A power communication effect evaluation system based on big data

Abstract

The present invention discloses a power communication effect evaluation system based on big data. The present invention quantifies qualitative problems by accurately monitoring the signal strength of the power communication network and calculating the shadow area, duration and number of abnormal areas of the abnormal area, thereby obtaining a signal evaluation index of the power communication network within a set time period, and comparing the signal evaluation index of the power communication network within the set time period with a preset threshold index. If the signal evaluation index is less than the preset threshold index, a test signaling is triggered, and an in-depth analysis is immediately performed. By separately analyzing the bit error rate, packet loss rate, delay and throughput of each group of data packets and calculating the effect evaluation index in real time, the performance of the power communication network is fully reflected, and an in-depth analysis and real-time evaluation of the performance of the power communication network are achieved, which helps to quickly identify and solve communication problems and improve the stability and reliability of the network.

Description

Technical Field

[0001] The present invention relates to the field of power communication technology, and in particular to a power communication effect evaluation system based on big data. Background Art

[0002] As the key support for smart grids, the power communication network undertakes important tasks such as power system monitoring, data transmission and remote control. Therefore, it is necessary to evaluate the communication effect of the power communication network.

[0003] However, the existing power communication effect evaluation system still has the following shortcomings:

[0004] They often focus on monitoring signal strength, resulting in a relatively simple assessment. They fail to comprehensively consider the multi-dimensional communication performance indicators of the power communication network, such as bit error rate, packet loss rate, latency, and throughput, based on the analysis results of signal strength. Consequently, the assessment accuracy and intelligence level are low.

[0005] At the same time, when the communication performance evaluation shows a decline, there is a lack of level assessment of the current communication performance decline, problem diagnosis and rapid response.

[0006] To this end, a power communication effect evaluation system based on big data is introduced. Summary of the Invention

[0007] In view of this, the present invention provides a power communication effect evaluation system based on big data to solve the problems raised by the above background technology.

[0008] The object of the present invention can be achieved by the following technical solutions: a power communication effect evaluation system based on big data, comprising an acquisition and preset module, a preliminary evaluation module, an in-depth analysis module, an effect evaluation module and an intelligent processing module;

[0009] The collection preset module is used to preset the time interval for collecting the power communication network signal strength, and after the preset time interval is reached, collect the signal strength changes of the power communication network within the set time period and send them to the preliminary evaluation module;

[0010] The preliminary evaluation module is used to receive and analyze the signal strength changes of the power communication network within a set time period to obtain the signal evaluation index Ma of the power communication network within the set time period; and compare the signal evaluation index Ma of the power communication network within the set time period with a preset threshold index. If the signal evaluation index Ma is less than the preset threshold index, a test signaling is triggered and sent to the in-depth analysis module;

[0011] Specifically:

[0012] Extract the signal strength of the power communication network at each time point within a set time period, and construct a signal strength change curve based on it, preset a normal range of signal strength, and draw the range interval corresponding to the preset normal range in the curve;

[0013] Mark the curve below the range interval, mark the area enclosed by the line below the range interval and the marked curve as the abnormal area, fill the abnormal area, calculate the shadow area of ​​the abnormal area, and accumulate the shadow areas of each abnormal area to obtain the total shadow value f1;

[0014] Further count the duration corresponding to each abnormal area, accumulate the duration of each group, and obtain the total duration f2;

[0015] Count the number of abnormal areas and mark the number of abnormal areas as f3;

[0016] According to the formula A weighted calculation is performed on the total shadow value f1, the total duration f2, and the number f3 of abnormal areas of the power communication network within a set time period to obtain the signal evaluation index Ma of the power communication network within the set time period; wherein a1, a2, and a3 are the influence weight factors of the total shadow value f1, the total duration f2, and the number f3 of abnormal areas, respectively; h1, h2, and h3 are the preset maximum allowable values ​​of the total shadow value f1, the total duration f2, and the number f3 of abnormal areas, respectively;

[0017] Real-time monitoring and evaluation: By receiving and analyzing signal strength changes in real time, it can promptly capture fluctuations in the status of the power communication network;

[0018] Visual analysis: Construct a signal strength change curve chart and compare it with the preset normal range to intuitively display abnormal signal strength;

[0019] Quantitative anomaly assessment: By calculating the shadow area, duration, and number of abnormal areas, qualitative issues are quantified, improving the accuracy of the assessment.

