A comprehensive management platform for electromagnetic interference measurement

Abstract

This invention discloses a comprehensive management platform for electromagnetic interference (EMI) measurement, relating to the field of EMI measurement technology. Based on communication quality coefficients, low-quality points are screened within a target area. If the density of low-quality points is higher than expected, the communication scenarios within the coverage area of ​​these low-quality points are identified. Then, an appropriate electromagnetic data sampling mode is selected based on the communication scenario to collect electromagnetic environment data. After determining the location of the interference source, the type of interference source is identified. An EMI degree is constructed from the EMI data of the interference source to determine the target interference source. Real-time collection of electromagnetic environment data and communication quality data in the vicinity of the target interference source is performed. Based on the relationship between interference correlation and correlation, a corresponding processing strategy is selected for the interference source. This achieves dynamic management of EMI sources, making the processing more targeted and ensuring dynamic communication quality within the target area.

Description

Technical Field

[0001] This invention relates to the field of electromagnetic interference measurement technology, specifically to a comprehensive management platform for electromagnetic interference measurement. Background Technology

[0002] Electromagnetic interference (EMI) is a complex and widespread problem stemming from the improper transfer of energy in electromagnetic fields. It can be caused by a variety of factors, including electromagnetic radiation from natural radiation sources or electronic equipment, power supply interference, grounding issues, cable bundle interactions, and electrostatic discharge. This interference can originate not only from the natural environment, such as atmospheric noise, but also from human activities, including unintentional interference from electronic equipment and intentionally created electromagnetic interference signals. EMI has profound effects on electronic equipment and communication systems, potentially leading to equipment malfunctions, damage, signal quality degradation, increased security risks, radio spectrum contention, and the leakage of sensitive information.

[0003] To reduce the impact of electromagnetic interference, comprehensive measures are needed, including using shielding technology to isolate electromagnetic fields, adding filters to circuits to eliminate interference signals, ensuring proper grounding of equipment, optimizing cable routing, adopting power management measures, and fully considering electromagnetic compatibility (EMC) issues during the equipment design phase, thereby ensuring the normal operation of electronic equipment and communication systems and data security.

[0004] Chinese invention patent application CN118275798 A discloses a facility-level electromagnetic interference monitoring and analysis system, comprising: an indoor monitoring terminal, an outdoor monitoring terminal, a signal sampling and processing module, a main control computer, and a protection module. Both the indoor and outdoor monitoring terminals utilize ultra-wideband omnidirectional receiving antennas to receive electromagnetic signals from their respective environments in real time. The signal sampling and processing module processes the electromagnetic signals received by the indoor and outdoor monitoring terminals into sampled data. The signal sampling and processing module is connected to the main control computer to transmit the sampled data to the main control computer in real time. The main control computer is used at least to process and analyze the sampled data, determining whether the facility is suffering from electromagnetic interference by comparing the electromagnetic signals of the internal and external environments. When electromagnetic interference is determined to be present, the protection module is triggered to implement electromagnetic protection for the facility. This invention achieves both facility-level electromagnetic protection and the assessment of the facility's electromagnetic protection capabilities.

[0005] Based on the above applications and existing technologies:

[0006] When base stations and related communication equipment are in communication mode, data communication quality is particularly important. However, considering that when there is a large flow of people or vehicles or when the communication scenario is complex, the data communication quality may fluctuate significantly when the communication equipment is in a complex electromagnetic environment, it is necessary to deal with the electromagnetic interference source if there is an electromagnetic interference source near the communication equipment in order to maintain data communication quality.

[0007] Before addressing electromagnetic interference (EMI) sources, it's necessary to screen and locate them based on several sets of electromagnetic environment data. However, existing EMI handling methods typically involve directly removing the identified EMI sources. This approach is rather simplistic, and EMI sources are often dynamically changing. Furthermore, many factors can affect data communication quality, and a single approach may not effectively improve communication quality. Constructing a density Fop based on the distribution of low-quality points allows for an overall assessment of data communication quality and the current level of EMI. If the target area is widely affected, it indicates severe EMI, enabling targeted evaluation.

