WIFI terminal intelligent configuration method based on wireless communication technology

Abstract

The invention discloses a WIFI terminal intelligent configuration method based on a wireless communication technology, and relates to the technical field of wireless communication, and the method comprises the steps: traversing an equipment array in a target transformer substation to carry out infrastructure information collection, and generating Q infrastructure operation information of Q infrastructures; determining Q data transmission quantities and Q transmission frequencies of the Q basic devices; generating a target transmission bandwidth distribution map; carrying out region division to generate M grid regions; performing terminal configuration to obtain M pieces of WIFI terminal configuration information; and performing WIFI terminal configuration based on the M grid areas, the M WIFI terminal configuration numbers and the M WIFI terminal configuration parameters. According to the method and the device, the technical problem of low reliability of monitoring operation of equipment in the substation caused by insufficient fitting degree of WIFI terminal configuration in the substation and actual requirements in the prior art is solved, and the technical effect of improving the fitting degree of the WIFI terminal configuration and the actual requirements of the substation is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication, and in particular to a WIFI terminal intelligent configuration method based on wireless communication technology. Background Art

[0002] In substations, the lack of fit between WiFi terminal configuration and actual needs may reduce the reliability of monitoring the operation of equipment in the substation. At present, the frequency range and channel bandwidth settings of WiFi terminals mainly rely on standard parameter settings, which are often not suitable for the complex electromagnetic environment of substations, resulting in signal interference and insufficient coverage, which in turn affects the data transmission stability of the equipment.

[0003] The existing technology has the technical problem that the configuration of WIFI terminals in substations is not sufficiently in line with actual needs, resulting in low reliability of monitoring the operation of equipment in the station. Summary of the invention

[0004] The present application provides a WIFI terminal intelligent configuration method based on wireless communication technology, which is used to solve the technical problem in the prior art that the WIFI terminal configuration in the substation is not sufficiently consistent with the actual demand, resulting in low reliability of monitoring the operation of equipment in the station.

[0005] In view of the above problems, the present application provides a WIFI terminal intelligent configuration method based on wireless communication technology.

[0006] In one aspect of the present application, a WIFI terminal intelligent configuration method based on wireless communication technology is provided, wherein the method is applied to a terminal intelligent configuration system, the terminal intelligent configuration system is communicatively connected to an equipment array of a target substation, and the method comprises: Traversing the equipment array in the target substation to collect basic equipment information, and generating Q basic equipment operation information of Q basic equipment, wherein the Q basic equipment includes Q positioning identifiers and Q equipment model identifiers; Perform cloud data transmission identification based on the Q device model identifiers, and determine Q data transmission volumes and Q transmission frequencies of the Q basic devices; Calculate Q transmission bandwidth requirements of the Q basic devices according to the Q data transmission amounts and the Q transmission frequencies, identify the transmission bandwidth distribution of the target substation according to the Q transmission bandwidth requirements and the Q positioning identifiers, and generate a target transmission bandwidth distribution map, wherein the target transmission bandwidth distribution map has Q scattered points; According to the sizes of the Q transmission bandwidth requirements, the target transmission bandwidth distribution map is divided into regions to generate M grid regions, wherein the M grid regions include M basic equipment sets and M transmission bandwidth requirement sets; Traversing and counting the area of ​​the M grid areas, obtaining the area of ​​the M grid areas, performing terminal configuration in combination with the M transmission bandwidth requirement sets and the WIFI terminal parameter interval of the target substation, and obtaining the M WIFI terminal configuration information of the M grid areas, wherein the M WIFI terminal configuration information includes the number of M WIFI terminal configurations and the M WIFI terminal configuration parameters; The target substation is configured with WIFI terminals based on the M grid areas, the M WIFI terminal configuration quantities and the M WIFI terminal configuration parameters.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The present application collects basic equipment information by traversing the equipment array in the target substation, generates Q basic equipment operation information of Q basic equipment, wherein the Q basic equipment includes Q positioning identifiers and Q equipment model identifiers, and then performs cloud data transmission identification based on the Q equipment model identifiers, determines the Q data transmission volumes and Q transmission frequencies of the Q basic equipment, and then calculates the Q transmission bandwidth requirements of the Q basic equipment according to the Q data transmission volumes and Q transmission frequencies, and identifies the transmission bandwidth distribution of the target substation according to the Q transmission bandwidth requirements and the Q positioning identifiers, generates a target transmission bandwidth distribution map, wherein the target transmission bandwidth distribution map has Q scattered points, and then according to the size of the Q transmission bandwidth requirements The target transmission bandwidth distribution map is divided into regions to generate M grid regions, wherein the M grid regions include M basic equipment sets and M transmission bandwidth demand sets, and the M grid region areas are obtained by traversing and counting the regional areas of the M grid regions, and the terminal configuration is performed in combination with the M transmission bandwidth demand sets and the WIFI terminal parameter interval of the target substation, and the M WIFI terminal configuration information of the M grid regions is obtained, wherein the M WIFI terminal configuration information includes the number of M WIFI terminal configurations and the M WIFI terminal configuration parameters, and then the WIFI terminal configuration of the target substation is performed based on the M grid regions, the number of M WIFI terminal configurations and the M WIFI terminal configuration parameters. The technical effect of improving the degree of fit between the WIFI terminal configuration and the actual needs of the substation is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1A schematic diagram of a flow chart of a WIFI terminal intelligent configuration method based on wireless communication technology provided in an embodiment of the present application; Figure 2 A schematic diagram of a flow chart of obtaining Q data transmission amounts and Q transmission frequencies in a WIFI terminal intelligent configuration method based on wireless communication technology provided in an embodiment of the present application; DETAILED DESCRIPTION

