Electric power communication network intelligent monitoring method based on dual-mode communication

Abstract

The invention relates to the technical field of dual-mode communication, in particular to an electric power communication network intelligent monitoring method based on dual-mode communication. The method comprises the following steps: analyzing the average distribution difference of all low-pull values, the difference of the total number of the low-pull values, the difference of the maximum mutation data, the difference of the moment corresponding to the maximum mutation data and the difference of the total number of the mutation data between each data transmission and historical data transmission, and determining the normal continuity; and comparing the difference of the moment corresponding to the first QoS value between each data transmission and the previous adjacent latest high-interference data transmission, the difference of all QoS values and the mutation data distribution in all QoS values in the adjacent latest high-interference data transmission process, determining the comprehensive disturbed degree, and judging whether to switch the communication mode or not by combining the normal continuity. The problem of frequent switching of communication modes caused by transient interference is solved, and the communication stability is improved while computing resources are saved.

Description

Technical Field

[0001] The present application relates to the field of dual-mode communication technology, and in particular to an intelligent monitoring method for a power communication network based on dual-mode communication. Background Art

[0002] The security of the power system is the foundation and prerequisite for the stability of grid operation. Traditional communication technologies in electricity consumption information collection systems primarily rely on single power line carrier communication or micro-power wireless networking communication technologies, resulting in low data collection capacity and success rates. With the advancement of communication technology, this has gradually evolved into a dual-mode communication mode: high-speed power line carrier communication (HPLC) and high-speed wireless radio frequency communication (HRF). Dual-mode communication automatically switches when needed. For example, when the power line communication quality is good, the dual-mode communication unit uses power line communication for data transmission; when the power line communication quality is poor, the dual-mode communication unit uses wireless communication for data transmission. This allows for adaptability to different scenarios and environments, providing better data transmission.

[0003] Normally, the communication mode will be switched only when the transmission quality degrades and the communication quality is lower than the preset threshold during the transmission process. However, there are many situations that interfere with the transmission quality during the transmission process. Short-term or instantaneous interference will cause the power communication network to frequently switch communication modes, resulting in a waste of computing resources and reduced communication stability. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides an intelligent monitoring method for power communication network based on dual-mode communication to solve the existing problems.

[0005] The intelligent monitoring method of the power communication network based on dual-mode communication in this application adopts the following technical solutions: An embodiment of the present application provides a method for intelligent monitoring of a power communication network based on dual-mode communication, the method comprising the following steps: In the dual-mode communication power communication network, the QoS value of each data transmission process is obtained in real time; The QoS values ​​at all times during each data transmission process are used as input to the threshold segmentation algorithm, and QoS values ​​greater than the segmentation threshold are recorded as low-pull values; the QoS variability of each data transmission process is determined by analyzing the difference in the average distribution of all low-pull values ​​and the difference in the total number of low-pull values ​​between each data transmission process and the previous data transmission process; the mutation data of all QoS values ​​during each data transmission process are extracted, and the difference in the maximum mutation data, the difference in the corresponding time of the maximum mutation data, and the difference in the total number of mutation data between each data transmission process and a preset number of data transmission processes before it are compared to determine the interference abnormal coefficient of each data transmission process, and the normal duration of each data transmission process is determined in combination with the QoS variability; Analyze the average distribution of QoS values ​​at all times during each data transmission process to obtain a high-interference data transmission process; compare the difference in the first QoS value corresponding time and the difference in all QoS values ​​between each data transmission process and its previous adjacent and most recent high-interference data transmission process to determine the first interference degree of each data transmission process; analyze the average distribution of all mutation data in all QoS values ​​in the adjacent and most recent high-interference data transmission process before each data transmission process and the average distribution of all QoS values ​​to determine the second interference degree of each data transmission process, and combine the first interference degree to determine the comprehensive interference degree of each data transmission process; Based on the normal continuity and the comprehensive interference degree, the mode sustainability of each data transmission process is determined to determine whether to switch the communication mode.

[0006] Preferably, the method for determining the QoS variation degree of each data transmission process is: Calculate the average of the low-pull values ​​at all times during each data transmission process, recorded as the low-pull value mean, and add the difference between the low-pull value mean of each data transmission process and its previous data transmission process to the difference in the total number of low-pull values ​​as the QoS change degree of each data transmission process.

[0007] Preferably, the method for determining the interference abnormal coefficient of each data transmission process is: Calculate the cumulative sum of the maximum mutation data difference between each data transmission process and the preset number of data transmission processes before it, the mean of the difference between the maximum mutation data at the corresponding time, and the mean of the difference in the total number of mutation data, and record them as the first mutation difference, second mutation difference, and third mutation difference of each data transmission process respectively; The results of the forward fusion of the first mutation difference, the second mutation difference and the third mutation difference in each data transmission process are taken as the interference abnormal coefficient of each data transmission process.

