CN117425135B - Lightning arrester monitoring system based on secure wireless network and operation method - Google Patents

Abstract

The application discloses arrester monitoring system and operation method based on safe wireless network belongs to safe wireless network technical field, includes: the server receives first monitoring data acquired by monitoring equipment; uniformly or non-uniformly segment caching the first monitoring data and generating at least two groups of segment caching data; establishing a transmission optimization model, taking the segmented cache data as input of the transmission optimization model, and carrying out model analysis; and optimizing the data transmission of the lightning arrester monitoring system according to the output result of the transmission optimization model, generating a load reference, and adjusting the segmentation of the buffer space according to the load reference. In the implementation process of the technical scheme, the first monitoring data is uniformly or non-uniformly cached in a segmented mode, at least two groups of segmented cached data are generated, so that the first monitoring data is subjected to load balancing, the processor cannot generate larger frequency fluctuation in the process of processing the data, and the service life is prolonged.

Description

Lightning arrester monitoring system based on secure wireless network and operation method

Technical Field

The application relates to the technical field of safe wireless networks, in particular to a lightning arrester monitoring system based on a safe wireless network and an operation method.

Background

The MOA arrester is important equipment in the power production process, the main function of the MOA arrester in a transformer substation and a power transmission line is to protect other equipment from being damaged by lightning overvoltage and system surge overvoltage, the MOA arrester is often affected by multiple factors such as production process, production materials, operation environment and the like, the problems that the MOA arrester is affected by damp or a zinc oxide valve plate is aged and the like are caused, leakage current is finally out of standard, and the MOA arrester is thermally collapsed due to increase of resistive current in the leakage current, so that power safety production accidents are caused, and the working state of the MOA arrester needs to be monitored.

In the prior art, the related monitoring system can monitor the running state of the MOA lightning arrester, but most of the adopted communication modes are wired communication modes, cables are required to be laid between all terminals, meanwhile, the MOA lightning arrester is generally arranged at the tail end of a line and finally gathered in a control room, a large number of facilities such as pipelines, cable ditches and cable bridges are required to be pre-buried in the path, the on-site wiring difficulty is high, the wiring topology structure is complex, and particularly for some built substations, the cable ditches are closed, pavement is even required to be cut during construction, and the transformation cost is high;

therefore, the wireless communication mode is obviously superior to the wired communication mode, however, the data transmission delay in the monitoring process of the MOA lightning arrester by the current wireless communication mode cannot be applied on a large scale, because the wireless communication mode has some problems, such as the monitoring of the lightning arrester by using a lightning arrester monitoring system in the operation process of the lightning arrester, the lightning arrester monitoring system can involve the collection, the receiving and the processing of a large amount of monitoring data in the operation process, and is influenced by different factors, the monitoring data usually have different load peaks, and the monitoring data with different load peaks are usually in a random state when being received, processed and analyzed by a server, so that the frequency fluctuation of a processor can be caused, the processing efficiency of the processor can be influenced, the service life of the processor can be reduced, and the monitoring data is difficult to be applied to the monitoring process of the MOA lightning arrester.

There is a need to provide a lightning arrester monitoring system and operating method based on a secure wireless network to solve the above-mentioned problems.

It should be noted that the above information disclosed in this background section is only for understanding the background of the present application concept and, therefore, it may contain information that does not constitute prior art.

Disclosure of Invention

Based on the above problems existing in the prior art, the problems to be solved by the present application are: the lightning arrester monitoring system based on the safe wireless network and the operation method thereof are provided, the effect of balancing the load peak value of data is achieved, and the service life of a processor is prolonged.

The technical scheme adopted for solving the technical problems is as follows: a method of operating a lightning arrester monitoring system based on a secure wireless network, comprising:

the method comprises the steps that a server receives first monitoring data collected by monitoring equipment, wherein the first monitoring data are operation data of a lightning arrester monitoring system;

uniformly or non-uniformly segment caching the first monitoring data and generating at least two groups of segment caching data;

establishing a transmission optimization model, taking the segmented cache data as input of the transmission optimization model, and carrying out model analysis;

and optimizing the data transmission of the lightning arrester monitoring system according to the output result of the transmission optimization model, generating a load reference, and adjusting the segmentation of the buffer space according to the load reference.