[0010] The present application provides a WIFI terminal intelligent configuration method based on wireless communication technology, which is used to solve the technical problem that the configuration of WIFI terminals in substations in the prior art is not sufficiently consistent with actual needs, resulting in low reliability of monitoring the operation of equipment in the station.

[0011] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0012] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices.

[0013] Embodiment 1 like Figure 1 As shown, the present application provides a WIFI terminal intelligent configuration method based on wireless communication technology, wherein the method is applied to a terminal intelligent configuration system, the terminal intelligent configuration system is communicatively connected with an equipment array of a target substation, and the method includes: S100: traversing the equipment array in the target substation to collect basic equipment information, and generating Q basic equipment operation information of Q basic equipment, wherein the Q basic equipment includes Q positioning identifiers and Q equipment model identifiers; In a possible embodiment, the target substation is any substation that needs to be configured with a WIFI terminal, and the target substation includes various types of equipment, such as substation equipment (transformers, switchgear, capacitors, current transformers, circuit breakers and grounding equipment, etc.), power distribution equipment (distribution transformers, distribution switchgear, distribution lines, etc.), and electronic power equipment (frequency converters, static VAR compensators, digital energy meters, etc.). Different devices need to be configured with WIFI terminals with different transmission powers to ensure the data transmission requirements of the devices in the station. The terminal intelligent configuration system is a system for intelligently configuring parameters of the WIFI terminals in the target substation.

[0014] Optionally, the device array reflects the distribution of devices deployed in the target substation, including the number of devices and the locations of device distribution. By collecting basic device information from the device array in the target substation, the distribution type and distribution location of the devices in the target substation are mastered, thereby obtaining Q basic device operation information of the Q basic devices. Among them, the Q basic device operation information reflects the location distribution and device type of the Q basic devices in the target substation, including Q positioning identifiers and Q device model identifiers.

[0015] Obtaining the Q device model identifiers paves the way for subsequent analysis of the data transmission bandwidth requirements of the Q basic devices, and obtaining the Q positioning identifiers provides data support for subsequent division of different grid areas.

[0016] S200: Perform cloud data transmission identification based on the Q device model identifiers, and determine Q data transmission volumes and Q transmission frequencies of the Q basic devices; Further, such as Figure 2 As shown, based on the Q device model identifiers, cloud data transmission identification is performed to determine Q data transmission volumes and Q transmission frequencies of the Q basic devices. Step S200 of the embodiment of the present application also includes: Using the Q device model identifiers as indexes, performing data retrieval in the cloud to obtain Q sample data transmission volume sets and Q sample transmission frequency sets; Performing fluctuation consistency analysis on the Q sample data transmission volume sets and the Q sample transmission frequency sets respectively to obtain fluctuation coefficients of the Q sample data transmission volumes and fluctuation coefficients of the Q sample transmission frequencies; Determine whether the fluctuation coefficients of the Q sample data transmission volumes and the fluctuation coefficients of the Q sample transmission frequencies meet a preset fluctuation coefficient threshold; if so, respectively calculate the means of the Q sample data transmission volume sets and the Q sample transmission frequency sets, and obtain the Q data transmission volumes and the Q transmission frequencies according to the calculation results.

