Intelligent diagnosis method and equipment for communication abnormity of metering terminal meter in low-voltage transformer area

Abstract

The invention relates to an intelligent diagnosis method for communication abnormity of a metering terminal meter in a low-voltage transformer area, which comprises the following steps: acquiring historical operation information of a low-voltage centralized reading link of each transformer area, and obtaining a historical operation database of the low-voltage centralized reading link; according to a preset fault information base, abnormal operation information is screened out from the historical operation database of the low-voltage centralized reading link, and a historical abnormal database of the low-voltage centralized reading link is obtained; when an abnormal problem occurs in the target station area, determining whether an abnormal type corresponding to the abnormal problem exists in a historical abnormal database of the low-voltage centralized reading link; if yes, outputting a diagnosis result; if not, performing exception type estimation on the exception problem according to a preset judgment rule; and performing problem definition on the exception type estimation according to a preset interpreter. According to the technical scheme, the problems that in the prior art, only basic operation data of a low-voltage transformer area can be known and faults occurring in the low-voltage centralized reading process cannot be diagnosed by monitoring operation information of power equipment through a system are solved.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a method, system, readable storage medium and computer equipment for intelligent diagnosis of abnormal communication of meters at low-voltage station terminals. Background Art

[0002] When the low-voltage area metering automation system collects and reads a large amount of data, it is usually accompanied by many low-voltage communication links and changeable power supply environment in the low-voltage area, which makes the remote meter reading system have problems such as unstable meter reading success rate and abnormal reading data in actual operation. To this end, in order to solve the problem of abnormal low-voltage communication, the main methods such as low-voltage area operation information monitoring, master station fault detection, and operation and maintenance full-link fault monitoring have been formed. Low-voltage area operation information monitoring mainly monitors the operation data of power equipment, and does not diagnose faults in the collection process; master station fault detection mainly focuses on problems such as inconsistent master station files and missing logs, and lacks diagnosis of abnormal problems such as terminals, smart meters and communication modules. The abnormal diagnosis involved in its method is too one-sided. The operation and maintenance full-link fault monitoring requires on-site personnel to diagnose through additional equipment, which greatly increases the operation and maintenance costs and investment costs, and cannot be further promoted and applied to low-voltage areas in different scenarios. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems existing in the prior art or related art.

[0004] To this end, the purpose of the present invention is to provide a method and device for intelligent diagnosis of communication anomalies of meters at low-voltage substations, which can effectively avoid the limitations when there is no data reference, reduce the use of on-site diagnostic tools, and reduce operation and maintenance and investment costs.

[0005] To achieve the above-mentioned purpose, the technical solution of the first aspect of the present invention provides a method for intelligently diagnosing abnormal communication of a meter at a low-voltage area metering terminal, comprising:

[0006] Obtain the historical operation information of the low-voltage centralized meter reading link of each substation, and obtain the historical operation database of the low-voltage centralized meter reading link;

[0007] According to the preset fault information library, abnormal operation information is filtered out in the low-voltage collection link historical operation database to obtain a low-voltage collection link historical abnormal database;

[0008] When an abnormal problem occurs in the target area, determine whether there is an abnormal type corresponding to the abnormal problem in the low-voltage collection link historical abnormality database; if so, output the diagnosis result;

[0009] If not, estimate the abnormal type of the abnormal problem according to the preset judgment rules;

[0010] A problem definition is performed for the anomaly type estimation according to a preset interpreter.

[0011] In the above technical solution, preferably, the abnormal problems occurring in the target area include:

[0012] When all measurement point data are missing:

[0013] Obtain TTU power outage alarm information and check whether the target area is in a power outage state during the current period;

[0014] The heartbeat message collected by the front end is used to know whether the concentrator is online;

[0015] Determine whether the target area is in a power outage state and the concentrator is offline during the current period. If so, output the corresponding diagnosis result;

[0016] If not, check the LCD display status of the concentrator to determine whether the concentrator power supply is normal. If so, output the corresponding diagnostic results;

[0017] If so, read the on-site logical address information of the concentrator to determine whether the logical address information of the concentrator is consistent with the on-site one;

[0018] If so, output the corresponding diagnosis result;

[0019] If not, check and determine whether the 4G signal of the concentrator fluid is missing;

[0020] If so, output the corresponding diagnosis result;

[0021] If not, the output is a diagnosis result that the 4G antenna is damaged, loose, or detached.