[0020] Weighted analysis: Weighted calculation takes into account the severity of different abnormal factors, making the assessment results more reasonable and comprehensive;

[0021] Threshold comparison mechanism: Comparison with preset thresholds provides a basis for decision-making for further in-depth analysis, enhancing the system's adaptability and response speed;

[0022] In summary, accurate monitoring of the signal strength of the power communication network is achieved, and the reliability and maintenance efficiency of the communication network are improved.

[0023] The in-depth analysis module is used to further test the relevant parameters of the power communication network at the current trigger time when the test signaling is triggered, obtain the effect evaluation index Tre of the power communication network at the current trigger time, and send it to the effect evaluation module; the relevant parameters include bit error rate, packet loss rate, delay estimation, and throughput;

[0024] Specifically:

[0025] Prepare X groups of test data packets; where X>3, the specific number is preset by the technician and can be adjusted later based on actual conditions. The size and type of the test data packets are different;

[0026] Set a sending strategy for X groups of test data packets; the sending strategy includes a sending interval and a sending order; and send the corresponding test data packets. Perform an integrity check on the received corresponding test data packets at the receiving end to determine the total number of transmitted bits and the number of error bits. Calculate the proportion of the number of error bits in the total number of transmitted bits, and use the calculated proportion as the bit error rate ti of the corresponding test data packets.

[0027] Record the sequence number and total number of packets sent by the sending end, and record the sequence number and total number of packets received by the receiving end, identify gaps in the sequence numbers, determine the number of lost packets, calculate the percentage of lost packets to the total number, and use the calculated percentage as the packet loss rate (pi) of the packets to be tested.

[0028] At the sending end, a sending timestamp is recorded for the corresponding data packet to be tested, and at the receiving end, a receiving timestamp is recorded for the corresponding data packet to be tested, and the round-trip time of the corresponding data packet to be tested is calculated, that is, the sending timestamp is subtracted from the receiving timestamp, and the round-trip time of the corresponding data packet to be tested is used as the delay estimate ni of the corresponding data packet to be tested;

[0029] When sending the corresponding data packet to be tested, the amount of data successfully transmitted by the corresponding data packet to be tested within the set time is collected, and the ratio between the amount of data successfully transmitted and the set time is calculated to obtain the throughput vi of the corresponding data packet to be tested;

[0030] Each group of data packets to be tested is represented by a number i, where i=1,2...X;

[0031] Based on the bit error rate ti, packet loss rate pi, delay estimate ni and throughput vi of each group of data packets to be tested, substitute into the formula Perform weighted calculation to obtain the effect evaluation index Tre of the power communication network at the current trigger time point; 、 、 as well as They represent the maximum allowable bit error rate, maximum allowable packet loss rate, longest allowable delay estimation, and minimum allowable throughput of the corresponding data packets to be tested; 、 、 as well as are the impact weight factors corresponding to the bit error rate ti, packet loss rate pi, delay estimation ni and throughput vi of the data packets to be tested respectively;

[0032] Comprehensive testing: This test uses multiple data packets of different sizes and types to comprehensively evaluate the performance of the power communication network under different conditions.

[0033] Detailed performance analysis: Analyzes the bit error rate, packet loss rate, latency, and throughput of each data packet individually, providing a detailed performance report.

[0034] Flexible test configuration: allows technicians to adjust the number, size, and sending strategy of data packets according to actual conditions to meet different test requirements;

[0035] Real-time feedback and evaluation: After the test signaling is triggered, in-depth analysis is immediately performed and the effect evaluation index Tre is calculated in real time;

[0036] Weighted comprehensive evaluation: Through weighted calculation, the impact of different performance indicators on communication network quality is reasonably considered, making the evaluation results more balanced and accurate;

[0037] Threshold comparison: Compares performance against preset thresholds for maximum allowable bit error rate, packet loss rate, latency estimate, and minimum throughput to quickly identify performance bottlenecks.

[0038] Early problem identification: timely detection of communication problems provides a basis for troubleshooting and performance optimization.

[0039] In summary, through meticulous and comprehensive testing and flexible configuration, we have achieved in-depth analysis and real-time evaluation of power communication network performance, helping to quickly identify and resolve communication problems and improve network stability and reliability.