[0017] Furthermore, step S200 of this embodiment further includes: If not, extracting a sample mode from the Q sample data transmission amount sets and the Q sample transmission frequency sets to obtain Q sample data transmission amount modes and Q sample transmission frequency modes; According to the modes of the Q sample data transmission amounts and the modes of the Q sample transmission frequencies, data fluctuation edges are identified in the Q sample data transmission amount sets and the Q sample transmission frequency sets, data distribution intensive areas are determined, and Q sample data transmission amount intensive sets and Q sample transmission frequency intensive sets are generated; Mean calculation is performed on the Q dense sets of sample data transmission amounts and the Q dense sets of sample transmission frequencies to generate the Q data transmission amounts and the Q transmission frequencies.

[0018] In one possible embodiment, cloud data transmission identification is performed on the Q device model identifiers. That is, based on the device models of the Q basic devices, the data transmission volume and transmission frequency required for the operation of cloud devices of the same model as the device are extracted from the cloud big data, thereby providing a basis for reliable analysis of the transmission bandwidth required for the Q basic devices.

[0019] Optionally, the Q data transmission volumes are the amount of data transmitted by the Q basic devices per unit time, usually expressed in bits or bytes. The size of the data transmission volume depends on factors such as the performance of the device, the connection speed, the transmission protocol, and the type and frequency of the data transmitted. The data transmission volume of the same type of devices under the same configuration fluctuates within a certain range. The Q transmission frequencies are the transmission rates of the transmission data of the Q basic devices per unit time, usually expressed in Hertz (Hz).

[0020] In a possible embodiment, the Q device model identifiers are used as indexes to perform data retrieval in a cloud database to obtain the operation status of devices of the same model as the Q basic devices, that is, the Q sample data transmission volume sets and the Q sample transmission frequency sets. Furthermore, after obtaining the Q sample data transmission volume sets and the Q sample transmission frequency sets, a fluctuation consistency analysis is performed based on the Q sample data transmission volume sets and the Q sample transmission frequency sets to determine the data fluctuation status of the Q sample data transmission volume sets and the Q sample transmission frequency sets, and obtain the Q sample data transmission volume fluctuation coefficients and the Q sample transmission frequency fluctuation coefficients.

[0021] Optionally, the Q sample data transmission volume fluctuation coefficients reflect the data transmission volume fluctuation of the Q sample device sets in unit time. The larger the sample data transmission volume fluctuation coefficient, the greater the data fluctuation of the corresponding sample device set from the dimension of data transmission volume, the poor consistency, and the need to perform edge data cleaning on the data to ensure data reliability. If the data fluctuation is small and the consistency is good, it indicates that the data quality is high. At this time, the Q data transmission volumes can be obtained by analysis based on the Q sample data transmission volume sets.

[0022] Based on the same principle, the Q sample transmission frequency fluctuation coefficients reflect the fluctuation of the data transmission frequency of the Q sample device sets within a unit time.

[0023] Furthermore, it is determined whether the fluctuation coefficients of the Q sample data transmission volumes and the fluctuation coefficients of the Q sample transmission frequencies meet a preset fluctuation coefficient threshold (a minimum fluctuation coefficient value pre-set by a person skilled in the art when the data quality is high and can be directly analyzed). If so, it indicates that the data quality of the Q sample data transmission volume set and the Q sample transmission frequency set is high. At this time, the means of the Q sample data transmission volume set and the Q sample transmission frequency set are calculated respectively, and the calculated means are used as the Q data transmission volumes and the Q transmission frequencies.

[0024] If not, it indicates that the data quality is not high and data screening is needed to extract the data with relatively concentrated distribution in the Q sample data transmission volume sets and the Q sample transmission frequency sets, so as to perform mean calculation as representative data to achieve the goal of improving the reliability of data analysis.

