CN117640345B - Method for evaluating network performance of equipment by using power distribution terminal test signal time point - Google Patents

Method for evaluating network performance of equipment by using power distribution terminal test signal time point Download PDF

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CN117640345B
CN117640345B CN202410102124.4A CN202410102124A CN117640345B CN 117640345 B CN117640345 B CN 117640345B CN 202410102124 A CN202410102124 A CN 202410102124A CN 117640345 B CN117640345 B CN 117640345B
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power distribution
terminal
network
time
distribution terminal
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CN117640345A (en
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朱明增
梁明臻
刘小兰
黄金
张炜
齐鹏辉
卢迎
曹德发
陶泽中
罗小波
黄应香
陈名良
蒋志儒
莫梓樱
龙玉荣
贝飞宇
何世潇
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NANJING UNITED GENERAL INFORMATION
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Abstract

The invention discloses a method for evaluating the network performance of equipment by using a power distribution terminal test signal time point, which relates to the technical field of power distribution station network evaluation.

Description

Method for evaluating network performance of equipment by using power distribution terminal test signal time point
Technical Field
The invention relates to the technical field of network evaluation of power distribution stations, in particular to a method for evaluating network performance of equipment by using a power distribution terminal test signal time point.
Background
At present, a large number of power distribution automation terminals are built, a foundation for distribution network automation management is laid, and meanwhile, a lot of equipment maintenance work is brought. The number of the terminal construction of the city scale varies from thousands to tens of thousands according to the city scale, as most of the power distribution automation terminals are widely distributed in the city, a considerable proportion of the terminals are accessed into a power distribution automation master station system by adopting a communication mode of a wireless public network, and the equipment logic processing efficiency, the communication network environment, the time period and the like have influence on the uploading of the operation parameters of the power distribution automation terminals, so that a plurality of operation problems with strong randomness and difficult retrospective reasoning are generated.
The signal generation and transmission process is as follows: the distribution automation terminal collects the analog quantity of the power line and the change of the state quantity of the equipment and carries out logic judgment, so that corresponding two remote signals are generated and sent to the master station. For example, when the current flowing through a certain switch exceeds a rated value for a certain range and time, the switch is quickly turned off according to the protection logic of the equipment, and analog quantity signals such as a protection signal, an SOE event signal, current and the like are formed, and are transmitted in a public network through a remote control protocol message such as 101/104 and the like, and reach a master station front-end processor. In daily operation and maintenance analysis, the generation time of analog excitation signals (such as current and voltage values) of current and voltage and the like is logically processed to form a tele-action message sending time, and the interval time and the like of the time when a master station receives a sending message are used as an important index, so that the operation analysis of a power distribution automation terminal can be assisted;
However, because part of terminals are accessed by adopting a communication mode of a wireless public network, the phenomenon that the interval time of a message to be sent is too long occurs in the daily operation and maintenance process, and because of the topology complexity of the wireless public network, the investigation of reasons of communication delay abnormality (including public network congestion, terminal single fault, design flaws of the same type of equipment and the like) is difficult, so that a technical scheme capable of guiding the investigation of network communication delay reasons based on a data analysis method is needed;
Patent application publication number CN115765202A discloses a power distribution automation terminal disconnection cause checking method and system, wherein the method comprises the following steps: when communication abnormality occurs between a power distribution main station and a power distribution terminal, the power distribution main station outputs a preliminary judgment result so as to attribute the reason of the communication abnormality to the power distribution main station, the power distribution terminal or a communication operator; and the power distribution terminal executes a further confirmation process according to the preliminary judgment result to determine the attribution of the reason. When communication abnormality occurs between a power distribution main station and a power distribution terminal, the power distribution main station outputs a preliminary judgment result so as to attribute the reason of the communication abnormality to the power distribution main station, the power distribution terminal or a communication operator; however, the method distinguishes the fault reasons of the power distribution main station, the power distribution terminal and the operators, the fault reasons in the power distribution terminal cannot be distinguished, and the method for judging the communication abnormality in the method cannot identify the situation that communication delay exists and communication disconnection does not exist;
therefore, the invention provides a method for evaluating the network performance of equipment by using the time point of the test signal of the power distribution terminal.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, the invention provides a method for evaluating the network performance of the equipment by using the power distribution terminal test signal time point, which improves the positioning efficiency of the communication delay reason, thereby providing decision support for later planning and correction.