[0008] Therefore, the present invention provides a comprehensive management platform for electromagnetic interference measurement. Summary of the Invention

[0009] (a) Technical problems to be solved

[0010] To address the shortcomings of existing technologies, this invention provides a comprehensive management platform for electromagnetic interference measurement. It collects electromagnetic environment data based on an electromagnetic data sampling pattern; after determining the location of the interference source, it identifies the type of the interference source and constructs an electromagnetic interference degree from the interference source's electromagnetic interference data to determine the target interference source; after real-time collection of electromagnetic environment data and communication quality data in the vicinity of the target interference source, it selects a corresponding processing strategy for the interference source based on the relationship between interference correlation degrees. This enables dynamic management of electromagnetic interference sources, making the processing methods more targeted and achieving dynamic assurance of communication quality; thus solving the technical problems mentioned in the background art.

[0011] (II) Technical Solution

[0012] To achieve the above objectives, the present invention provides the following technical solution:

[0013] This includes a communication quality assessment unit, which collects communication quality data within the target area and constructs a communication quality coefficient. Based on the communication quality coefficient, it filters out low-quality points within the target area. If the density of low-quality points is higher than expected, it issues an interference measurement command.

[0014] The scene analysis unit identifies communication scenarios within the coverage area of ​​low-quality points, selects the corresponding electromagnetic data sampling mode based on the communication scenario, and completes electromagnetic environment data acquisition by combining the constrained data sampling rate.

[0015] The interference source analysis unit determines the location of the interference source from the electromagnetic environment data, identifies the type of interference source, constructs the electromagnetic interference degree from the electromagnetic interference data of the interference source, and determines the target interference source based on the electromagnetic interference degree.

[0016] The correlation processing unit collects electromagnetic environment data and communication quality data in the vicinity of the target interference source in real time, and selects the corresponding processing strategy for the interference source based on the relationship between the interference correlation degree and the correlation degree.

[0017] Furthermore, several evenly distributed monitoring points are selected within the target area, and communication quality data is collected and recorded at the monitoring points, including at least the connection establishment time, request response time, and client processing time during data communication. The data is then aggregated to generate a communication quality data set.

[0018] Furthermore, a communication quality coefficient is generated from the communication quality data set. If the communication quality coefficient is lower than the communication quality threshold, the corresponding monitoring point is designated as a low-quality point. The location information of the low-quality points is then marked on the electronic map, and the density of the low-quality points is constructed.

[0019] Furthermore, under dimensionless conditions, the communication quality coefficients Qts are generated from the communication quality dataset as follows:

[0020]

[0021] Weighting coefficients, 0≤α≤1, 0≤β≤1, and α+β=1, St i St is the connection establishment time on the i-th acquisition node. a Its qualified standard value; Kt i Let Kt be the request response time on the i-th data collection node. a Xs is its acceptable standard value; μXs is its expected value; and σXs is its standard deviation.

[0022] Furthermore, upon receiving the interference measurement command, communication scenario data is collected at low-quality points;

[0023] Using communication scene data within the low-quality point coverage area as input, the trained communication scene recognition model is used to identify the corresponding data communication scene and obtain the corresponding communication scene.

[0024] Furthermore, based on the correspondence between the sampling mode and the communication scenario, the corresponding electromagnetic data sampling mode is matched to the current communication scenario, and the data sampling rate is constrained according to the communication quality coefficient.

[0025] Electromagnetic data is sampled at a sampling frequency that meets the constraints, and the acquired electromagnetic environment data is aggregated to generate an electromagnetic environment data set.

[0026] Furthermore, based on measurement data at different low-mass points, a triangulation algorithm is used to determine the location of the interference source; after analyzing the electromagnetic environment data, the interference index data of the interference source is obtained, and the data are summarized to generate an electromagnetic interference data set of the electromagnetic interference source.

[0027] Furthermore, using electromagnetic interference characteristic data as input, the trained interference source identification model is used to identify the type of interference source, and the electromagnetic interference degree is constructed after acquiring the current electromagnetic interference data.

[0028] If the obtained electromagnetic interference level exceeds the interference threshold, it is used as the target interference source and its location is marked.

[0029] Furthermore, after collecting the electromagnetic interference degree and communication quality coefficient in each sub-cycle, an interference correlation degree is constructed. After labeling the observation cycle with the interference correlation degree, a correlation threshold is constructed.