[0025] Optionally, the sample mode (the most distributed data in the set) is extracted from the Q sample data transmission volume sets and the Q sample transmission frequency sets to obtain the Q sample data transmission volume mode and the Q sample transmission frequency mode. Further, data fluctuation edge identification is performed in the Q sample data transmission volume sets and the Q sample transmission frequency sets based on the Q sample data transmission volume mode and the Q sample transmission frequency mode, and the data distribution intensive area is determined to generate Q sample data transmission volume intensive sets and Q sample transmission frequency intensive sets. Then, the mean calculation is performed on the Q sample data transmission volume intensive sets and the Q sample transmission frequency intensive sets, and the Q data transmission volumes and the Q transmission frequencies are generated based on the mean calculation result.

[0026] Further, according to the modes of the Q sample data transmission amounts and the modes of the Q sample transmission frequencies, data fluctuation edges are identified in the Q sample data transmission amount sets and the Q sample transmission frequency sets, data distribution intensive areas are determined, and Q sample data transmission amount intensive sets and Q sample transmission frequency intensive sets are generated. Step S200 of the embodiment of the present application further includes: Counting the number of differences between the sample data transmission amounts in the Q sample data transmission amount sets and the modes of the Q sample data transmission amounts within a preset step length, and taking the ratios of the Q first statistical results to the preset step length as Q first fluctuation densities; Counting again the number of differences between the sample data transmission amounts in the Q sample data transmission amount sets and the modes of the Q sample data transmission amounts within two preset step sizes, and taking the ratio of the Q second statistical results to the sum of the two preset step sizes as Q second fluctuation densities; Determine whether the difference between the Q first fluctuation densities and the Q second fluctuation densities meets a preset fluctuation density difference, and if so, take a plurality of sample data transmission amounts in the set of Q sample data transmission amounts whose difference between the sample data transmission amounts and the mode of the Q sample data transmission amounts is within a preset step length as a dense set of Q sample data transmission amounts; If not, continue to calculate Q third fluctuation densities, perform data fluctuation edge identification based on the Q third fluctuation densities and the Q second fluctuation densities, and determine the data distribution dense area, wherein the Q third fluctuation densities are the number of differences between the sample data transmission amounts in the Q sample data transmission amount sets and the modes of the Q sample data transmission amounts within three preset step sizes, to obtain Q third statistical results, and compare the Q third statistical results with the sum of the three preset step sizes to obtain the ratio.

[0027] In a possible embodiment, the number of differences between the sample data transmission amounts in the Q sample data transmission amount sets and the modes of the Q sample data transmission amounts within a preset step length is counted respectively, and then the ratio of the Q first statistical results to the preset step length is used as the Q first fluctuation densities. The Q first fluctuation densities reflect the density of data distribution within the preset step length. The preset step length is the data transmission amount size preset by those skilled in the art.

[0028] The number of differences between the sample data transmission amounts in the Q sample data transmission amount sets and the modes of the Q sample data transmission amounts within two preset step sizes is counted again, and the ratio of the Q second statistical results to the sum of the two preset step sizes is used as the Q second fluctuation densities. The Q second fluctuation densities reflect the density of the distribution of the Q sample data transmission amount sets within the two preset step sizes of the modes of the Q sample data transmission amounts.

[0029] Determine whether the difference between the Q first fluctuation densities and the Q second fluctuation densities meets the preset fluctuation density difference. If so, take multiple sample data transmission amounts in the set of Q sample data transmission amounts whose difference between the sample data transmission amounts and the mode of the Q sample data transmission amounts within a preset step size as a dense set of Q sample data transmission amounts.

[0030] If not, continue to calculate Q third fluctuation densities, perform data fluctuation edge identification based on the Q third fluctuation densities and the Q second fluctuation densities, and determine the data distribution dense area, wherein the Q third fluctuation densities are the number of differences between the sample data transmission amounts in the Q sample data transmission amount sets and the modes of the Q sample data transmission amounts within three preset step sizes, to obtain Q third statistical results, and compare the Q third statistical results with the sum of the three preset step sizes to obtain the ratio.

[0031] Based on the same obtaining principle, data fluctuation edge identification is performed according to the modes of the Q sample transmission frequencies and the sets of the Q sample transmission frequencies to obtain the dense set of the Q sample transmission frequencies.