To achieve the above object, a method for evaluating network performance of a device by using a power distribution terminal to test signal time points is provided, which comprises the following steps:
Step one: collecting terminal position data and terminal model data in advance; acquiring a terminal set of a division area based on the terminal position data;
step two: collecting a pre-divided period set; collecting the communication transmission average time of the same day and the historical communication transmission average time of each power distribution terminal in each divided period of each day;
Step three: generating an area network abnormality judgment result for each divided area based on the current day communication transmission average time and the historical communication transmission average time of the terminals in each divided area, and turning to the fourth step if the area network abnormality judgment result is normal; if the regional network abnormality judgment result is abnormal, initiating regional network congestion warning;
step four: generating a terminal single network anomaly judgment result for each power distribution terminal in the divided area with a normal regional network anomaly judgment result based on the current day communication transmission average time and the historical communication transmission average time of each divided period;
Step five: the distribution terminals with abnormal judging results of all terminal single network abnormal are used as abnormal single terminals, and model network abnormal alarms and single network abnormal alarms are generated based on the terminal model data of all the abnormal single terminals;
the mode of collecting the terminal position data and the terminal model data in advance is as follows:
Collecting the geographic position coordinates of each power distribution terminal and the equipment model of each power distribution terminal, wherein the geographic position coordinates of all the power distribution terminals form terminal position data, and the equipment models of all the power distribution terminals form terminal model data;
The method for obtaining the terminal set of the divided area is as follows:
Collecting the positions of all core network nodes in the city;
Counting the main core network nodes through which each power distribution terminal transmits signals through a public network; the main core network node is the core network node through which the power distribution terminal transmits signals most frequently;
establishing a slave terminal set for each core network node, wherein the slave terminal set comprises all power distribution terminals taking the core network node as a main core network node;
All the subordinate terminal sets form a terminal set of a division area;
the statistical mode of the main core network node is as follows:
Each power distribution terminal transmits a plurality of analog signals to the master station front-end processor, and then counts all core network nodes passing through in the route of each analog signal;
for each power distribution terminal, taking the core network node with the most occurrence frequency in the route of all analog signals sent by the power distribution terminal as a main core network node;
The method for collecting the daily communication transmission average time and the historical communication transmission average time of each power distribution terminal in each divided period of each day is as follows:
After each power distribution terminal generates two remote signals, recording the generation time of the two remote signals;
The power distribution terminal sends two remote signals to the master station front-end processor, and the master station front-end processor records the receiving time of each received two remote signals;
subtracting the generation time from the receiving time of each two remote signals to obtain the network transmission time of the two remote signals;
The master station front-end processor classifies the two remote signals received by the latest date as current two remote signals according to the date of the receiving time of the two remote signals, takes each date before the latest date as a historical date, and takes the two remote signals received by each historical date as historical two remote signals;
determining the dividing period of each current two remote signals according to the generation time of the current two remote signals;
For each power distribution terminal, calculating the average value of network transmission time of current two remote signals sent by the power distribution terminal in each divided period, and taking the average value of network transmission time of the current two remote signals as the communication transmission average time of the power distribution terminal in the same day in the divided period;
Determining the dividing period of each historical two remote signal according to the generation time of the two remote signals;
In each history period, for each power distribution terminal, calculating the average value of network transmission time of the two remote signals of the history transmitted by the power distribution terminal in each divided period, and taking the average value of network transmission time of the two remote signals of the history as the average time of historical communication transmission of the power distribution terminal in the divided period;
The method for generating the regional network abnormality judgment result for each divided region comprises the following steps:
For each divided region:
presetting a communication delay threshold Y and historical reference days N;
the number of the power distribution terminals in the dividing area is marked as I, and the total number of the power distribution terminals in the dividing area is marked as I;