[0022] In any of the above technical solutions, preferably, the abnormal problems occurring in the target area include:

[0023] When the data of some measurement points are missing for the entire period:

[0024] Read the meter reading directory of the concentrator and compare it with the metering ledger of the master station to determine whether the meter reading directory of the concentrator is consistent with the metering ledger of the master station. If not, output the corresponding diagnosis result;

[0025] If so, check whether the master station's copy instruction contains illegal measurement points and output the corresponding diagnosis results.

[0026] In any of the above technical solutions, preferably, the abnormal problems occurring in the target area include:

[0027] When data for some periods of time at a measurement point are missing:

[0028] Check the master station's supplementary copying instructions;

[0029] Determine whether the supplementary copy instruction contains the specified number of segments of data at the specified measurement point, and if so, output the corresponding diagnosis result;

[0030] If not, check whether there is any record of collector or meter replacement in the current period and output the corresponding diagnosis result.

[0031] In any of the above technical solutions, preferably, the abnormal problems occurring in the target area include:

[0032] When the table code is illegal:

[0033] The concentrator actively calls for meter data to check whether the downlink communication is normal and outputs the corresponding diagnostic results.

[0034] In any of the above technical solutions, preferably, the abnormal problems occurring in the target area include:

[0035] When the meter turns over or flies away:

[0036] Check whether there is a record of meter replacement in the current period. If not, output the corresponding diagnosis result;

[0037] If so, check whether the logical addresses of the measuring points before and after the meter is reversed or flies away are consistent, and output the corresponding diagnostic results.

[0038] In any of the above technical solutions, preferably, the fields of the low voltage meter reading link historical operation database are:

[0039] Field Name Data Types Not empty Field Definition device_id nvarchar yes Equipment identification sta_num nvarchar yes Exception number timestamp datetime yes Data collection time voltage nvarchar yes Voltage value current nvarchar yes Current value power nvarchar yes power power_factor nvarchar yes Power Factor status nvarchar yes Equipment status (normal / abnormal) raw_data nvarchar yes Raw data anomaly_type nvarchar yes Fault type ;

[0041] The fields of the low voltage collection link historical abnormality database are:

[0042]

[0043]

[0044] The technical solution of the second aspect of the present invention provides a low-voltage area metering terminal meter communication abnormality intelligent diagnosis system, comprising:

[0045] An acquisition module is configured to acquire historical operation information of the low-voltage collection link of each substation area to obtain a historical operation database of the low-voltage collection link;

[0046] The abnormal data identification module is configured to filter out abnormal operation information in the low-voltage collection link historical operation database according to a preset fault information library to obtain a low-voltage collection link historical abnormal database;

[0047] The abnormality type identification module is configured to determine whether there is an abnormality type corresponding to the abnormality problem in the low-voltage collection link historical abnormality database when an abnormality problem occurs in the target substation; if so, output a diagnosis result;

[0048] An abnormality type assessment module is configured to estimate the abnormality type of the abnormal problem according to a preset judgment rule;

[0049] The anomaly type definition module is configured to perform problem definition on the anomaly type estimation according to a preset interpreter.

[0050] The technical solution of the third aspect of the present invention provides a readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the intelligent diagnosis method for communication anomalies of meters in low-voltage substations provided by the technical solution of the first aspect are implemented.

[0051] The technical solution of the fourth aspect of the present invention provides a computer device, including a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to implement the steps of the intelligent diagnosis method for communication anomalies of meters in low-voltage substations provided by the technical solution of the first aspect.