[0032] S300: Calculate Q transmission bandwidth requirements of the Q basic devices according to the Q data transmission volumes and the Q transmission frequencies, identify the transmission bandwidth distribution of the target substation according to the Q transmission bandwidth requirements and the Q positioning identifiers, and generate a target transmission bandwidth distribution map, wherein the target transmission bandwidth distribution map has Q scattered points; Furthermore, step S300 of the embodiment of the present application further includes: Multiplying the Q data transmission amounts and the Q transmission frequencies respectively to obtain the Q transmission bandwidth requirements; According to the Q positioning identifiers of the Q basic equipment corresponding to the Q transmission bandwidth requirements, a scatter plot is drawn for the transmission bandwidth requirement distribution in the target substation, where each scatter point corresponds to a transmission bandwidth requirement, and the target transmission bandwidth distribution map is generated.

[0033] In a possible embodiment, after obtaining the Q data transmission amounts and the Q transmission frequencies, the Q data transmission amounts and the Q transmission frequencies are multiplied respectively to obtain the Q transmission bandwidth requirements, wherein the Q transmission bandwidth requirements reflect the transmission bandwidth required by the Q basic devices for data transmission.

[0034] Then, the transmission bandwidth distribution of the target substation is identified according to the Q transmission bandwidth requirements and the Q positioning identifiers, and Q scattered points in the target transmission bandwidth distribution map in the target substation are determined according to the Q positioning identifiers, and then the Q scattered points are identified using the Q transmission bandwidth requirements to obtain a constructed target transmission bandwidth distribution map. The target transmission bandwidth distribution map reflects the transmission bandwidth distribution of the target substation.

[0035] S400: Dividing the target transmission bandwidth distribution map into regions according to the sizes of the Q transmission bandwidth requirements to generate M grid regions, wherein the M grid regions include M basic equipment sets and M transmission bandwidth requirement sets; Further, the target transmission bandwidth distribution map is divided into regions according to the sizes of the Q transmission bandwidth requirements to generate M grid regions. Step S400 of the embodiment of the present application further includes: Randomly extract P transmission bandwidth requirements from the Q transmission bandwidth requirements, and use the P scattered points corresponding to the P transmission bandwidth requirements as P starting scattered points; Performing a neighbor search on the P starting scattered points to determine a set of P neighbor scattered points; The neighboring scattered points in the P neighboring scattered point sets, whose transmission bandwidth requirements are within a preset requirement difference range and whose transmission bandwidth requirements are within a preset requirement difference range, are integrated into the P starting areas of the P starting scattered points, wherein the P starting areas have P starting transmission bandwidth requirements, and the P starting transmission bandwidth requirements are the averages of multiple transmission bandwidth requirements of multiple neighboring scattered points in the P starting areas; Taking the P starting areas as starting points, neighbor search is performed again until the edge of the target transmission bandwidth distribution graph is reached to obtain P starting grid areas.

[0036] Further, P starting grid areas are obtained, and then step S400 of the embodiment of the present application further includes: It is determined whether the areas of the P starting grid regions are less than or equal to a preset grid area. If so, they are integrated into a neighboring starting grid region with the smallest starting bandwidth requirement difference to obtain M grid regions.

[0037] In a possible embodiment, after obtaining the Q transmission bandwidth requirements, according to the sizes of the Q transmission bandwidth requirements, the areas with relatively similar bandwidth requirements in the target transmission bandwidth distribution diagram are determined to obtain M grid areas. The M grid areas include M basic equipment sets and M transmission bandwidth requirement sets. The M transmission bandwidth requirement sets are obtained by summarizing the transmission bandwidth requirements corresponding to the M basic equipment sets in the M grid areas.

[0038] In one embodiment, P transmission bandwidth requirements are randomly selected from the Q transmission bandwidth requirements, and the P scattered points corresponding to the P transmission bandwidth requirements are used as P starting scattered points. According to the positions of the P starting scattered points, a neighbor search is performed, and multiple scattered points adjacent to the P starting scattered points are added to the P neighbor scattered point sets to obtain the P neighbor scattered point sets.