For each power distribution terminal, collecting historical communication transmission average time of N historical dates of previous historical reference days, and numbering the historical dates in time sequence as N, n=1, 2, 3..n;
Calculating the average value and variance of the communication transmission average time of the current day of the I power distribution terminals in the dividing area, respectively serving as the average value and variance of the current day area time, and respectively marking the average value and variance of the current day area time as AD and FD;
Calculating the average value of the communication transmission average time of the I power distribution terminals in the nth historical period in the dividing area as the time average value of the historical area, and marking the time average value of the historical area as AHn;
Calculating an area abnormality reference value Z of the divided area in a manner that ; Wherein b1 and b2 are respectively preset proportionality coefficients;
If the regional abnormality reference value Z is larger than a preset abnormal value threshold value, the regional network abnormality judgment result is abnormal;
If the regional abnormality reference value Z is smaller than or equal to a preset abnormal value threshold value, the regional network abnormality judgment result is normal;
the method for generating the terminal single network abnormity judgment result for each power distribution terminal comprises the following steps:
marking the communication transmission average time of the ith power distribution terminal on the same day as TDi, and marking the historical communication transmission average time of the ith power distribution terminal on the nth day as THin;
Calculating a monomer abnormal reference value Zi of an ith power distribution terminal;
the calculation formula of the monomer anomaly reference value Zi is as follows:
If the communication transmission average time TDi of the current day is larger than a preset communication delay threshold or a monomer abnormality reference value Zi is larger than a preset monomer fluctuation abnormality threshold, setting a terminal monomer network abnormality judgment result of the power distribution terminal as abnormality;
If the communication transmission average time TDi of the current day is smaller than or equal to a preset communication delay threshold value and the monomer anomaly reference value Zi is smaller than or equal to a preset monomer fluctuation anomaly threshold value, setting a terminal monomer network anomaly judgment result of the power distribution terminal to be normal;
the mode of generating model network abnormal alarms and monomer network abnormal alarms is as follows:
The number of the equipment model is marked as x;
Counting the abnormal specific gravity of the power distribution terminal of the x-th equipment model in all abnormal single terminals for the x-th equipment model, and marking the abnormal specific gravity as wx;
If the abnormal specific gravity of the x-th equipment model exceeds a preset abnormal specific gravity threshold, marking the equipment model as an abnormal equipment model, and initiating model network abnormal alarm for the x-th equipment model;
And initiating a single network anomaly alarm for all power distribution terminals with non-anomaly equipment types in the anomaly single terminals.
An electronic device is proposed, comprising: a processor and a memory, wherein the memory stores a computer program for the processor to call;
the processor executes the method for evaluating the network performance of the equipment by using the power distribution terminal test signal time point by calling the computer program stored in the memory.
A computer-readable storage medium is proposed, on which a computer program is stored that is erasable;
The computer program, when run on a computer device, causes the computer device to perform the method for evaluating device network performance using the power distribution terminal test signal time points described above.
Compared with the prior art, the invention has the beneficial effects that:
The method comprises the steps of acquiring a terminal set of a division area based on terminal position data by collecting the terminal position data and the terminal model data in advance, and collecting a pre-divided division period set; collecting the average time of the communication transmission on the same day and the average time of the communication transmission on the same history of each power distribution terminal in each divided area, generating an area network abnormality judgment result for each divided area based on the average time of the communication transmission on the same day and the average time of the communication transmission on the same history of the terminals in each divided area, and switching to the step four if the area network abnormality judgment result is normal; if the regional network anomaly judgment result is abnormal, initiating regional network congestion warning, generating a terminal single network anomaly judgment result for each power distribution terminal in a partitioned area with a normal regional network anomaly judgment result based on the communication transmission average time and the historical communication transmission average time of each partitioned period, taking all power distribution terminals with abnormal terminal single network anomaly judgment results as abnormal single terminals, and generating model network anomaly warning and single network anomaly warning based on the terminal model data of all abnormal single terminals; analyzing and calculating real-time communication delay data and historical communication delay data samples every day, analyzing time delay problems caused by networks of different operators, different areas and time periods from the statistical perspective, and improving the positioning efficiency of communication delay reasons, so that decision support is provided for later planning and correction.