[0052] Compared with the prior art, the advantages of the intelligent diagnosis method and equipment for communication anomalies of meters in low-voltage metering terminals provided by the present invention are that the following shortcomings or deficiencies in the prior art are solved: 1. By monitoring the operating information of power equipment through the system, only the basic operating data of the low-voltage substation can be understood, and the faults occurring during the low-voltage collective meter reading process cannot be diagnosed; 2. When detecting fault data from the master station side, only the inconsistent files on the master station side, the missing and damaged master station logs, and other problems can be partially diagnosed. Only some faults can be detected through the master station side, and there is a lack of abnormal detection methods for other links, which has a small improvement on the success rate of meter reading; 3. Relying on on-site personnel to screen the fault problems of each module through the monitoring device, the advantage of the fault detection method of the master station is that it monitors and diagnoses the fault problems of the entire link, but it is still time-consuming and labor-intensive in the diagnosis link, and cannot reduce the operation and maintenance costs. In addition, it is necessary to consider the problems of the device itself and the corresponding investment costs, and the promotion and popularization rate in different scenarios of low-voltage substations is low. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0054] Figure 1 A flowchart of an intelligent diagnosis method for abnormal communication of meters in a low-voltage area metering terminal according to an embodiment of the present invention is shown;

[0055] Figure 2A schematic diagram of the logic for determining missing data of all measuring points involved in an embodiment of the present invention is shown;

[0056] Figure 3 A schematic diagram of the logic for judging missing data of all time periods at some measuring points involved in an embodiment of the present invention is shown;

[0057] Figure 4 A schematic diagram of the logic for judging missing data in some time periods of a measuring point involved in an embodiment of the present invention is shown;

[0058] Figure 5 A schematic diagram of the table code illegality judgment logic involved in an embodiment of the present invention is shown;

[0059] Figure 6 The figure shows a schematic diagram of the logic for judging the inversion or flight of the table code involved in the embodiment of the present invention;

[0060] Figure 7 The structural block diagram of the intelligent diagnosis system for communication abnormality of meters at low-voltage station terminals involved in an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0061] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0062] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0063] like Figure 1 As shown, according to an embodiment of the present invention, a method for intelligently diagnosing abnormal communication of a meter at a low-voltage area metering terminal includes:

[0064] S1, obtain the historical operation information of the low-voltage collection link of each substation, and obtain the historical operation database of the low-voltage collection link;

[0065] In this step, the historical operation data in the historical operation database of the low-voltage meter reading link comes from the metering automation system.

[0066] S2, filtering out abnormal operation information in the low-voltage centralized meter reading link historical operation database according to a preset fault information database to obtain a low-voltage centralized meter reading link historical abnormality database;

[0067] In this step, the preset fault information database includes an abnormal database of missing data of all measuring points, an abnormal database of missing data of some measuring points for the entire period, an abnormal database of missing data of some measuring points for the entire period, an abnormal database of illegal table codes, and an abnormal database of table code reversal or flight away. Numbers are assigned according to different abnormal situations: missing data of all measuring points is numbered 01, missing data of some measuring points for the entire period is numbered 02, missing data of some measuring points for the entire period is numbered 03, illegal table codes are numbered 04, and table code reversal, flight away, etc. are numbered 05.

[0068] S3, when an abnormal problem occurs in the target area, determine whether there is an abnormal type corresponding to the abnormal problem in the low-voltage collection link historical abnormality database; if so, output the diagnosis result;

[0069] If not, S4, estimating the abnormal type of the abnormal problem according to a preset judgment rule;

[0070] S5, defining a problem for estimating the anomaly type according to a preset interpreter.

