Communication control method based on power carrier dual-mode communication module

Abstract

The invention relates to the technical field of power line carrier communication control, in particular to a communication control method based on a power line carrier dual-mode communication module, which comprises the following steps of: S1, constructing a channel quality dynamic scoring model and outputting a channel quality score by collecting data packets of HPLC (High Performance Liquid Chromatography) and HRF (High Frequency Radio Frequency) carrier channels in real time; s2, establishing a dual-mode communication time period dynamic decision algorithm, setting a dynamic threshold value at the same time, and automatically triggering a dual-mode communication time period forward mechanism according to the channel quality score; when the method is used, the dual-mode verification strategy is intelligently adjusted according to the real-time communication state, the verification frequency and duration can be conveniently improved in the serious interference time period, the overall communication reliability and the data accuracy can be improved, the adoption of the dual-mode verification strategy in the fixed time period is avoided, and meanwhile, the verification efficiency is improved. When the channel quality is good, the communication burden is reduced, the communication efficiency is improved, and the purpose of considering both stability and high efficiency is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of power line carrier communication control, and in particular to a communication control method based on a power line carrier dual-mode communication module. Background Art

[0002] A power line carrier dual-mode communication module is a device that combines power line carrier communication (PLC) with another communication mode (such as wireless communication technologies such as RF, ZigBee, and Wi-Fi). This dual-mode design aims to overcome the limitations of a single communication method and provide a more stable and reliable communication link. It has widespread application in smart grids, the Internet of Things (IoT), smart homes, and other fields.

[0003] The patent publication number is CN117614895A, which states in its specification that "the present invention discloses a communication control method and system based on a dual-mode communication module, which relates to the field of power carrier communication technology and adopts a dual-mode communication module for power data communication. The dual-mode communication module includes an HPLC broadband carrier module, an HRF micro-power wireless module and a chip-based communication control module; the present invention mainly uses the high-speed carrier communication of the HPLC broadband carrier module and the high-speed wireless communication of the HRF micro-power wireless module as a supplement; during the dual-mode simultaneous communication period, the HPLC broadband carrier module and the HRF micro-power wireless module both work, and the remote server calculates the packet loss rate of the HPLC broadband carrier module. If the packet loss rate is greater than the set packet loss rate threshold, Output carrier communication abnormality results, alarm to remind staff to carry out timely maintenance, use HRF micro-power wireless module to temporarily replace HPLC broadband carrier module to collect power operation data, greatly improving the reliability of power data collection. "Although the above technology improves the reliability and anti-interference capability of power data collection through dual-mode collaboration, dynamic verification and intelligent switching, it is particularly suitable for data backhaul scenarios such as smart meters in complex power grid environments. However, the existing technology generally adopts a fixed-time dual-mode verification mechanism (such as uniformly set during the low-load period in the early morning), resulting in poor dynamic adaptability and serious energy efficiency waste. At the same time, the existing dual-mode verification method has the shortcomings of lack of spatiotemporal correlation and multi-modal data fragmentation in the abnormality tracing link.

[0004] In summary, developing a communication control method based on a power line carrier dual-mode communication module is still a key issue that needs to be urgently addressed in the field of power line carrier communication control technology. Summary of the Invention

[0005] The purpose of the present invention is to solve the problems in the prior art. Although the above-mentioned technology achieves the effect of improving the reliability and anti-interference ability of power data collection through dual-mode collaboration, dynamic verification and intelligent switching, and is particularly suitable for data backhaul scenarios of smart meters and other equipment in complex power grid environments, the prior art generally adopts a fixed-time dual-mode verification mechanism (such as uniformly setting it in the low-load period in the early morning), which leads to the defects of poor dynamic adaptability and serious energy efficiency waste. At the same time, the existing dual-mode verification method has the problems of lack of spatiotemporal correlation and multi-modal data fragmentation in the abnormal tracing link.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The present invention provides a communication control method based on a power line carrier dual-mode communication module, comprising the following steps: S1, constructing a channel quality dynamic scoring model by real-time acquisition of data packets of HPLC and HRF carrier channels, and outputting a channel quality score;

[0008] S2. Establish a dynamic decision algorithm for the dual-mode communication period and set a dynamic threshold, and automatically trigger the dual-mode communication period forward shift mechanism based on the channel quality score;

[0009] S3, adding a four-dimensional space-time identification code to the HPLC data packet, and embedding wireless signal strength grid coordinates into the HRF data packet;

[0010] S4. Reconstructing the power line channel propagation model on the server side through the topological mapping relationship of the four-dimensional space-time identification code to identify abnormal packet loss within 300 meters of the transformer outlet;

[0011] S5. When the HPLC packet loss rate exceeds the set adaptive threshold, the simultaneous spatial coordinate HRF data is called for local compensation and the interference source is located to the tower level accuracy.

[0012] Furthermore, in step S1, by collecting data packets of HPLC and HRF carrier channels in real time, a channel quality dynamic scoring model is constructed, and the method for outputting the channel quality score is as follows:

[0013] The data packet includes noise interference intensity, signal attenuation rate and historical packet loss rate data. The channel quality dynamic scoring model is constructed based on instantaneous interference pulse density, frequency band occupancy and signal-to-noise ratio fluctuation coefficient, and is expressed as follows:

[0014] Where Q(t) is the channel quality score at time t, Z is a constant, express Add 1 and take the natural logarithm, represents the square of x1, represents the square of x3, represents the square of x2, exp[·] represents the natural exponential function, W1, W2, and W3 are weight coefficients, x1 is the instantaneous interference pulse density, x2 is the frequency band occupancy, and x3 is the signal-to-noise ratio fluctuation coefficient. The scoring dimensions of the dynamic channel quality scoring model include instantaneous interference pulse density, frequency band occupancy, and signal-to-noise ratio fluctuation coefficient, and the output channel quality score Q(t)∈(0,1].