[0008] Preferably, the normal duration of each data transmission process is the ratio of the interference abnormal coefficient of each data transmission process to the QoS variation degree.

[0009] Preferably, the process of obtaining high-interference data transmission includes: Calculate the average QoS value at all times during each data transmission process, and record it as the QoS mean; The QoS mean of all data transmission processes within a preset time period before each data transmission process is used as the input of the threshold segmentation algorithm, and the segmentation threshold is output and recorded as the QoS threshold. The data transmission process corresponding to the QoS mean greater than the QoS threshold is regarded as a high-interference data transmission process.

[0010] Preferably, the first interference degree of each data transmission process is: the time interval between the first QoS value corresponding moment of each data transmission process and the previous adjacent data transmission process with the second highest interference divided by the difference between all QoS values.

[0011] Preferably, the expression of the second interference degree of each data transmission process is: Where, represents the second interference degree of the i-th data transmission process; represents the mean of all mutation data in all QoS values ​​in the most recent high-interference data transmission process before the i-th data transmission process; represents the mean of all QoS values ​​in the adjacent and most recent high-interference data transmission process before the i-th data transmission process; Indicates a preset constant greater than 0.

[0012] Preferably, the comprehensive interference degree of each data transmission process is the product of the first interference degree and the second interference degree of each data transmission process.

[0013] Preferably, the mode sustainability of each data transmission process is the ratio of the normal sustainability of each data transmission process to the comprehensive interference degree.

[0014] Preferably, the determining whether to switch the communication mode includes: The mode sustainability of all data transmission processes within the preset time length between the current data transmission process is used as the input of the threshold segmentation algorithm, and the segmentation threshold is output and recorded as the sustainability threshold. If the mode sustainability of the current data transmission process is greater than the sustainability threshold, the communication mode of the current data transmission process is maintained. Otherwise, the communication mode of the current data transmission process is switched.

[0015] This application has at least the following beneficial effects: This application first quantifies the QoS variation degree that measures the short-term fluctuations in communication quality and the interference abnormality coefficient of interference abnormality by analyzing the differences in the low-pull value distribution and the historical differences in mutation data of QoS values, and combines the two to obtain the normal continuity, so as to judge whether the current communication mode is sustainable, avoiding the problem of waste of computing resources caused by frequent switching of communication modes due to short-term interference, thereby helping to improve communication stability; further, this application analyzes the QoS value distribution, calculates the first interference degree and the second interference degree, and combines the two to obtain the comprehensive interference degree to evaluate the interference risk of data transmission, and intelligently decides whether to switch the communication mode, effectively distinguishes between continuous interference and accidental interference, reduces misjudgment, optimizes communication resource utilization, and improves communication stability and quality. This application addresses the problem of frequent switching of communication modes due to transient interference in power communication networks, which leads to waste of resources and decreased communication stability. By obtaining QoS values ​​in real time, the normal continuity is calculated by analyzing the differences in low-pull value distribution and historical differences in mutation data, and the stability of the current communication mode is evaluated. At the same time, by analyzing the QoS mean distribution to identify high-interference processes, the comprehensive interference sensitivity is calculated, and the risk of future interference from continuing to use the current communication mode is evaluated. Finally, the mode sustainability is constructed by combining the normal continuity and the comprehensive interference sensitivity, so as to decide whether to switch the communication mode, effectively distinguish between short-term interference and continuous interference, avoid unnecessary mode switching, save computing resources, and improve communication stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 A flowchart of the steps of a method for intelligent monitoring of a power communication network based on dual-mode communication provided in one embodiment of the present application; Figure 2 A schematic diagram of the pattern sustainability extraction process provided in one embodiment of the present application. DETAILED DESCRIPTION

[0018] To further illustrate the technical means and effects employed by this application to achieve the intended invention objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation, structure, features, and effects of the intelligent monitoring method for a power communication network based on dual-mode communication proposed in this application. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0019] Unless defined otherwise, all 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.

[0020] The specific scheme of the intelligent monitoring method of the power communication network based on dual-mode communication provided by this application is described in detail below with reference to the accompanying drawings.

[0021] An embodiment of the present application provides an intelligent monitoring method for a power communication network based on dual-mode communication. Specifically, the following intelligent monitoring method for a power communication network based on dual-mode communication is provided. Figure 1 , the method comprises the following steps: Step S1: In a dual-mode communication power communication network, the QoS value of each data transmission process is obtained in real time.

[0022] The electric power communication network is used to transmit data. Power line communication is particularly susceptible to various factors such as changes in the load on the power line, the start and stop of electrical appliances, and environmental noise. When the transmission quality decreases and exceeds a preset threshold during the transmission process, the communication mode will be switched. However, there may be some short-term or transient interference during the transmission process, which will cause the electric power communication network based on dual-mode communication to frequently switch communication modes, resulting in a waste of computing resources. In this embodiment, the dual-mode communication mode includes a high-speed power line carrier communication (HPLC) and a high-speed wireless radio frequency communication (HRF) dual-mode communication mode.

