Communication method between power transmission line on-line monitoring device and master station system

Abstract

The invention discloses a communication method between a power transmission line on-line monitoring device and a master station system, which comprises the following steps of: in a physical layer, adopting OFDM (Orthogonal Frequency Division Multiplexing) modulation to maximize the utilization of bandwidth and signal transmission capability of a communication medium; in a data link layer, coding the data frame by adopting a recursive systematic code coding algorithm; in a network layer, a routing optimization algorithm and a network topology design are adopted to reduce communication delay and improve network throughput; in a transmission layer, optimizing a transmission protocol and implementing a congestion control mechanism so as to balance the data transmission rate and the network load; in an application layer, an LZW compression algorithm is adopted to realize data compression and optimization; and implementing a feedback mechanism and a dynamic adjustment strategy, and automatically adjusting communication parameters and strategies according to a real-time network state and a performance index so as to optimize the performance and efficiency of a communication system. According to the invention, the performance and efficiency of the communication system can be effectively improved, and the communication between the power transmission line online monitoring device and the master station system is more reliable and efficient.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission line monitoring, and in particular to a communication method between a power transmission line online monitoring device and a master station system. Background Art

[0002] Transmission line online monitoring devices are devices used to monitor the status and performance of power transmission lines in real time. These devices usually include various sensors, monitoring equipment and data transmission systems, which can monitor parameters such as current, voltage, temperature, humidity, vibration, and line status, load conditions, local faults and other information in real time. By collecting and analyzing these data, abnormal conditions and potential faults of the line can be discovered in time, which helps to improve the safety, stability and reliability of the transmission system. Traditional communication systems are often optimized at a single level, while modern communication systems are composed of multiple levels, which are interrelated and influence each other. Therefore, it is necessary to comprehensively consider the optimization of each level to improve the performance and efficiency of the entire communication system. Summary of the invention

[0003] In order to solve the above problems, the present invention provides a communication method between an online monitoring device for a power transmission line and a master station system.

[0004] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0005] The communication method between the online monitoring device of the transmission line and the master station system comprises the following steps:

[0006] Step 1: At the physical layer, OFDM modulation is used to maximize the bandwidth and signal transmission capacity of the communication medium;

[0007] Step 2: At the data link layer, a recursive systematic code encoding algorithm is used to encode the data frame, and the encoded data bits and error detection codes are arranged and combined according to the data frame structure;

[0008] Step 3: At the network layer, use routing optimization algorithms and network topology design to reduce communication delays and improve network throughput;

[0009] Step 4: At the transport layer, optimize the transport protocol and implement congestion control mechanisms to balance the data transmission rate and network load;

[0010] Step 5: At the application layer, the LZW compression algorithm is used to achieve data compression and optimization to reduce the amount of data transmission and improve communication efficiency;

[0011] Step 6: Implement feedback mechanisms and dynamic adjustment strategies to automatically adjust communication parameters and strategies based on real-time network status and performance indicators to optimize the performance and efficiency of the communication system.

[0012] Further: Step 1 comprises:

[0013] According to the bandwidth and spectrum resources of the communication system, the spectrum is divided into multiple subcarriers and allocated to different data streams. The formula is as follows:

[0014] f k =f c +k·Δf

[0015] Among them, f k is the frequency of the kth subcarrier, f c is the center frequency of the carrier, Δf is the subcarrier spacing;

[0016] The digital data stream to be transmitted is mapped to each subcarrier and QAM modulated. The formula is as follows:

[0017] s k (t) = A k ·cos(2πf k t+φ k )

[0018] Among them, s k (t) is the modulation signal of the kth subcarrier, A k is the amplitude, φ k is the phase;

[0019] The modulated subcarrier signals are transmitted in parallel to the communication medium to achieve multiplexing. The formula is as follows:

[0020]

[0021] Among them, s(t) is the final modulated signal, and N is the number of subcarriers;

[0022] At the receiving end, the received signal is demodulated and signal processed, each subcarrier is demodulated, combined and demodulated to restore the original data stream.

