Fault self-diagnosis method and system based on NB-IOT water meter data

Abstract

The disclosed embodiment discloses a fault self-diagnosis method and system based on NB-IOT water meter data, an electronic device and a storage medium, and relates to the technical field of smart water meters. The method comprises: receiving NB-IOT water meter data, the NB-IOT water meter data comprising: flow data, pressure data and valve control signal; diagnosing whether the water meter valve passage is faulty based on the pressure data, and generating water meter valve passage fault diagnosis data; diagnosing whether the pipeline is faulty based on the flow data, and generating pipeline fault diagnosis data; diagnosing whether the water meter valve control is faulty based on the valve control signal and the flow data, and generating water meter valve control fault diagnosis data; generating water meter fault warning information based on any one or more of the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data. The method diagnoses water meter faults through NB-IOT water meter data, and generates warning information according to the diagnosis results.

Description

Technical Field

[0001] The present disclosure relates to the technical field of smart water meters, and in particular to a fault self-diagnosis method and system based on NB-IOT water meter data, an electronic device and a storage medium. Background Art

[0002] NB-LoT (Narrowband IoT abbreviation, Chinese name is Low Power Wide Area Network) is a cellular communication technology designed for the Internet of Things, aiming to provide a competitive solution in terms of battery life, cost and connection reliability. NB-LoT is mainly used for communication of low-power devices such as remote devices and sensors to meet the needs of these devices for long-term use and low cost.

[0003] The structure of a smart water meter with NB-LoT technology usually includes the following parts:

[0004] Counter module: responsible for real-time monitoring of water consumption of the water meter, and uploading the data to the remote server through NB-LoT communication technology. Sensor module: used to measure water flow, pressure, temperature and other information, and convert them into data that can be recognized by the counter module. Power module: provides a stable working voltage for the water meter. Communication module: responsible for uploading the collected data to the remote server through NB-LoT communication technology, and sending the received commands and settings to the water meter for execution. Display module: can provide local display of water consumption, current status and other information for user viewing. Housing: used to install and protect the above modules, while taking into account functions such as aesthetics and waterproofing.

[0005] At present, smart water meters with NB-LoT technology only have measurement functions and cannot self-diagnose. Water meter failures cannot be discovered in time through manual diagnosis, which can easily cause economic losses.

[0006] In summary, how to perform fault self-diagnosis based on NB-IOT water meter data is an issue that needs to be solved. Summary of the invention

[0007] In view of this, the embodiments of the present disclosure provide a fault self-diagnosis method and system based on NB-IOT water meter data, an electronic device and a storage medium, which perform fault self-diagnosis through NB-IOT water meter data.

[0008] In a first aspect, the present disclosure provides a fault self-diagnosis method based on NB-IOT water meter data, which adopts the following technical solution:

[0009] Receive NB-IOT water meter data, including flow data, pressure data and valve control signals;

[0010] diagnose whether a water meter valve passage is faulty based on the pressure data, and generate water meter valve passage fault diagnosis data;

[0011] diagnose whether the pipeline is faulty based on the flow data, and generate pipeline fault diagnosis data;

[0012] Diagnose whether the water meter valve control is faulty based on the valve control signal and the flow data, and generate water meter valve control fault diagnosis data;

[0013] Water meter fault warning information is generated based on any one or more of the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data.

[0014] As an optional implementation, diagnosing whether a water meter valve passage is faulty based on the pressure data includes:

[0015] The pressure data includes first pressure data and second pressure data of the water meter, and the pressure difference is calculated according to the first pressure data and the second pressure data;

[0016] Using the pressure threshold model to generate a pressure difference threshold according to current time data;

[0017] If the pressure difference exceeds the pressure difference threshold, a water meter valve passage fault is diagnosed.

[0018] As an optional implementation, diagnosing whether a pipeline is faulty based on the flow data includes:

[0019] Use the traffic threshold model to generate a traffic threshold according to the current time data;

[0020] If the flow data is greater than the flow threshold and the duration exceeds the first time threshold, diagnose a back-end pipeline fault;

[0021] If the flow data is less than the flow threshold and the duration exceeds the second time threshold, the front-end flow data is acquired. If the front-end flow data is within the normal flow range, a front-end pipeline fault is diagnosed.