[0071] like Figure 2 As shown, in the above embodiment, preferably, the abnormal problems occurring in the target area include:

[0072] When all measurement point data are missing:

[0073] Obtain TTU power outage alarm information and check whether the target area is in a power outage state during the current period;

[0074] The heartbeat message collected by the front end is used to know whether the concentrator is online;

[0075] Determine whether the target area is in a power outage state and the concentrator is offline during the current period. If so, output the corresponding diagnosis result;

[0076] The corresponding diagnostic results in this step are: due to the power outage in the current substation, all measurement points are missing; the corresponding diagnostic results when the concentrator is online are: 1. Whether the power supply of the concentrator is normal; 2. Whether the logical address of the concentrator is consistent with the master station file; 3. Whether the concentrator is in a confined space such as a basement, resulting in a weakened 4G signal; 4. Whether the 4G antenna of the concentrator is normal; 5. Whether the 4G module of the concentrator is normal; 6. Whether the downlink communication module of the concentrator is normal.

[0077] If not, check the LCD display status of the concentrator to determine whether the concentrator power supply is normal. If so, output the corresponding diagnostic results;

[0078] The corresponding diagnosis result in this step is: due to the abnormal power supply of the concentrator, the data of all measurement points are missing.

[0079] If so, read the on-site logical address information of the concentrator to determine whether the logical address information of the concentrator is consistent with the on-site one;

[0080] If so, output the corresponding diagnosis result;

[0081] The corresponding diagnostic result in this step is: due to the inconsistency between the concentrator logical address master station and the site, the data of all measurement points are missing.

[0082] If not, check and determine whether the 4G signal of the concentrator fluid is missing;

[0083] If so, output the corresponding diagnosis result;

[0084] The corresponding diagnosis result in this step is: the data of all measurement points may be missing due to the weakening of 4G signal. If this happens for a long time, it is recommended to change the location of the concentrator.

[0085] If not, the output is a diagnosis result that the 4G antenna is damaged, loose, or detached.

[0086] In this embodiment, it also includes:

[0087] Read the concentrator clock;

[0088] Retrieve the meter reading directory of the concentrator and compare it with the metering record of the master station to determine whether the clocks of the master station and the concentrator are consistent;

[0089] If not, output the intermediate result of judgment: Temp1=0; if so, output the intermediate result of judgment Temp1=1;

[0090] Determine whether the metering ledger of the master station is consistent with the meter reading directory of the concentrator;

[0091] If not, output the intermediate result of judgment: Temp2=0; if so, output the intermediate result of judgment Temp2=1;

[0092] Among them, 1. If Temp1=0 and Temp2=1, it is diagnosed that all measurement points are missing due to the inconsistency between the master station and the concentrator clock, and it is recommended to calibrate the concentrator clock; 2. If Temp1=1 and Temp2=0, it is diagnosed that all measurement points are missing due to the inconsistency between the master station metering ledger and the concentrator meter reading directory, and it is recommended to remotely update the concentrator meter reading directory; 3. If Temp1=0 and Temp2=0, it is diagnosed that all measurement point data are missing due to the inconsistency between the master station clock and the concentrator, and there is an abnormal file configuration. It is recommended to calibrate the concentrator clock and remotely update the concentrator meter reading directory; 4. If Temp1=1 and Temp2=1, it is suspected that: (1) there may be an abnormality in the concentrator downlink module; (2) there may be an abnormal problem with the hub collector node failure.

[0093] like Figure 3 As shown, in any of the above embodiments, preferably, the abnormal problems occurring in the target area include:

[0094] When the data of some measurement points are missing for the entire period:

[0095] Read the meter reading directory of the concentrator and compare it with the metering ledger of the master station to determine whether the meter reading directory of the concentrator is consistent with the metering ledger of the master station. If not, output the corresponding diagnosis result;

[0096] The corresponding diagnostic result in this step is: because the concentrator meter reading directory is not completely consistent with the master station metering ledger, some measurement points are missing data for the entire period. It is recommended to remotely update the concentrator meter reading directory.

