline;
obtaining the water outlet flow in the branch pipeline; wherein the branch pipe is connected with the main pipe;
and acquiring a flow difference value between the initial water flow and the outlet water flow, and acquiring blocking fault information if the flow difference value is larger than a preset flow standard threshold value.
8. The method for diagnosing faults of an intelligent water meter of the internet of things according to claim 1, wherein the detecting whether the target water meter has abnormal information comprises:
acquiring operation monitoring data of a target water meter;
acquiring operation standard data of a preset standard table;
comparing the operation monitoring data with the operation standard data and obtaining a comparison result;
and if the comparison results are different, judging that the target water meter has abnormal information.
9. An intelligent water meter fault diagnosis device, characterized by comprising:
the abnormality detection module is used for detecting whether the target water meter has abnormality information or not;
the abnormal type identification module is used for identifying the abnormal type of the abnormal information if the abnormal information exists; the abnormal type comprises a first abnormal type and a second abnormal type, wherein the first abnormal type is idle running of the water meter, and the second abnormal type is stalling of the water meter;
the first acquisition module is used for acquiring first fault information corresponding to the first abnormal type if the first abnormal type is identified; wherein, the first fault information comprises a first fault reason for causing the water meter to idle;
the second acquisition module is used for acquiring second fault information corresponding to the second abnormal type if the second abnormal type is identified; wherein the second fault information comprises a second fault cause causing the water meter to stop running;
the output module is used for outputting a fault diagnosis report; wherein the fault diagnosis report includes the first fault information or the second fault information.
10. A computer device, characterized in that it comprises a memory in which a computer program is stored and a processor which executes the computer program, implementing the method according to any of claims 1-8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117664281A (en) * | 2024-01-29 | 2024-03-08 | 成都秦川物联网科技股份有限公司 | Ultrasonic water meter fault detection and automatic calibration method and system based on Internet of things |
| CN117788083A (en) * | 2024-02-27 | 2024-03-29 | 成都秦川物联网科技股份有限公司 | Ultrasonic water meter management method, internet of things system, equipment and medium |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117664281A (en) * | 2024-01-29 | 2024-03-08 | 成都秦川物联网科技股份有限公司 | Ultrasonic water meter fault detection and automatic calibration method and system based on Internet of things |
| CN117664281B (en) * | 2024-01-29 | 2024-04-09 | 成都秦川物联网科技股份有限公司 | Ultrasonic water meter fault detection and automatic calibration method and system based on Internet of Things |
| CN117788083A (en) * | 2024-02-27 | 2024-03-29 | 成都秦川物联网科技股份有限公司 | Ultrasonic water meter management method, internet of things system, equipment and medium |
| CN117788083B (en) * | 2024-02-27 | 2024-05-14 | 成都秦川物联网科技股份有限公司 | Ultrasonic water meter management method, internet of things system, equipment and medium |
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