[0040] The effect evaluation module is used to receive the effect evaluation index Tre of the power communication network at the current trigger time point, and further analyze it to obtain the abnormality evaluation level of the power communication network at the current trigger time point; the abnormality evaluation level includes a slight impact level, a general impact level, and a severe impact level; and send the obtained abnormality evaluation level to the intelligent processing module;

[0041] Specifically:

[0042] Three groups of index value ranges are preset for the effect evaluation index Tre, and each group of index value ranges is set to correspond to an abnormality assessment level. The effect evaluation index Tre of the electric power communication network at the current trigger time point is matched with the three preset index value ranges to obtain the abnormality assessment level of the electric power communication network at the current trigger time point;

[0043] The intelligent processing module is used to receive the abnormality assessment level of the power communication network at the current trigger time point and execute corresponding steps based on the specific type of the abnormality assessment level;

[0044] Specifically:

[0045] If the abnormality assessment level of the power communication network at the current trigger time is a minor impact level, an automated diagnosis is first performed; the automated diagnosis includes a network connection status check, a network resource usage check, and a security scan. If the automated diagnosis shows no problems, the current assessment results are first recorded, and the preset time interval in the collection preset module is adjusted; the specific adjustment range is preset by the technicians. Based on the adjusted time interval, the effect evaluation index of the power communication network is analyzed again. If a minor impact level is still generated, the generated minor impact level is upgraded to a general impact level.

[0046] If the abnormality assessment level of the power communication network at the current trigger time is a general impact level, an automated diagnosis is first performed. If the automated diagnosis shows no problem, a general warning signal is sent to the manager who is in working status at the current time point. After confirmation, the manager establishes a remote connection and implements optimization measures, including adjusting the signal modulation method, enhancing signal amplification, and adjusting resource allocation. The preset time interval in the collection preset module is also adjusted. Based on the adjusted time interval, the effect evaluation index of the power communication network is analyzed again. If a general impact level is still generated, the generated general impact level is upgraded to a severe impact level.

[0047] If the abnormality assessment level of the power communication network at the current triggering time point is a serious impact level, an automatic diagnosis is performed first. If the automatic diagnosis shows that there is no problem, an emergency response signal is triggered immediately, and a circle is drawn with the location of the power communication equipment as the center and the distance as the radius. The maintenance personnel within the circle are screened, and a position feedback signal is sent to the mobile terminal of each maintenance personnel. After each maintenance personnel confirms the position feedback signal, the location of each maintenance personnel corresponding to the current time point is obtained, and the distance between each maintenance personnel and the location of the flow abnormality is calculated. At the same time, the historical selection times of each maintenance personnel are obtained, and the duration of each maintenance is further obtained from each selection times of each maintenance personnel. The time point when the maintenance personnel arrives at the location is marked as the starting time point, and the time point when the maintenance is completed is marked as the ending time point. The time difference between the starting time point and the ending time point is calculated to obtain the duration of maintenance of this maintenance personnel; the average duration of each group of each maintenance personnel is calculated to obtain the average maintenance time of each maintenance personnel;

[0048] Further obtain the working years of each maintenance personnel, mark the distance traveled, average maintenance time and working years of each maintenance personnel as k1, k2 and k3 respectively, and substitute them into the formula A weighted calculation is performed to obtain the maintenance merit value Ze of each maintenance personnel; b1, b2, and b3 are the influencing weight factors of travel distance, average maintenance time, and years of service, respectively;

[0049] The maintenance personnel with the highest maintenance merit value Ze are selected from among all maintenance personnel, and an emergency response signaling is sent to the maintenance personnel's mobile terminal. After receiving the signaling, the maintenance personnel arrives at the location of the power equipment to investigate the cause of the problem.

[0050] Refined management: Take different treatment measures according to different abnormality assessment levels to achieve refined management of the communication network;

[0051] Preventive maintenance: Early identification and adjustment of minor impact level problems to prevent them from becoming serious;

[0052] Resource optimization: Under normal impact levels, optimize the use of communication resources by adjusting signal modulation, signal amplification, and resource allocation;

[0053] Emergency response mechanism: For serious impact levels, the emergency response process is quickly initiated to ensure that the problem can be handled in a timely manner;

[0054] Intelligent scheduling: By calculating the maintenance personnel's maintenance merit value Ze, the most suitable maintenance personnel are intelligently selected for on-site inspections, improving maintenance efficiency;

[0055] Continuous performance monitoring: Ensure continuous optimization of communication network performance by adjusting preset time intervals and continuously monitoring the effect evaluation index;

[0056] Through the above measures, the overall stability and reliability of the power communication network will be improved.