[0023] Further: Step 2 comprises:

[0024] The recursive systematic code encoding algorithm is used to encode the data frame. The encoding process is expressed as the following recursive formula:

[0025] c i =(d i +c i-1 +c i-2 )mod 2

[0026] Among them, c i is the ith encoded output, d i is the i-th input data bit, ci-1 and c i-2 Output for the first two codes;

[0027] Insert a frame synchronization flag into the data frame to identify the starting position of the data frame so that the receiving end can perform frame synchronization and analysis;

[0028] An error detection code is added to the encoded data frame to detect errors during data transmission. The formula is as follows:

[0029] R=M mod G

[0030] Among them, R is the remainder, M is the data to be checked, and G is the generating polynomial;

[0031] The encoded data bits and error detection codes are arranged and combined according to the data frame structure, including the data field, control field, and check word.

[0032] Further: Step 3 includes:

[0033] According to the physical structure and connection relationship of the communication network, a network topology diagram is constructed. The network topology diagram includes nodes and edges. Nodes represent devices or routers in the network, and edges represent connections between nodes.

[0034] For each node, the distance is initialized to infinity and the path is empty; for the source node, the distance is initialized to 0;

[0035] Starting from the source node, for each node, calculate the shortest path to that node. The steps are as follows:

[0036] For the current node, traverse all its neighboring nodes;

[0037] For each neighbor node, calculate the distance from the source node to the neighbor node, that is, the distance of the current node plus the weight of the edge from the current node to the neighbor node;

[0038] If the calculated distance is less than the distance currently recorded by the neighbor node, the distance and path of the neighbor node are updated;

[0039] Mark the current node as visited;

[0040] When all nodes have been visited, the shortest path from the source node to each node is obtained;

[0041] Update the routing table based on the calculated shortest path.

[0042] Further: Step 4 includes:

[0043] The sender dynamically adjusts the size of the sending window based on the network load and congestion. The sender dynamically adjusts the size of the sending window based on the received ACK packets and network delay.

[0044] The receiver detects network congestion signals based on the received data packets and network status. Once a congestion signal is detected, the receiver feeds the congestion signal back to the sender, triggering the sender's congestion control mechanism.

[0045] The sender uses the congestion window adjustment algorithm to adjust the size of the sending window according to the received congestion signal and the current network status. The formula is as follows:

[0046]

[0047] Where W(t) is the adjustment amount of the congestion window size, e(t) is the error of the congestion signal, and K p , K i and K d are the proportional, integral and differential coefficients respectively.

[0048] Further: Step 5 comprises:

[0049] Initialize a dictionary containing all possible characters and some initial phrases;

[0050] Encode the data to be transmitted and convert the continuous character sequence into the corresponding code. The steps are as follows:

[0051] Read the first character from the input data as the current character;

[0052] Check if the string consisting of the current character and the previous character is in the dictionary;

[0053] If it is in the dictionary, continue reading the next character until a string is found that is not in the dictionary;

[0054] Output the encoding corresponding to the current string and add the string to the dictionary;

[0055] Take the next character as the current character and continue the above steps;

[0056] At the receiving end, the received compressed data is decoded to restore the original data; the specific steps are as follows:

[0057] Read the first code from the compressed data and output the corresponding string;

[0058] Use the output string as a new entry in the dictionary;

[0059] Continue to read the next code and repeat the above steps.

[0060] Further: Step 6 comprises:

[0061] Introducing a real-time performance monitoring module into the communication system to continuously monitor the real-time status and performance indicators of the network;

[0062] Analyze and evaluate performance indicators based on real-time monitoring data, identify network bottlenecks and performance bottlenecks, and determine communication parameters and strategies that need to be adjusted;

[0063] According to the results of performance indicator analysis, an adaptive adjustment strategy based on the following formula is adopted to dynamically adjust communication parameters and strategies. The formula is as follows:

[0064] Q(s,a)=(1-α)·Q(s,a)+α·(R+γ·maxQ(s ′ ,a ′ ))

[0065] Among them, Q(s,a) represents the value of executing action a in state s, α is the learning rate, R is the reward, γ is the discount factor, and s ′ is the next state, a ′ For the next action;

[0066] According to the results of the adaptive adjustment strategy, the adjusted communication parameters and strategies are fed back to the communication system to implement real-time adjustment.