[0030] Furthermore, if the interference correlation of the interference source is lower than the correlation threshold, the interference source will not be processed.

[0031] If the interference correlation is within the correlation threshold, adjust the operating frequency of base stations in the vicinity of the interference source to avoid frequency overlap with the interference source, and adjust the transmission power of the base stations.

[0032] If the interference correlation is higher than the correlation threshold, shielding facilities should be installed between the interference source and the interfered equipment, and the installation positions of base stations and antennas in the vicinity of the interference source should be adjusted.

[0033] (III) Beneficial Effects

[0034] This invention provides a comprehensive management platform for electromagnetic interference measurement, which has the following advantages:

[0035] 1. By adopting different measurement strategies in different communication scenarios, the reliability of the collected and measured data can be ensured. By constraining the data sampling rate based on the communication quality coefficient, the electromagnetic data acquisition frequency is matched with the actual sampling frequency, avoiding omissions or shortages in the data acquisition process, and ensuring the reliability of the judgment when judging the electromagnetic environment.

[0036] 2. The location of the interference source can be determined through the triangulation algorithm. After the interference source is determined, measures can be taken to deal with the interference source and improve the current data communication environment.

[0037] 3. Determine the interference intensity of the interference source. Does the interference intensity of the interference source on data communication exceed expectations? If it exceeds expectations, designate it as the target interference source. By taking targeted measures against the selected target interference source, the impact of the target interference source on data communication can be reduced.

[0038] 4. Based on the correlation, the degree of impact of the target interference source on the electromagnetic interference in the vicinity can be determined. If the degree of electromagnetic interference exceeds the expectation, and the target interference source cannot intervene in time, the data communication quality may be further affected.

[0039] 5. Based on the relationship between interference correlation degree and correlation threshold, determine whether the impact of electromagnetic interference on communication quality exceeds expectations, and adopt different processing strategies for the electromagnetic interference source. Since both interference correlation degree and correlation threshold are dynamic, it is possible to achieve [further details omitted].

[0040] Figure 1 This is a schematic diagram of the comprehensive management method for electromagnetic interference measurement according to the present invention.

[0041] Figure 2 This is a schematic diagram of the comprehensive management platform structure for electromagnetic interference measurement according to the present invention. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] Please see Figure 1 This invention provides a comprehensive management method for electromagnetic interference measurement, including:

[0044] Step 1: After collecting communication quality data in the target area, construct the communication quality coefficient Qts. Based on the communication quality coefficient Qts, select low-quality points in the target area. If the density of low-quality points is higher than expected, issue an interference measurement command.

[0045] Step one includes the following:

[0046] Step 101: Select the area where electromagnetic interference may exist and needs to be measured as the target area. Select several evenly distributed monitoring points in the target area and collect and record communication quality data at the monitoring points, including connection establishment time, request response time and client processing time when data communication occurs. After summarizing, generate a communication quality data set.

[0047] Step 102: Under dimensionless conditions, generate communication quality coefficients Qts from the communication quality dataset, as follows:

[0048]

[0049] Weighting coefficients, 0≤α≤1, 0≤β≤1, and α+β=1, St i St is the connection establishment time on the i-th acquisition node. a Its qualified standard value; Kt i Let Kt be the request response time on the i-th data collection node. a Xs is its acceptable standard value; μXs is its expected value; σXs is its standard deviation.

[0050] Based on historical data and expectations for communication quality management, communication quality thresholds are set in advance;

[0051] If the communication quality coefficient Qts is lower than the corresponding communication quality threshold, it indicates that the communication quality at the corresponding monitoring point is poor and there may be electromagnetic interference. Adjustment is required. In this case, the corresponding monitoring point is regarded as a low quality point.

[0052] When using this system, if electromagnetic interference needs to be collected and detected, communication data at each monitoring point is first collected, and a communication quality coefficient Qts is constructed from the collected data. Based on the communication quality coefficient Qts, the communication quality at the monitoring point can be evaluated. If the communication quality is poor, it indicates that the current data communication may be subject to a certain degree of electromagnetic interference, and the current electromagnetic environment is not conducive to the normal operation of data communication. Therefore, there may be electromagnetic interference sources in the area where the monitoring point is located, which affects the data communication status.