[0023] In order to reduce the frequent switching of communication modes, it is necessary to monitor the communication quality of the data transmission process in real time. Since the QoS value directly reflects the communication quality of the current communication mode, this embodiment obtains the QoS value of each data transmission process in real time in the dual-mode communication power communication network, where data is transmitted from the sending end to the receiving end as one data transmission. The data acquisition frequency is set to f. In this embodiment, the value of f is 1000 Hz. In actual application, as other implementation methods, the implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0024] Step S2: The QoS values ​​at all times during each data transmission process are used as inputs to the threshold segmentation algorithm, and the QoS values ​​greater than the segmentation threshold are recorded as low-pull values; the QoS variation of each data transmission process is determined by analyzing the difference in the average distribution of all low-pull values ​​and the difference in the total number of low-pull values ​​between each data transmission process and the previous data transmission process; the mutation data of all QoS values ​​during each data transmission process are extracted, and the difference in the maximum mutation data, the difference in the corresponding time of the maximum mutation data, and the difference in the total number of mutation data between each data transmission process and the previous preset number of data transmission processes are compared to determine the interference abnormal coefficient of each data transmission process, and the normal duration of each data transmission process is determined in combination with the QoS variation.

[0025] During data transmission in the power communication network, high-speed power line carrier communication mainly uses power lines for communication. Therefore, there will inevitably be a certain amount of noise interference, but the interference is usually low, and the QoS value fluctuates within a small range. When passing through urban and rural areas, various electrical appliances are operating normally, which increases the load on the power line, thereby having a certain impact on high-speed power line carrier communication. However, this impact has a clear trend. For example, from night to early morning, most electrical appliances in urban and rural areas are not in operation. At this time, the load on the power line is small, and the interference to high-speed power line carrier communication is also small. As time goes by, residents begin to use more electrical appliances, which increases the load on the power line, and the interference to HPLC communication gradually increases. Therefore, during data transmission in the power communication network, the QoS value of each data transmission from night to day will decrease as the load increases. Specifically, from night to day, the QoS value of each transmission decreases based on the previous one.

[0026] Generally, when the data transmission process of the power communication network is disturbed, its QoS value will show a downward trend. In order to filter out the disturbed parts of all QoS values ​​in each data transmission process, the QoS values ​​at all times in each data transmission process are used as the input of the threshold segmentation algorithm, and the segmentation threshold is output. The QoS value less than or equal to the segmentation threshold is recorded as the low pull value.

[0027] It should be noted that there are many commonly used threshold segmentation algorithms. In this embodiment, the Otsu threshold segmentation algorithm is used to classify QoS values. In actual application, as other implementation methods, implementers can also adopt other methods based on specific circumstances. This embodiment does not impose any special restrictions.

[0028] Among them, the Otsu threshold segmentation algorithm is a well-known technology, and its specific principle is not repeated here.

[0029] It is supplemented that, unless otherwise specified, all contents related to threshold segmentation in this embodiment adopt the Otsu threshold segmentation algorithm.

[0030] Furthermore, this embodiment determines the QoS variability of each data transmission process by analyzing the difference in the average distribution of all low-pull values ​​and the difference in the total number of low-pull values ​​between each data transmission process and the previous data transmission process, which is used to characterize the changing trend of the communication quality between adjacent data transmission processes. Specifically, In this embodiment, the average of the low-pull values ​​at all times during each data transmission process is calculated and recorded as the low-pull value average. The difference between the low-pull value averages of each data transmission process and the previous data transmission process plus the difference in the total number of low-pull values ​​is taken as the QoS change degree of each data transmission process.

[0031] According to the QoS variation degree of each data transmission process, it can be understood that the QoS variation degree reflects the difference in QoS variation trends between two adjacent data transmission processes; if the difference between the mean QoS value of the current data transmission process and that of the previous data transmission process is greater, it means that the interference intensity of the communication quality has changed significantly. Therefore, the difference in the variation trend of the QoS value between the two adjacent data transmission processes is large, which indirectly reflects that the communication quality of the current data transmission process is poor; conversely, if the difference between the mean QoS value of the current data transmission process and that of the previous data transmission process is small, it means that the interference intensity of the communication quality has not changed significantly. Therefore, the difference in the variation trend of the QoS value between the two adjacent data transmission processes is small, which indirectly reflects that the communication quality of the current data transmission process is relatively stable or good.

[0032] Furthermore, this embodiment extracts mutation data of all QoS values ​​during each data transmission process, compares the difference in maximum mutation data between each data transmission process and a preset number of data transmission processes before it, the difference in the corresponding time of the maximum mutation data, and the difference in the total number of mutation data, and determines the interference abnormal coefficient of each data transmission process for characterization, which is specifically: In this embodiment, first, the QoS values ​​at all times during each data transmission process are used as inputs of a mutation point detection algorithm, and mutation data within all QoS values ​​during each data transmission process are output.