Drawings
FIG. 1 is a flow chart of a method for evaluating device network performance using a distribution terminal test signal time point in embodiment 1 of the present invention;
Fig. 2 is a schematic structural diagram of an electronic device in embodiment 2 of the present invention;
fig. 3 is a schematic diagram of a computer-readable storage medium according to embodiment 3 of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, the method for evaluating the network performance of the equipment by using the time point of the test signal of the power distribution terminal comprises the following steps:
Step one: collecting terminal position data and terminal model data in advance; acquiring a terminal set of a division area based on the terminal position data;
step two: collecting a pre-divided period set; collecting the communication transmission average time of the same day and the historical communication transmission average time of each power distribution terminal in each divided period of each day;
Step three: generating an area network abnormality judgment result for each divided area based on the current day communication transmission average time and the historical communication transmission average time of the terminals in each divided area, and turning to the fourth step if the area network abnormality judgment result is normal; if the regional network abnormality judgment result is abnormal, initiating regional network congestion warning;
step four: generating a terminal single network anomaly judgment result for each power distribution terminal in the divided area with a normal regional network anomaly judgment result based on the current day communication transmission average time and the historical communication transmission average time of each divided period;
Step five: the distribution terminals with abnormal judging results of all terminal single network abnormal are used as abnormal single terminals, and model network abnormal alarms and single network abnormal alarms are generated based on the terminal model data of all the abnormal single terminals;
the method for collecting the terminal position data and the terminal model data in advance comprises the following steps:
Collecting the geographic position coordinates of each power distribution terminal and the equipment model of each power distribution terminal, wherein the geographic position coordinates of all the power distribution terminals form terminal position data, and the equipment models of all the power distribution terminals form terminal model data;
The geographic position coordinates can be longitude and latitude coordinates, or two-dimensional plane coordinates generated after the city is modeled in an equal proportion;
the equipment model comprises the network operators of the power distribution terminal equipment and the numbers of the equipment models of the power distribution terminals in the corresponding network operators;
further, the method for obtaining the terminal set of the divided area based on the terminal position data is as follows:
collecting the positions of all core network nodes in the city; specifically, the core network nodes include, but are not limited to, core routers and core switches in a metropolitan area network, backbone link segments or key relay nodes (network nodes connecting different subnets or network segments), and the like;
Counting the main core network nodes through which each power distribution terminal transmits signals through a public network; the main core network node is the core network node through which the power distribution terminal transmits signals most frequently;
establishing a slave terminal set for each core network node, wherein the slave terminal set comprises all power distribution terminals taking the core network node as a main core network node;
All the subordinate terminal sets form a terminal set of a division area;
Specifically, the statistical manner of the primary core network node may be:
Each power distribution terminal transmits a plurality of analog signals to the master station front-end processor, and then counts all core network nodes passing through in the route of each analog signal;
for each power distribution terminal, taking the core network node with the most occurrence frequency in the route of all analog signals sent by the power distribution terminal as a main core network node;
Further, the method for collecting the pre-divided time period set is as follows:
Dividing the time of each day into a plurality of time periods according to actual experience based on the actual distribution condition of network flow of each core network node in the urban area at different times, wherein each time period corresponds to one division period; for example, will 2:00-6:00 as a time period, and every 4 hours later as a time period;
Further, the method for collecting the average time of the communication transmission on the same day and the average time of the historical communication transmission of each power distribution terminal in each divided period of each day is as follows:
After each power distribution terminal generates two remote signals, recording the generation time of the two remote signals; the two remote signals are the sum of remote signals and remote signaling signals respectively generated after the distribution automation terminal collects the analog quantity of the power line and the change of the state quantity of equipment and carries out logic judgment;