[0015] Furthermore, in step S2, a dynamic decision algorithm for the dual-mode communication period is established and a dynamic threshold is set. According to the channel quality score, the method for automatically triggering the dual-mode communication period forward shifting mechanism is as follows:

[0016] The dynamic decision algorithm for establishing a dual-mode communication period is set to a fixed time period ΔT for the communication period. A score is sampled once at the end of each period to form a discrete score sequence, which is expressed as: Among them E k represents the set of discrete scoring sequences, Q(k·ΔT) represents the score at time point k·ΔT, ΔT is the time interval, k is the current cycle number, and N is the total length of the discrete scoring sequence. represents the scoring window with a scoring sequence length of 3 for the current period k and its two previous periods (k-1, k-2), E k-2 ,E k-1 ,E k , respectively represent the scores of cycles (k-1, k-2, k), It is a low score judgment function that judges whether the score is low based on the scores of three consecutive cycles. It represents the maximum value of the scores of the current cycle k and the two cycles before it. 1 means that the low score judgment is true (i.e., the score is low), and 0 means that the low score judgment is false (i.e., the score is not low).

[0017] Furthermore, in step S2, a dynamic decision algorithm for the dual-mode communication period is established and a dynamic threshold is set. According to the channel quality score, the method for automatically triggering the dual-mode communication period forward shifting mechanism is as follows:

[0018] The dynamic threshold sets the communication time period of the whole day to [0, 24] hours, which is divided into M equal-width windows r i =[t i ,t i+1 ], calculate the average interference density and score volatility of each window, and express it as: in is the average interference density of the i-th window, R imp (t j ) is the interference density at time t j The collected interference density data, n irepresents the number of sampling points in the i-th time window, t j is the jth moment, is the rating volatility of the ith window, E(t j ) is the signal strength at time t at time j j The ratings collected, is the average score of the i-th window, and the interference index is calculated by weighting the two indicators. The expression formula is: Where β(i) is the channel quality score of the i-th element, and α1 is the weight coefficient 1 used to adjust Contribution to the channel quality score, is the average interference density of the i-th window, and α2 is the weight coefficient 2 used to adjust Contribution to the channel quality score, is the score volatility of the i-th window. The high-interference window is selected by the maximum value index. The dual-mode communication period forward shift mechanism is automatically triggered. When the score is low, the dual-mode verification period is adaptively adjusted to the current high-interference period and extended to 2 hours. When the score is high or low, the pulsed dual-mode verification mode is started, and 5% of the time windows are randomly selected every day for data comparison.

[0019] Furthermore, in step S3, a method of adding a four-dimensional spatiotemporal identification code to the HPLC data packet and embedding wireless signal strength grid coordinates into the HRF data packet is as follows:

[0020] The four-dimensional space-time identification code includes the acquisition time stamp + power line topology location code + phase angle information + substation level code, and the HPLC data packet collected at the time t is set. Add four-dimensional space-time identification code Θ HPLC = <τ,Λ(x,y),δ,S>, where

[0021] is the set of HPLC data packets at time t, q1,q2,...,q n is the data element in the data packet at that moment, n is the number of elements in the data packet, and each q i Represents a data item, Θ HPLC is a four-dimensional space-time identification code, τ is a timestamp, Λ(x,y) is a channel quality function representing the channel quality at spatial positions x and y, δ is a phase angle, S is a hash value, and a standardized UTC millisecond timestamp τ is collected. The power line topology location code Where Λ(x,y) is the channel quality function representing the channel quality at spatial positions x and y, χ1 is the weight coefficient 1 used to adjust the size of the contribution of I(x), χ2 is the weight coefficient 2 used to adjust the contribution of V(y) in the total channel quality, I(x) represents the horizontal component related to x, V(y) represents the vertical component related to y, and the phase angle information Where δ is the phase angle, and atn is the inverse tangent function used to calculate an angle. Respectively represent the values of the in-phase O component and the orthogonal A component of the signal at time t, P O (t) is a component in the signal used to represent the amplitude information of the signal, P A (t) is another component in the signal used to represent the part orthogonal to the in-phase component, k represents the phase correction by adding an integer multiple of 2π, k∈{0,1,2} is the value range of the integer k, and the substation level code S=Hash CRC-16 (StationID 父级 ||StationID 本级 ), where S is the hash value, Hash CRC-16 It is CRC-16 hash algorithm (Cyclic Redundancy Check, a common error detection code used to verify data integrity), StationID 父级 Is the ID of the parent site, StationID 本级 is the ID of the current site, and || is a connector that concatenates the parent site ID and the current site ID. The final structure of the HPLC data package is in represents the HPLC signal intensity corresponding to time t.

[0022] Furthermore, in step S3, the method for embedding the wireless signal strength grid coordinates for the HRF data packet into the four-dimensional spatiotemporal identification code for the HPLC data packet is as follows:

[0023] Set HRF data package Each of these a i Corresponding to a signal measurement point The signal measurement point corresponds to the grid coordinate identifier a i , let the actual measured RSSI value be RSSI(x,y,t), and construct the signal field equipotential function: Where Γ(x,y,t) represents the flow change of signal strength at point (x,y) and time t, is a vector operator, ε is the conductivity of the medium, is the gradient of the signal strength (RSSI) relative to the spatial coordinates (x, y) and time t, RSSI(x, y, t) is the received signal strength indicator (RSSI) indicating the signal strength at the position (x, y) and time t, discretizing the signal field equipotential function into a two-dimensional grid F m×n ,make: Each a i The attached signal strength is marked as: where φi Represents the ratio of the signal strength of node i at time t to that of all nodes in the entire network, RSSI i (t) is the received signal strength indicator of node i at time t, is the sum of the total signal strength of all m nodes at time t, a i is the position coordinate of node i, is the temporal information of node i at time t, and the final structure of the HRF data packet is in represents the set of data packets containing all nodes i.

[0024] Furthermore, in step S4, the power line channel propagation model is reconstructed on the server side through the topological mapping relationship of the four-dimensional space-time identification code, and the method for identifying abnormal packet loss within 300 meters of the transformer outlet is as follows:

[0025] The topological mapping relationship of the four-dimensional space-time identification code and the power line node set are: Each G i =(Λ i ,δ i ,S i ), set any two nodes G i ,G j The effective communication link function is: Among them H ij (t) is the effective communication link function between node i and node j at time t, is the Gaussian physical proximity, γ(δ i ,δ j ) is the phase matching degree, η(S i ,S j ) indicates whether it is in the same substation subnet structure, the power line channel propagation model is rebuilt on the server side, and all valid links H in the topology diagram are ij , construct the propagation channel response function as: Among them J ij (f,t) is the frequency domain response function of the channel from node i to node j at frequency f and time t, is the lth path amplitude, is the propagation delay, λ(f) is the frequency-dependent loss coefficient, It is made by i ,Λ j The Euclidean distance obtained by topological mapping, is the propagation speed, is the sum of all L′ multipath signal paths, represents the frequency-dependent phase delay of the lth path, The signal transmission distance The frequency-dependent attenuation term on .