[0067] Compared with the prior art, the present invention has the following technical advances:

[0068] The present invention comprehensively considers all levels of the communication system, including the physical layer, data link layer, network layer, transport layer and application layer, and realizes the coordinated optimization of the entire communication system by optimizing the communication parameters and strategies of each level. The present invention improves the overall performance of the communication system, including transmission rate, response speed, stability, etc., by adopting appropriate modulation mode and transmission technology at the physical layer, designing appropriate data frame structure and error control mechanism at the data link layer, adopting routing optimization algorithm and network topology design at the network layer, optimizing transmission protocol and implementing congestion control mechanism at the transport layer, and adopting data compression and optimization technology at the application layer.

[0069] The present invention improves the efficiency of the communication system by reducing the amount of data transmission, reducing communication delays, and enhancing data integrity and reliability, thereby achieving faster and more stable data transmission. The method of the present invention introduces a reliability feedback mechanism and a dynamic adjustment strategy, and automatically adjusts communication parameters and strategies according to real-time network status and performance indicators, so that the communication system can respond to different communication environments and workloads in a timely manner, thereby improving the flexibility and adaptability of the system. The present invention improves the stability and reliability of the communication system by enhancing data integrity and reliability, optimizing transmission protocols and congestion control mechanisms, and implementing reliability feedback and dynamic adjustment strategies, thereby reducing errors and losses in data transmission and ensuring the security and accuracy of data.

[0070] In summary, the present invention can effectively improve the performance and efficiency of the communication system in solving multi-level communication optimization problems, making the communication between the online monitoring device of the transmission line and the master station system more reliable and efficient, and providing strong support for smart grid construction and energy operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0072] In the attached picture:

[0073] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0074] The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0075] like Figure 1 As shown, the present invention discloses a communication method between an online monitoring device for a power transmission line and a master station system, comprising the following steps:

[0076] Step 1: At the physical layer, OFDM modulation is used to maximize the bandwidth and signal transmission capacity of the communication medium.

[0077] At the physical layer, OFDM modulation method is adopted to maximize the bandwidth and signal transmission capacity of the communication medium.

[0078] Specific implementation steps:

[0079] 1.1 Subcarrier allocation: According to the bandwidth and spectrum resources of the communication system, the spectrum is divided into multiple subcarriers and reasonably allocated to different data streams. The formula is as follows:

[0080] f k =f c +k·Δf

[0081] Among them, f k is the frequency of the kth subcarrier, f c is the center frequency of the carrier, and Δf is the subcarrier spacing.

[0082] 1.2 Data modulation: Map the digital data stream to be transmitted to each subcarrier and perform appropriate modulation, such as QAM modulation. The formula is as follows:

[0083] s k (t) = A k ·cos(2πf k t+φ k )

[0084] Among them, s k (t) is the modulation signal of the kth subcarrier, A k is the amplitude, φ k For phase.

[0085] 1.3 Parallel transmission: The modulated subcarrier signals are transmitted in parallel to the communication medium to achieve multiplexing. The formula is as follows:

[0086]

[0087] Wherein, s(t) is the final modulated signal, and N is the number of subcarriers.

[0088] 1.4 Processing at the receiving end: At the receiving end, the received signal is demodulated and signal processed, each subcarrier is demodulated, combined and demodulated to restore the original data stream.

[0089] Through the above steps, the spectrum resources of the communication medium can be fully utilized, the bandwidth utilization and anti-interference capability of the communication system can be improved, thereby achieving optimization of signal modulation and transmission.

[0090] Step 2: At the data link layer, a recursive systematic code encoding algorithm is used to encode the data frame, and the encoded data bits and error detection codes are arranged and combined according to the data frame structure.