The power distribution terminal sends two remote signals to the master station front-end processor, and the master station front-end processor records the receiving time of each received two remote signals;
subtracting the generation time from the receiving time of each two remote signals to obtain the network transmission time of the two remote signals;
The master station front-end processor classifies the two remote signals received by the latest date as current two remote signals according to the date of the receiving time of the two remote signals, takes each date before the latest date as a historical date, and takes the two remote signals received by each historical date as historical two remote signals;
determining the dividing period of each current two remote signals according to the generation time of the current two remote signals;
For each power distribution terminal, calculating the average value of network transmission time of current two remote signals sent by the power distribution terminal in each divided period, and taking the average value of network transmission time of the current two remote signals as the communication transmission average time of the power distribution terminal in the same day in the divided period;
Determining the dividing period of each historical two remote signal according to the generation time of the two remote signals;
In each history period, for each power distribution terminal, calculating the average value of network transmission time of the two remote signals of the history transmitted by the power distribution terminal in each divided period, and taking the average value of network transmission time of the two remote signals of the history as the average time of historical communication transmission of the power distribution terminal in the divided period;
Further, the method for generating the regional network anomaly judgment result for each divided region based on the current day communication transmission average time and the historical communication transmission average time of the terminals in each divided region is as follows:
For each divided region:
presetting a communication delay threshold Y and historical reference days N;
the number of the power distribution terminals in the dividing area is marked as I, and the total number of the power distribution terminals in the dividing area is marked as I;
For each power distribution terminal, collecting historical communication transmission average time of N historical dates of previous historical reference days, and numbering the historical dates in time sequence as N, n=1, 2, 3..n; for example, the last N days have a history date stamp number of 1 and yesterday have a history date stamp number of N; it can be understood that the comparison result with more referential property is obtained by comparing with the historical communication data of the previous N days;
Calculating the average value and variance of the communication transmission average time of the current day of the I power distribution terminals in the dividing area, respectively serving as the average value and variance of the current day area time, and respectively marking the average value and variance of the current day area time as AD and FD;
Calculating the average value of the communication transmission average time of the I power distribution terminals in the nth historical period in the dividing area as the time average value of the historical area, and marking the time average value of the historical area as AHn;
Calculating an area abnormality reference value Z of the divided area in a manner that ; Wherein b1 and b2 are respectively preset proportionality coefficients; it will be appreciated that in the formula) The n in (2) expresses the reference weight for improving the communication delay, and obviously, the closer the historical date is to the current date, the greater the reference value is;
If the regional abnormality reference value Z is larger than a preset abnormal value threshold value, the regional network abnormality judgment result is abnormal;
If the regional abnormality reference value Z is smaller than or equal to a preset abnormal value threshold value, the regional network abnormality judgment result is normal;
further, the method for generating the terminal single network anomaly judgment result for each power distribution terminal based on the current day communication transmission average time and the historical communication transmission average time of each divided period is as follows:
marking the communication transmission average time of the ith power distribution terminal on the same day as TDi, and marking the historical communication transmission average time of the ith power distribution terminal on the nth day as THin;
Calculating a monomer abnormal reference value Zi of an ith power distribution terminal;
the calculation formula of the monomer anomaly reference value Zi is as follows:
If the communication transmission average time TDi of the current day is larger than a preset communication delay threshold or a monomer abnormality reference value Zi is larger than a preset monomer fluctuation abnormality threshold, setting a terminal monomer network abnormality judgment result of the power distribution terminal as abnormality;
If the communication transmission average time TDi of the current day is smaller than or equal to a preset communication delay threshold value and the monomer anomaly reference value Zi is smaller than or equal to a preset monomer fluctuation anomaly threshold value, setting a terminal monomer network anomaly judgment result of the power distribution terminal to be normal;