[0026] Furthermore, in step S4, the power line channel propagation model is reconstructed on the server side through the topological mapping relationship of the four-dimensional space-time identification code, and the method for identifying abnormal packet loss within 300 meters of the transformer outlet is as follows:

[0027] The identification of abnormal packet loss within 300 meters of the transformer outlet, for each transformer main node G c Define its 300-meter physical neighborhood as: in is the neighborhood node set with transformer c as the center and a radius of 300 meters. Node i is a member of the node set G. i is the spatial position coordinate of node i, Λ c is the spatial position coordinate of transformer c, ||Λ i -Λ c || is the distance between node i and transformer Λ c The spatial distance between them is less than 300 meters, which means it is within the radius of 300 meters from the transformer outlet. is the packet loss rate on link ij at time t, expressed as: in is the packet loss probability from node i to node j at time t, exp(·) is an exponential function used to map channel energy to a probability value. The larger the value, the lower the probability of packet loss. min ,f max are the minimum and maximum frequencies used by the communication system, is a normalizing constant, f is the frequency, |J ij (f,t)| 2 is the square of the channel frequency domain response function.

[0028] Furthermore, in step S5, when the HPLC packet loss rate exceeds the set adaptive threshold, the method of calling the simultaneous spatial coordinate HRF data for local compensation and locating the interference source to the tower-level accuracy is as follows:

[0029] The adaptive threshold modeling, setting node G i The HPLC packet loss rate at time t is: The variable threshold strategy based on empirical risk minimization is adopted, and the expression formula is: where θ i (t) is the adaptive threshold of packet loss rate of node i at time t, is the historical average packet loss rate of node i at time t, σ i (t) is the standard deviation of the packet loss rate of node i at time t, ρ is the confidence weight coefficient, is the rate-of-change adjustment coefficient, is the packet loss rate change of node i at time t, and the grid coordinate π is embedded in the HRF data packet. i (t) = {x i ,y i ,z i ,τ i}, construct a dual-mode spatiotemporal fusion kernel function for precise compensation, expressed as: in is the dual-mode spatiotemporal fusion kernel function value between nodes i and j, exp(·) is the exponential function output ranging from 0 to 1, is the square of the three-dimensional space coordinate distance between node i and node j, is the square of the spatial scale parameter, is the square of the time scale parameter.

[0030] Furthermore, in step S5, when the HPLC packet loss rate exceeds the set adaptive threshold, the method of calling the simultaneous spatial coordinate HRF data for local compensation and locating the interference source to the tower-level accuracy is as follows:

[0031] The interference source is located to the tower level with accuracy. This is based on the graph neural network anomaly tracing model, which performs positioning by comparing the spatiotemporal offset characteristics of the dual-mode data packets. The graph neural network anomaly tracing model defines a heterogeneous graph. in is the entire heterogeneous graph, is a collection of nodes, Is an edge set, including HPLC and HRF observation points, each node

[0032]

[0033] Embedding vector Expression formula: where p i is the eigenvector of the i-th node, is the HPLC channel quality score corresponding to the i-th node, is the wireless signal strength of the i-th HRF observation point, is the power phase angle information of node i, is the historical packet loss statistics covariance matrix, is the spatial coordinate vector of node i, τ i is the timestamp of node i, is the edge weight between node i and node j, is the square of the Euclidean distance between node i and node j in space, ζ is the normalization parameter of spatial distance, τ0 is the normalization parameter of time window, and the graph neural network anomaly tracing model uses graph convolutional neural network to realize information propagation. The last layer of the network outputs the interference probability of each node as follows: in The probability that the i-th node is judged as "abnormal" is between 0 and 1, and Sigmoid(·) is the output value range of the activation function. is the output weight matrix, It is the first The feature vector of the i-th node output by the layer, the spatiotemporal offset feature, defines the dual-mode spatiotemporal offset degree, for each tower subordinate node set Define the anomaly score and express the formula: exist It is determined that there is an interference source on the tower, and the interference source is output: where Ψ 干扰 is the set of towers identified as interference sources, g represents a specific tower number, is the abnormal score value of the g-th tower, θ g is the abnormality judgment threshold corresponding to the g-th tower.

[0034] Beneficial effects

[0035] Compared with the known public technology, the technical solution provided by the present invention has the following advantages:

[0036] Beneficial effects:

[0037] When in use, the present invention intelligently adjusts the dual-mode verification strategy according to the real-time communication status, which is convenient for increasing the verification frequency and duration during periods of severe interference, is beneficial to improving overall communication reliability and data accuracy, and avoids the use of a fixed-period dual-mode verification strategy. At the same time, when the channel quality is good, the communication burden is reduced, the communication efficiency is improved, and the purpose of balancing stability and high efficiency is achieved.

[0038] When in use, the present invention calculates the signal strength ratio of each node at a specific time point, as well as its position and temporal information, to facilitate accurate description of the spatial distribution state of the wireless signal, which is conducive to subsequent rapid tracing and fault analysis, greatly shortening the troubleshooting cycle, and ensuring the correct archiving and reliable traceability of key data even in an environment with large data volume and dense nodes. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of a communication control method based on a power line carrier dual-mode communication module of the present invention. DETAILED DESCRIPTION

[0040] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0041] It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. It should be understood that the numbers used in this manner are interchangeable where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to these processes, methods, products, or apparatuses.