[0091] At the data link layer, the present invention designs a data frame structure and an error control mechanism to enhance the integrity and reliability of data. Specific implementation steps:

[0092] 2.1 Recursive systematic code encoding: The recursive systematic code encoding algorithm is used to encode the data frame. The encoding process can be expressed as the following recursive formula:

[0093] c i =(di +c i-1 +c i-2 )mod 2

[0094] Among them, c i is the ith encoded output, d i is the i-th input data bit, c i-1 and c i-2 Output for the first two codes.

[0095] 2.2 Frame synchronization flag insertion: A frame synchronization flag is inserted into a data frame to identify the starting position of the data frame so that the receiving end can perform frame synchronization and analysis. The frame synchronization flag can use a specific bit sequence, such as 10101010.

[0096] 2.3 Error detection code addition: Add an error detection code to the encoded data frame to detect errors in the data transmission process. The cyclic redundancy check (CRC) algorithm is used. The formula is as follows:

[0097] R=M mod G

[0098] Among them, R is the remainder, M is the data to be checked, and G is the generating polynomial.

[0099] 2.4 Data frame structure design: The encoded data bits and error detection codes are arranged and combined according to a specific data frame structure, including data fields, control fields, check fields, etc. For example:

[0100]

[0101] Start flag and end flag: used to identify the start and end positions of the data frame, usually using a specific byte sequence, such as the start flag is 0xFF and the end flag is 0xFE.

[0102] Data length field: used to indicate the length of the data field so that the receiving end can correctly parse the data. The data length field is usually two bytes, and the maximum data length that can be represented depends on the specific implementation.

[0103] Data field: contains the encoded data bits, with a variable length determined by the data length field. This part of the data is the encoded transmission data.

[0104] Check field: used to detect errors in data to ensure the integrity of data transmission. Usually a check code generated by a CRC check algorithm is used, with a length of two bytes.

[0105] Through this data frame structure design, the encoded data bits and error detection codes can be arranged and combined in a specific order to achieve data integrity and reliability. At the same time, the start flag and end flag are used to identify the boundaries of the data frame, so that the receiving end can accurately identify and parse the data frame, thereby achieving reliable data transmission.

[0106] By adopting recursive systematic code encoding and error control mechanism, the integrity and reliability of data can be enhanced, and data frame structure design and error control can be implemented at the data link layer to ensure the integrity and reliability of data during data transmission.

[0107] Step 3: At the network layer, routing optimization algorithms and network topology design are used to reduce communication delays and improve network throughput.

[0108] At the network layer, the shortest path algorithm is used to implement routing optimization and network topology design to reduce communication delays and improve network throughput. The specific implementation steps are as follows:

[0109] 3.1 Constructing a network topology graph: First, based on the physical structure and connection relationship of the communication network, a network topology graph is constructed. This graph consists of nodes and edges. Nodes represent devices or routers in the network, and edges represent connections between nodes.

[0110] 3.2 Initialize distance and path: For each node, initialize the distance to infinity and the path to empty. For the source node, the distance is initialized to 0.

[0111] 3.3 Traversing nodes: Starting from the source node, for each node, calculate the shortest path to that node. The specific steps are as follows:

[0112] For the current node, traverse all its neighboring nodes.

[0113] For each neighbor node, calculate the distance from the source node to the neighbor node, that is, the distance of the current node plus the weight of the edge from the current node to the neighbor node.

[0114] If the calculated distance is less than the currently recorded distance of the neighbor node, the distance and path of the neighbor node are updated.

[0115] Mark the current node as visited.

[0116] 3.4 Select the shortest path: When all nodes have been visited, the shortest path from the source node to each node is obtained.

[0117] 3.5 Update routing table: Update the routing table based on the calculated shortest path. The routing table records the next hop node from the source node to each target node.

[0118] By adopting the shortest path algorithm, routing optimization and network topology design can be achieved at the network layer to ensure that data packets can be transmitted from the source node to the destination node at the fastest speed, thereby reducing communication delays and improving network throughput.

