CN116774135A - Remote meter reading abnormity monitoring method and system - Google Patents
Remote meter reading abnormity monitoring method and system Download PDFInfo
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- CN116774135A CN116774135A CN202311054679.8A CN202311054679A CN116774135A CN 116774135 A CN116774135 A CN 116774135A CN 202311054679 A CN202311054679 A CN 202311054679A CN 116774135 A CN116774135 A CN 116774135A
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Abstract
The application relates to the technical field of anomaly monitoring, in particular to a remote meter reading anomaly monitoring method and a system, wherein the method dynamically monitors and obtains first real-time operation information of a first ammeter terminal in a plurality of ammeter terminals, and analyzes the first real-time operation information through an ammeter monitoring model to obtain a first operation health index of the first ammeter terminal; judging whether the first operation health index meets a preset health index threshold value or not, if not, identifying the first real-time operation information through an ammeter abnormal support vector machine to obtain a first ammeter abnormal type; traversing a first exception handling scheme of the first ammeter exception type in a preset exception handling database, and sending the first exception handling scheme to a first display of the first ammeter terminal. Compared with the prior art, the application can carry out all-around monitoring analysis on the remote meter reading process, and improves the scientificity and effectiveness of remote meter reading monitoring.
Description
Technical Field
The application relates to the technical field of anomaly monitoring, in particular to a remote meter reading anomaly monitoring method and system.
Background
Remote meter reading is a technology integrating data acquisition, processing, transmission and storage, and is widely applied along with the continuous development of smart grids. The remote meter reading system generally comprises an ammeter, a collector, a remote control center and the like, and in terms of structure, a system main station of independent networking transmits user side data to a processing control module through an RS-485 protocol and the like, and a GPRS module and the like transmit the data to the remote control center, so that the data collection and instruction interaction are finally realized. In practice, when the remote meter reading system is applied, a plurality of intelligent electric meters are corresponding to one remote meter reading system, and the intelligent electric meters perform data transmission interaction through multithreading, so that various abnormal faults are very easy to occur. In general, the existing method has the defect that scientific and effective dynamic monitoring cannot be carried out on the remote meter reading process, so that abnormality in remote meter reading cannot be found in time, the abnormal fault processing efficiency is further affected, and the safety and stability of remote meter reading operation are finally affected.
Therefore, how to dynamically monitor the remote meter reading process in multiple dimensions, discover the abnormal operation and process the abnormal operation in a targeted manner in time becomes a problem to be solved urgently.
Disclosure of Invention
The application mainly aims to provide a remote meter reading abnormity monitoring method and a system, which aim to improve dynamic monitoring in a remote meter reading process and improve the safety and stability of remote meter reading operation.
In order to achieve the above purpose, the application provides a remote meter reading abnormality monitoring method, comprising the following steps:
monitoring and analyzing: dynamically monitoring to obtain first real-time operation information of a first ammeter terminal in a plurality of ammeter terminals, and analyzing the first real-time operation information through an ammeter monitoring model to obtain a first operation health index of the first ammeter terminal;
judging and identifying: judging whether the first operation health index meets a preset health index threshold value or not, if not, identifying the first real-time operation information through an ammeter abnormal support vector machine to obtain a first ammeter abnormal type;
an exception handling step: traversing a first exception handling scheme of the first ammeter exception type in a preset exception handling database, and sending the first exception handling scheme to a first display of the first ammeter terminal.
In addition, in order to achieve the above objective, the present application further provides a remote meter reading anomaly monitoring system, which includes a memory and a processor, wherein the memory stores a remote meter reading anomaly monitoring program, and when the remote meter reading anomaly monitoring program is executed by the processor, the method comprises the following steps:
monitoring and analyzing: dynamically monitoring to obtain first real-time operation information of a first ammeter terminal in a plurality of ammeter terminals, and analyzing the first real-time operation information through an ammeter monitoring model to obtain a first operation health index of the first ammeter terminal;
judging and identifying: judging whether the first operation health index meets a preset health index threshold value or not, if not, identifying the first real-time operation information through an ammeter abnormal support vector machine to obtain a first ammeter abnormal type;
an exception handling step: traversing a first exception handling scheme of the first ammeter exception type in a preset exception handling database, and sending the first exception handling scheme to a first display of the first ammeter terminal.