[0042] The present invention is described in further detail below with reference to the accompanying drawings:

[0043] Example:

[0044] like Figure 1 As shown, the present invention provides a communication control method based on a power line carrier dual-mode communication module, comprising the following steps: S1, constructing a channel quality dynamic scoring model by real-time acquisition of data packets of HPLC and HRF carrier channels, and outputting a channel quality score;

[0045] Furthermore, in step S1, by collecting data packets of HPLC and HRF carrier channels in real time, a channel quality dynamic scoring model is constructed, and the method for outputting the channel quality score is as follows:

[0046] The data packet includes noise interference intensity, signal attenuation rate and historical packet loss rate data. The channel quality dynamic scoring model is constructed based on instantaneous interference pulse density, frequency band occupancy and signal-to-noise ratio fluctuation coefficient, and is expressed as follows:

[0047] Where Q(t) is the channel quality score at time t, Z is a constant, express Add 1 and take the natural logarithm, represents the square of x1, represents the square of x3, represents the square of x2, exp[·] represents the natural exponential function, W1, W2, and W3 are weight coefficients, x1 is the instantaneous interference pulse density, x2 is the frequency band occupancy, and x3 is the signal-to-noise ratio fluctuation coefficient. The scoring dimensions of the dynamic channel quality scoring model include instantaneous interference pulse density, frequency band occupancy, and signal-to-noise ratio fluctuation coefficient, and the output channel quality score Q(t)∈(0,1].

[0048] In this embodiment, a dynamic channel quality scoring method is established by real-time collection of data packet information during HPLC (high-frequency narrowband carrier) and HRF (high-frequency wireless) channel transmission. The collected data packets mainly include key communication quality indicators such as noise interference intensity, signal attenuation rate, and historical packet loss rate. This facilitates real-time and accurate evaluation of communication quality in complex and dynamically changing power line and wireless channel environments, greatly improving the reliability and stability of data transmission. At the same time, by introducing multi-dimensional dynamic parameter modeling, different types of channel degradation causes such as short-term noise and frequency band congestion can be better distinguished, which is helpful for subsequent intelligent scheduling and fault tracing.

[0049] S2. Establish a dynamic decision algorithm for the dual-mode communication period and set a dynamic threshold, and automatically trigger the dual-mode communication period forward shift mechanism based on the channel quality score;

[0050] Furthermore, in step S2, a dynamic decision algorithm for the dual-mode communication period is established and a dynamic threshold is set. According to the channel quality score, the method for automatically triggering the dual-mode communication period forward shifting mechanism is as follows:

[0051] The dynamic decision algorithm for establishing a dual-mode communication period is set to a fixed time period ΔT for the communication period. A score is sampled once at the end of each period to form a discrete score sequence, which is expressed as: Among them E k represents the set of discrete scoring sequences, Q(k·ΔT) represents the score at time point k·ΔT, ΔT is the time interval, k is the current cycle number, and N is the total length of the discrete scoring sequence. represents the scoring window with a scoring sequence length of 3 for the current period k and its two previous periods (k-1, k-2), E k-2 ,E k-1 ,E k , respectively represent the scores of cycles (k-1, k-2, k), It is a low score judgment function that judges whether the score is low based on the scores of three consecutive cycles. It represents the maximum value of the scores of the current cycle k and the two cycles before it. 1 means that the low score judgment is true (i.e., the score is low), and 0 means that the low score judgment is false (i.e., the score is not low).

[0052] Furthermore, in step S2, a dynamic decision algorithm for the dual-mode communication period is established and a dynamic threshold is set. According to the channel quality score, the method for automatically triggering the dual-mode communication period forward shifting mechanism is as follows:

[0053] The dynamic threshold sets the communication time period of the whole day to [0, 24] hours, which is divided into M equal-width windows r i =[t i ,t i+1 ], calculate the average interference density and score volatility of each window, and express it as: in is the average interference density of the i-th window, R imp (t j ) is the interference density at time t j The collected interference density data, n i represents the number of sampling points in the i-th time window, t j is the jth moment, is the rating volatility of the ith window, E(t j ) is the signal strength at time t at time j j The ratings collected, is the average score of the i-th window, and the interference index is calculated by weighting the two indicators. The expression formula is: Where β(i) is the channel quality score of the i-th element, and α1 is the weight coefficient 1 used to adjust Contribution to the channel quality score, is the average interference density of the i-th window, and α2 is the weight coefficient 2 used to adjust Contribution to the channel quality score, is the score volatility of the i-th window. The high-interference window is selected by the maximum value index. The dual-mode communication period forward shift mechanism is automatically triggered. When the score is low, the dual-mode verification period is adaptively adjusted to the current high-interference period and extended to 2 hours. When the score is high or low, the pulsed dual-mode verification mode is started, and 5% of the time windows are randomly selected every day for data comparison.

[0054] In this embodiment, the communication process is divided into fixed-length cycles, and the channel score is sampled at the end of each cycle to form a discrete score sequence. The score changes over three consecutive cycles (i.e., a small window) are used to determine whether continuous low-quality communication (i.e., three consecutive scores below the preset threshold of 60 / 100) have occurred. If continuous low scores occur, the verification period of dual-mode communication is dynamically adjusted to the time period with high interference, and the verification time is automatically extended to 2 hours. If the channel score is high (i.e., score ≥85 / 100), the pulse verification mode is activated, and 5% of the time period is randomly selected every day for rapid data verification. At the same time, in order to accurately identify the time period with high interference, the system further divides the communication time of the whole day into several equal-width time windows, and calculates the average interference density and score volatility of each window. The interference index is synthesized by weighting the interference density and score volatility, and the time window with the highest interference index is selected as the high-interference interval. This facilitates the accurate advancement of dual-mode verification to the time period with the most serious problems. The dual-mode verification strategy can be intelligently adjusted according to the real-time communication status, and the verification frequency and duration can be increased during the period with severe interference to ensure the overall communication reliability and data accuracy of the system. At the same time, when the channel quality is good, the system burden is reduced, the communication efficiency is improved, and the goal of balancing stability and efficiency is achieved.