Further, the mode of generating the model network abnormal alarm and the monomer network abnormal alarm based on the terminal model data of all abnormal monomer terminals is as follows:
The number of the equipment model is marked as x;
Counting the abnormal specific gravity of the power distribution terminal of the x-th equipment model in all abnormal single terminals for the x-th equipment model, and marking the abnormal specific gravity as wx;
If the abnormal specific gravity of the x-th equipment model exceeds a preset abnormal specific gravity threshold, marking the equipment model as an abnormal equipment model, and initiating model network abnormal alarm for the x-th equipment model;
Initiating a single network anomaly alarm for all power distribution terminals of non-anomaly equipment types in the anomaly single terminals;
The regional network abnormity judging result judges whether abnormal delay exists in the regional network communication, when the regional network is not delayed, whether abnormal delay exists in the power distribution terminal monomer is judged, and whether the abnormal delay exists in the terminal monomer is further judged, and whether the abnormal delay exists is caused by using the same equipment model or not is judged, so that the reason of abnormal communication delay is analyzed, the efficiency of positioning the reason of communication delay is improved, and decision support is provided for later planning and correction.
Example 2
Fig. 2 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 2, there is also provided an electronic device 100 according to yet another aspect of the present application. The electronic device 100 may include one or more processors and one or more memories. Wherein the memory has stored therein computer readable code which, when executed by the one or more processors, is capable of performing the method of evaluating device network performance using power distribution terminal test signal time points as described above.
The method or apparatus according to embodiments of the present application may also be implemented by means of the architecture of the electronic device shown in fig. 2. As shown in fig. 2, the electronic device 100 may include a bus 101, one or more CPUs 102, a ROM103, a RAM104, a communication port 105 connected to a network, an input/output component 106, a hard disk 107, and the like. A storage device, such as ROM103 or hard disk 107, in electronic device 100 may store the method of evaluating device network performance using power distribution terminal test signal time points provided by the present application. The method for evaluating the network performance of a device using the point in time of the test signal of the power distribution terminal may, for example, comprise the steps of: step one: collecting terminal position data and terminal model data in advance; acquiring a terminal set of a division area based on the terminal position data; step two: collecting a pre-divided period set; collecting the communication transmission average time of the same day and the historical communication transmission average time of each power distribution terminal in each divided period of each day; step three: generating an area network abnormality judgment result for each divided area based on the current day communication transmission average time and the historical communication transmission average time of the terminals in each divided area, and turning to the fourth step if the area network abnormality judgment result is normal; if the regional network abnormality judgment result is abnormal, initiating regional network congestion warning; step four: generating a terminal single network anomaly judgment result for each power distribution terminal in the divided area with a normal regional network anomaly judgment result based on the current day communication transmission average time and the historical communication transmission average time of each divided period; step five: the distribution terminals with abnormal judging results of all terminal single network abnormal are used as abnormal single terminals, and model network abnormal alarms and single network abnormal alarms are generated based on the terminal model data of all the abnormal single terminals;
Further, the electronic device 100 may also include a user interface 108. Of course, the architecture shown in fig. 2 is merely exemplary, and one or more components of the electronic device shown in fig. 2 may be omitted as may be practical in implementing different devices.
Example 3
FIG. 3 is a schematic diagram of a computer-readable storage medium according to one embodiment of the present application. Shown in fig. 3 is a computer readable storage medium 200 according to one embodiment of the present application. The computer-readable storage medium 200 has stored thereon computer-readable instructions. When the computer readable instructions are executed by the processor, the method for evaluating the network performance of the device using the distribution terminal test signal time points according to the embodiment of the present application described with reference to the above drawings may be performed. Computer-readable storage medium 200 includes, but is not limited to, for example, volatile memory and/or nonvolatile memory. Volatile memory can include, for example, random Access Memory (RAM), cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like.