[0033] It should be noted that there are many commonly used mutation point detection algorithms. In this embodiment, the isolation forest algorithm is used to extract mutation data in all QoS values ​​during each data transmission process. In actual application, as other implementation methods, implementers can also choose other methods based on specific circumstances. Regarding the selection of mutation point detection methods, this embodiment does not impose any special restrictions.

[0034] The isolation forest algorithm is a well-known technology, and the specific process of using the isolation forest algorithm to extract mutation data in the QoS value during each data transmission process will not be described in detail.

[0035] Furthermore, the cumulative sum of the maximum mutation data difference between each data transmission process and the preset number of data transmission processes before it, the mean of the difference between the maximum mutation data at the corresponding moment, and the mean of the difference in the total number of mutation data are calculated respectively, and recorded as the first mutation difference, second mutation difference, and third mutation difference of each data transmission process respectively; The results of the forward fusion of the first mutation difference, the second mutation difference and the third mutation difference in each data transmission process are taken as the interference abnormal coefficient of each data transmission process.

[0036] It should be noted that the value of the preset number is set manually. In this embodiment, the value of the preset number is 10. In actual application, the implementer can also set it by himself based on the specific situation. This embodiment does not impose any special restrictions. When the number of data transmission processes before the data transmission process is less than the preset number, the data at this time will not be analyzed.

[0037] It should be noted that there are many methods for measuring the differences between data. In this embodiment, the absolute value of the maximum mutation data difference between each data transmission process and the data transmission processes before it is a preset number of times is used as the difference between the maximum mutation data between each data transmission process and the data transmission processes before it is a preset number of times; the time interval between the corresponding moment of the maximum mutation data between each data transmission process and the data transmission processes before it is a preset number of times is used as the difference between the corresponding moment of the maximum mutation data between each data transmission process and the data transmission processes before it is a preset number of times; the absolute value of the difference between the total number of mutation data between each data transmission process and the data transmission processes before it is a preset number of times is used as the difference between the total number of mutation data between each data transmission process and the data transmission processes before it is a preset number of times. In actual application, the implementer may also adopt other methods of measuring the differences between data, such as ratios, in combination with specific circumstances, and this embodiment does not impose any special restrictions.

[0038] It is to be supplemented that, unless otherwise specified, in this embodiment, all methods involving measuring the difference between data adopt the method of taking the absolute value of the difference.

[0039] It should be understood that forward fusion refers to combining two or more indicators through addition or multiplication to obtain a comprehensive indicator, thereby more comprehensively and accurately evaluating a phenomenon or problem. This fusion method is not limited to simple arithmetic operations and can also include more complex statistical models and analysis methods. Implementers can choose according to their specific circumstances and this embodiment does not impose any special restrictions.

[0040] Preferably, as an implementation mode, in this embodiment, the sum of the first mutation difference, the second mutation difference and the third mutation difference in each data transmission process is used as the interference abnormal coefficient of each data transmission process.

[0041] According to the interference abnormal coefficient of each data transmission process, it can be understood that the interference abnormal coefficient reflects the difference between the instantaneous sudden interference occurring in the data transmission process and the sudden interference between the historical data transmission processes. If the difference in the maximum mutation data between the current data transmission process and the previous preset number of data transmission processes is greater, the time interval corresponding to the maximum mutation data is greater, and the difference in the total number of mutation data is greater, it means that the interference suffered by the current data transmission process is not a normal increase in power load, which causes interference to the communication link and reduces the communication quality. This means that the sudden interference to the current data transmission process may be an accidental event, and there is no need to switch the communication mode of the current data transmission process. Therefore, the corresponding current interference abnormal coefficient has a larger value; On the contrary, if the difference in the maximum mutation data between the current data transmission process and the previous preset number of data transmission processes is smaller, the time interval between the corresponding moments of the maximum mutation data is smaller, and the difference in the total number of mutation data is smaller, it means that the interference to the current data transmission process is more like a normal increase in power load or other conventional factors that cause interference to the communication link and reduce communication quality. This means that the interference has a certain regularity or continuity, and may be an environmental factor that the current communication mode itself is difficult to cope with stably. In this case, it may be necessary to consider switching the communication mode to obtain more stable transmission quality. Therefore, the corresponding current interference abnormal coefficient is smaller.

[0042] Furthermore, this embodiment determines the normal duration of each data transmission process based on the interference abnormal coefficient of each data transmission process and in combination with the QoS variability, specifically: In this embodiment, the ratio of the abnormal interference coefficient to the QoS variation degree in each data transmission process is used as the normal duration of each data transmission process.