[0055] S3, adding a four-dimensional space-time identification code to the HPLC data packet, and embedding wireless signal strength grid coordinates into the HRF data packet;

[0056] Furthermore, in step S3, a method of adding a four-dimensional spatiotemporal identification code to the HPLC data packet and embedding wireless signal strength grid coordinates into the HRF data packet is as follows:

[0057] The four-dimensional space-time identification code includes the acquisition time stamp + power line topology location code + phase angle information + substation level code, and the HPLC data packet collected at the time t is set. Add four-dimensional space-time identification code Θ HPLC = <τ,Λ(x,y),δ,S>, where is the set of HPLC data packets at time t, q1,q2,...,q n is the data element in the data packet at that moment, n is the number of elements in the data packet, and each q i Represents a data item, Θ HPLC is a four-dimensional space-time identification code, τ is a timestamp, Λ(x,y) is a channel quality function representing the channel quality at spatial positions x and y, δ is a phase angle, S is a hash value, and a standardized UTC millisecond timestamp τ is collected. The power line topology location code Where Λ(x,y) is the channel quality function representing the channel quality at spatial positions x and y, χ1 is the weight coefficient 1 used to adjust the size of the contribution of I(x), χ2 is the weight coefficient 2 used to adjust the contribution of V(y) in the total channel quality, I(x) represents the horizontal component related to x, V(y) represents the vertical component related to y, and the phase angle information Where δ is the phase angle, and atn is the inverse tangent function used to calculate an angle. Respectively represent the values of the in-phase O component and the orthogonal A component of the signal at time t, P O (t) is a component in the signal used to represent the amplitude information of the signal, P A (t) is another component in the signal used to represent the part orthogonal to the in-phase component, k represents the phase correction by adding an integer multiple of 2π, k∈{0,1,2} is the value range of the integer k, and the substation level code S=Hash CRC-16 (StationID 父级 ||StationID 本级 ), where S is the hash value, Hash CRC-16 It is CRC-16 hash algorithm (Cyclic Redundancy Check, a common error detection code used to verify data integrity), StationID 父级 Is the ID of the parent site, StationID 本级 is the ID of the current site, and || is a connector that concatenates the parent site ID and the current site ID. The final structure of the HPLC data package is in represents the HPLC signal intensity corresponding to time t.

[0058] Furthermore, in step S3, the method for embedding the wireless signal strength grid coordinates for the HRF data packet into the four-dimensional spatiotemporal identification code for the HPLC data packet is as follows:

[0059] Set HRF data package Each of these a i Corresponding to a signal measurement point The signal measurement point corresponds to the grid coordinate identifier a i , let the actual measured RSSI value be RSSI(x,y,t), and construct the signal field equipotential function: Where Γ(x,y,t) represents the flow change of signal strength at point (x,y) and time t, is a vector operator, ε is the conductivity of the medium, is the gradient of the signal strength (RSSI) relative to the spatial coordinates (x, y) and time t, RSSI(x, y, t) is the received signal strength indicator (RSSI) indicating the signal strength at the position (x, y) and time t, discretizing the signal field equipotential function into a two-dimensional grid F m×n ,make: Each a i The attached signal strength is marked as: where φ i Represents the ratio of the signal strength of node i at time t to that of all nodes in the entire network, RSSI i (t) is the received signal strength indicator of node i at time t, is the sum of the total signal strength of all m nodes at time t, a i is the position coordinate of node i, is the temporal information of node i at time t, and the final structure of the HRF data packet is in represents the set of data packets containing all nodes i.

[0060] In this embodiment, a four-dimensional space-time identification code is added to the HPLC (power line communication) data packet, including: collection timestamp, power line topology location code, phase angle information and substation level code. For the HRF (high frequency wireless) data packet, after RSSI (received signal strength indication) is collected at each wireless measurement point, it is divided into a two-dimensional grid according to the actual position, and a signal field equipotential function is constructed to discretize the RSSI signal of each measurement point to the corresponding grid coordinate. By calculating the signal strength ratio of each node at a specific time point, as well as its position and temporal information, it is convenient to accurately describe the spatial distribution state of the wireless signal, which is conducive to subsequent rapid tracing and fault analysis, greatly shortening the troubleshooting cycle, and ensuring the correct archiving and reliable traceability of key data even in an environment with large data volume and dense nodes.

[0061] S4. Reconstructing the power line channel propagation model on the server side through the topological mapping relationship of the four-dimensional space-time identification code to identify abnormal packet loss within 300 meters of the transformer outlet;

[0062] Furthermore, in step S4, the power line channel propagation model is reconstructed on the server side through the topological mapping relationship of the four-dimensional space-time identification code, and the method for identifying abnormal packet loss within 300 meters of the transformer outlet is as follows:

[0063] The topological mapping relationship of the four-dimensional space-time identification code and the power line node set are: Each G i =(Λ i ,δ i ,S i ), set any two nodes Gi ,G j The effective communication link function is: Among them H ij (t) is the effective communication link function between node i and node j at time t, is the Gaussian physical proximity, γ(δ i ,δ j ) is the phase matching degree, η(S i ,S j ) indicates whether it is in the same substation subnet structure, the power line channel propagation model is rebuilt on the server side, and all valid links H in the topology diagram are ij , construct the propagation channel response function as: Among them J ij (f,t) is the frequency domain response function of the channel from node i to node j at frequency f and time t, is the lth path amplitude, is the propagation delay, λ(f) is the frequency-dependent loss coefficient, It is made by i ,Λ j The Euclidean distance obtained by topological mapping, is the propagation speed, is the sum of all L′ multipath signal paths, represents the frequency-dependent phase delay of the lth path, The signal transmission distance The frequency-dependent attenuation term on .

[0064] Furthermore, in step S4, the power line channel propagation model is reconstructed on the server side through the topological mapping relationship of the four-dimensional space-time identification code, and the method for identifying abnormal packet loss within 300 meters of the transformer outlet is as follows:

[0065] The identification of abnormal packet loss within 300 meters of the transformer outlet, for each transformer main node G c Define its 300-meter physical neighborhood as: in is the neighborhood node set with transformer c as the center and a radius of 300 meters. Node i is a member of the node set G. i is the spatial position coordinate of node i, Λ c is the spatial position coordinate of transformer c, ||Λ i -Λ c || is the distance between node i and transformer Λ c The spatial distance between them is less than 300 meters, which means it is within the radius of 300 meters from the transformer outlet. is the packet loss rate on link ij at time t, expressed as: in is the packet loss probability from node i to node j at time t, exp(·) is an exponential function used to map channel energy to a probability value. The larger the value, the lower the probability of packet loss. min ,f max are the minimum and maximum frequencies used by the communication system, is a normalizing constant, f is the frequency, |J ij (f,t)| 2 is the square of the channel frequency domain response function.