[0039] Furthermore, neighbor scattered points in the P neighbor scattered point sets whose transmission bandwidth requirements are within a preset requirement difference range with those of the P starting scattered points are integrated into P starting areas of the P starting scattered points, wherein the P starting areas have P starting transmission bandwidth requirements, and the P starting transmission bandwidth requirements are the averages of multiple transmission bandwidth requirements of multiple neighbor scattered points in the P starting areas.

[0040] Then, starting from the P starting areas and taking the P starting areas as the center, the nearest neighbor search is performed again until the edge of the target transmission bandwidth distribution map is reached to obtain P starting grid areas. Then, the area of ​​the P starting grid areas is counted respectively to determine whether the area of ​​the P starting grid areas is less than or equal to the preset grid area. If so, it is integrated into the nearest neighbor starting grid area with the smallest difference in starting bandwidth requirements to obtain M grid areas. Avoid over-fine division of grid areas, which leads to waste of WIFI configuration resources.

[0041] S500: Traverse and count the area of ​​the M grid areas to obtain the areas of the M grid areas, perform terminal configuration in combination with the M transmission bandwidth requirement sets and the WIFI terminal parameter interval of the target substation, and obtain M WIFI terminal configuration information of the M grid areas, wherein the M WIFI terminal configuration information includes the number of M WIFI terminal configurations and M WIFI terminal configuration parameters; S600: Perform WIFI terminal configuration on the target substation based on the M grid areas, the M WIFI terminal configuration quantities and the M WIFI terminal configuration parameters.

[0042] Furthermore, step S500 of the embodiment of the present application further includes: Obtaining multiple historical grid area areas, multiple historical transmission bandwidth requirement sets, multiple historical WIFI terminal parameter intervals, and multiple historical WIFI terminal configuration information as historical data; Performing supervised training on the encoder and decoder using the historical data until preset requirements are met, thereby obtaining a trained terminal configuration identifier; The terminal configuration identifier is used to identify the area of ​​the M grid areas, the M transmission bandwidth requirement sets and the WIFI terminal parameter interval of the target substation to obtain M WIFI terminal configuration information.

[0043] In a possible embodiment, the area of ​​the M grid areas is counted respectively, and the area of ​​the M grid areas is combined with the M transmission bandwidth requirement sets and the WIFI terminal parameter interval of the target substation to complete the WIFI terminal configuration of the M grid areas, thereby obtaining the M WIFI terminal configuration information of the M grid areas, wherein the M WIFI terminal configuration information includes the number of M WIFI terminal configurations and M WIFI terminal configuration parameters. The WIFI terminal configuration parameters include parameters such as frequency range, channel bandwidth, security protocol, and power level.

[0044] After obtaining the M WIFI terminal configuration information, the WIFI terminal is configured for the target substation according to the M grid areas, the M WIFI terminal configuration quantities and the M WIFI terminal configuration parameters, thereby achieving the goal of configuring the WIFI terminal in accordance with the actual equipment requirements of the target substation.

[0045] In a possible embodiment, historical configuration records of substations of the same type as the target substation are collected to obtain multiple historical grid area areas, multiple historical transmission bandwidth requirement sets, multiple historical WIFI terminal parameter intervals, and multiple historical WIFI terminal configuration information. The multiple historical WIFI terminal configuration information is used as historical data.

[0046] Then, the historical data is used as training data to supervise the encoder and decoder training, and the multiple historical grid area, multiple historical transmission bandwidth requirement sets and multiple historical WIFI terminal parameter intervals are used as input data, and the multiple historical WIFI terminal configuration information is used as output data. According to the input and output conditions, the parameters of the encoder and decoder are continuously adjusted, so that the model converges and the trained terminal configuration identifier is obtained. The terminal configuration identifier is a functional device that performs intelligent configuration of regional WIFI terminals according to the area of ​​different grid areas, transmission bandwidth requirements and WIFI terminal parameter intervals.

[0047] The area of ​​the M grid areas, the M transmission bandwidth requirement sets and the WIFI terminal parameter interval of the target substation are input into the terminal configuration identifier for intelligent identification to obtain the M WIFI terminal configuration information. The technical effect of intelligently configuring the WIFI terminal in accordance with the actual situation of the target substation is achieved.