[0043] According to the normal duration of each data transmission process, it can be understood that the normal duration is used to characterize the possibility of the data transmission process not needing to switch the communication mode. If the interference abnormal coefficient of the current data transmission process is larger, it means that the sudden interference of the current data transmission process is more accidental. Therefore, there is no need to switch the current communication mode, and the corresponding normal duration is correspondingly larger. At the same time, if the QoS variation of the current data transmission process is smaller, it means that the interference situation of the current data transmission process is relatively stable, and the interference intensity of the current communication quality has not changed significantly. This means that the current communication mode can better adapt to this stable interference environment, that is, the sustainability of the current communication mode is high, and the corresponding normal duration is large. On the contrary, if the interference abnormal coefficient of the current data transmission process is smaller, it means that the sudden interference of the current data transmission process is more similar to the history, and it may be a continuous or regular interference. This suggests that the current communication mode may be difficult to cope with long-term stability, increasing the necessity of switching communication modes, so the corresponding normal continuity is correspondingly smaller; at the same time, if the QoS variation of the current data transmission process is greater, it means that the interference situation of the current data transmission process fluctuates violently, and the interference intensity of the communication quality is changing significantly, which means that the current communication mode may not be able to adapt to this rapidly changing environment, and its sustainability is reduced, so the corresponding normal continuity is also smaller.

[0044] At this point, this embodiment quantified the QoS variability that measures the short-term fluctuations in communication quality and the interference abnormality coefficient that measures the abnormality of interference by analyzing the differences in the low-pull value distribution and the historical differences in mutation data of the QoS value, and combined the two to obtain the normal continuity, so as to judge whether the current communication mode is sustainable, avoiding the problem of wasting computing resources due to frequent switching of communication modes due to short-term interference, and helping to improve communication stability.

[0045] Step S3: Analyze the average distribution of QoS values ​​at all times during each data transmission process to obtain a high-interference data transmission process; compare the difference in the first QoS value corresponding time between each data transmission process and its previous adjacent and most recent high-interference data transmission process and the difference in all QoS values ​​to determine the first interference degree of each data transmission process; analyze the average distribution of all mutation data in all QoS values ​​in the previous adjacent and most recent high-interference data transmission process and the average distribution of all QoS values ​​to determine the second interference degree of each data transmission process, and combine the first interference degree to determine the comprehensive interference degree of each data transmission process.

[0046] Furthermore, in both urban and rural areas, some electrical equipment is often activated simultaneously during a specific time period. For example, street lights turn on in the evening and off in the morning. The activation of these power facilities also causes significant load changes on the power lines. However, due to the varying operating times of equipment in different regions, these sudden load changes are uncertain and can persist for extended periods, causing sudden increases in interference in power communications. This situation may be misjudged as a high interference abnormality coefficient, meaning that the interference is highly random, leading to the assumption that the current transmission quality is acceptable and no mode switching is necessary. Therefore, the aforementioned methods alone may not be sufficient to accurately identify this type of persistent or regular interference, and further judgment mechanisms are needed.

[0047] Specifically, within a city, lighting systems typically start at a certain interval, and the intervals between each turn-on are similar. For example, if a system starts at 7 p.m., the next day it will also start at 7 p.m. The further away a data transmission is from the last time the city's lighting system was turned on, the more likely the next data transmission will be interfered with by the city's lighting system.

[0048] When the city lighting system is turned on, the load on the power line increases, the interference to data transmission increases, and the QoS value decreases. After a period of time, the city lighting system is turned off, the load on the power line decreases, the interference to data transmission weakens, and the QoS value recovers. That is, when the city lighting system is turned on during a certain data transmission process, its QoS value will decrease and then recover after a period of time.

[0049] Based on the above analysis, this embodiment further analyzes the average distribution of QoS values ​​at all times during each data transmission process to obtain a high-interference data transmission process; compares the difference in the first QoS value corresponding time between each data transmission process and the previous adjacent and most recent high-interference data transmission process and the difference in all QoS values ​​to determine the first interference degree of each data transmission process; analyzes the average distribution of all mutation data in all QoS values ​​in the adjacent and most recent high-interference data transmission process before each data transmission process and the average distribution of all QoS values ​​to determine the second interference degree of each data transmission process, and combines the first interference degree to determine the comprehensive interference degree of each data transmission process to judge the degree of interference of the data transmission process, thereby evaluating whether to switch the communication mode. The specific process is as follows: First, to characterize the time when the urban lighting system is turned on and off, this embodiment analyzes the average distribution of QoS values ​​at all times during each data transmission process to obtain high-interference data transmission processes, which are used to screen out data transmission processes with sudden changes in communication quality. Specifically, In this embodiment, the average of the QoS values ​​at all times during each data transmission process is calculated and recorded as the QoS average; The QoS mean of all data transmission processes within a preset time period before each data transmission process is used as the input of the threshold segmentation algorithm, and the segmentation threshold is output and recorded as the QoS threshold. The data transmission process corresponding to the QoS mean greater than the QoS threshold is regarded as a high-interference data transmission process.