[0066] In this embodiment, the actual topology of the power line network is restored on the server side by utilizing the four-dimensional spatiotemporal identifier (time, location, phase, and hierarchy information) previously added to each communication data packet. A valid communication link is set between any two nodes, and the feasibility of the link is defined by considering factors such as geographic proximity, phase synchronization, and whether they belong to the same substation subnet. On this basis, a propagation model of the power line channel is constructed for each pair of nodes. This propagation model takes into account realistic factors such as signal multipath effects (delay and attenuation caused by different propagation paths), distance attenuation, and frequency-dependent losses. A physical neighborhood with a radius of 300 meters is set for each transformer outlet, and all nearby communication nodes are included in the monitoring range. By calculating the channel energy loss on each node link and further calculating the link packet loss rate, this method not only reconstructs the detailed propagation path of the entire distribution network, but also can proactively detect potential communication anomalies or power quality issues (such as cable aging, local short circuits, severe interference, etc.) within 300 meters of the transformer and locate them at the specific location or node, significantly improving operation and maintenance efficiency.

[0067] S5. When the HPLC packet loss rate exceeds the set adaptive threshold, the simultaneous spatial coordinate HRF data is called for local compensation and the interference source is located to the tower level accuracy;

[0068] Furthermore, in step S5, when the HPLC packet loss rate exceeds the set adaptive threshold, the method of calling the simultaneous spatial coordinate HRF data for local compensation and locating the interference source to the tower-level accuracy is as follows:

[0069] The adaptive threshold modeling, setting node G i The HPLC packet loss rate at time t is:

[0070] The variable threshold strategy based on empirical risk minimization is adopted, and the expression formula is: where θ i (t) is the adaptive threshold of packet loss rate of node i at time t, is the historical average packet loss rate of node i at time t, σ i (t) is the standard deviation of the packet loss rate of node i at time t, ρ is the confidence weight coefficient, is the rate-of-change adjustment coefficient, is the packet loss rate change of node i at time t, and the grid coordinate π is embedded in the HRF data packet. i (t) = {x i ,y i ,z i ,τ i}, construct a dual-mode spatiotemporal fusion kernel function for precise compensation, expressed as: in is the dual-mode spatiotemporal fusion kernel function value between nodes i and j, exp(·) is the exponential function output ranging from 0 to 1, is the square of the three-dimensional space coordinate distance between node i and node j, is the square of the spatial scale parameter, is the square of the time scale parameter.

[0071] Furthermore, in step S5, when the HPLC packet loss rate exceeds the set adaptive threshold, the method of calling the simultaneous spatial coordinate HRF data for local compensation and locating the interference source to the tower-level accuracy is as follows:

[0072] The interference source is located to the tower level with accuracy. This is based on the graph neural network anomaly tracing model, which performs positioning by comparing the spatiotemporal offset characteristics of the dual-mode data packets. The graph neural network anomaly tracing model defines a heterogeneous graph. in is the entire heterogeneous graph, is a collection of nodes, Is an edge set, including HPLC and HRF observation points, each node Embedding vector Expression formula: where p i is the eigenvector of the i-th node, is the HPLC channel quality score corresponding to the i-th node, is the wireless signal strength of the i-th HRF observation point, is the power phase angle information of node i, is the historical packet loss statistics covariance matrix, is the spatial coordinate vector of node i, τ i is the timestamp of node i, is the edge weight between node i and node j, is the square of the Euclidean distance between node i and node j in space, ζ is the normalization parameter of spatial distance, τ0 is the normalization parameter of time window, and the graph neural network anomaly tracing model uses graph convolutional neural network to realize information propagation. The last layer of the network outputs the interference probability of each node as follows: in The probability that the i-th node is judged as "abnormal" is between 0 and 1, and Sigmoid(·) is the output value range of the activation function. is the output weight matrix, It is the first The feature vector of the i-th node output by the layer, the spatiotemporal offset feature, defines the dual-mode spatiotemporal offset degree, for each tower subordinate node set Define the anomaly score and express the formula: exist It is determined that there is an interference source on the tower, and the interference source is output: where Ψ 干扰 is the set of towers identified as interference sources, g represents a specific tower number, is the abnormal score value of the g-th tower, θ g is the abnormality judgment threshold corresponding to the g-th tower.

[0073] In this embodiment, a dynamically changing packet loss rate threshold is set for each communication node. This threshold is not fixed but is adjusted in real time based on the node's own historical packet loss average, standard deviation, packet loss change rate, and other indicators. This adheres to the principle of empirical risk minimization, thereby more accurately adapting to fluctuations in the actual communication environment. This method also defines a dual-mode spatiotemporal offset index, focusing on the set of nodes under each tower. If the anomaly score of a tower exceeds a preset threshold, it is determined that there is an interference source near the tower. In this way, this method can accurately locate communication anomalies to specific tower numbers, achieving fine-grained traceability, which is conducive to improving network stability. Spatial fusion using HRF wireless measurement data improves the accuracy and practicality of packet loss compensation.

[0074] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A communication control method based on a power line carrier dual-mode communication module, characterized in that: The following steps are involved: S1, by real-time collection of HPLC and HRF carrier channel data packets, build a channel quality dynamic scoring model and output channel quality scores; S2. Establish a dynamic decision algorithm for the dual-mode communication period and set a dynamic threshold, and automatically trigger the dual-mode communication period forward shift mechanism based on the channel quality score; S3, adding a four-dimensional space-time identification code to the HPLC data packet, and embedding wireless signal strength grid coordinates into the HRF data packet; S4. Reconstructing the power line channel propagation model on the server side through the topological mapping relationship of the four-dimensional space-time identification code to identify abnormal packet loss within 300 meters of the transformer outlet; S5. When the HPLC packet loss rate exceeds the set adaptive threshold, the simultaneous spatial coordinate HRF data is called for local compensation and the interference source is located to the tower level accuracy.