[0048] In summary, the embodiments of the present application have at least the following technical effects: This application collects basic equipment information by traversing the equipment array in the target substation, generates Q basic equipment operation information of Q basic equipment, and then performs cloud data transmission identification based on Q equipment model identification, determines Q data transmission volume and Q transmission frequency of Q basic equipment, and then calculates Q transmission bandwidth requirements of Q basic equipment according to Q data transmission volume and Q transmission frequency, and identifies the transmission bandwidth distribution of the target substation according to Q transmission bandwidth requirements and Q positioning identification, generates a target transmission bandwidth distribution map, and then divides the target transmission bandwidth distribution map into regions according to the size of Q transmission bandwidth requirements, generates M grid areas, obtains M grid area areas by traversing and counting the area areas of M grid areas, and performs terminal configuration in combination with M transmission bandwidth requirement sets and WIFI terminal parameter intervals of the target substation, obtains M WIFI terminal configuration information of M grid areas, and then performs WIFI terminal configuration on the target substation based on M grid areas, M WIFI terminal configuration quantities and M WIFI terminal configuration parameters. The technical effect of improving the degree of fit between WIFI terminal configuration and actual substation needs and improving the accuracy of WIFI terminal configuration is achieved.

[0049] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0050] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0051] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. A WIFI terminal intelligent configuration method based on wireless communication technology, characterized in that: The method is applied to a terminal intelligent configuration system, the terminal intelligent configuration system is communicatively connected with a device array of a target substation, and the method comprises: Traversing the equipment array in the target substation to collect basic equipment information, and generating Q basic equipment operation information of Q basic equipment, wherein the Q basic equipment includes Q positioning identifiers and Q equipment model identifiers; Perform cloud data transmission identification based on the Q device model identifiers, and determine Q data transmission volumes and Q transmission frequencies of the Q basic devices; Calculate Q transmission bandwidth requirements of the Q basic devices according to the Q data transmission amounts and the Q transmission frequencies, identify the transmission bandwidth distribution of the target substation according to the Q transmission bandwidth requirements and the Q positioning identifiers, and generate a target transmission bandwidth distribution map, wherein the target transmission bandwidth distribution map has Q scattered points; According to the sizes of the Q transmission bandwidth requirements, the target transmission bandwidth distribution map is divided into regions to generate M grid regions, wherein the M grid regions include M basic equipment sets and M transmission bandwidth requirement sets; Traversing and counting the area of ​​the M grid areas, obtaining the area of ​​the M grid areas, performing terminal configuration in combination with the M transmission bandwidth requirement sets and the WIFI terminal parameter interval of the target substation, and obtaining the M WIFI terminal configuration information of the M grid areas, wherein the M WIFI terminal configuration information includes the number of M WIFI terminal configurations and the M WIFI terminal configuration parameters; The target substation is configured with WIFI terminals based on the M grid areas, the M WIFI terminal configuration quantities and the M WIFI terminal configuration parameters.

2. The method according to claim 1, characterized in that Based on the Q device model identifiers, cloud data transmission identification is performed to determine Q data transmission amounts and Q transmission frequencies of the Q basic devices, and the method includes: Using the Q device model identifiers as indexes, performing data retrieval in the cloud to obtain Q sample data transmission volume sets and Q sample transmission frequency sets; Performing fluctuation consistency analysis on the Q sample data transmission volume sets and the Q sample transmission frequency sets respectively to obtain fluctuation coefficients of the Q sample data transmission volumes and fluctuation coefficients of the Q sample transmission frequencies; Determine whether the fluctuation coefficients of the Q sample data transmission volumes and the fluctuation coefficients of the Q sample transmission frequencies meet a preset fluctuation coefficient threshold; if so, respectively calculate the means of the Q sample data transmission volume sets and the Q sample transmission frequency sets, and obtain the Q data transmission volumes and the Q transmission frequencies according to the calculation results.

3. The method according to claim 2, characterized in that The method comprises: If not, extracting a sample mode from the Q sample data transmission amount sets and the Q sample transmission frequency sets to obtain Q sample data transmission amount modes and Q sample transmission frequency modes; According to the modes of the Q sample data transmission amounts and the modes of the Q sample transmission frequencies, data fluctuation edges are identified in the Q sample data transmission amount sets and the Q sample transmission frequency sets, data distribution intensive areas are determined, and Q sample data transmission amount intensive sets and Q sample transmission frequency intensive sets are generated; Mean calculation is performed on the Q dense sets of sample data transmission amounts and the Q dense sets of sample transmission frequencies to generate the Q data transmission amounts and the Q transmission frequencies.