[0022] As an optional implementation, diagnosing whether the water meter valve control is faulty based on the valve control signal and the flow data includes:

[0023] The water meter valve control signal includes valve control time and valve control state;

[0024] According to the valve control time, obtain the flow data corresponding to the time in the flow data;

[0025] The water meter valve control fault is diagnosed according to the flow data and valve control status corresponding to the time.

[0026] As an optional implementation, the NB-IOT water meter data further includes a unique identification of the water meter;

[0027] Generating water meter fault warning information based on the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data includes:

[0028] The water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data are spliced ​​with the diagnosis data of the fault and the unique identification of the water meter to obtain the water meter fault warning information.

[0029] As an optional implementation, it also includes: determining whether NB-IOT water meter data is received at a preset time node; if not, diagnosing a NB-IOT system fault of the water meter and generating NB-IOT system fault data of the water meter.

[0030] In a second aspect, the embodiment of the present disclosure further provides a fault self-diagnosis system based on NB-IOT water meter data, including:

[0031] Receiving module, receiving NB-IOT water meter data, including: flow data, pressure data and valve control signal;

[0032] A water meter valve passage fault diagnosis module, which diagnoses whether the water meter valve passage is faulty based on the pressure data and generates water meter valve passage fault diagnosis data;

[0033] A pipeline fault diagnosis module, which diagnoses whether the pipeline is faulty based on the flow data and generates pipeline fault diagnosis data;

[0034] A water meter valve control fault diagnosis module, which diagnoses whether the water meter valve control is faulty based on the valve control signal and the flow data, and generates water meter valve control fault diagnosis data;

[0035] The water meter fault warning information generating module generates water meter fault warning information based on the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control diagnosis fault data.

[0036] As an optional implementation, it also includes:

[0037] The water meter NB-IOT system fault diagnosis module determines whether the NB-IOT water meter data is received at a preset time node; if not, the NB-IOT system fault of the water meter is diagnosed and the NB-IOT system fault data of the water meter is generated.

[0038] In a third aspect, the present disclosure also provides an electronic device, which adopts the following technical solution:

[0039] The electronic device comprises:

[0040] at least one processor; and,

[0041] a memory communicatively connected to the at least one processor; wherein,

[0042] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute any of the above-mentioned fault self-diagnosis methods based on NB-IOT water meter data.

[0043] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable a computer to execute any of the above-mentioned fault self-diagnosis methods based on NB-IOT water meter data.

[0044] In summary, the technical effects of the fault self-diagnosis method based on NB-IOT water meter data provided by the present disclosure are:

[0045] The fault self-diagnosis method based on NB-IOT water meter data provided in the embodiment of the present disclosure diagnoses water meter valve path faults, pipeline faults, and water meter valve control faults through NB-IOT water meter data and time data, performs diagnosis in a timely and accurate manner, and generates early warning information based on the diagnosis results to reduce losses caused by the faults.

[0046] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the following preferred embodiments are specifically cited and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0048] Figure 1 A flowchart of a fault self-diagnosis method based on NB-IOT water meter data provided by an embodiment of the present disclosure;

[0049] Figure 2 A schematic diagram of the structure of a fault self-diagnosis system based on NB-IOT water meter data provided in an embodiment of the present disclosure;

[0050] Figure 3A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0051] The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.

[0052] It should be clear that the following embodiments of the present disclosure are described by specific specific examples, and those skilled in the art can easily understand other advantages and effects of the present disclosure from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all of the embodiments. The present disclosure can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present disclosure. It should be noted that the following embodiments and features in the embodiments can be combined with each other in the absence of conflict. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present disclosure.