[0097] If so, check whether the master station's supplementary copy instruction contains illegal measurement points and output the corresponding diagnosis results;

[0098] In this step, if the master station's supplementary reading instruction does not include illegal measurement points, the corresponding diagnostic results are: 1. Heavy rain, thunder and other bad weather may cause downlink communication abnormalities, thereby affecting the integrity of data reading; 2. It is recommended to check whether the concentrator's micro-power antenna is normal; 3. It is recommended to check on-site whether the concentrator and downlink module files are consistent; 4. It is recommended to check on-site whether the meter body or communication module is normal;

[0099] If the master station's supplementary copy instruction contains illegal measurement points, the corresponding diagnostic result is: because the master station's supplementary copy command contains illegal measurement points, data of some measurement points are missing for the entire period. It is recommended to repair the master station's supplementary copy command bug.

[0100] like Figure 4 As shown, in any of the above embodiments, preferably, the abnormal problems occurring in the target area include:

[0101] When data for some periods of time at a measurement point are missing:

[0102] Check the master station's supplementary copying instructions;

[0103] Determine whether the supplementary copy instruction contains the specified number of segments of data at the specified measurement point, and if so, output the corresponding diagnosis result;

[0104] The corresponding diagnostic result in this step is: it is recommended that the master station make targeted supplementary copies and pay attention to checking the accuracy of the supplementary copy instructions.

[0105] If not, check whether there is a record of collector or meter replacement in the current period and output the corresponding diagnosis result;

[0106] In this step, if there is a record of replacement of the collector or meter in the current period, the corresponding diagnosis result is: due to the change of the collector / meter, there is a lack of data in some periods of the measurement point, and it is recommended to pay close attention to the data reading in the subsequent periods;

[0107] If there is no record of collector or meter replacement in the current period, the corresponding diagnostic results are: 1. Severe weather such as heavy rain and thunder may cause downlink communication abnormalities, thereby affecting the integrity of data reading; 2. It is recommended to check whether the concentrator micro-power antenna is normal.

[0108] like Figure 5 As shown, in any of the above embodiments, preferably, the abnormal problems occurring in the target area include:

[0109] When the table code is illegal:

[0110] Actively call for meter data through the concentrator to check whether the downlink communication is normal and output the corresponding diagnosis results;

[0111] If the downlink communication is abnormal, the corresponding diagnosis result is: it is suspected that the meter code is illegal due to downlink communication interference. It is recommended to actively call for testing multiple times to check for random errors. If the problem is solved, consider replacing the meter body / module;

[0112] If the downlink communication is normal, the corresponding diagnosis result is: it is recommended to continuously read the daily frozen power data of the same meter on the same day of the concentrator to check the storage status of the concentrator.

[0113] like Figure 6 As shown, in any of the above embodiments, preferably, the abnormal problems occurring in the target area include:

[0114] When the meter turns over or flies away:

[0115] Check whether there is a record of meter replacement in the current period. If not, output the corresponding diagnosis result;

[0116] The corresponding diagnosis result in this step is: due to the change of the collector / meter, some meters are reversed, flying away, etc. It is recommended to pay close attention to the data reading in the subsequent period.

[0117] If so, check whether the logical addresses of the measuring points before and after the meter is reversed or flies away are consistent, and output the corresponding diagnosis results;

[0118] If the logical addresses of the measuring points before and after the meter turns over or flies away are inconsistent, the corresponding diagnostic result is: the meter code abnormality is caused by the replacement of the meter, and it is recommended to pay close attention to the data reading in the future; if the logical addresses of the measuring points before and after the meter turns over or flies away are consistent, the corresponding diagnostic result is: it is recommended that the master station actively call up the meter code clock and compare it with the master station standard clock. There may be a large clock deviation problem.