In addition, according to embodiments of the present application, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, the present application provides a non-transitory machine-readable storage medium storing machine-readable instructions executable by a processor to perform instructions corresponding to the method steps provided by the present application, which when executed by a Central Processing Unit (CPU), perform the functions defined above in the method of the present application.
The methods and apparatus, devices of the present application may be implemented in numerous ways. For example, the methods and apparatus, devices of the present application may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present application are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present application may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present application. Thus, the present application also covers a recording medium storing a program for executing the method according to the present application.
In addition, in the foregoing technical solutions provided in the embodiments of the present application, parts consistent with implementation principles of corresponding technical solutions in the prior art are not described in detail, so that redundant descriptions are avoided.
The purpose, technical scheme and beneficial effects of the invention are further described in detail in the detailed description. It is to be understood that the above description is only of specific embodiments of the present invention and is not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
The above preset parameters or preset thresholds are set by those skilled in the art according to actual conditions or are obtained by mass data simulation.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.

Claims (3)

1. The method for evaluating the network performance of the equipment by using the power distribution terminal test signal time points is characterized by comprising the following steps:
Step one: collecting terminal position data and terminal model data in advance; acquiring a terminal set of a division area based on the terminal position data;
step two: collecting a pre-divided period set; collecting the communication transmission average time of the same day and the historical communication transmission average time of each power distribution terminal in each divided period of each day;
Step three: generating an area network abnormality judgment result for each divided area based on the current day communication transmission average time and the historical communication transmission average time of the terminals in each divided area, and turning to the fourth step if the area network abnormality judgment result is normal; if the regional network abnormality judgment result is abnormal, initiating regional network congestion warning;
step four: generating a terminal single network anomaly judgment result for each power distribution terminal in the divided area with a normal regional network anomaly judgment result based on the current day communication transmission average time and the historical communication transmission average time of each divided period;
Step five: the distribution terminals with abnormal judging results of all terminal single network abnormal are used as abnormal single terminals, and model network abnormal alarms and single network abnormal alarms are generated based on the terminal model data of all the abnormal single terminals;
the mode of collecting the terminal position data and the terminal model data in advance is as follows:
Collecting the geographic position coordinates of each power distribution terminal and the equipment model of each power distribution terminal, wherein the geographic position coordinates of all the power distribution terminals form terminal position data, and the equipment models of all the power distribution terminals form terminal model data;
The method for obtaining the terminal set of the divided area is as follows:
Collecting the positions of all core network nodes in the city;
Counting the main core network nodes through which each power distribution terminal transmits signals through a public network; the main core network node is the core network node through which the power distribution terminal transmits signals most frequently;
establishing a slave terminal set for each core network node, wherein the slave terminal set comprises all power distribution terminals taking the core network node as a main core network node;
All the subordinate terminal sets form a terminal set of a division area;
the statistical mode of the main core network node is as follows:
Each power distribution terminal transmits a plurality of analog signals to the master station front-end processor, and then counts all core network nodes passing through in the route of each analog signal;
for each power distribution terminal, taking the core network node with the most occurrence frequency in the route of all analog signals sent by the power distribution terminal as a main core network node;
The method for collecting the daily communication transmission average time and the historical communication transmission average time of each power distribution terminal in each divided period of each day is as follows:
After each power distribution terminal generates two remote signals, recording the generation time of the two remote signals;
The power distribution terminal sends two remote signals to the master station front-end processor, and the master station front-end processor records the receiving time of each received two remote signals;
subtracting the generation time from the receiving time of each two remote signals to obtain the network transmission time of the two remote signals;