[0053] Step 103: Construct an electronic map covering the target area, mark the location information of the low-quality points on the electronic map, and construct the density (Fop) of the low-quality points, as follows:

[0054]

[0055] Weighting coefficients, 0≤α≤1, 0≤β≤1, and α+β=1; the weighting coefficient values ​​remain consistent with the previous values; k is the number of low-quality points, G ij G is the shortest distance between the i-th low-quality point and the j-th low-quality point. a This is the average value of the shortest distance.

[0056] Based on historical data and expectations for communication quality management, a density threshold is pre-set;

[0057] If the density Fop is higher than the density threshold, it indicates that there are many locations with poor communication quality in the target area. This may be due to a certain degree of electromagnetic interference causing poor data communication quality. In this case, an interference measurement command is sent to the outside.

[0058] When using it, refer to steps 101 to 103:

[0059] After identifying low-quality points and determining their location information, a density Fop is constructed based on the distribution of these low-quality points. The density Fop can be used to judge the overall data communication quality and the current level of electromagnetic interference. If the target area is generally affected, it indicates that the electromagnetic interference is relatively serious, thus enabling targeted evaluation.

[0060] Based on the above applications and existing technologies:

[0061] When base stations and related communication equipment are in communication mode, data communication quality is particularly important. However, considering that when there is a large flow of people or vehicles or when the communication scenario is complex, the data communication quality may fluctuate significantly when the communication equipment is in a complex electromagnetic environment, it is necessary to deal with the electromagnetic interference source if there is an electromagnetic interference source near the communication equipment in order to maintain data communication quality.

[0062] Before dealing with electromagnetic interference sources, it is necessary to screen and locate them based on several sets of electromagnetic environment data. However, in existing electromagnetic interference processing methods, the electromagnetic interference sources are usually removed directly after being screened. However, this processing method is relatively simple. Moreover, electromagnetic interference sources are often in a dynamic state, and there are many factors that affect the quality of data communication. Adopting a single processing method may not effectively reverse the communication quality.

[0063] Step 2: After identifying the communication scenarios within the low-quality point coverage area, select the corresponding electromagnetic data sampling mode based on the communication scenario, and complete the electromagnetic environment data acquisition by combining the constrained data sampling rate.

[0064] Step two includes the following:

[0065] Step 201: After receiving the interference measurement command, perform electromagnetic interference measurement at the low-quality point, select measurement equipment, such as spectrum analyzer and signal receiver; collect communication scenario data at the low-quality point, such as the number and density of base stations, and the flow of people, vehicles and population density at different times.

[0066] A convolutional neural network is trained using labeled sample data to obtain a trained communication scene recognition model;

[0067] Using communication scene data within the low-quality point coverage area as input, the trained communication scene recognition model is used to identify the corresponding data communication scene and obtain the corresponding communication scene.

[0068] When using electromagnetic environment data collection, the data communication quality may fluctuate significantly in different communication scenarios without additional electromagnetic interference. Therefore, adopting different measurement strategies in different communication scenarios can ensure the reliability of the collected and measured data.

[0069] Step 202: After acquiring several electromagnetic data sampling modes through online deep retrieval or offline collection, summarize them to generate a sampling mode library; based on the correspondence between the sampling mode and the communication scenario, match the corresponding electromagnetic data sampling mode to the current communication scenario, for example, set the device to continuous measurement mode to capture changes in the electromagnetic environment in real time.

[0070] Step 203: After selecting the sampling mode, under dimensionless conditions, constrain the data sampling rate Rcp according to the communication quality coefficient Qts, as follows:

[0071]

[0072] Among them, Qts i For the data communication quality within the i-th sub-cycle, Rcp is the average data communication quality over the first i sub-cycles. max The maximum acceptable data sampling rate;

[0073] Electromagnetic data is sampled according to the data sampling frequency that meets the constraints, and the acquired electromagnetic environment data is aggregated to generate an electromagnetic environment data set.

[0074] When using this method, refer to steps 201 to 203:

[0075] After determining the current communication scenario and electromagnetic data sampling mode, the data sampling rate is constrained based on the communication quality coefficient to match the electromagnetic data acquisition frequency with the actual sampling frequency. This avoids omissions or shortages in the data acquisition process and ensures the reliability of the judgment when the electromagnetic environment is judged after the electromagnetic data acquisition is completed.