[0119] Step 4: At the transport layer, optimize the transport protocol and implement congestion control mechanisms to balance the data transmission rate and network load.

[0120] At the transport layer, a congestion control algorithm is used to balance the data transmission rate and network load to ensure the effective use of network resources. The specific implementation steps are as follows:

[0121] 4.1. Dynamically adjust the sending window size: A feedback-based dynamic sending window adjustment mechanism is introduced to dynamically adjust the sending window size according to network load and congestion. The sender dynamically adjusts the sending window size according to the received ACK packets and network delay to avoid network congestion caused by too fast sending rate.

[0122] 4.2. Congestion signal detection: The receiver detects network congestion signals based on the received data packets and network status. Once the congestion signal is detected, the receiver feeds the congestion signal back to the sender, triggering the sender's congestion control mechanism.

[0123] 4.3. Congestion window adjustment algorithm: The sender uses a complex congestion window adjustment algorithm to adjust the size of the sending window based on the received congestion signal and the current network status. This algorithm can be a feedback-based PID control algorithm, and the formula is as follows:

[0124]

[0125] Where W(t) is the adjustment amount of the congestion window size, e(t) is the error of the congestion signal, and K p , K i and K d are the proportional, integral and differential coefficients respectively.

[0126] 4.4. Dynamic timeout setting: Dynamically adjust the timeout period according to the network congestion situation. When the network congestion is serious, extend the timeout period to reduce the number of retransmissions and reduce the network load.

[0127] By adopting complex congestion control algorithms, it is possible to achieve transmission protocol optimization and congestion control at the transport layer, ensuring that the data transmission rate and network load are balanced, thereby improving network performance and efficiency.

[0128] Step 5: At the application layer, the LZW compression algorithm is used to achieve data compression and optimization to reduce the amount of data transmission and improve communication efficiency.

[0129] At the application layer, the Lempel-Ziv-Welch (LZW) compression algorithm is used to achieve data compression and optimization to reduce data transmission volume and improve communication efficiency. The specific implementation steps are as follows:

[0130] 5.1. Dictionary initialization: First, initialize a dictionary containing all possible characters and some initial phrases. Usually, the initial dictionary contains all single characters.

[0131] 5.2. Encoding process: Encode the data to be transmitted and convert the continuous character sequence into the corresponding code. The specific steps are as follows:

[0132] Read the first character from the input data as the current character.

[0133] Checks whether the string consisting of the current character and the previous characters is in the dictionary.

[0134] If it is in the dictionary, it continues reading the next character until it finds a string that is not in the dictionary.

[0135] Output the encoding corresponding to the current string and add the string to the dictionary.

[0136] Set the next character as the current character and continue the above steps.

[0137] 5.3. Decoding process: At the receiving end, the received compressed data is decoded to restore the original data. The specific steps are as follows:

[0138] Read the first code from the compressed data and output the corresponding string.

[0139] Write the output string as a new entry in the dictionary.

[0140] Continue to read the next code and repeat the above steps.

[0141] By adopting the LZW compression algorithm, data compression and optimization can be achieved at the application layer, converting continuous character sequences into compact codes, thereby reducing the amount of data transmission and improving communication efficiency.

[0142] Step 6: Implement feedback mechanisms and dynamic adjustment strategies to automatically adjust communication parameters and strategies based on real-time network status and performance indicators to optimize the performance and efficiency of the communication system.

[0143] In order to implement the reliability feedback mechanism and dynamic adjustment strategy, an adaptive communication algorithm is introduced to automatically adjust communication parameters and strategies according to real-time network status and performance indicators, thereby optimizing the performance and efficiency of the communication system. The specific implementation steps are as follows:

[0144] 6.1. Real-time performance monitoring: A real-time performance monitoring module is introduced into the communication system to continuously monitor the real-time status and performance indicators of the network, including bandwidth utilization, latency, packet loss rate, etc.