In the implementation process of the technical scheme, the first monitoring data is uniformly or non-uniformly cached in a segmented mode, at least two groups of segmented cached data are generated, so that the first monitoring data is subjected to load balancing, the processor cannot generate larger frequency fluctuation in the process of processing the data, and the service life is prolonged.

Further, the method for uniformly segment caching the first monitoring data further comprises the following steps:

determining the size of a cache space according to the system requirement and the throughput of a server;

uniformly dividing the determined cache space in a segmented mode, wherein the dividing basis is the maximum load of the server;

distributing the first monitoring data into different segments using a distribution algorithm;

and establishing a cache replacement strategy, and dynamically regulating and controlling the data in the cache space.

Further, the allocation algorithm adopts a range-based allocation method.

Furthermore, the cache replacement strategy adopts a peak value alternate average comparison method.

Further, the peak value alternate average comparison method comprises the following steps:

judging peak value data in each segment, setting a threshold value range, averaging the peak value data in all segments to obtain a first average peak value after the current distribution is finished, comparing the first average peak value with the monitoring data in each segment, returning the monitoring data in the threshold value range lower or higher than the first average peak value to the first monitoring data, and selecting the monitoring data in the threshold value range of the first average peak value from the first monitoring data to replace the monitoring data in each segment.

Further, the method for non-uniformly segment caching the first monitoring data further comprises the following steps:

extracting the first monitoring data, and determining a segmentation basis based on load;

segmenting the first monitoring data to generate at least two data segments;

acquiring the data quantity of monitoring data in each data segment;

and determining the segmentation duty ratio of the buffer space according to the data quantity, and segmenting the buffer space.

Further, the load-based segmentation is based on the adoption of a load peak segmentation method.

A lightning arrester monitoring system based on a secure wireless network, the system comprising:

the receiving module is used for receiving first monitoring data acquired by the monitoring equipment from the server, wherein the first monitoring data are operation data of the lightning arrester monitoring system;

the segmented cache module is used for carrying out uniform or non-uniform segmented cache on the first monitoring data and generating at least two groups of segmented cache data;

the model building module is used for building a transmission optimization model, taking the segmented cache data as input of the transmission optimization model and carrying out model analysis;

and the transmission optimization module is used for monitoring the lightning arrester system according to the output result of the transmission optimization model.

And optimizing data transmission, generating a load reference, and adjusting the segmentation of the buffer space according to the load reference.

The beneficial effects of this application are: according to the lightning arrester monitoring system and the operation method based on the secure wireless network, the first monitoring data are uniformly or non-uniformly cached in a segmented mode, and at least two groups of segmented cache data are generated, so that load balancing is conducted on the first monitoring data, a processor cannot generate larger frequency fluctuation in the data processing process, the service life is prolonged, a cache replacement strategy is established, and data in a cache space are dynamically regulated and controlled.

In addition to the objects, features, and advantages described above, there are other objects, features, and advantages of the present application. The present application will be described in further detail with reference to the drawings.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:

fig. 1 is a flow chart of an operation method of a lightning arrester monitoring system based on a secure wireless network in the present application;

fig. 2 is a schematic diagram of the module configuration of a lightning arrester monitoring system based on a secure wireless network in the present application.

Detailed Description

It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.

Embodiment one: fig. 1 is a flowchart of steps of an operation method of an arrester monitoring system based on a secure wireless network, where the operation method is generally applied to an arrester monitoring system, and generally has a certain compatibility, and can also be applied to a monitoring system of other equipment terminals, so as to implement transmission optimization on an applied wireless communication manner, and improve safety and integrity of monitoring data, as shown in fig. 1, the operation method includes the following steps:

step 101: the method comprises the steps that a server receives first monitoring data collected by monitoring equipment, wherein the first monitoring data are operation data of a lightning arrester monitoring system;

in the operation process of the lightning arrester monitoring system, operation data need to be collected through preloaded monitoring equipment, wherein the monitoring equipment comprises (but is not limited to) various sensors, such as bus voltage/current sensors with WAPI interfaces, temperature and humidity sensors arranged at all the equipment, mechanical parameter sensors and the like, a data collection terminal, image and/or video monitoring equipment, a cloud platform, a user interface, an alarm system and the like, and in the embodiment, the lightning arrester monitoring system can adopt a WAPI-based wireless local area network safety standard, and in other embodiments, can also adopt a WPA, RADIUS-based standard and the like to improve the safety in the wireless transmission process;