[0053] It should be noted that various aspects of the embodiments within the scope of the appended claims are described below. It should be apparent that the aspects described herein may be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present disclosure, it should be understood by those skilled in the art that an aspect described herein may be implemented independently of any other aspect, and two or more of these aspects may be combined in various ways. For example, any number of aspects described herein may be used to implement the device and / or practice the method. In addition, other structures and / or functionalities other than one or more of the aspects described herein may be used to implement this device and / or practice this method.

[0054] It should also be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present disclosure. The drawings only show components related to the present disclosure rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0055] Additionally, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects described may be practiced without these specific details.

[0056] NB-LoT (Narrowband IoT abbreviation, Chinese name is Low Power Wide Area Network) is a cellular communication technology designed for the Internet of Things, aiming to provide a competitive solution in terms of battery life, cost and connection reliability. NB-LoT is mainly used for communication of low-power devices such as remote devices and sensors to meet the needs of these devices for long-term use and low cost.

[0057] The structure of a smart water meter with NB-LoT technology usually includes the following parts:

[0058] Counter module: responsible for real-time monitoring of water consumption of the water meter, and uploading the data to the remote server through NB-LoT communication technology. Sensor module: used to measure water flow, pressure, temperature and other information, and convert them into data that can be recognized by the counter module. Power module: provides a stable working voltage for the water meter. Communication module: responsible for uploading the collected data to the remote server through NB-LoT communication technology, and sending the received commands and settings to the water meter for execution. Display module: can provide local display of water consumption, current status and other information for user viewing. Housing: used to install and protect the above modules, while taking into account functions such as aesthetics and waterproofing.

[0059] At present, smart water meters with NB-LoT technology only have measurement functions and cannot self-diagnose. Water meter failures cannot be discovered in time through manual diagnosis, which can easily cause economic losses.

[0060] In summary, how to perform fault self-diagnosis based on NB-IOT water meter data is an issue that needs to be solved.

[0061] Reference Figure 1 The first aspect of the present invention provides a fault self-diagnosis method based on NB-IOT water meter data, comprising:

[0062] Step S1, receiving NB-IOT water meter data, the NB-IOT water meter data including: flow data, pressure data and valve control signal;

[0063] NB-IOT water meter data refers to the water meter data received through NB-IOT. The flow data is the instantaneous flow at each time point. The valve control signal refers to the signal that controls the state of the valve at each time period or time point. The valve state can include open state and closed state.

[0064] Step S2, diagnose whether the water meter valve passage is faulty based on the pressure data, and generate water meter valve passage fault diagnosis data; it should be noted that the water meter valve passage fault refers to a mechanical fault of the valve itself, for example, being stuck by mud and sand, rusting, etc., which causes the valve to be unable to open and close normally, and is not a control fault.

[0065] As an optional implementation, diagnosing whether a water meter valve passage is faulty based on the pressure data includes:

[0066] The pressure data includes the first pressure data and the second pressure data of the water meter, and the pressure difference is calculated based on the first pressure data and the second pressure data; specifically, the first pressure and the second pressure are measured at the water inlet and water outlet of the water meter respectively, that is, the first pressure and the second pressure are one of the water inlet pressure and the other of the water outlet pressure. When there is no problem with the valve of the water meter, the difference between the first pressure and the second pressure should be very small.

[0067] A pressure difference threshold is generated according to current time data using a pressure threshold model; specifically, the pressure threshold model is trained using an autoregressive model or a neural network model using historical data, and the training data includes time data and pressure difference data corresponding to the time data.

[0068] If the pressure difference exceeds the pressure difference threshold, a water meter valve passage fault is diagnosed.

[0069] Generally speaking, the pressure difference of the water supply pipeline is small, but in real life, the water consumption is different at different times, which will cause different pressure differences in the pipeline. When the water meter valve fails, for example, the valve cannot be fully opened, it will cause the pressure difference at both ends of the water meter to be too large. By comparing the pressure difference with the pressure difference threshold, it is determined whether the water meter valve passage is faulty.