In addition, to achieve the above object, the present application also proposes a computer device, including a processor and a memory;
the processor is used for processing and executing the remote meter reading abnormality monitoring method;
the memory is coupled to the processor and is configured to store the remote meter reading anomaly monitoring program, which when executed by the processor, causes the system to perform the steps of the remote meter reading anomaly monitoring method.
The method comprises the steps of dynamically monitoring to obtain first real-time operation information of a first ammeter terminal in a plurality of ammeter terminals, and analyzing the first real-time operation information through an ammeter monitoring model to obtain a first operation health index of the first ammeter terminal; judging whether the first operation health index meets a preset health index threshold value or not, if not, identifying the first real-time operation information through an ammeter abnormal support vector machine to obtain a first ammeter abnormal type; traversing a first exception handling scheme of the first ammeter exception type in a preset exception handling database, and sending the first exception handling scheme to a first display of the first ammeter terminal. Compared with the prior art, the application can carry out all-around monitoring analysis on the operation of the ammeter terminal, the integrated circuit card and the meter reading accounting accuracy in the remote meter reading process, and improves the scientificity and effectiveness of remote meter reading monitoring.
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 required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a remote meter reading anomaly monitoring method according to the present application;
FIG. 2 is a schematic flow chart of displaying the normal decision of the first card in real time through the first display in the remote meter reading abnormality monitoring method of the present application;
FIG. 3 is a schematic flow chart of the method for monitoring abnormal meter reading according to the present application, wherein the first training data is supervised and learned to obtain the abnormal support vector machine of the electric meter;
FIG. 4 is a schematic flow chart of constructing the predetermined abnormality processing database in the remote meter reading abnormality monitoring method of the present application;
FIG. 5 is a schematic flow chart of the method for monitoring remote meter reading abnormality for adjusting the first running health index by calling the first real-time deviation;
FIG. 6 is a schematic diagram of an operating environment of a remote meter reading anomaly monitoring program according to the present application;
FIG. 7 is a program block diagram of a remote meter reading anomaly monitoring program according to the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
In the figure:
the meter reading abnormality monitoring system comprises an electronic device 6, a remote meter reading abnormality monitoring program 60, a memory 61, a processor 62, a display 63, a monitoring analysis module 701, a judgment and identification module 702 and an abnormality processing module 703.
Detailed Description
The principles and features of the present application are described below with reference to the drawings, the examples are illustrated for the purpose of illustrating the application and are not to be construed as limiting the scope of the application.
The application provides a remote meter reading abnormity monitoring method.
As shown in fig. 1, fig. 1 is a flow chart of the remote meter reading abnormality monitoring method of the present application.
In this embodiment, the remote meter reading anomaly monitoring method is applied to a remote meter reading anomaly monitoring system, and the remote meter reading anomaly monitoring system is in communication connection with a plurality of electric meter terminals, and the method includes:
step S100: dynamically monitoring to obtain first real-time operation information of a first ammeter terminal in a plurality of ammeter terminals, and analyzing the first real-time operation information through an ammeter monitoring model to obtain a first operation health index of the first ammeter terminal;
step S200: judging whether the first operation health index meets a preset health index threshold value or not, if not, identifying the first real-time operation information through an ammeter abnormal support vector machine to obtain a first ammeter abnormal type;
step S300: traversing a first exception handling scheme of the first ammeter exception type in a preset exception handling database, and sending the first exception handling scheme to a first display of the first ammeter terminal.
Firstly, when abnormal monitoring is carried out in a remote meter reading process, firstly, dynamically monitoring the real-time running state of an ammeter terminal, namely, firstly, monitoring any one ammeter terminal in a plurality of ammeter terminals in communication connection with the remote meter reading abnormal monitoring system, namely, obtaining the first ammeter terminal, then, sorting the real-time running data of the first ammeter terminal, further, carrying out intelligent analysis processing on the sorted real-time data, namely, the first real-time running information through a previously trained ammeter monitoring model, and correspondingly obtaining an output result of the ammeter monitoring model, namely, obtaining the real-time running health condition result of the first ammeter terminal. The higher the first operation health index is, the more stable the operation state of the corresponding first ammeter terminal is, and the lower the probability of abnormality such as failure is. In addition, the ammeter monitoring model is a neural network model which is obtained after the relevant recorded information of the remote meter reading is arranged and supervised learning is carried out.