[0076] Step 3: After determining the location of the interference source from the electromagnetic environment data, identify the type of interference source. Construct the electromagnetic interference degree Tep from the electromagnetic interference data of the interference source, and determine the target interference source based on the electromagnetic interference degree.

[0077] Step three includes the following:

[0078] Step 301: Preprocess the data in the electromagnetic environment dataset. Based on the measurement data at different low-quality points, use the triangulation algorithm to determine the location of the interference source and mark the location of the interference source on the electronic map.

[0079] After analyzing electromagnetic environment data, the frequency, waveform, intensity and other characteristic parameters of the interference source are obtained, and then the electromagnetic interference data set of the electromagnetic interference source is generated.

[0080] When in use, by selecting different measurement and acquisition locations, the location of the interference source can be determined through the triangulation algorithm. After the interference source is determined, measures can be taken to deal with the interference source and improve the current data communication environment.

[0081] Step 302: After training a convolutional neural network with labeled sample data, obtain the trained interference source identification model; use electromagnetic interference characteristic data as input, and use the trained interference source identification model to identify the type of interference source, such as industrial equipment or illegal emission source;

[0082] Under dimensionless conditions, the electromagnetic interference degree Tep is constructed after acquiring the current electromagnetic interference data, as follows:

[0083]

[0084] E i Let E be the i-th electromagnetic interference index. i The weighted values ​​for the corresponding electromagnetic interference indicators fall within [0,1]; the weighting coefficients are 0≤F1≤1, 0≤F2≤1, 0≤F3≤1, and the weighting coefficients can be obtained by referring to the analytic hierarchy process.

[0085] Based on historical data and acceptable expectations of the electromagnetic intensity of the interference source, an interference threshold is preset.

[0086] If the obtained electromagnetic interference level Tep exceeds the interference threshold, it indicates that the electromagnetic interference generated by the current electromagnetic interference source is relatively serious. It is then used as the target interference source and its location is marked.

[0087] When using this method, refer to steps 301 and 302:

[0088] After determining the type of interference source based on electromagnetic data, an electromagnetic interference level (Tep) is constructed based on pre-collected electromagnetic environment data. The interference intensity of the interference source can be judged based on the Tep. If the interference intensity of the interference source on data communication exceeds expectations, it is identified as a target interference source. By taking targeted measures against the selected target interference sources, the impact of the target interference sources on data communication can be reduced.

[0089] Step 4: After real-time collection of electromagnetic environment data and communication quality data in the vicinity of the target interference source, select the corresponding processing strategy for the interference source based on the relationship between interference correlation degree and correlation degree.

[0090] Step four includes the following:

[0091] Step 401: Pre-set an observation period containing several sub-cycles. After collecting the electromagnetic interference level Tep and communication quality coefficient Qts in each sub-cycle, construct the interference correlation degree Ltp between the electromagnetic interference level Tep and the communication quality coefficient Qts in each sub-cycle as follows:

[0092] The electromagnetic interference level Tep and the communication quality coefficient Qts are linearly normalized, and the corresponding data values ​​are mapped to the interval [0,1] as follows:

[0093]

[0094] Among them, Tep i Let Qts be the electromagnetic interference level in the i-th sub-period. i Let m be the communication quality coefficient in the i-th sub-cycle, m be the number of sub-cycles, and ρ be the weighting coefficient, where 0 ≤ ρ ≤ 1.

[0095] After labeling the observation period with the interference correlation degree Ltp, the correlation threshold [Ka, Kb] is constructed as follows:

[0096]

[0097] Where i = 1, 2, ..., m, m is the number of sub-periods, Ltp i Let Ltp be the interference correlation degree within the i-th sub-period. a This represents the mean of the interference correlation.

[0098] When in use, after identifying the target interference source, the interference correlation degree Ltp is generated by using the electromagnetic interference degree Tep and the communication quality coefficient Qts. Based on the correlation degree, the influence of the target interference source on the electromagnetic interference in the vicinity can be judged. If the electromagnetic interference degree exceeds the expectation, and the target interference source cannot intervene in time, the data communication quality may be further affected.