the first monitoring data comprise state data of the lightning arrester, and are used for monitoring the working state of the lightning arrester, such as whether the lightning arrester works normally, whether faults exist or not, and the like; environmental data, which is used for monitoring the related data of the environment where the lightning arrester is located, such as temperature, humidity, air pressure and the like; electrical parameter data for monitoring electrical parameter data, such as current, voltage, etc., contacted by the arrester; mechanical parameter data for monitoring mechanical parameters of the lightning arrester, such as vibration, displacement, etc.; timestamp data for recording the time points or periods of data acquisition for providing a time dimension for the monitored data, which can all be used as parameters for the operation of the lightning arrester monitoring system.

It should be noted that, in this embodiment, the server refers to a hardware terminal with receiving, storing and processing capabilities, and is not a large server device in a conventional sense, and the monitoring device generally has a buffering function, and in the operation process of the monitoring device, the monitored data may be buffered, and after a specific start signal is sent to the server, the buffered first data set is sent to the server.

Step 102: uniformly or non-uniformly segment caching the first monitoring data and generating at least two groups of segment caching data;

in the operation process of the lightning arrester monitoring system, a large amount of monitoring data are usually required to be collected and analyzed in real time to monitor the state and performance of the lightning arrester, the monitoring data have the characteristics of real-time performance, burst performance and the like, and once a server for receiving and processing the monitoring data is excessively high in load or wide in fluctuation range, negative events such as slow data receiving, low analysis efficiency and even data loss are likely to be caused to influence the normal operation of the lightning arrester monitoring system, so that after the first monitoring data are collected, the first monitoring data are required to be optimized to be matched with the performance and the load capacity of the server;

specifically, a segmented caching method is adopted for optimizing the first monitoring data, wherein the segmented caching refers to dividing the data to be cached into a plurality of segments (or partitions), and each segment (or partition) stores a part of data.

In this embodiment, in order to avoid uneven data size distribution between different segments, which results in overload of data in some segments, and relatively less data size in other segments, thereby affecting an analysis and processing process of a server, a uniform segment buffer method may be used to perform uniform segment buffer on the first monitored data, and specifically, the method includes:

step a: determining the size of a cache space according to the system requirement and the throughput of a server;

in order to realize the buffer function, besides meeting the corresponding hardware requirement, the size of the buffer space is determined according to the system requirement and the throughput condition of the server, and the size of the buffer space is required to be smaller than the maximum buffer space supported by hardware, when the size of the buffer space determined according to the system requirement and the throughput of the server is larger than the maximum buffer space supported by hardware, the current throughput of the server is indicated to be overlarge, and an early warning message is sent out, and the early warning is released after the size of the buffer space is smaller than the maximum buffer space supported by hardware, so that the instantaneous throughput of the server is effectively prevented from being overlarge, and negative conditions such as low processing efficiency and the like are caused;

in order to improve the operation efficiency, the size of the buffer space is generally not equal to the maximum buffer space supported by hardware, so that proper allowance is provided, the buffer space is prevented from being in a full-load state for a long time, and the service life of the monitoring equipment is prolonged;

step b: uniformly dividing the determined cache space in a segmented mode, wherein the dividing basis is the maximum load of the server;

after the size of the cache space is determined, the cache space is required to be uniformly segmented, and the size of each segment is determined based on the maximum load of the server, so that the monitoring data can be received and processed under the condition that the server is fully loaded, and the data in the determined size of the segment is prevented from exceeding the maximum load range of the server, so that the analysis processing process of the server is influenced;

the load of the server is generally judged according to multiple aspects, such as a CPU utilization rate, a memory utilization rate, a network bandwidth usage amount, a hard disk IO usage condition, a temperature change curve and the like, in this embodiment, a comprehensive judging method is adopted to assign different specific gravities to different factors, and comprehensively judge the load of the server, where the method can be adjusted according to factory characteristics and usage situations of the server, such as when the usage situations are situations with higher requirements on the CPU, the specific gravity of the CPU utilization rate can be increased, the load of the server is judged, and when the usage situations are situations with higher requirements on the memory, the specific gravity of the memory utilization rate can be increased, and other similar methods are not repeated here and below;