And then, comparing the first operation health index obtained by intelligent analysis of the ammeter monitoring model with a preset health index threshold comprehensively set by a related technology researcher in combination with actual ammeter operation conditions, namely system monitoring analysis conditions, model monitoring analysis conditions and the like. When the first operation health index meets the preset health index threshold, the operation condition of the first ammeter terminal is good, and sudden fault abnormality is not easy to occur. When the first operation health index does not meet the preset health index threshold, the operation condition of the first ammeter terminal is not optimistic, and the first ammeter terminal is in a state of extremely easy occurrence of fault abnormality, and at the moment, intelligent prediction is needed to be further conducted on possible abnormality and faults of the first ammeter terminal so as to make preparation for coping in advance. The first real-time operation information is classified and identified through an ammeter anomaly support vector machine, and the anomaly and the fault type possibly occurring in the first ammeter terminal are correspondingly obtained, namely, the first ammeter anomaly type is recorded. The ammeter abnormal support vector machine is an ammeter fault type prediction and identification model trained based on historical related abnormal monitoring data.
And finally, traversing the first ammeter anomaly type obtained by intelligent analysis of the ammeter anomaly support vector machine in a preset anomaly processing database, and correspondingly obtaining a first anomaly processing scheme of the first ammeter anomaly type. The first exception handling scheme is an optimal handling and coping scheme when the first ammeter exception type fault is historically encountered. And finally, the first exception handling scheme is sent to a first display of the first ammeter terminal so as to guide related maintenance technicians to provide reference schemes and guidance for carrying out fault maintenance treatment on the first ammeter terminal, thereby improving the pertinence and scientificity of exception maintenance and finally improving the safety and fault tolerance of remote meter reading operation.
As shown in fig. 2, in this embodiment, after the exception handling step, the method further includes:
the method comprises the steps that first integrated circuit cards on a first ammeter terminal are monitored in real time, and a first card real-time image is obtained;
performing image preprocessing on the first card real-time image to obtain a first preprocessed card image;
thirdly, performing color recognition on a first preset area in the first preprocessing card image to obtain first color data;
judging whether the first color data accords with preset color data or not, if so, performing character recognition on a second preset area in the first preprocessing card image to obtain a first number;
fifthly, judging whether the first card number is in a preset state or not;
a sixth step of generating a first card normal decision if yes, wherein the first card normal decision is a decision of the first integrated circuit card in normal state;
and seventhly, displaying the normal decision of the first card in real time through the first display.
Besides the dynamic monitoring of the first ammeter terminal, the first integrated circuit card on the first ammeter terminal is also monitored in real time, and accordingly a first card real-time image of the first integrated circuit card is obtained. And then carrying out noise reduction and enhancement processing on the first card real-time image, and correspondingly obtaining a first preprocessing card image. And then, positioning the first preprocessing card image based on the first preset area, and intelligently identifying the color of the positioning position to obtain the first color data. The first predetermined area refers to any one area of the integrated circuit card defined in advance, and color characteristic parameters of the area, such as RGB parameters, are stored in the system correspondingly. And then judging whether the first color data accords with the preset color parameters of the first preset area, namely, if so, indicating that the monitored card inserting mode of the first integrated circuit card is correct and abnormal card inserting phenomenon does not occur. Such as a reverse plug-in card or a fake plug-in card, etc. Further, character recognition is performed on a second preset area in the first preprocessing card image, and character number information of a corresponding position of the first preprocessing card image is correspondingly obtained, namely the character number information is used as the first number.
And further judging whether the first card number is in a preset state, if so, indicating that the current state of the first integrated circuit card is normal, and correspondingly generating a first card normal decision. The predetermined state refers to that the integrated circuit card is in an account opening state. The first card normal decision refers to a decision that the state of the first integrated circuit card is normal. And finally, displaying the normal decision of the first card in real time through the first display so as to enable related personnel to intuitively observe the real-time state of the integrated circuit card.