4. The method according to claim 3, characterized in that According to the modes of the Q sample data transmission amounts and the modes of the Q sample transmission frequencies, data fluctuation edges are identified in the Q sample data transmission amount sets and the Q sample transmission frequency sets, a data distribution intensive area is determined, and a Q sample data transmission amount intensive set and a Q sample transmission frequency intensive set are generated. The method includes: Counting the number of differences between the sample data transmission amounts in the Q sample data transmission amount sets and the modes of the Q sample data transmission amounts within a preset step length, and taking the ratios of the Q first statistical results to the preset step length as Q first fluctuation densities; Counting again the number of differences between the sample data transmission amounts in the Q sample data transmission amount sets and the modes of the Q sample data transmission amounts within two preset step sizes, and taking the ratio of the Q second statistical results to the sum of the two preset step sizes as Q second fluctuation densities; Determine whether the difference between the Q first fluctuation densities and the Q second fluctuation densities meets a preset fluctuation density difference, and if so, take a plurality of sample data transmission amounts in the set of Q sample data transmission amounts whose difference between the sample data transmission amounts and the mode of the Q sample data transmission amounts is within a preset step length as a dense set of Q sample data transmission amounts; If not, continue to calculate Q third fluctuation densities, perform data fluctuation edge identification based on the Q third fluctuation densities and the Q second fluctuation densities, and determine the data distribution dense area, wherein the Q third fluctuation densities are the number of differences between the sample data transmission amounts in the Q sample data transmission amount sets and the modes of the Q sample data transmission amounts within three preset step sizes, to obtain Q third statistical results, and compare the Q third statistical results with the sum of the three preset step sizes to obtain the ratio.

5. The method according to claim 1, characterized in that The method comprises: Multiplying the Q data transmission amounts and the Q transmission frequencies respectively to obtain the Q transmission bandwidth requirements; According to the Q positioning identifiers of the Q basic equipment corresponding to the Q transmission bandwidth requirements, a scatter plot is drawn for the transmission bandwidth requirement distribution in the target substation, where each scatter point corresponds to a transmission bandwidth requirement, and the target transmission bandwidth distribution map is generated.

6. The method according to claim 1, characterized in that The target transmission bandwidth distribution map is divided into regions according to the sizes of the Q transmission bandwidth requirements to generate M grid regions, and the method includes: Randomly extract P transmission bandwidth requirements from the Q transmission bandwidth requirements, and use the P scattered points corresponding to the P transmission bandwidth requirements as P starting scattered points; Performing a neighbor search on the P starting scattered points to determine a set of P neighbor scattered points; The neighbor scattered points in the P neighbor scattered point sets, whose transmission bandwidth requirements are within a preset requirement difference range and whose transmission bandwidth requirements are within a preset requirement difference range, are integrated into the P starting areas of the P starting scattered points, wherein the P starting areas have P starting transmission bandwidth requirements, and the P starting transmission bandwidth requirements are the averages of multiple transmission bandwidth requirements of multiple neighbor scattered points in the P starting areas; Taking the P starting areas as starting points, neighbor search is performed again until the edge of the target transmission bandwidth distribution graph is reached to obtain P starting grid areas.

7. The method according to claim 6, characterized in that After obtaining P starting grid regions, the method further comprises: It is determined whether the areas of the P starting grid regions are less than or equal to a preset grid area. If so, they are integrated into a neighboring starting grid region with the smallest starting bandwidth requirement difference to obtain M grid regions.

8. The method according to claim 1, characterized in that The method comprises: Obtaining multiple historical grid area areas, multiple historical transmission bandwidth requirement sets, multiple historical WIFI terminal parameter intervals, and multiple historical WIFI terminal configuration information as historical data; Performing supervised training on the encoder and decoder using the historical data until preset requirements are met, thereby obtaining a trained terminal configuration identifier; The terminal configuration identifier is used to identify the area of ​​the M grid areas, the M transmission bandwidth requirement sets and the WIFI terminal parameter interval of the target substation to obtain M WIFI terminal configuration information.

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