[0099] Step 402: Based on the correlation degree of interference and the relationship between correlation degrees, select the corresponding processing strategy for the interference source, including:

[0100] If the interference correlation degree Ltp of the interference source is lower than the correlation threshold [Ka, Kb], no action is taken on the interference source;

[0101] If the interference correlation degree Ltp is within the correlation threshold [Ka, Kb], adjust the operating frequency of the base station in the vicinity of the interference source to avoid frequency overlap with the interference source, and adjust the transmission power of the base station to reduce the interference impact;

[0102] If the interference correlation degree Ltp is higher than the correlation threshold [Ka, Kb], install shielding facilities, such as shielding covers and conductive cloth, between the interference source and the interfered equipment; or adjust the installation position of base stations and antennas in the vicinity of the interference source to avoid the interference source.

[0103] When using this method, refer to the content in steps 401 and 402;

[0104] When it is necessary to process the target interference source and maintain the communication quality within the target area, the relationship between the interference correlation degree Ltp and the correlation threshold [Ka, Kb] can be used to determine whether the impact of electromagnetic interference on the communication quality in the current stage exceeds expectations. Based on the judgment result, different processing strategies can be adopted for the electromagnetic interference source. At the same time, since both the interference correlation degree and the correlation threshold are dynamic, dynamic management of the electromagnetic interference source can be realized, making the processing method more targeted and achieving dynamic protection of the communication quality within the target area.

[0105] The Analytic Hierarchy Process (AHP) is a decision-making method that decomposes decision-related elements into hierarchical levels such as objectives, criteria, and alternatives, and then performs qualitative and quantitative analysis based on these levels. It is particularly suitable for handling objective systems with hierarchical and interleaved evaluation indicators, and is an effective decision-making tool when objective values ​​are difficult to describe quantitatively.

[0106] The core of the Analytic Hierarchy Process (AHP) lies in decomposing the decision problem into multiple levels, forming a hierarchical structure. This structure typically includes an objective level, a criterion level, a sub-criterion level, and an alternative level. By solving for the eigenvectors of the judgment matrix, the priority weight of each element at each level relative to an element at the previous level is obtained. Finally, a weighted summation method is used to hierarchically merge the final weights of each alternative with respect to the overall objective, thereby finding the optimal solution.

[0107] Please see Figure 2 This invention provides a comprehensive management platform for electromagnetic interference measurement, comprising:

[0108] The communication quality assessment unit collects communication quality data in the target area and constructs a communication quality coefficient. Based on the communication quality coefficient, it filters out low-quality points in the target area. If the density of low-quality points is higher than expected, it issues an interference measurement command.

[0109] The scene analysis unit identifies communication scenarios within the coverage area of ​​low-quality points, selects the corresponding electromagnetic data sampling mode based on the communication scenario, and completes electromagnetic environment data acquisition by combining the constrained data sampling rate.

[0110] The interference source analysis unit determines the location of the interference source from the electromagnetic environment data, identifies the type of interference source, constructs the electromagnetic interference degree from the electromagnetic interference data of the interference source, and determines the target interference source based on the electromagnetic interference degree.

[0111] The correlation processing unit collects electromagnetic environment data and communication quality data in the vicinity of the target interference source in real time, and selects the corresponding processing strategy for the interference source based on the relationship between the interference correlation degree and the correlation degree.

[0112] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0113] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0114] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0115] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0116] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0117] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0118] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0119] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A comprehensive management platform for electromagnetic interference measurement, characterized in that: include, The communication quality assessment unit collects communication quality data in the target area and constructs a communication quality coefficient. Based on the communication quality coefficient, it filters out low-quality points in the target area. If the density of low-quality points is higher than expected, it issues an interference measurement command. The scene analysis unit identifies communication scenarios within the coverage area of ​​low-quality points, selects the corresponding electromagnetic data sampling mode based on the communication scenario, and completes electromagnetic environment data acquisition by combining the constrained data sampling rate. The interference source analysis unit determines the location of the interference source from the electromagnetic environment data, identifies the type of interference source, constructs the electromagnetic interference degree from the electromagnetic interference data of the interference source, and determines the target interference source. The correlation processing unit collects electromagnetic environment data and communication quality data in the vicinity of the target interference source in real time, and selects the corresponding processing strategy for the interference source based on the relationship between the interference correlation degree and the correlation degree. An observation period consisting of several sub-cycles is pre-set, and the electromagnetic interference level within each sub-cycle is collected. and communication quality coefficient Then, the electromagnetic interference level within each sub-cycle is constructed in the following manner. With communication quality coefficient Interference correlation between ,in: Electromagnetic interference and communication quality coefficient Perform linear normalization and map the corresponding data values ​​to intervals. Inside, in the following manner: ； in, For the first i Electromagnetic interference level within each sub-cycle For the first i Communication quality coefficient within each sub-cycle The number of sub-periods. These are the weighting coefficients. ; In terms of interference correlation After labeling the observation period, an association threshold is constructed. The method is as follows: ； in, , m The number of sub-periods. For the first i Interference correlation within each sub-cycle This represents the mean of the interference correlation.