[0119] In any of the above embodiments, preferably, the fields of the low voltage meter reading link historical operation database are:

[0120] Field Name Data Types Not empty Field Definition device_id nvarchar yes Equipment identification sta_num nvarchar yes Exception number timestamp datetime yes Data collection time voltage nvarchar yes Voltage value current nvarchar yes Current value power nvarchar yes power power_factor nvarchar yes Power Factor status nvarchar yes Equipment status (normal / abnormal) raw_data nvarchar yes Raw data anomaly_type nvarchar yes Fault type ;

[0122] The fields of the low voltage collection link historical abnormality database are:

[0123]

[0124]

[0125] like Figures 1 to 6 As shown, according to another embodiment of the present invention, a low-voltage area metering terminal meter communication abnormality intelligent diagnosis system 100 includes:

[0126] The acquisition module 1 is configured to acquire the historical operation information of the low-voltage collection link of each substation area and obtain the historical operation database of the low-voltage collection link;

[0127] The abnormal data identification module 2 is configured to filter out abnormal operation information in the low-voltage collection link historical operation database according to a preset fault information library to obtain a low-voltage collection link historical abnormal database;

[0128] The abnormality type identification module 3 is configured to determine whether there is an abnormality type corresponding to the abnormality problem in the low-voltage collection link historical abnormality database when an abnormality problem occurs in the target substation; if so, output a diagnosis result;

[0129] The abnormality type evaluation module 4 is configured to estimate the abnormality type of the abnormal problem according to a preset judgment rule;

[0130] The anomaly type definition module 5 is configured to perform problem definition on the anomaly type estimation according to a preset interpreter.

[0131] Based on the above Figures 1 to 6 The method shown, accordingly, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the intelligent diagnosis method for communication anomalies of meters in low-voltage substations and metering terminals of any of the above embodiments are implemented.

[0132] Based on this understanding, the technical solution of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, USB flash drive, mobile hard disk, etc.), including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of the present application.

[0133] Based on the above Figures 1 to 6 The method shown, and Figure 7The virtual device embodiment shown, in order to achieve the above-mentioned purpose, the embodiment of the present application also provides a computer device, including a storage medium and a processor; the storage medium is used to store computer programs; the processor is used to execute the computer program to implement the steps of the intelligent diagnosis method of communication anomalies of low-voltage substation metering terminal meters in any of the above-mentioned embodiments.

[0134] Optionally, the computer device may further include a user interface, a network interface, a camera, a radio frequency (RF) circuit, a sensor, an audio circuit, a WI-FI module, etc. The user interface may include a display, an input unit such as a keyboard, etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (such as a Bluetooth interface, a WI-FI interface), etc.

[0135] Those skilled in the art will appreciate that the computer device structure provided in this embodiment does not limit the computer device, and may include more or fewer components, or a combination of certain components, or different component arrangements.

[0136] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages and saves the hardware and software resources of the computer device, and supports the operation of information processing programs and other software and / or programs. The network communication module is used to realize communication between the components inside the storage medium, and communication with other hardware and software in the physical device.

[0137] In the description of this specification, the description of the terms "one embodiment", "some embodiments", "specific embodiments", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0138] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for intelligent diagnosis of abnormal communication of meter terminals in low-voltage areas, characterized in that: include: Obtain the historical operation information of the low-voltage centralized meter reading link of each substation, and obtain the historical operation database of the low-voltage centralized meter reading link; According to the preset fault information library, abnormal operation information is filtered out in the low-voltage collection link historical operation database to obtain a low-voltage collection link historical abnormal database; When an abnormal problem occurs in the target area, determine whether there is an abnormal type corresponding to the abnormal problem in the low-voltage collection link historical abnormality database; if so, output the diagnosis result; If not, estimate the abnormal type of the abnormal problem according to the preset judgment rules; A problem definition is performed for the anomaly type estimation according to a preset interpreter.