[0070] Finally, it should be noted that the generation of water meter valve path fault diagnosis data includes:

[0071] If the water meter valve path fails, a flag bit corresponding to the fault is generated, and the flag bit corresponding to the fault and the actual value are concatenated to obtain water meter valve path fault diagnosis data;

[0072] If there is no fault in the water meter valve passage, a flag bit corresponding to no fault is generated, and the flag bit and a preset string are used to obtain the water meter valve passage fault diagnosis data. For example, the flag bit corresponding to the fault is "Y", and the flag bit corresponding to no fault is "N".

[0073] In this step, the pressure threshold model is used to dynamically generate a pressure difference threshold based on the current time data. The pressure difference calculated based on the first pressure data and the second pressure data is compared with the pressure difference threshold, so as to accurately diagnose whether the water meter valve passage is faulty.

[0074] Step S3, diagnosing whether the pipeline is faulty based on the flow data, and generating pipeline fault diagnosis data;

[0075] As an optional implementation, diagnosing whether a pipeline is faulty based on the flow data includes:

[0076] Use the traffic threshold model to generate a traffic threshold based on current time data;

[0077] If the flow data is greater than the flow threshold and the duration exceeds the first time threshold, the back-end pipeline fault is diagnosed; the flow threshold can be fixed or dynamic. The dynamic one can be generated by combining the historical data training model with the current time, or by combining the flow data of the previous period of time through some algorithms such as the average value maximum value. The first time threshold is generally preset according to the actual situation.

[0078] For example, a normal household will not open all the taps to the maximum and keep them open for a long time. This step uses the dual factors of flow data and time to determine problems such as pipe leakage.

[0079] If the flow data is less than the flow threshold and the duration exceeds the second time threshold, the front-end flow data is acquired, and if the front-end flow data is in the normal flow range, the front-end pipeline fault is diagnosed. The normal flow range is preset.

[0080] Here, the front-end pipeline fault is judged by the dual factors of flow data and time, and a second confirmation is performed through the front-end flow data.

[0081] Step S4, diagnosing whether the water meter valve control is faulty based on the valve control signal and the flow data, and generating water meter valve control fault diagnosis data;

[0082] As an optional implementation, diagnosing whether the water meter valve control is faulty based on the valve control signal and the flow data includes:

[0083] The water meter valve control signal includes valve control time and valve control state;

[0084] According to the valve control time, obtain the flow data corresponding to the time in the flow data;

[0085] The water meter valve control fault is diagnosed based on the flow data corresponding to the time and the valve control state. For example, when the valve control state is closed, the flow data corresponding to the time should be 0, or a preset very small flow. If the flow data corresponding to the time when the control state is closed is the same as the flow data when the valve is fully open, the valve control fault occurs. Here, whether the valve can be controlled normally is diagnosed based on whether the valve state is closed and the corresponding flow data.

[0086] Step S5, generating water meter fault warning information based on any one or more of the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data.

[0087] As an optional implementation, the NB-IOT water meter data further includes a unique identification of the water meter;

[0088] Generating water meter fault warning information based on the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data includes:

[0089] The water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data are spliced ​​with the diagnosis data of the fault and the unique identification of the water meter to obtain the water meter fault warning information.

[0090] The fault self-diagnosis method based on NB-IOT water meter data provided in the embodiment of the present disclosure diagnoses water meter valve path faults, pipeline faults, and water meter valve control faults through NB-IOT water meter data and time data, performs diagnosis in a timely and accurate manner, and generates early warning information based on the diagnosis results to reduce losses caused by the faults.

[0091] As an optional implementation, it also includes: determining whether NB-IOT water meter data is received at a preset time node; if not, diagnosing a NB-IOT system fault of the water meter and generating NB-IOT system fault data of the water meter.

[0092] As an optional implementation, it also includes: generating water meter fault warning information according to NB-IOT system fault data.