2. The comprehensive management platform for electromagnetic interference measurement according to claim 1, characterized in that: Select several evenly distributed monitoring points within the target area, and collect and record communication quality data at the monitoring points, including at least the connection establishment time, request response time, and client processing time during data communication. The data are then aggregated to generate a communication quality data set.

3. The comprehensive management platform for electromagnetic interference measurement according to claim 2, characterized in that: A communication quality coefficient is generated from the communication quality data set. If the communication quality coefficient is lower than the communication quality threshold, the corresponding monitoring point is designated as a low-quality point. The location information of the low-quality points is then marked on the electronic map, and the density of the low-quality points is constructed.

4. The comprehensive management platform for electromagnetic interference measurement according to claim 3, characterized in that: Under dimensionless conditions, communication quality coefficients are generated from a set of communication quality data. The method is as follows: ； Weighting coefficients ， ,and , The connection establishment duration for the i-th acquisition node. Its qualified standard value; Let be the request response time on the i-th data collection node. Its qualified standard value; This is the median quality value. For their expectations, Its standard deviation.

5. The comprehensive management platform for electromagnetic interference measurement according to claim 4, characterized in that: Upon receiving the interference measurement command, data collection for the communication scenario is performed at the low-quality point. Using communication scene data within the low-quality point coverage area as input, the trained communication scene recognition model is used to identify the corresponding data communication scene and obtain the corresponding communication scene.

6. The comprehensive management platform for electromagnetic interference measurement according to claim 5, characterized in that: Based on the correspondence between the sampling mode and the communication scenario, the corresponding electromagnetic data sampling mode is matched according to the current communication scenario, and the data sampling rate is constrained according to the communication quality coefficient; Electromagnetic data is sampled at a sampling frequency that meets the constraints, and the acquired electromagnetic environment data is aggregated to generate an electromagnetic environment data set.

7. The comprehensive management platform for electromagnetic interference measurement according to claim 6, characterized in that: Based on measurement data at different low-quality points, the location of the interference source is determined using a triangulation algorithm; After analyzing electromagnetic environment data, interference index data of interference sources are obtained, and a set of electromagnetic interference data of electromagnetic interference sources is generated.

8. The comprehensive management platform for electromagnetic interference measurement according to claim 7, characterized in that: Using electromagnetic interference characteristic data as input, the trained interference source identification model is used to identify the type of interference source, and the electromagnetic interference degree is constructed after acquiring the current electromagnetic interference data. If the obtained electromagnetic interference level exceeds the interference threshold, it is used as the target interference source and its location is marked.

9. The comprehensive management platform for electromagnetic interference measurement according to claim 8, characterized in that: After collecting the electromagnetic interference degree and communication quality coefficient in each sub-cycle, an interference correlation degree is constructed. After labeling the observation cycle with the interference correlation degree, a correlation threshold is constructed.

10. A comprehensive management platform for electromagnetic interference measurement according to claim 9, characterized in that: If the interference correlation of the interference source is lower than the correlation threshold, no action will be taken on the interference source. If the interference correlation is within the correlation threshold, adjust the operating frequency of base stations in the vicinity of the interference source to avoid frequency overlap with the interference source, and adjust the transmission power of the base stations. If the interference correlation is higher than the correlation threshold, shielding facilities should be installed between the interference source and the interfered equipment, and the installation positions of base stations and antennas in the vicinity of the interference source should be adjusted.

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