[0057] Compared with the prior art, the present invention has the following beneficial effects:

[0058] The present invention quantifies qualitative problems by accurately monitoring the signal strength of the power communication network and calculating the shadow area, duration and number of abnormal areas of the abnormal area, thereby obtaining a signal evaluation index of the power communication network within a set time period. The signal evaluation index of the power communication network within the set time period is compared with a preset threshold index. If the signal evaluation index is less than the preset threshold index, a test signaling is triggered and an in-depth analysis is immediately performed. By separately analyzing the bit error rate, packet loss rate, delay and throughput of each group of data packets and calculating the effect evaluation index in real time, the performance of the power communication network is fully reflected, and an in-depth analysis and real-time evaluation of the performance of the power communication network are achieved, which helps to quickly identify and solve communication problems and improve the stability and reliability of the network.

[0059] The present invention presets three groups of index value ranges for effect evaluation indices, sets each group of index value ranges to correspond to an abnormality evaluation level, matches the effect evaluation index of the electric power communication network at the current triggering time point with the preset three groups of index value ranges, obtains the abnormality evaluation level of the electric power communication network at the current triggering time point, and adopts different processing measures according to different abnormality evaluation levels to realize refined management of the communication network. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Further details, features and advantages of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which:

[0061] Figure 1 It is a principle block diagram of the present invention;

[0062] Figure 2 This is a signal intensity variation curve diagram of the present invention. DETAILED DESCRIPTION

[0063] Several embodiments of the present application will be described in more detail below with reference to the accompanying drawings so that those skilled in the art can implement the present application. The present application can be embodied in many different forms and for many different purposes and should not be limited to the embodiments described herein. These embodiments are provided to make the present application comprehensive and complete and to fully convey the scope of the present application to those skilled in the art. The embodiments do not limit the present application.

[0064] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the relevant art and / or the context of this specification, and will not be interpreted in an idealized or overly formal sense unless expressly defined as such herein.

[0065] See also Figure 1-Figure 2 As shown, a power communication effect evaluation system based on big data includes a collection and preset module, a preliminary evaluation module, an in-depth analysis module, an effect evaluation module and an intelligent processing module;

[0066] The collection preset module is used to preset the time interval for collecting the power communication network signal strength, and after the preset time interval is reached, collect the signal strength changes of the power communication network within the set time period and send them to the preliminary evaluation module;

[0067] The preliminary evaluation module is used to receive and analyze the signal strength changes of the power communication network within a set time period to obtain the signal evaluation index Ma of the power communication network within the set time period; and compare the signal evaluation index Ma of the power communication network within the set time period with a preset threshold index. If the signal evaluation index Ma is less than the preset threshold index, a test signaling is triggered and sent to the in-depth analysis module;

[0068] Specifically:

[0069] Extract the signal strength of the power communication network at each time point within a set time period, and construct a signal strength change curve based on it, preset a normal range of signal strength, and draw the range interval corresponding to the preset normal range in the curve;

[0070] Mark the curve below the range interval, mark the area enclosed by the line below the range interval and the marked curve as the abnormal area, fill the abnormal area, calculate the shadow area of ​​the abnormal area, and accumulate the shadow areas of each abnormal area to obtain the total shadow value f1;

[0071] Further count the duration corresponding to each abnormal area, accumulate the duration of each group, and obtain the total duration f2;

[0072] Count the number of abnormal areas and mark the number of abnormal areas as f3;

[0073] According to the formula A weighted calculation is performed on the total shadow value f1, the total duration f2, and the number f3 of abnormal areas of the power communication network within a set time period to obtain the signal evaluation index Ma of the power communication network within the set time period; wherein a1, a2, and a3 are the influence weight factors of the total shadow value f1, the total duration f2, and the number f3 of abnormal areas, respectively; h1, h2, and h3 are the preset maximum allowable values ​​of the total shadow value f1, the total duration f2, and the number f3 of abnormal areas, respectively;

[0074] It should be noted that real-time monitoring and evaluation: by receiving and analyzing changes in signal strength in real time, it is possible to promptly capture fluctuations in the state of the power communication network;

[0075] Visual analysis: Construct a signal strength change curve chart and compare it with the preset normal range to intuitively display abnormal signal strength;

[0076] Quantitative anomaly assessment: By calculating the shadow area, duration, and number of abnormal areas, qualitative issues are quantified, improving the accuracy of the assessment.