2. The intelligent diagnosis method for abnormal communication of meter terminals in low-voltage areas according to claim 1 is characterized in that: The abnormal problems that occur in the target area include: When all measurement point data are missing: Obtain TTU power outage alarm information and check whether the target area is in a power outage state during the current period; The heartbeat message collected by the front end is used to know whether the concentrator is online; Determine whether the target area is in a power outage state and the concentrator is offline during the current period. If so, output the corresponding diagnosis result; If not, check the LCD display status of the concentrator to determine whether the concentrator power supply is normal. If so, output the corresponding diagnostic results; If so, read the on-site logical address information of the concentrator to determine whether the logical address information of the concentrator is consistent with the on-site one; If so, output the corresponding diagnosis result; If not, check and determine whether the 4G signal of the concentrator fluid is missing; If so, output the corresponding diagnosis result; If not, the output is a diagnosis result that the 4G antenna is damaged, loose, or detached.

3. The intelligent diagnosis method for abnormal communication of metering terminals in low-voltage areas according to claim 1 or 2, characterized in that: The abnormal problems in the target area include: When the data of some measurement points are missing for the entire period: Read the meter reading directory of the concentrator and compare it with the metering ledger of the master station to determine whether the meter reading directory of the concentrator is consistent with the metering ledger of the master station. If not, output the corresponding diagnosis result; If so, check whether the master station's copy instruction contains illegal measurement points and output the corresponding diagnosis results.

4. The intelligent diagnosis method for abnormal communication of metering terminals in low-voltage areas according to claim 1 or 2, characterized in that: The abnormal problems in the target area include: When data for some periods of time at a measurement point are missing: Check the master station's supplementary copying instructions; Determine whether the supplementary copy instruction contains the specified number of segments of data at the specified measurement point, and if so, output the corresponding diagnosis result; If not, check whether there is any record of collector or meter replacement in the current period and output the corresponding diagnosis result.

5. The intelligent diagnosis method for abnormal communication of metering terminals in low-voltage areas according to claim 1 or 2, characterized in that: The abnormal problems in the target area include: When the table code is illegal: The concentrator actively calls for meter data to check whether the downlink communication is normal and outputs the corresponding diagnostic results.

6. The intelligent diagnosis method for abnormal communication of meter terminals in low-voltage areas according to claim 1 or 2, characterized in that: The abnormal problems that occur in the target area include: When the meter turns upside down or flies away: Check whether there is a record of meter replacement in the current period. If not, output the corresponding diagnosis result; If so, check whether the logical addresses of the measuring points before and after the meter is reversed or flies away are consistent, and output the corresponding diagnostic results.

7. The intelligent diagnosis method for abnormal communication of meter terminals in low-voltage areas according to claim 1 or 2, characterized in that: The fields of the low voltage collection link historical operation database are: ； The fields of the low voltage collection link historical abnormality database are: 。 8. An intelligent diagnosis system for abnormal communication of meter terminals in low-voltage areas, characterized in that: include: An acquisition module is configured to acquire historical operation information of the low-voltage collection link of each substation area to obtain a historical operation database of the low-voltage collection link; The abnormal data identification module is configured to filter out abnormal operation information in the low-voltage collection link historical operation database according to a preset fault information library to obtain a low-voltage collection link historical abnormal database; The abnormality type identification module is configured to determine whether there is an abnormality type corresponding to the abnormality problem in the low-voltage collection link historical abnormality database when an abnormality problem occurs in the target substation; if so, output a diagnosis result; An abnormality type assessment module is configured to estimate the abnormality type of the abnormal problem according to a preset judgment rule; The anomaly type definition module is configured to perform problem definition on the anomaly type estimation according to a preset interpreter.

9. A readable storage medium, characterized in that: A computer program is stored thereon, and when the program is executed by a processor, the steps of the intelligent diagnosis method for communication abnormality of a meter at a low-voltage station metering terminal as described in any one of claims 1 to 7 are implemented.

10. A computer device, characterized in that: It includes a storage medium and a processor; the storage medium is used to store a computer program; the processor is used to execute the computer program to implement the steps of the intelligent diagnosis method for communication anomalies of low-voltage metering terminal meters as described in any one of claims 1 to 6.

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