In this embodiment, after determining whether the first color data meets the predetermined color data, the method includes:
firstly, if the first card is not in conformity with the first card, generating a first card abnormal decision, wherein the first card abnormal decision refers to a decision of the first integrated circuit card in abnormal card insertion mode;
and then, displaying the first card abnormal decision in real time through the first display.
When the first color data is judged to be not in accordance with the preset color data, the fact that the current first integrated circuit card is not inserted according to actual regulations is indicated, and the color which should appear at a certain position of the card cannot appear under the accurate condition of the actual card insertion. For example, the front and back sides of the integrated circuit card are different in color, when the card is inserted in the forward direction, the first preset area displays a certain color on the front side of the integrated circuit card, and when the color displayed at the moment is not the preset color, the card insertion error is indicated. That is, if the first color data does not conform to the predetermined color data, the system automatically generates a first card anomaly decision. The first card abnormal decision is a decision of abnormal card insertion mode of the first integrated circuit card. And finally, displaying the first card abnormal decision in real time through the first display.
In this embodiment, after determining whether the first card number is in the predetermined state, the method includes:
firstly, if not, generating a second card abnormal decision, wherein the second card abnormal decision is a decision of abnormal card insertion type of the first integrated circuit card;
and then, displaying the abnormal decision of the second card in real time through the first display.
After the card inserting mode of the first integrated circuit card is judged to be correct, in order to judge whether the state of the inserted first integrated circuit card is normal or not, the card number information of the card surface of the first integrated circuit card is intelligently identified, that is, the position of the card surface number of the integrated circuit card is firstly determined, and the second preset area is correspondingly determined. And then, performing character recognition on the second preset area of the first integrated circuit card to obtain card number information, and matching whether the card number information is in an account opening state or not based on the card number information, if the card number information is not in the account opening state, the card is temporarily unusable, so that the system automatically generates a second card abnormal decision. Wherein the second card exception decision is a decision that the card insertion type of the first integrated circuit card is abnormal. And finally, displaying the abnormal decision of the second card in real time through the first display.
As shown in fig. 3, in this embodiment, before the step of determining and identifying, the method includes:
firstly, a history remote meter reading log is called, wherein the history remote meter reading log comprises a history remote meter reading abnormal log;
then, a first historical abnormality log in the historical remote meter reading abnormality log is extracted, wherein the first historical abnormality log comprises a first historical abnormality characterization and a first historical abnormality type;
then, taking the first historical anomaly characterization and the first historical anomaly type as first training data;
and finally, performing supervised learning on the first training data to obtain the ammeter abnormal support vector machine.
Before the first real-time operation information is identified through the ammeter abnormal support vector machine, firstly, a history remote meter reading log is called, and a training data set is constructed by utilizing data in the history remote meter reading log and training of the ammeter abnormal support vector machine is carried out. Firstly, extracting a history remote meter reading abnormal log in the history remote meter reading abnormal log, and then sequentially analyzing fault data generated during each group of history remote meter reading in the history remote meter reading abnormal log, namely randomly extracting and recording the fault data as a first history abnormal log. The first historical anomaly log comprises a first historical anomaly characterization and a first historical anomaly type. The first historical abnormal representation refers to surface characteristic information when the remote meter reading abnormality occurs historically, and an exemplary meter memory is provided with faults due to the fact that the maximum current of the load is greater than 1.2 times, the maximum current of the load is the abnormal representation at the moment, and the faults of the meter memory are of the fault type. And taking the first historical anomaly characterization and the first historical anomaly type as first training data, and performing supervised learning on the first training data through a computer technology to obtain the ammeter anomaly support vector machine.
In this embodiment, after performing supervised learning on the first training data to obtain the ammeter abnormal support vector machine, the method further includes:
a first step of constructing a first historical abnormality index set based on the first historical abnormality characterization;
step two, performing union processing on the first historical abnormal index set to obtain a target index set, and taking the target index set as a monitoring index for monitoring the first ammeter terminal;
and thirdly, initializing an in-table card, storing in-table memory current and an in-table security chip by the target index set.