[0077] Weighted analysis: Weighted calculation takes into account the severity of different abnormal factors, making the assessment results more reasonable and comprehensive;

[0078] Threshold comparison mechanism: Comparison with preset thresholds provides a basis for decision-making for further in-depth analysis, enhancing the system's adaptability and response speed;

[0079] In summary, accurate monitoring of the signal strength of the power communication network is achieved, and the reliability and maintenance efficiency of the communication network are improved.

[0080] The in-depth analysis module is used to further test the relevant parameters of the power communication network at the current trigger time when the test signaling is triggered, obtain the effect evaluation index Tre of the power communication network at the current trigger time, and send it to the effect evaluation module; the relevant parameters include bit error rate, packet loss rate, delay estimation, and throughput;

[0081] Specifically:

[0082] Prepare X groups of test data packets; where X>3, the specific number is preset by the technician and can be adjusted later based on actual conditions. The size and type of the test data packets are different;

[0083] Set a sending strategy for X groups of test data packets; the sending strategy includes a sending interval and a sending order; and send the corresponding test data packets. Perform an integrity check on the received corresponding test data packets at the receiving end to determine the total number of transmitted bits and the number of error bits. Calculate the proportion of the number of error bits in the total number of transmitted bits, and use the calculated proportion as the bit error rate ti of the corresponding test data packets.

[0084] Record the sequence number and total number of packets sent by the sending end, and record the sequence number and total number of packets received by the receiving end, identify gaps in the sequence numbers, determine the number of lost packets, calculate the percentage of lost packets to the total number, and use the calculated percentage as the packet loss rate (pi) of the packets to be tested.

[0085] At the sending end, a sending timestamp is recorded for the corresponding data packet to be tested, and at the receiving end, a receiving timestamp is recorded for the corresponding data packet to be tested, and the round-trip time of the corresponding data packet to be tested is calculated, that is, the sending timestamp is subtracted from the receiving timestamp, and the round-trip time of the corresponding data packet to be tested is used as the delay estimate ni of the corresponding data packet to be tested;

[0086] When sending the corresponding data packet to be tested, the amount of data successfully transmitted by the corresponding data packet to be tested within the set time is collected, and the ratio between the amount of data successfully transmitted and the set time is calculated to obtain the throughput vi of the corresponding data packet to be tested;

[0087] Each group of data packets to be tested is represented by a number i, where i=1,2...X;

[0088] Based on the bit error rate ti, packet loss rate pi, delay estimate ni and throughput vi of each group of data packets to be tested, substitute into the formula Perform weighted calculation to obtain the effect evaluation index Tre of the power communication network at the current trigger time point; 、 、 as well as They represent the maximum allowable bit error rate, maximum allowable packet loss rate, longest allowable delay estimation, and minimum allowable throughput of the corresponding data packets to be tested; 、 、 as well as are the impact weight factors corresponding to the bit error rate ti, packet loss rate pi, delay estimation ni and throughput vi of the data packets to be tested respectively;

[0089] It should be noted that comprehensive testing: comprehensively evaluates the performance of the power communication network under different conditions through multiple sets of data packets of different sizes and types;

[0090] Detailed performance analysis: Analyzes the bit error rate, packet loss rate, latency, and throughput of each data packet individually, providing a detailed performance report.

[0091] Flexible test configuration: allows technicians to adjust the number, size, and sending strategy of data packets according to actual conditions to meet different test requirements;

[0092] Real-time feedback and evaluation: After the test signaling is triggered, in-depth analysis is immediately performed and the effect evaluation index Tre is calculated in real time;

[0093] Weighted comprehensive evaluation: Through weighted calculation, the impact of different performance indicators on communication network quality is reasonably considered, making the evaluation results more balanced and accurate;

[0094] Threshold comparison: Compares performance against preset thresholds for maximum allowable bit error rate, packet loss rate, latency estimate, and minimum throughput to quickly identify performance bottlenecks.

[0095] Early problem identification: timely detection of communication problems provides a basis for troubleshooting and performance optimization.

[0096] In summary, through meticulous and comprehensive testing and flexible configuration, we have achieved in-depth analysis and real-time evaluation of power communication network performance, helping to quickly identify and resolve communication problems and improve network stability and reliability.