2. A communication control method based on a power line carrier dual-mode communication module according to claim 1, characterized in that: In step S1, by collecting data packets of HPLC and HRF carrier channels in real time, a channel quality dynamic scoring model is constructed, and the method for outputting the channel quality score is as follows: The data packet includes noise interference intensity, signal attenuation rate and historical packet loss rate data. The channel quality dynamic scoring model is constructed based on instantaneous interference pulse density, frequency band occupancy and signal-to-noise ratio fluctuation coefficient, and is expressed as follows: Where Q(t) is the channel quality score at time t, Z is a constant, express Add 1 and take the natural logarithm, represents the square of x1, represents the square of x3, represents the square of x2, exp[·] represents the natural exponential function, W1, W2, and W3 are weight coefficients, x1 is the instantaneous interference pulse density, x2 is the frequency band occupancy, and x3 is the signal-to-noise ratio fluctuation coefficient. The scoring dimensions of the dynamic channel quality scoring model include instantaneous interference pulse density, frequency band occupancy, and signal-to-noise ratio fluctuation coefficient, and the output channel quality score Q(t)∈(0,1].

3. A communication control method based on a power line carrier dual-mode communication module according to claim 2, characterized in that: In step S2, a dynamic decision algorithm for the dual-mode communication period is established and a dynamic threshold is set. According to the channel quality score, the method for automatically triggering the dual-mode communication period forward shift mechanism is as follows: The dynamic decision algorithm for establishing a dual-mode communication period is set to a fixed time period ΔT for the communication period. A score is sampled once at the end of each period to form a discrete score sequence, which is expressed as: Among them E k represents the set of discrete score sequences, Q(k·ΔT) shows the score at time point k·ΔT, ΔT is the time interval, k is the current cycle number, N is the total length of the discrete score sequence, represents the scoring window with a scoring sequence length of 3 for the current period k and its two previous periods (k-1, k-2), E k-2 ,E k-1 ,E k , respectively represent the scores of cycles (k-1, k-2, k), It is a low score judgment function that judges whether the score is low based on the scores of three consecutive cycles. It represents the maximum value of the scores of the current cycle k and the two cycles before it. 1 means that the low score judgment is true (i.e., the score is low), and 0 means that the low score judgment is false (i.e., the score is not low).

4. A communication control method based on a power line carrier dual-mode communication module according to claim 3, characterized in that: In step S2, a dynamic decision algorithm for the dual-mode communication period is established and a dynamic threshold is set. According to the channel quality score, the method for automatically triggering the dual-mode communication period forward shift mechanism is as follows: The dynamic threshold sets the communication time period of the whole day to [0, 24] hours, which is divided into M equal-width windows r i =[t i ,t i+1 ], calculate the average interference density and score volatility of each window, and express it as: in is the average interference density of the i-th window, R imp (t j ) is the interference density at time t j The collected interference density data, n i represents the number of sampling points in the i-th time window, t j is the jth moment, is the rating volatility of the ith window, E(t j ) is the signal strength at time t at time j j The ratings collected, is the average score of the i-th window, and the interference index is calculated by weighting the two indicators. The expression formula is: Where β(i) is the channel quality score of the i-th element, and α1 is the weight coefficient 1 used to adjust Contribution to the channel quality score, is the average interference density of the i-th window, and α2 is the weight coefficient 2 used to adjust Contribution to the channel quality score, is the score volatility of the i-th window. The high-interference window is selected by the maximum value index. The dual-mode communication period forward shift mechanism is automatically triggered. When the score is low, the dual-mode verification period is adaptively adjusted to the current high-interference period and extended to 2 hours. When the score is high or low, the pulsed dual-mode verification mode is started, and 5% of the time windows are randomly selected every day for data comparison.

5. A communication control method based on a power line carrier dual-mode communication module according to claim 4, characterized in that: In step S3, the method of adding a four-dimensional space-time identification code to the HPLC data packet and embedding the wireless signal strength grid coordinates into the HRF data packet is as follows: The four-dimensional space-time identification code includes the acquisition time stamp + power line topology location code + phase angle information + substation level code, and the HPLC data packet collected at the time t is set. Add four-dimensional space-time identification code Θ HPLC = <τ,Λ(x,y),δ,S>, where is the set of HPLC data packets at time t, q1,q2,...,q n is the data element in the data packet at that moment, n is the number of elements in the data packet, and each q i Represents a data item, Θ HPLC is a four-dimensional space-time identification code, τ is a timestamp, Λ(x,y) is a channel quality function representing the channel quality at spatial positions x and y, δ is a phase angle, S is a hash value, and a standardized UTC millisecond timestamp τ is collected. The power line topology location code Where Λ(x,y) is the channel quality function expressed in space χ1+χ2=1 The channel quality at positions x and y between the two channels, χ1 is the weight coefficient 1 used to adjust the size of the contribution of I(x), χ2 is the weight coefficient 2 used to adjust the contribution of V(y) in the total channel quality, I(x) represents the horizontal component related to x, V(y) represents the vertical component related to y, and the phase angle information Where δ is the phase angle, and atn is the inverse tangent function used to calculate an angle. Respectively represent the values of the in-phase O component and the orthogonal A component of the signal at time t, P O (t) is a component in the signal used to represent the amplitude information of the signal, P A (t) is another component in the signal used to represent the part orthogonal to the in-phase component, k represents the phase correction by adding an integer multiple of 2π, k∈{0,1,2} is the value range of the integer k, and the substation level code S=Hash CRC-16 (StationID 父级 ||StationID 本级 ), where S is the hash value, Hash CRC-16 It is CRC-16 hash algorithm (Cyclic Redundancy Check, a common error detection code used to verify data integrity), StationID 父级 Is the ID of the parent site, StationID 本级 is the ID of the current site, and || is a connector that concatenates the parent site ID and the current site ID. The final structure of the HPLC data package is in represents the HPLC signal intensity corresponding to time t.