And acquiring fault characterization information of each historical remote meter reading abnormality in the historical remote meter reading abnormality log in sequence to obtain the first historical abnormal index set. Exemplary are, for example, account balances of 0, system outages, maximum current with a load greater than 1.2 times, voltage greater than 1.5 times, reverse access, integrated circuit card plugging, etc. Further, the first historical abnormal index set is subjected to union processing, so that all abnormal characterization during each time of history abnormality is obtained, and a target index set is obtained. And then taking the target index set as a monitoring index for monitoring the first ammeter terminal. The account balance, whether the system is powered off, load current, voltage, whether the incoming and outgoing lines are connected reversely, whether the integrated circuit card is plugged reversely and the like are taken as indexes to be monitored practically. And determining a final key monitoring index after analysis and screening. The target index set comprises an in-table card initialization, an in-table memory current and an in-table security chip.
As shown in fig. 4, in this embodiment, after performing supervised learning on the first training data to obtain the abnormal support vector machine of the electric meter, the method further includes:
firstly, performing union processing on the first historical abnormal type to obtain a target abnormal type set;
then, sequentially designating an exception handling scheme of each exception type in the target exception type set;
and finally, constructing the preset exception handling database according to the mapping relation between the exception type and the exception handling scheme.
After the specific exception types of each exception log in the historical remote meter reading exception logs are analyzed, the first historical exception types are processed in a union mode, and a target exception type set is obtained correspondingly. That is, the set of target anomaly types includes all remote meter reading anomaly types that historically occur. Further, sequentially designating an exception handling scheme of each exception type in the target exception type set. The processing schemes of the various abnormal types are determined by related professionals based on professional knowledge and actual processing experience, and the optimal processing scheme is determined after comprehensive analysis. And finally, constructing the preset exception handling database according to the mapping relation between the exception type and the exception handling scheme.
As shown in fig. 5, in this embodiment, after the monitoring and analyzing step, the method further includes:
the method comprises the steps of firstly, reading a first real-time reading of a first ammeter terminal;
step two, calling a first reading time sequence of the first ammeter terminal in a preset period;
third, matching a first loop ratio reading of the first real-time reading in the first reading timing sequence;
a fourth step of calculating a first real-time deviation of the first real-time reading from the first loop ratio reading;
fifthly, if the first real-time deviation exceeds a preset deviation range, a verification instruction is sent out, and the first real-time reading is verified according to the verification instruction;
and sixthly, if the verification result is abnormal, calling the first real-time deviation to adjust the first operation health index.
Besides the dynamic monitoring of the first ammeter terminal, the real-time reading of the integrated circuit card inserted on the first ammeter terminal is acquired, namely the first real-time reading of the first ammeter terminal is read. And then, calling a first reading time sequence of the first ammeter terminal in a preset period. Wherein the predetermined period is a predetermined period manually determined, such as a day, a week, a month, or the like. The first reading timing refers to a sequence of readings of the card at different reading moments in the predetermined period, and each reading corresponds to one moment. Then, a first loop ratio reading of the first real-time reading is matched in the first reading timing sequence. Exemplary as currently the seventh day of the month, the seventh day of the month is matched as the corresponding ring ratio reading. Further, a difference between the first real-time reading and the first loop ratio reading is calculated and is noted as a first real-time deviation. And further judging whether the first real-time deviation is within a preset range, that is, if the first real-time deviation exceeds the preset deviation range, indicating that the previous deviation is larger and the card is possibly abnormal, automatically sending a verification instruction by the system, and verifying the first real-time reading according to the verification instruction. Further, if the verification result is abnormal, the system automatically calls the first real-time deviation and adjusts the first running health index based on the first real-time deviation.
The method comprises the steps of dynamically monitoring to obtain first real-time operation information of a first ammeter terminal in a plurality of ammeter terminals, and analyzing the first real-time operation information through an ammeter monitoring model to obtain a first operation health index of the first ammeter terminal; judging whether the first operation health index meets a preset health index threshold value or not, if not, identifying the first real-time operation information through an ammeter abnormal support vector machine to obtain a first ammeter abnormal type; traversing a first exception handling scheme of the first ammeter exception type in a preset exception handling database, and sending the first exception handling scheme to a first display of the first ammeter terminal. Compared with the prior art, the application can carry out all-around monitoring analysis on the operation of the ammeter terminal, the integrated circuit card and the meter reading accounting accuracy in the remote meter reading process, and improves the scientificity and effectiveness of remote meter reading monitoring.