[0097] The effect evaluation module is used to receive the effect evaluation index Tre of the power communication network at the current trigger time point, and further analyze it to obtain the abnormality evaluation level of the power communication network at the current trigger time point; the abnormality evaluation level includes a slight impact level, a general impact level, and a severe impact level; and send the obtained abnormality evaluation level to the intelligent processing module;

[0098] Specifically:

[0099] Three groups of index value ranges are preset for the effect evaluation index Tre, and each group of index value ranges is set to correspond to an abnormality assessment level. The effect evaluation index Tre of the electric power communication network at the current trigger time point is matched with the three preset index value ranges to obtain the abnormality assessment level of the electric power communication network at the current trigger time point;

[0100] The intelligent processing module is used to receive the abnormality assessment level of the power communication network at the current trigger time point and execute corresponding steps based on the specific type of the abnormality assessment level;

[0101] Specifically:

[0102] If the abnormality assessment level of the power communication network at the current trigger time is a minor impact level, an automated diagnosis is first performed; the automated diagnosis includes a network connection status check, a network resource usage check, and a security scan. If the automated diagnosis shows no problems, the current assessment results are first recorded, and the preset time interval in the collection preset module is adjusted; the specific adjustment range is preset by the technicians. Based on the adjusted time interval, the effect evaluation index of the power communication network is analyzed again. If a minor impact level is still generated, the generated minor impact level is upgraded to a general impact level.

[0103] If the abnormality assessment level of the power communication network at the current trigger time is a general impact level, an automated diagnosis is first performed. If the automated diagnosis shows no problem, a general warning signal is sent to the manager who is in working status at the current time point. After confirmation, the manager establishes a remote connection and implements optimization measures, including adjusting the signal modulation method, enhancing signal amplification, and adjusting resource allocation. The preset time interval in the collection preset module is also adjusted. Based on the adjusted time interval, the effect evaluation index of the power communication network is analyzed again. If a general impact level is still generated, the generated general impact level is upgraded to a severe impact level.

[0104] If the abnormality assessment level of the power communication network at the current triggering time point is a serious impact level, an automatic diagnosis is performed first. If the automatic diagnosis shows that there is no problem, an emergency response signal is triggered immediately, and a circle is drawn with the location of the power communication equipment as the center and the distance as the radius. The maintenance personnel within the circle are screened, and a position feedback signal is sent to the mobile terminal of each maintenance personnel. After each maintenance personnel confirms the position feedback signal, the location of each maintenance personnel corresponding to the current time point is obtained, and the distance between each maintenance personnel and the location of the flow abnormality is calculated. At the same time, the historical selection times of each maintenance personnel are obtained, and the duration of each maintenance is further obtained from each selection times of each maintenance personnel. The time point when the personnel arrives at the location is marked as the starting time point, and the time point when the maintenance is completed is marked as the ending time point. The time difference between the starting time point and the ending time point is calculated to obtain the duration of this personnel maintenance; the average duration of each group of maintenance personnel is calculated to obtain the average maintenance time of each maintenance personnel;

[0105] Further obtain the working years of each maintenance personnel, mark the distance traveled, average maintenance time and working years of each maintenance personnel as k1, k2 and k3 respectively, and substitute them into the formula A weighted calculation is performed to obtain the maintenance merit value Ze of each maintenance personnel; b1, b2, and b3 are the influencing weight factors of travel distance, average maintenance time, and years of service, respectively;

[0106] The maintenance personnel with the highest maintenance excellence value Ze are selected from all maintenance personnel, and an emergency response signaling is sent to the personnel's mobile terminal. After receiving the signaling, the personnel arrives at the location of the power equipment to investigate the cause of the problem.

[0107] It should be noted that

[0108] Refined management: Take different treatment measures according to different abnormality assessment levels to achieve refined management of the communication network;

[0109] Preventive maintenance: Early identification and adjustment of minor impact level problems to prevent them from becoming serious;

[0110] Resource optimization: Under normal impact levels, optimize the use of communication resources by adjusting signal modulation, signal amplification, and resource allocation;

[0111] Emergency response mechanism: For serious impact levels, the emergency response process is quickly initiated to ensure that the problem can be handled in a timely manner;

[0112] Intelligent scheduling: By calculating the maintenance personnel's maintenance merit value Ze, the most suitable maintenance personnel are intelligently selected for on-site inspections, improving maintenance efficiency;

[0113] Continuous performance monitoring: Ensure continuous optimization of communication network performance by adjusting preset time intervals and continuously monitoring the effect evaluation index;

[0114] Through the above measures, the overall stability and reliability of the power communication network will be improved;

[0115] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The influencing weight factors and specific coefficient values ​​in the formula are set by technical personnel in this field according to actual conditions, and can be adjusted and modified later.