[0093] In a second aspect, the embodiment of the present disclosure further provides a fault self-diagnosis system based on NB-IOT water meter data, including:

[0094] Receiving module, receiving NB-IOT water meter data, including: flow data, pressure data and valve control signal;

[0095] A water meter valve passage fault diagnosis module, which diagnoses whether the water meter valve passage is faulty based on the pressure data and generates water meter valve passage fault diagnosis data;

[0096] A pipeline fault diagnosis module, which diagnoses whether the pipeline is faulty based on the flow data and generates pipeline fault diagnosis data;

[0097] A water meter valve control fault diagnosis module, which diagnoses whether the water meter valve control is faulty based on the valve control signal and the flow data, and generates water meter valve control fault diagnosis data;

[0098] The water meter fault warning information generating module generates water meter fault warning information based on the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control diagnosis fault data.

[0099] As an optional implementation, it also includes:

[0100] The water meter NB-IOT system fault diagnosis module determines whether the NB-IOT water meter data is received at a preset time node; if not, the NB-IOT system fault of the water meter is diagnosed and the NB-IOT system fault data of the water meter is generated.

[0101] The fault self-diagnosis system based on NB-IOT water meter data provided by the embodiment of the present disclosure diagnoses water meter valve path faults, pipeline faults, and water meter valve control faults through NB-IOT water meter data and time data, performs diagnosis in a timely and accurate manner, and generates early warning information based on the diagnosis results to reduce losses caused by the faults.

[0102] The electronic device according to an embodiment of the present disclosure includes a memory and a processor. The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may, for example, include a read-only memory (ROM), a hard disk, a flash memory, etc.

[0103] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is used to run the computer-readable instructions stored in the memory, so that the electronic device performs all or part of the steps of the fault self-diagnosis method based on NB-IOT water meter data of the aforementioned embodiments of the present disclosure.

[0104] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0105] like Figure 3 The present invention provides a schematic diagram of the structure of an electronic device according to an embodiment of the present invention, which is suitable for implementing the electronic device in the embodiment of the present invention. Figure 3 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0106] like Figure 3As shown, the electronic device may include a processor (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) or a program loaded from a storage device into a random access memory (RAM). In the RAM, various programs and data required for the operation of the electronic device are also stored. The processor, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0107] Typically, the following devices can be connected to the I / O interface: input devices such as sensors or visual information acquisition devices; output devices such as display screens; storage devices such as magnetic tapes and hard disks; and communication devices. The communication device can allow the electronic device to communicate with other devices (such as edge computing devices) wirelessly or by wire to exchange data. Figure 3 An electronic device having various devices is shown, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0108] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processor, all or part of the steps of the fault self-diagnosis method based on NB-IOT water meter data of an embodiment of the present disclosure are executed.

[0109] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0110] According to the computer-readable storage medium of the embodiment of the present disclosure, non-transitory computer-readable instructions are stored thereon. When the non-transitory computer-readable instructions are executed by the processor, all or part of the steps of the fault self-diagnosis method based on NB-IOT water meter data of the aforementioned embodiments of the present disclosure are executed.

[0111] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0112] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0113] The basic principles of the present disclosure are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present disclosure are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present disclosure. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, and are not limitations. The above details do not limit the present disclosure to the necessity of adopting the above specific details to be implemented.

[0114] In the present disclosure, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. The block diagrams of the devices, devices, equipment, and systems involved in the present disclosure are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0115] Additionally, as used herein, "or" used in a list of items beginning with "at least one" indicates a separate list, so that, for example, a list of "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not mean that the example described is preferred or better than other examples.

[0116] It should also be noted that in the system and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0117] Various changes, substitutions, and modifications of the techniques described herein may be made without departing from the teachings defined by the appended claims. Furthermore, the scope of the claims of the present disclosure is not limited to the specific aspects of the processes, machines, manufactures, compositions of events, means, methods, and actions described above. Currently existing or later to be developed processes, machines, manufactures, compositions of events, means, methods, or actions that perform substantially the same functions or achieve substantially the same results as the corresponding aspects described herein may be utilized. Thus, the appended claims include such processes, machines, manufactures, compositions of events, means, methods, or actions within their scope.