6. A communication control method based on a power line carrier dual-mode communication module according to claim 5, characterized in that: In step S3, the method for embedding the wireless signal strength grid coordinates for the HRF data packet into the four-dimensional spatiotemporal identification code of the HPLC data packet is as follows: Set HRF data package Each of these a i Corresponding to a signal measurement point The signal measurement point corresponds to the grid coordinate identifier a i , let the actual measured RSSI value be RSSI(x,y,t), and construct the signal field equipotential function: Where Γ(x,y,t) represents the flow change of signal strength at point (x,y) and time t, is a vector operator, ε is the conductivity of the medium, is the gradient of the signal strength (RSSI) relative to the spatial coordinates (x, y) and time t, RSSI(x, y, t) is the received signal strength indicator (RSSI) indicating the signal strength at the position (x, y) and time t, discretizing the signal field equipotential function into a two-dimensional grid F m×n ,make: Each a i The attached signal strength is marked as: where φ i Represents the ratio of the signal strength of node i at time t to that of all nodes in the entire network, RSSI i (t) is the received signal strength indicator of node i at time t, is the sum of the total signal strength of all m nodes at time t, a i is the position coordinate of node i, is the temporal information of node i at time t, and the final structure of the HRF data packet is in represents the set of data packets containing all nodes i.

7. A communication control method based on a power line carrier dual-mode communication module according to claim 6, characterized in that: In step S4, the power line channel propagation model is reconstructed on the server side through the topological mapping relationship of the four-dimensional space-time identification code, and the method for identifying abnormal packet loss within 300 meters of the transformer outlet is as follows: The topological mapping relationship of the four-dimensional space-time identification code and the power line node set are: Each G i =(Λ i ,δ i ,S i ), set any two nodes G i ,G j The effective communication link function is: Among them H ij (t) is the effective communication link function between node i and node j at time t, is the Gaussian physical proximity, γ(δ i ,δ j ) is the phase matching degree, η(S i ,S j ) indicates whether it is in the same substation subnet structure, the power line channel propagation model is rebuilt on the server side, and all valid links H in the topology diagram are ij , construct the propagation channel response function as: Among them J ij (f,t) is the frequency domain response function of the channel from node i to node j at frequency f and time t, is the lth path amplitude, is the propagation delay, λ(f) is the frequency-dependent loss coefficient, It is made by i ,Λ j The Euclidean distance obtained by topological mapping, is the propagation speed, is the sum of all L′ multipath signal paths, represents the frequency-dependent phase delay of the lth path, The signal transmission distance The frequency-dependent attenuation term on .

8. A communication control method based on a power line carrier dual-mode communication module according to claim 7, characterized in that: In step S4, the power line channel propagation model is reconstructed on the server side through the topological mapping relationship of the four-dimensional space-time identification code, and the method for identifying abnormal packet loss within 300 meters of the transformer outlet is as follows: The identification of abnormal packet loss within 300 meters of the transformer outlet, for each transformer main node G c Define its 300-meter physical neighborhood as: in is the neighborhood node set with transformer c as the center and a radius of 300 meters. Node i is a member of the node set G. i is the spatial position coordinate of node i, Λ c is the spatial position coordinate of transformer c, ||Λ i -Λ c || is the distance between node i and transformer Λ c The spatial distance between them is less than 300 meters, which means it is within the radius of 300 meters from the transformer outlet. is the packet loss rate on link ij at time t, expressed as: in is the packet loss probability from node i to node j at time t, exp(·) is an exponential function used to map channel energy to a probability value. The larger the value, the lower the probability of packet loss. min ,f max are the minimum and maximum frequencies used by the communication system, is a normalizing constant, f is the frequency, |J ij (f,t)| 2 is the square of the channel frequency domain response function.

9. A communication control method based on a power line carrier dual-mode communication module according to claim 8, characterized in that: In step S5, when the HPLC packet loss rate exceeds the set adaptive threshold, the simultaneous spatial coordinate HRF data is called for local compensation, and the interference source is located to the tower level accuracy as follows: The adaptive threshold modeling, setting node G i The HPLC packet loss rate at time t is: Adopting the variable threshold strategy based on empirical risk minimization, the expression formula is: where θ i (t) is the adaptive threshold of packet loss rate of node i at time t, is the historical average packet loss rate of node i at time t, σ i (t) is the standard deviation of the packet loss rate of node i at time t, ρ is the confidence weight coefficient, ζ is the rate of change adjustment coefficient, is the packet loss rate change of node i at time t, and the grid coordinate π is embedded in the HRF data packet. i (t) = {x i ,y i ,z i ,τ i }, construct a dual-mode spatiotemporal fusion kernel function for precise compensation, expressed as: in is the dual-mode spatiotemporal fusion kernel function value between nodes i and j, exp(·) is the exponential function output ranging from 0 to 1, is the square of the three-dimensional space coordinate distance between node i and node j, is the square of the spatial scale parameter, is the square of the time scale parameter.

10. A communication control method based on a power line carrier dual-mode communication module according to claim 8, characterized in that: In step S5, when the HPLC packet loss rate exceeds the set adaptive threshold, the simultaneous spatial coordinate HRF data is called for local compensation, and the interference source is located to the tower level accuracy as follows: The interference source is located to the tower level with accuracy. This is based on the graph neural network anomaly tracing model, which performs positioning by comparing the spatiotemporal offset characteristics of the dual-mode data packets. The graph neural network anomaly tracing model defines a heterogeneous graph. in is the entire heterogeneous graph, is a collection of nodes, Is an edge set, including HPLC and HRF observation points, each node Embedding vector Expression formula: where p i is the eigenvector of the i-th node, is the HPLC channel quality score corresponding to the i-th node, is the wireless signal strength of the i-th HRF observation point, is the power phase angle information of node i, is the historical packet loss statistics covariance matrix, is the spatial coordinate vector of node i, τ i is the timestamp of node i, is the edge weight between node i and node j, is the square of the Euclidean distance between node i and node j in space, ζ is the normalization parameter of spatial distance, τ0 is the normalization parameter of time window, and the graph neural network anomaly tracing model uses graph convolutional neural network to realize information propagation. The last layer of the network outputs the interference probability of each node as follows: in The probability that the i-th node is judged as "abnormal" is between 0 and 1, and Sigmoid(·) is the output value range of the activation function. is the output weight matrix, It is the first The feature vector of the i-th node output by the layer, the spatiotemporal offset feature, defines the dual-mode spatiotemporal offset degree, for each tower subordinate node set Define the anomaly score and express the formula: exist It is determined that there is an interference source on the tower, and the interference source is output: where Ψ 干扰 is the set of towers identified as interference sources, g represents a specific tower number, is the abnormal score value of the g-th tower, θ g is the abnormality judgment threshold corresponding to the g-th tower.

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