step c: distributing the first monitoring data into different segments using a distribution algorithm;

after the determined cache space is segmented, the first monitoring data is also required to be distributed to each segment, so that uniform cache of the first monitoring data is realized, load balancing and data segmentation are realized, the throughput of the system is improved, and the load of a server is reduced;

the allocation of the first monitored data to the different segments is typically implemented using an allocation algorithm, such as a hash algorithm-based allocation, a range-based allocation, a load balancing-based allocation, a heat-based allocation, etc., and in the uniform segment cache, a range-based allocation is typically implemented, where the allocation method is to divide the data according to a range of a certain attribute, specifically:

when the first monitoring data is collected, corresponding time stamps are recorded, time attributes are used as distribution basis, a time stamp range corresponding to each segment is set, the first monitoring data in the range is put into the corresponding segment, each segment is provided with a unique time stamp mark, uniform segment caching of the monitoring data can be achieved, each segment mark is obvious, the receiving and subsequent tracing of the server are facilitated, the time stamp unit can be customized, for example, the monitoring data recorded every other hour is used as one segment.

Step d: and establishing a cache replacement strategy, and dynamically regulating and controlling the data in the cache space.

Because a uniform segment caching method is adopted, the length or the size of each segment is the same, but the distributed monitoring data also has non-uniformity, for example, in the step c, when the time attribute is used as the distribution basis to distribute the data, although each segment is uniformly split, the data distributed in each segment has non-uniformity, so that the overload of some segments or the unbalanced load among segments are caused, therefore, a cache replacement strategy needs to be established, the data in the cache space is dynamically regulated, and the loads among different segments are in a relatively balanced state, and the method is specific:

the current common cache replacement strategies have the modes of Least Recently Used (LRU), first-in first-out (FIFO), least-used (LFU), random Replacement (RR) and the like, and the methods are not suitable for coping with load balancing in different segments, so that a peak value alternate average comparison method is adopted, the method only needs to judge peak value data in each segment (namely data causing the maximum load of a server), sets a threshold range, averages the peak value data in all segments to obtain a first average peak value after the current distribution, compares the first average peak value with monitoring data in each segment, returns the monitoring data in a threshold range lower than or higher than the first average peak value to the first monitoring data, and selects the monitoring data in the threshold range of the first average peak value from the first monitoring data to replace the monitoring data in each segment, thereby realizing load balancing;

after the replacement is finished, the monitoring data in each segment can be received by the server, all segments are emptied, the next round of monitoring data distribution is carried out, a second average peak value is obtained by adopting the same method until all data in the first monitoring data are distributed, the load in each round of segments can be in a balanced state by the method, and frequent frequency fluctuation caused by the load difference of the monitoring data cannot influence the analysis processing efficiency in the process of analyzing the segments by the server;

the threshold range can be defined according to the performance of the server;

it should be noted that, the peak value in this embodiment is different from the existing peak value comparison method (PAR), and the existing peak value comparison method is generally used for measuring the difference between the peak value and the average value of the signal waveform, so as to evaluate the amplitude variation and the dynamic range of the signal, while the peak value in this embodiment is used for making the monitoring data received by each round of server have a relatively stable load range, so that no relatively large frequency fluctuation is generated in the analysis process, the analysis efficiency is improved, and the service life is prolonged.

The step is to uniformly segment the first monitoring data by using a uniform segment caching method, and the following description will describe a non-uniform segment caching method for non-uniform segment caching of the first monitoring data, specifically:

in the above step, the buffer space is uniformly segmented, and the first monitoring data is distributed to each uniform segment by adopting a distribution algorithm, and then the monitoring data in the buffer space is dynamically regulated and controlled by a buffer replacement strategy, so as to realize load balancing.