[0116] The preferred embodiments of the present invention disclosed above are intended only to help illustrate the present invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the present invention to specific embodiments. Obviously, many modifications and variations are possible based on the contents of this specification. These embodiments are selected and described in detail in this specification to better explain the principles and practical applications of the present invention, thereby enabling those skilled in the art to better understand and utilize the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A power communication effect evaluation system based on big data, characterized in that: include: Collection preset module: presets the time interval for collecting the signal strength of the power communication network, and after the preset time interval is reached, collects the signal strength changes of the power communication network within the set time period and sends them to the preliminary evaluation module; Preliminary evaluation module: receives the signal strength changes of the power communication network within a set time period, analyzes them, and obtains the signal evaluation index Ma of the power communication network within the set time period; The signal evaluation index Ma of the power communication network within a set time period is compared with a preset threshold index. If the signal evaluation index Ma is less than the preset threshold index, a test signaling is triggered and sent to the in-depth analysis module; In-depth analysis module: When the test signaling is triggered, the relevant parameters of the power communication network at the current triggering time are further tested to obtain the effect evaluation index Tre of the power communication network at the current triggering time and send it to the effect evaluation module; the relevant parameters include bit error rate, packet loss rate, delay estimation and throughput; Effect evaluation module: receives the effect evaluation index Tre of the power communication network at the current trigger time, and further analyzes it to obtain the abnormality evaluation level of the power communication network at the current trigger time; the abnormality evaluation level includes slight impact level, general impact level and severe impact level; and sends the obtained abnormality evaluation level to the intelligent processing module; Intelligent processing module: receives the abnormality assessment level of the power communication network at the current trigger time point, and executes corresponding steps based on the specific type of the abnormality assessment level; Receive the signal strength changes of the power communication network within a set time period and analyze them, specifically: Extract the signal strength of the power communication network at each time point within a set time period, and construct a signal strength change curve based on it, preset a normal range of signal strength, and draw the range interval corresponding to the preset normal range in the curve; Mark the curve below the range interval, mark the area enclosed by the line below the range interval and the marked curve as the abnormal area, fill the abnormal area, calculate the shadow area of ​​the abnormal area, and accumulate the shadow areas of each abnormal area to obtain the total shadow value f1; Further count the duration corresponding to each abnormal area, accumulate the duration of each group, and obtain the total duration f2; The number of abnormal areas is counted and marked as f3; the signal evaluation index Ma of the power communication network in the set time period is obtained, specifically: According to the formula The total shadow value f1, the total duration f2 and the number f3 of the abnormal areas of the power communication network within the set time period are weightedly calculated to obtain the signal evaluation index Ma of the power communication network within the set time period; wherein a1, a2 and a3 are the influence weight factors of the total shadow value f1, the total duration f2 and the number f3 of the abnormal areas, respectively, and h1, h2 and h3 are the preset maximum allowable values ​​of the total shadow value f1, the total duration f2 and the number f3 of the abnormal areas, respectively.

2. The power communication effect evaluation system based on big data according to claim 1 is characterized in that: Further test the relevant parameters of the power communication network at the current trigger time, specifically: Prepare X groups of data packets to be tested; where X>3; Set a sending strategy for X groups of test data packets; the sending strategy includes a sending interval and a sending order; and send the corresponding test data packets. Perform an integrity check on the received corresponding test data packets at the receiving end to determine the total number of transmitted bits and the number of error bits. Calculate the proportion of the number of error bits in the total number of transmitted bits, and use the calculated proportion as the bit error rate ti of the corresponding test data packets. Record the sequence number and total number of packets sent by the sending end, and record the sequence number and total number of packets received by the receiving end, identify gaps in the sequence numbers, determine the number of lost packets, calculate the percentage of lost packets to the total number, and use the calculated percentage as the packet loss rate (pi) of the packets to be tested. At the sending end, a sending timestamp is recorded for the corresponding data packet to be tested, and at the receiving end, a receiving timestamp is recorded for the corresponding data packet to be tested, and the round-trip time of the corresponding data packet to be tested is calculated, that is, the sending timestamp is subtracted from the receiving timestamp, and the round-trip time of the corresponding data packet to be tested is used as the delay estimate ni of the corresponding data packet to be tested; When sending the corresponding data packet to be tested, the amount of data successfully transmitted within the set time of the corresponding data packet to be tested is collected, and the ratio between the amount of data successfully transmitted and the set time is calculated to obtain the throughput vi of the corresponding data packet to be tested.