[0050] It should be noted that the value of the preset duration is set manually. In this embodiment, the value of the preset duration is 24 hours. In actual application, as other implementation methods, the implementer can also set it by himself based on the specific situation. This embodiment does not impose any special restrictions.

[0051] Furthermore, this embodiment determines the first interference degree of each data transmission process by comparing the difference in the first QoS value corresponding to the time between each data transmission process and the previous adjacent and most recently highest interference data transmission process, as well as the difference in all QoS values, to characterize the similarity between the current communication quality state and the communication quality state before the interference occurred in history, specifically: As a specific implementation method, in this embodiment, the time interval corresponding to the first QoS value between each data transmission process and its previous adjacent and most recently high-interference data transmission process is divided by the difference in all QoS values, and the result is recorded as the first interference degree of each data transmission process.

[0052] It should be noted that there are many methods for measuring the differences between data groups. In this embodiment, the DTW distance of all QoS values ​​between each data transmission process and its previous adjacent and nearest high-interference data transmission process is used as the difference between all QoS values ​​between each data transmission process and its previous adjacent and nearest high-interference data transmission process. Specifically, the QoS values ​​at the same time between each data transmission process and its previous adjacent and nearest high-interference data transmission process are respectively used as two variables in the DTW distance. The DTW distance of all QoS values ​​between the data transmission process and the high-interference data transmission process is calculated according to the calculation formula of the DTW distance as the difference of all QoS values. In actual application, as other implementation methods, the implementer may also adopt other methods for measuring the differences between data groups, such as Euclidean distance or Manhattan distance, in combination with specific circumstances. Regarding the selection of methods for measuring differences between data groups, this embodiment does not impose any special restrictions.

[0053] The calculation method of the DTW distance is a well-known technology, and its specific calculation process is not repeated here.

[0054] According to the first interference degree of each data transmission process, it can be understood that the first interference degree is used to characterize the possibility that the communication quality of the current data transmission is interfered with. If the time interval between the first QoS value corresponding to the current data transmission process and its previous adjacent and most recently high-interference data transmission process is larger, it means that the current data transmission process is closer to the moment of the next communication interference, indicating that the possibility of the current data transmission process being interfered with is greater, and therefore the corresponding first interference degree is greater; at the same time, if the difference in all QoS values ​​between the current data transmission process and its previous adjacent and most recently high-interference data transmission process is smaller, it means that the similarity between the current data transmission process and its previous adjacent and most recently high-interference data transmission process is greater, indicating that the possibility of the current data transmission process being interfered with is greater, and therefore the corresponding first interference degree is correspondingly larger; On the contrary, if the time interval between the first QoS value corresponding to the current data transmission process and its previous adjacent and most recent high-interference data transmission process is smaller, it means that the current data transmission process is farther away from the moment of the next communication interference, indicating that the current data transmission process is less likely to be interfered with, and therefore the corresponding first interference degree is smaller; at the same time, if the difference in all QoS values ​​between the current data transmission process and its previous adjacent and most recent high-interference data transmission process is greater, it means that the similarity between the current data transmission process and its previous adjacent and most recent high-interference data transmission process is smaller, indicating that the current data transmission process is less likely to be interfered with, and therefore the corresponding first interference degree is correspondingly smaller.

[0055] Furthermore, this embodiment determines the second interference degree of each data transmission process by analyzing the average distribution of all mutation data in all QoS values ​​and the average distribution of all QoS values ​​in the adjacent and most recent second highest interference data transmission process before each data transmission process, which is used to evaluate the magnitude of the interference intensity of the data transmission process. Specifically, As an implementation manner, in this embodiment, the expression of the second interference degree of each data transmission process is: Where, represents the second interference degree of the i-th data transmission process; represents the mean of all mutation data in all QoS values ​​in the most recent high-interference data transmission process before the i-th data transmission process; represents the mean of all QoS values ​​in the adjacent and most recent high-interference data transmission process before the i-th data transmission process; Indicates a constant greater than 0 to prevent the denominator from being 0. The value of is set artificially. The value of is 0.01. In actual application, as other implementation methods, the implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0056] According to the second interference degree of each data transmission process, it can be understood that if the proportion of the mean of all mutation data in all QoS values ​​in the adjacent and most recent high-interference data transmission process before the i-th data transmission process is greater than the proportion of the mean of all QoS values, that is, The larger the value is, the greater the peak intensity of the interference will be when the i-th data transmission process encounters interference similar to that encountered by the most recent high-interference data transmission process. Therefore, the corresponding second interference degree will be larger. On the contrary, if the proportion of the mean of all mutation data in all QoS values ​​in the adjacent and most recent high-interference data transmission process before the i-th data transmission process is smaller than that in the mean of all QoS values, that is, The smaller it is, the smaller the peak intensity of the interference will be when the i-th data transmission process encounters interference similar to that encountered by its most recent data transmission process with the second highest interference. Therefore, the corresponding second interference degree will be smaller.