The application provides a remote meter reading abnormality monitoring program.
Referring to FIG. 6, a schematic diagram of an operating environment of a remote meter reading anomaly monitoring program 60 according to the present application is shown.
In the present embodiment, the remote meter reading abnormality monitoring program 60 is installed and run in the electronic device 6. The electronic device 6 may be a computing device such as a desktop computer, a notebook computer, a palm top computer, a server, etc. The electronic device 6 may include, but is not limited to, a memory 61, a processor 62, and a display 63. Fig. 6 shows only the electronic device 6 with components 11-13, but it is understood that not all shown components are required to be implemented, and that more or fewer components may alternatively be implemented.
The memory 61 may in some embodiments be an internal storage unit of the electronic device 6, such as a hard disk or a memory of the electronic device 6. The memory 61 may also be an external storage device of the electronic apparatus 6 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic apparatus 6. Further, the memory 61 may also include both an internal storage unit and an external storage device of the electronic apparatus 6. The memory 61 is used for storing application software and various data installed in the electronic device 6, such as program codes of the remote meter reading abnormality monitoring program 60. The memory 61 may also be used to temporarily store data that has been output or is to be output.
The processor 62 may in some embodiments be a central processing unit (Central Processing Unit, CPU), microprocessor or other data processing chip for running program code or processing data stored in the memory 61, such as executing the remote meter reading anomaly monitoring program 60 or the like.
The display 63 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like in some embodiments. The display 63 is used for displaying information processed in the electronic device 6 and for displaying a visualized user interface. The components 11-13 of the electronic device 6 communicate with each other via a program bus.
Referring to FIG. 7, a block diagram of a remote meter reading anomaly monitoring program 60 according to the present application is shown.
In this embodiment, the remote meter reading anomaly monitoring program 60 can be divided into one or more modules, and one or more modules are stored in the memory 61 and executed by one or more processors (the processor 62 in this embodiment) to complete the present application. For example, in fig. 7, the remote meter reading abnormality monitoring program 60 may be divided into a monitoring analysis module 701, a judgment recognition module 702, and an abnormality processing module 703. The modules described in the present application refer to a series of computer program instruction segments capable of performing specific functions, more suitable than the program for describing the execution of the remote meter reading anomaly monitoring program 60 in the electronic device 6, wherein:
monitoring and analyzing module 701: dynamically monitoring to obtain first real-time operation information of a first ammeter terminal in a plurality of ammeter terminals, and analyzing the first real-time operation information through an ammeter monitoring model to obtain a first operation health index of the first ammeter terminal;
the judgment and identification module 702: judging whether the first operation health index meets a preset health index threshold value or not, if not, identifying the first real-time operation information through an ammeter abnormal support vector machine to obtain a first ammeter abnormal type;
exception handling module 703: traversing a first exception handling scheme of the first ammeter exception type in a preset exception handling database, and sending the first exception handling scheme to a first display of the first ammeter terminal.
The application also provides an electronic device, which comprises a processor and a memory;
the processor, configured to process and execute the steps of the remote meter reading anomaly monitoring method according to any one of the above embodiments;
the memory is coupled to the processor for storing a program that, when executed by the processor, causes the system to perform the steps of any of the remote meter reading anomaly monitoring methods described above.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the scope of the application, and all equivalent structural changes made by the description of the present application and the accompanying drawings or direct/indirect application in other related technical fields are included in the scope of the application.
Claims (9)
1. The remote meter reading abnormality monitoring method is characterized by being applied to a remote meter reading abnormality monitoring system, wherein the remote meter reading abnormality monitoring system is in communication connection with a plurality of ammeter terminals, and the remote meter reading abnormality monitoring method comprises the following steps:
monitoring and analyzing: dynamically monitoring to obtain first real-time operation information of a first ammeter terminal in a plurality of ammeter terminals, and analyzing the first real-time operation information through an ammeter monitoring model to obtain a first operation health index of the first ammeter terminal;
judging and identifying: judging whether the first operation health index meets a preset health index threshold value or not, if not, identifying the first real-time operation information through an ammeter abnormal support vector machine to obtain a first ammeter abnormal type;
an exception handling step: traversing a first exception handling scheme of the first ammeter exception type in a preset exception handling database, and sending the first exception handling scheme to a first display of the first ammeter terminal.