3. The power communication effect evaluation system based on big data according to claim 1 is characterized in that: The effect evaluation index Tre of the power communication network at the current triggering time point is obtained, specifically: Each group of data packets to be tested is represented by a number i, where i=1,2...X; Based on the bit error rate ti, packet loss rate pi, delay estimate ni and throughput vi of each group of data packets to be tested, substitute into the formula Perform weighted calculation to obtain the effect evaluation index Tre of the power communication network at the current trigger time point; 、 、 as well as They represent the maximum allowable bit error rate, maximum allowable packet loss rate, longest allowable delay estimation, and minimum allowable throughput of the corresponding data packets to be tested; 、 、 as well as are the impact weight factors corresponding to the bit error rate ti, packet loss rate pi, delay estimation ni and throughput vi of the data packet to be tested.

4. The power communication effect evaluation system based on big data according to claim 1 is characterized in that: Get the abnormal assessment level of the power communication network at the current trigger time, specifically: Three groups of index value ranges of the preset effect evaluation index Tre are set, and each group of index value ranges is set to correspond to an abnormality assessment level. The effect evaluation index Tre of the power communication network at the current trigger time point is matched with the preset three groups of index value ranges to obtain the abnormality assessment level of the power communication network at the current trigger time point.

5. The power communication effect evaluation system based on big data according to claim 1 is characterized in that: Based on the specific type of abnormal assessment level, the corresponding steps are performed, specifically: If the abnormality assessment level of the power communication network at the current trigger time is a minor impact level, an automated diagnosis is first performed; if the automated diagnosis shows no problem, the current assessment result is first recorded, and the preset time interval in the collection preset module is adjusted; based on the adjusted time interval, the effect assessment index of the power communication network is analyzed again. If a minor impact level is still generated, the generated minor impact level is upgraded to a general impact level; If the abnormality assessment level of the power communication network at the current trigger time is a general impact level, an automated diagnosis is first performed. If the automated diagnosis shows no problem, a general warning signal is sent to the manager who is in working status at the current time point. After confirmation, the manager establishes a remote connection and implements optimization measures, including adjusting the signal modulation method, enhancing signal amplification, and adjusting resource allocation. The preset time interval in the collection preset module is also adjusted. Based on the adjusted time interval, the effect evaluation index of the power communication network is analyzed again. If a general impact level is still generated, the generated general impact level is upgraded to a severe impact level. If the abnormality assessment level of the power communication network at the current triggering time point is a serious impact level, an automatic diagnosis is performed first. If the automatic diagnosis shows that there is no problem, an emergency response signal is triggered immediately, and a circle is drawn with the location of the power communication equipment as the center and the distance as the radius. The maintenance personnel within the circle are screened, and a position feedback signal is sent to the mobile terminal of each maintenance personnel. After each maintenance personnel confirms the position feedback signal, the location of each maintenance personnel corresponding to the current time point is obtained, and the distance between each maintenance personnel and the location of the flow abnormality is calculated. At the same time, the historical selection times of each maintenance personnel are obtained, and the duration of each maintenance is further obtained from each selection times of each maintenance personnel. The time point when the maintenance personnel arrives at the location is marked as the starting time point, and the time point when the maintenance is completed is marked as the ending time point. The time difference between the starting time point and the ending time point is calculated to obtain the duration of maintenance of this maintenance personnel; the average duration of each group of each maintenance personnel is calculated to obtain the average maintenance time of each maintenance personnel; Further obtain the working years of each maintenance personnel, mark the distance traveled, average maintenance time and working years of each maintenance personnel as k1, k2 and k3 respectively, and substitute them into the formula A weighted calculation is performed to obtain the maintenance merit value Ze of each maintenance personnel; b1, b2, and b3 are the influencing weight factors of travel distance, average maintenance time, and years of service, respectively; The maintenance personnel with the largest maintenance excellence value Ze is selected from all maintenance personnel, and an emergency response signaling is sent to the maintenance personnel's mobile terminal. After receiving the signaling, the maintenance personnel arrives at the location of the power equipment to investigate the cause of the problem.

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