[0057] Furthermore, this embodiment determines the comprehensive interference degree of each data transmission process by combining the first interference degree and the second interference degree of each data transmission process, which is used to characterize the degree of interference risk that the current data transmission process may actually face. Specifically, In this embodiment, the product of the first interference degree and the second interference degree in each data transmission process is used as the comprehensive interference degree in each data transmission process.

[0058] According to the comprehensive interference degree of each data transmission process, it can be understood that if the first interference degree and the second interference degree of the current data transmission process are greater, it means that the risk of the current data transmission being strongly interfered with is greater. Therefore, the corresponding comprehensive interference degree is correspondingly greater, and it is more necessary to switch the communication mode to improve the communication quality; conversely, if the first interference degree and the second interference degree of the current data transmission process are smaller, it means that the risk of the current data transmission being strongly interfered with is smaller. Therefore, the corresponding comprehensive interference degree is correspondingly smaller, and there is less need to switch the communication mode. It is sufficient to maintain the current communication mode to avoid frequent switching of communication modes causing waste of communication resources and degradation of communication performance.

[0059] At this point, this embodiment analyzes the QoS value distribution, calculates the first interference degree and the second interference degree, and combines the two to derive a comprehensive interference degree to assess the interference risk of data transmission, and intelligently decides whether to switch the communication mode. It effectively distinguishes between continuous interference and accidental interference, reduces misjudgment, optimizes communication resource utilization, and improves communication stability and quality.

[0060] Step S4: Based on the normal continuity and the comprehensive interference degree, the mode sustainability of each data transmission process is determined to determine whether to switch the communication mode.

[0061] Based on the normal continuity and comprehensive interference degree obtained in steps S2 and S3, respectively, in order to more comprehensively determine when to switch the communication mode, this embodiment further determines the mode sustainability of each data transmission process by integrating the normal continuity and comprehensive interference degree of each data transmission process to determine whether to switch the communication mode. Specifically, In this embodiment, first, the ratio of the normal duration of each data transmission process to the comprehensive interference degree is used as the mode sustainability of each data transmission process.

[0062] Preferably, the schematic diagram of the pattern sustainability extraction process provided in this embodiment is as follows: Figure 2 shown.

[0063] According to the mode sustainability of each data transmission process, it can be understood that the mode sustainability reflects the possibility that the power communication network can continue to work stably using the current communication mode. If the normal continuity of the current data transmission process is greater, it means that the communication quality of the current data transmission process is good, the current communication mode is very stable, and it can be safely continued to be used, and the corresponding mode sustainability is relatively large; at the same time, if the comprehensive interference degree of the current data transmission process is smaller, it means that the communication mode of the current data transmission process has a lower risk of encountering significant interference in the short term in the future, and the mode sustainability is relatively large. Therefore, there is no need to switch the current communication mode.

[0064] Furthermore, the mode sustainability of all data transmission processes within a preset time period between the current data transmission process is used as the input of the threshold segmentation algorithm, and the segmentation threshold is output and recorded as the sustainability threshold. If the mode sustainability of the current data transmission process is greater than the sustainability threshold, the communication mode of the current data transmission process is maintained; otherwise, the communication mode of the current data transmission process is switched, wherein the communication mode is the dual-mode communication mode of high-speed power line carrier communication (HPLC) and high-speed wireless radio frequency communication (HRF) mentioned in step S1 of this embodiment.

[0065] So far, this embodiment addresses the problem of frequent switching of communication modes due to transient interference in power communication networks, resulting in waste of resources and decreased communication stability. By obtaining QoS values ​​in real time, the normal continuity is calculated by analyzing the differences in low-pull value distribution and historical differences in mutation data, and the stability of the current communication mode is evaluated. At the same time, by analyzing the QoS mean distribution to identify high-interference processes, the comprehensive interference sensitivity is calculated, and the risk of future interference from continuing to use the current communication mode is evaluated. Finally, the mode sustainability is constructed by combining the normal continuity and the comprehensive interference sensitivity to decide whether to switch the communication mode, effectively distinguishing between short-term interference and continuous interference, avoiding unnecessary mode switching, saving computing resources, and improving communication stability.