Step A: extracting the first monitoring data, and determining a segmentation basis based on load;

extracting the first monitoring data comprises preprocessing the data, such as data cleaning, denoising, normalization and the like, so that the accuracy and consistency of the first monitoring data are ensured, and a load-based segmentation basis is established in the process, so that the subsequent segmentation of the first monitoring data is facilitated;

the load-based segmentation criterion refers to selecting a segmentation criterion according to the load condition of data distribution when segmenting a certain group of data, and in the embodiment, a load peak segmentation method is adopted, namely, segmentation is performed according to the load peak of each data in the first monitoring data;

and (B) step (B): segmenting the first monitoring data to generate at least two data segments;

the load peak value refers to the maximum load peak value generated when certain data is received and processed by the server, and in the processing process of the server, stable peak value change is required to be carried out in each receiving and processing process of the server as much as possible, so that the processing efficiency and the service life of the server are improved, after the load peak value of each monitoring data in the first monitoring data is obtained, the load peak value of all the monitoring data is sequenced according to the load peak value, the average load peak value of all the monitoring data is calculated, then the monitoring data in the first monitoring data is selected based on the average load peak value, a plurality of data segments are generated, and the average load peak value of the monitoring data in each data segment is consistent with the average load peak value of the first monitoring data, so that the segmentation of the first monitoring data is completed;

in addition, in addition to making the average load peak value of the monitored data in each data segment coincide with the average load peak value of the first monitored data, a corresponding threshold value may be set, so that the difference between the average load peak value of the monitored data in each data segment and the average load peak value of the first monitored data is within the threshold value, and the threshold value may be set according to the load level of the server;

step C: acquiring the data quantity of monitoring data in each data segment;

after the data segments are generated, the monitoring data in each data segment has a corresponding data volume, and the data volume can be obtained through various methods, such as file statistics, API call and the like, which are not repeated here;

step D: determining the segmentation duty ratio of the cache space according to the data quantity, and segmenting the cache space;

after the data volume is determined, the ratio of the buffer space can be determined according to the data volume of the monitoring data, specifically, the ratio of the data volume in one data segment to all the data volumes is the buffer space segment ratio of the data segment, so that the segments of the buffer space are divided based on the data volume of each data segment;

according to the method, the first monitoring data are segmented based on the load, then the average load peak value method is adopted to enable each data segment to contain the monitoring data with stable peak value, the segmentation proportion of the buffer space is determined according to the data size of each segment, the segmentation of the buffer space is completed, the size of each segment in the buffer space after the segmentation is completed is not necessarily the same, but after the load balancing and the data size segmentation, the data contained in each segment of the buffer space received by the server cannot enable the server to generate larger frequency fluctuation, so that the receiving and analyzing efficiency is improved, and the service lives of the server and related equipment are prolonged.

Step 103: establishing a transmission optimization model, taking the segmented cache data as input of the transmission optimization model, and carrying out model analysis;

the transmission optimization model is a model for improving data transmission efficiency, reducing cost, and enhancing reliability before or during data transmission, and in this embodiment, the transmission optimization model may be set to various types, including (but not limited to):

the bandwidth optimization model ensures that the transmission requirements of all tasks are met while the bandwidth is efficiently utilized by reasonably distributing network bandwidth resources;

the route optimization model selects the optimal data transmission path through optimizing a route algorithm, so that delay and congestion of data transmission are reduced, and transmission efficiency and reliability are improved;

the data compression and coding model reduces the transmission quantity of data through compression and coding technology, thereby improving the transmission efficiency and reducing the transmission cost;

the cache optimization model caches commonly used data locally by reasonably setting a cache strategy, so that delay of data transmission and consumption of network bandwidth are reduced;

the data slicing and parallel transmission model divides large data into a plurality of small blocks, and data transmission is performed in a parallel transmission mode, so that the transmission speed and efficiency are improved;

QoS (Quality of Service) optimization model ensures that the transmission priority and bandwidth requirement of the key task are met by reasonably setting the priority and service quality of data transmission;

the fault tolerance and redundancy optimization model ensures the reliability and safety of data transmission by introducing redundancy data and a fault tolerance mechanism so as to cope with the situations of network faults and data loss.