[0118] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

[0119] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A fault self-diagnosis method based on NB-IOT water meter data, characterized in that: include: Receive NB-IOT water meter data, including flow data, pressure data and valve control signals; diagnose whether a water meter valve passage is faulty based on the pressure data, and generate water meter valve passage fault diagnosis data; diagnose whether the pipeline is faulty based on the flow data, and generate pipeline fault diagnosis data; Diagnose whether the water meter valve control is faulty based on the valve control signal and the flow data, and generate water meter valve control fault diagnosis data; Generate water meter fault warning information based on any one or more of the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data; Diagnosing whether the water meter valve passage is faulty based on the pressure data includes: The pressure data includes first pressure data and second pressure data of the water meter, and the pressure difference is calculated according to the first pressure data and the second pressure data; Using the pressure threshold model to generate a pressure difference threshold according to current time data; If the pressure difference exceeds the pressure difference threshold, a water meter valve passage fault is diagnosed.

2. The fault self-diagnosis method based on NB-IOT water meter data according to claim 1 is characterized in that: Diagnosing whether a pipeline is faulty based on the flow data includes: Use the traffic threshold model to generate a traffic threshold according to the current time data; If the flow data is greater than the flow threshold and the duration exceeds the first time threshold, diagnose a back-end pipeline fault; If the flow data is less than the flow threshold and the duration exceeds the second time threshold, the front-end flow data is acquired. If the front-end flow data is within the normal flow range, a front-end pipeline fault is diagnosed.

3. The fault self-diagnosis method based on NB-IOT water meter data according to claim 2 is characterized in that: Diagnosing whether the water meter valve control is faulty based on the valve control signal and the flow data includes: The water meter valve control signal includes valve control time and valve control state; According to the valve control time, obtain the flow data corresponding to the time in the flow data; The water meter valve control fault is diagnosed according to the flow data and valve control status corresponding to the time.

4. The fault self-diagnosis method based on NB-IOT water meter data according to claim 3 is characterized in that: The NB-IOT water meter data also includes a unique identification of the water meter; Generating water meter fault warning information based on the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data includes: The water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control fault diagnosis data are spliced ​​with the diagnosis data of the fault and the unique identification of the water meter to obtain the water meter fault warning information.

5. The fault self-diagnosis method based on NB-IOT water meter data according to claim 4 is characterized in that: Also includes: Determine whether to receive NB-IOT water meter data at a preset time node; If not, diagnose the NB-IOT system fault of the water meter and generate the NB-IOT system fault data of the water meter.

6. A fault self-diagnosis system based on NB-IOT water meter data, characterized in that: include: Receiving module, receiving NB-IOT water meter data, including: flow data, pressure data and valve control signal; A water meter valve passage fault diagnosis module, which diagnoses whether the water meter valve passage is faulty based on the pressure data and generates water meter valve passage fault diagnosis data; A pipeline fault diagnosis module, which diagnoses whether the pipeline is faulty based on the flow data and generates pipeline fault diagnosis data; A water meter valve control fault diagnosis module, which diagnoses whether the water meter valve control is faulty based on the valve control signal and the flow data, and generates water meter valve control fault diagnosis data; A water meter fault warning information generating module, which generates water meter fault warning information based on the water meter valve fault diagnosis data, the pipeline fault diagnosis data and the water meter valve control diagnosis fault data; Diagnosing whether the water meter valve passage is faulty based on the pressure data includes: The pressure data includes first pressure data and second pressure data of the water meter, and the pressure difference is calculated according to the first pressure data and the second pressure data; Using the pressure threshold model to generate a pressure difference threshold according to current time data; If the pressure difference exceeds the pressure difference threshold, a water meter valve passage fault is diagnosed.

7. The NB-IOT water meter data fault self-diagnosis system according to claim 6 is characterized in that: Also includes: The water meter NB-IOT system fault diagnosis module determines whether the NB-IOT water meter data is received at the preset time node; If not, diagnose the NB-IOT system fault of the water meter and generate the NB-IOT system fault data of the water meter.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the fault self-diagnosis method based on NB-IOT water meter data as described in any one of claims 1-5.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, which are used to enable a computer to execute the fault self-diagnosis method based on NB-IOT water meter data as described in any one of claims 1 to 5.

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