[0066] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0067] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0068] The above-described embodiments are only used to illustrate the technical solutions of the present application, and not to limit them. Modifications to the technical solutions described in the aforementioned embodiments, or equivalent replacements of some of the technical features therein, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. An intelligent monitoring method for power communication network based on dual-mode communication, characterized in that: The method comprises the following steps: In the dual-mode communication power communication network, the QoS value of each data transmission process is obtained in real time; The QoS values ​​at all times during each data transmission process are used as input to the threshold segmentation algorithm, and QoS values ​​greater than the segmentation threshold are recorded as low-pull values; the QoS variability of each data transmission process is determined by analyzing the difference in the average distribution of all low-pull values ​​and the difference in the total number of low-pull values ​​between each data transmission process and the previous data transmission process; the mutation data of all QoS values ​​during each data transmission process are extracted, and the difference in the maximum mutation data, the difference in the corresponding time of the maximum mutation data, and the difference in the total number of mutation data between each data transmission process and a preset number of data transmission processes before it are compared to determine the interference abnormal coefficient of each data transmission process, and the normal duration of each data transmission process is determined in combination with the QoS variability; Analyze the average distribution of QoS values ​​at all times during each data transmission process to obtain a high-interference data transmission process; compare the difference in the first QoS value corresponding time and the difference in all QoS values ​​between each data transmission process and its previous adjacent and most recent high-interference data transmission process to determine the first interference degree of each data transmission process; analyze the average distribution of all mutation data in all QoS values ​​in the adjacent and most recent high-interference data transmission process before each data transmission process and the average distribution of all QoS values ​​to determine the second interference degree of each data transmission process, and combine the first interference degree to determine the comprehensive interference degree of each data transmission process; Based on the normal continuity and the comprehensive interference degree, the mode sustainability of each data transmission process is determined to determine whether to switch the communication mode.

2. The method for intelligent monitoring of a power communication network based on dual-mode communication according to claim 1, wherein: The method for determining the QoS variation degree of each data transmission process is as follows: Calculate the average of the low-pull values ​​at all times during each data transmission process, recorded as the low-pull value mean, and add the difference between the low-pull value mean of each data transmission process and its previous data transmission process to the difference in the total number of low-pull values ​​as the QoS change degree of each data transmission process.

3. The method for intelligent monitoring of a power communication network based on dual-mode communication according to claim 1, wherein: The method for determining the interference abnormal coefficient of each data transmission process is as follows: Calculate the cumulative sum of the maximum mutation data difference between each data transmission process and the preset number of data transmission processes before it, the mean of the difference between the maximum mutation data at the corresponding time, and the mean of the difference in the total number of mutation data, and record them as the first mutation difference, second mutation difference, and third mutation difference of each data transmission process respectively; The results of the forward fusion of the first mutation difference, the second mutation difference and the third mutation difference in each data transmission process are used as the interference abnormal coefficient of each data transmission process.

4. The method for intelligent monitoring of a power communication network based on dual-mode communication according to claim 1, wherein: The normal duration of each data transmission process is the ratio of the interference abnormal coefficient of each data transmission process to the QoS variation.

5. The method for intelligent monitoring of a power communication network based on dual-mode communication according to claim 1, wherein: The process of obtaining high-interference data transmission includes: Calculate the average QoS value at all times during each data transmission process, and record it as the QoS mean; The QoS mean of all data transmission processes within a preset time period before each data transmission process is used as the input of the threshold segmentation algorithm, and the segmentation threshold is output and recorded as the QoS threshold. The data transmission process corresponding to the QoS mean greater than the QoS threshold is regarded as a high-interference data transmission process.

6. The method for intelligent monitoring of a power communication network based on dual-mode communication according to claim 1, wherein: The first interference degree of each data transmission process is: the time interval between each data transmission process and the first QoS value corresponding moment of the previous adjacent data transmission process with the second highest interference divided by the difference of all QoS values.

7. The method for intelligent monitoring of a power communication network based on dual-mode communication according to claim 1, wherein: The expression of the second interference degree of each data transmission process is: Where, represents the second interference degree of the i-th data transmission process; represents the mean of all mutation data in all QoS values ​​in the most recent high-interference data transmission process before the i-th data transmission process; represents the mean of all QoS values ​​in the adjacent and most recent high-interference data transmission process before the i-th data transmission process; Indicates a preset constant greater than 0.

8. The method for intelligent monitoring of a power communication network based on dual-mode communication according to claim 1, wherein: The comprehensive interference degree of each data transmission process is the product of the first interference degree and the second interference degree of each data transmission process.

9. The method for intelligent monitoring of a power communication network based on dual-mode communication according to claim 1, wherein: The mode sustainability of each data transmission process is the ratio of the normal sustainability of each data transmission process to the comprehensive interference degree.

10. The method for intelligent monitoring of a power communication network based on dual-mode communication according to claim 1, wherein: The determining whether to switch the communication mode includes: The mode sustainability of all data transmission processes within the preset time length between the current data transmission process is used as the input of the threshold segmentation algorithm, and the segmentation threshold is output and recorded as the sustainability threshold. If the mode sustainability of the current data transmission process is greater than the sustainability threshold, the communication mode of the current data transmission process is maintained. Otherwise, the communication mode of the current data transmission process is switched.

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