Step 104: optimizing data transmission of the lightning arrester monitoring system according to an output result of the transmission optimization model, generating a load reference, and adjusting segmentation of the buffer space according to the load reference;

after analysis is carried out through the transmission optimization model, a result is output according to the current data information, the result can represent the processing pressure of the current server, and a load reference is generated based on the output result, the load reference can better reflect the running pressure of the server, compared with the situation that a worker judges the running pressure of the server according to experience, the segmentation of the buffer space is adjusted, the method can carry out transmission optimization according to the running condition of the server more accurately, and therefore the data transmission efficiency of the lightning arrester monitoring system in the running process is improved.

Embodiment two: as shown in fig. 2, the present invention provides a lightning arrester monitoring system based on a secure wireless network, the system operating in the first embodiment of the system, the system comprising:

the receiving module is used for receiving first monitoring data acquired by the monitoring equipment from the server, wherein the first monitoring data are operation data of the lightning arrester monitoring system;

the segmented cache module is used for carrying out uniform or non-uniform segmented cache on the first monitoring data and generating at least two groups of segmented cache data;

the model building module is used for building a transmission optimization model, taking the segmented cache data as input of the transmission optimization model and carrying out model analysis;

and the transmission optimization module is used for optimizing the data transmission of the lightning arrester monitoring system according to the output result of the transmission optimization model, generating a load reference and adjusting the segmentation of the buffer space according to the load reference.

The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the same, but rather, various modifications and variations may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims (2)

1. An operation method of a lightning arrester monitoring system based on a safe wireless network is characterized in that: comprising the following steps:

the method comprises the steps that a server receives first monitoring data collected by monitoring equipment, wherein the first monitoring data are operation data of a lightning arrester monitoring system;

uniformly or non-uniformly segment caching the first monitoring data and generating at least two groups of segment caching data;

establishing a transmission optimization model, taking the segmented cache data as input of the transmission optimization model, and carrying out model analysis; the transmission optimization model comprises a bandwidth optimization model, a routing optimization model, a data compression and coding model, a cache optimization model, a data slicing and parallel transmission model, a QoS optimization model, a fault tolerance and redundancy optimization model;

optimizing data transmission of the lightning arrester monitoring system according to an output result of the transmission optimization model, generating a load reference, and adjusting segmentation of the buffer space according to the load reference;

the method for uniformly and sectionally caching the first monitoring data further comprises the following steps:

determining the size of a cache space according to the system requirement and the throughput of a server;

uniformly dividing the determined cache space in a segmented mode, wherein the dividing basis is the maximum load of the server;

distributing the first monitoring data into different segments using a distribution algorithm;

establishing a cache replacement strategy, and dynamically regulating and controlling data in a cache space;

the allocation algorithm adopts a range-based allocation method;

the cache replacement strategy adopts a peak value alternate average comparison method;

the peak value alternate average comparison method comprises the following steps:

judging peak value data in each segment, setting a threshold value range, averaging the peak value data in all segments to obtain a first average peak value after the current distribution is finished, comparing the first average peak value with the monitoring data in each segment, returning the monitoring data in the threshold value range lower or higher than the first average peak value to the first monitoring data, and selecting the monitoring data in the threshold value range of the first average peak value from the first monitoring data to replace the monitoring data in each segment;

the method for non-uniformly segment caching of the first monitoring data further comprises the following steps:

extracting the first monitoring data, and determining a segmentation basis based on load;

segmenting the first monitoring data to generate at least two data segments;

acquiring the data quantity of monitoring data in each data segment;

determining the segmentation duty ratio of the cache space according to the data quantity, and segmenting the cache space;

the load-based segmentation is based on the adoption of a load peak segmentation method.

2. A secure wireless network based arrester monitoring system for implementing a method of operating a secure wireless network based arrester monitoring system as defined in claim 1, wherein: the system comprises:

the receiving module is used for receiving first monitoring data acquired by the monitoring equipment from the server, wherein the first monitoring data are operation data of the lightning arrester monitoring system;

the segmented cache module is used for carrying out uniform or non-uniform segmented cache on the first monitoring data and generating at least two groups of segmented cache data;

the model building module is used for building a transmission optimization model, taking the segmented cache data as input of the transmission optimization model and carrying out model analysis;

and the transmission optimization module is used for optimizing the data transmission of the lightning arrester monitoring system according to the output result of the transmission optimization model, generating a load reference and adjusting the segmentation of the buffer space according to the load reference.