2. The method of claim 1, further comprising, after the exception handling step:
the method comprises the steps of monitoring a first integrated circuit card on a first ammeter terminal in real time to obtain a first card real-time image;
performing image preprocessing on the first card real-time image to obtain a first preprocessing card image;
performing color recognition on a first preset area in the first preprocessing card image to obtain first color data;
judging whether the first color data accords with preset color data, if so, performing character recognition on a second preset area in the first preprocessing card image to obtain a first number;
judging whether the first card number is in a preset state or not;
if yes, generating a first card normal decision, wherein the first card normal decision refers to a decision of the first integrated circuit card in normal state;
and displaying the normal decision of the first card in real time through the first display.
3. The method according to claim 2, comprising, after said determining whether the first color data meets a predetermined color data:
if the first card is not matched with the second card, generating a first card abnormal decision, wherein the first card abnormal decision refers to a decision of the first integrated circuit card abnormal in the card inserting mode;
and displaying the first card abnormal decision in real time through the first display.
4. The method according to claim 2, wherein after said determining whether the first card number is in a predetermined state, comprising:
if not, generating a second card abnormal decision, wherein the second card abnormal decision refers to a decision of abnormal card insertion type of the first integrated circuit card;
and displaying the abnormal decision of the second card in real time through the first display.
5. The method of claim 1, comprising, prior to the step of determining and identifying:
the method comprises the steps of calling a history remote meter reading log, wherein the history remote meter reading log comprises a history remote meter reading abnormal log;
extracting a first historical anomaly log in the historical remote meter reading anomaly log, wherein the first historical anomaly log comprises a first historical anomaly characterization and a first historical anomaly type;
taking the first historical anomaly characterization and the first historical anomaly type as first training data;
and performing supervised learning on the first training data to obtain the ammeter abnormal support vector machine.
6. The method of claim 5, further comprising, after said performing supervised learning on said first training data to obtain said ammeter anomaly support vector machine:
constructing a first historical anomaly metrics set based on the first historical anomaly characterization;
performing union processing on the first historical abnormal index set to obtain a target index set, and taking the target index set as a monitoring index for monitoring the first ammeter terminal;
the target index set comprises an in-table card initialization, an in-table memory current and an in-table security chip.
7. The method of claim 6, further comprising, after the performing supervised learning on the first training data to obtain the ammeter anomaly support vector machine:
performing union processing on the first historical abnormal type to obtain a target abnormal type set;
sequentially designating an exception handling scheme of each exception type in the target exception type set;
and constructing the preset exception handling database according to the mapping relation between the exception type and the exception handling scheme.
8. The method of claim 1, further comprising, after the monitoring analysis step:
reading a first real-time reading of the first ammeter terminal;
invoking a first reading time sequence of the first ammeter terminal in a preset period;
a first loop ratio reading that matches the first real-time reading in the first reading timing sequence;
calculating a first real-time deviation of the first real-time reading from the first loop ratio reading;
if the first real-time deviation exceeds a preset deviation range, a verification instruction is sent out, and the first real-time reading is verified according to the verification instruction;
and if the verification result is abnormal, calling the first real-time deviation to adjust the first operation health index.
9. The remote meter reading abnormality monitoring system comprises a memory and a processor, and is characterized in that a remote meter reading abnormality monitoring program is stored in the memory, and the remote meter reading abnormality monitoring program is executed by the processor to realize the following steps:
monitoring and analyzing: dynamically monitoring to obtain first real-time operation information of a first ammeter terminal in a plurality of ammeter terminals, and analyzing the first real-time operation information through an ammeter monitoring model to obtain a first operation health index of the first ammeter terminal;
judging and identifying: judging whether the first operation health index meets a preset health index threshold value or not, if not, identifying the first real-time operation information through an ammeter abnormal support vector machine to obtain a first ammeter abnormal type;
an exception handling step: traversing a first exception handling scheme of the first ammeter exception type in a preset exception handling database, and sending the first exception handling scheme to a first display of the first ammeter terminal.
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