The master station front-end processor classifies the two remote signals received by the latest date as current two remote signals according to the date of the receiving time of the two remote signals, takes each date before the latest date as a historical date, and takes the two remote signals received by each historical date as historical two remote signals;
determining the dividing period of each current two remote signals according to the generation time of the current two remote signals;
For each power distribution terminal, calculating the average value of network transmission time of current two remote signals sent by the power distribution terminal in each divided period, and taking the average value of network transmission time of the current two remote signals as the communication transmission average time of the power distribution terminal in the same day in the divided period;
Determining the dividing period of each historical two remote signal according to the generation time of the two remote signals;
In each history period, for each power distribution terminal, calculating the average value of network transmission time of the two remote signals of the history transmitted by the power distribution terminal in each divided period, and taking the average value of network transmission time of the two remote signals of the history as the average time of historical communication transmission of the power distribution terminal in the divided period;
The method for generating the regional network abnormality judgment result for each divided region comprises the following steps:
For each divided region:
presetting a communication delay threshold Y and historical reference days N;
the number of the power distribution terminals in the dividing area is marked as I, and the total number of the power distribution terminals in the dividing area is marked as I;
For each power distribution terminal, collecting historical communication transmission average time of N historical dates of previous historical reference days, and numbering the historical dates in time sequence as N, n=1, 2, 3..n;
Calculating the average value and variance of the communication transmission average time of the current day of the I power distribution terminals in the dividing area, respectively serving as the average value and variance of the current day area time, and respectively marking the average value and variance of the current day area time as AD and FD;
Calculating the average value of the communication transmission average time of the I power distribution terminals in the nth historical period in the dividing area as the time average value of the historical area, and marking the time average value of the historical area as AHn;
Calculating an area abnormality reference value Z of the divided area;
If the regional abnormality reference value Z is larger than a preset abnormal value threshold value, the regional network abnormality judgment result is abnormal;
If the regional abnormality reference value Z is smaller than or equal to a preset abnormal value threshold value, the regional network abnormality judgment result is normal;
The calculation mode of the regional abnormal reference value is as follows ; Wherein b1 and b2 are respectively preset proportionality coefficients;
the method for generating the terminal single network abnormity judgment result for each power distribution terminal comprises the following steps:
marking the communication transmission average time of the ith power distribution terminal on the same day as TDi, and marking the historical communication transmission average time of the ith power distribution terminal on the nth day as THin;
Calculating a monomer abnormal reference value Zi of an ith power distribution terminal;
the calculation formula of the monomer anomaly reference value Zi is as follows:
If the communication transmission average time TDi of the current day is larger than a preset communication delay threshold or a monomer abnormality reference value Zi is larger than a preset monomer fluctuation abnormality threshold, setting a terminal monomer network abnormality judgment result of the power distribution terminal as abnormality;
If the communication transmission average time TDi of the current day is smaller than or equal to a preset communication delay threshold value and the monomer anomaly reference value Zi is smaller than or equal to a preset monomer fluctuation anomaly threshold value, setting a terminal monomer network anomaly judgment result of the power distribution terminal to be normal;
the mode of generating model network abnormal alarms and monomer network abnormal alarms is as follows:
The number of the equipment model is marked as x;
Counting the abnormal specific gravity of the power distribution terminal of the x-th equipment model in all abnormal single terminals for the x-th equipment model, and marking the abnormal specific gravity as wx;
if the abnormal specific gravity wx of the x-th equipment model exceeds a preset abnormal specific gravity threshold value, marking the equipment model as an abnormal equipment model, and initiating model network abnormal alarm for the x-th equipment model;
And initiating a single network anomaly alarm for all power distribution terminals with non-anomaly equipment types in the anomaly single terminals.
2. An electronic device, comprising: a processor and a memory, wherein:
the memory stores a computer program which can be called by the processor;
The processor performs the method of evaluating device network performance using the power distribution terminal test signal time points of claim 1 in the background by invoking a computer program stored in the memory.
3. A computer readable storage medium having stored thereon a computer program that is erasable;
The computer program, when run on a computer device, causes the computer device to perform the method of evaluating device network performance using a power distribution terminal test signal time point as claimed in claim 1.
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