[0145] 6.2. Performance indicator analysis: Based on real-time monitoring data, analyze and evaluate performance indicators, identify network bottlenecks and performance bottlenecks, and determine the communication parameters and strategies that need to be adjusted.

[0146] 6.3. Adaptive adjustment strategy: According to the results of performance indicator analysis, an adaptive adjustment strategy based on the following formula is adopted to dynamically adjust communication parameters and strategies. The formula is as follows:

[0147] Q(s,a)=(1-α)·Q(s,a)+α·(R+γ·maxQ(s ′ ,a ′ ))

[0148] Among them, Q(s,a) represents the value of executing action a in state s, α is the learning rate, R is the reward, γ is the discount factor, and s ′ is the next state, a ′ For the next action.

[0149] 6.4. Parameter adjustment feedback: Based on the results of the adaptive adjustment strategy, the adjusted communication parameters and strategies are fed back to the communication system to implement real-time adjustments. In this way, the communication system can dynamically adjust its own operating status and behavior according to the real-time network status and performance indicators to achieve optimized communication performance and efficiency.

[0150] By introducing complex adaptive communication algorithms, reliability feedback mechanisms and dynamic adjustment strategies can be implemented in the communication system, and communication parameters and strategies can be automatically adjusted according to real-time network status and performance indicators, thereby optimizing the performance and efficiency of the communication system.

[0151] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein with equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the scope of protection of the claims of the present invention.

Claims

1. A communication method between an online monitoring device for a transmission line and a master station system, characterized in that: The steps include: Step 1: At the physical layer, OFDM modulation is used to maximize the bandwidth and signal transmission capacity of the communication medium; Step 2: At the data link layer, a recursive systematic code encoding algorithm is used to encode the data frame, and the encoded data bits and error detection codes are arranged and combined according to the data frame structure; Step 3: At the network layer, use routing optimization algorithms and network topology design to reduce communication delays and improve network throughput; Step 4: At the transport layer, optimize the transport protocol and implement congestion control mechanisms to balance the data transmission rate and network load; Step 5: At the application layer, the LZW compression algorithm is used to achieve data compression and optimization to reduce the amount of data transmission and improve communication efficiency; Step 6: Implement feedback mechanisms and dynamic adjustment strategies to automatically adjust communication parameters and strategies based on real-time network status and performance indicators to optimize the performance and efficiency of the communication system.

2. The communication method between the online monitoring device of a power transmission line and the master station system according to claim 1, characterized in that: The step 1 comprises: According to the bandwidth and spectrum resources of the communication system, the spectrum is divided into multiple subcarriers and allocated to different data streams. The formula is as follows: f k =f c +k·Δf Among them, f k is the frequency of the kth subcarrier, f c is the center frequency of the carrier, Δf is the subcarrier spacing; The digital data stream to be transmitted is mapped to each subcarrier and QAM modulated. The formula is as follows: s k ()=A k ·cOs(2 k t+φ k ) Among them, s k () is the modulation signal of the kth subcarrier, A k is the amplitude, φ k is the phase; The modulated subcarrier signals are transmitted in parallel to the communication medium to achieve multiplexing. The formula is as follows: Among them, s(t) is the final modulated signal, and N is the number of subcarriers; At the receiving end, the received signal is demodulated and signal processed, each subcarrier is demodulated, combined and demodulated to restore the original data stream.

3. The communication method between the online monitoring device of the power transmission line and the master station system according to claim 2, characterized in that: The step 2 comprises: The recursive systematic code encoding algorithm is used to encode the data frame. The encoding process is expressed as the following recursive formula: c i =(d i +c i-1 +c i-2 )mod2 Among them, c i is the ith encoded output, d i is the i-th input data bit, c i-1 and c i-2 Output for the first two codes; Insert a frame synchronization flag into the data frame to identify the starting position of the data frame so that the receiving end can perform frame synchronization and analysis; An error detection code is added to the encoded data frame to detect errors during data transmission. The formula is as follows: R=M mod G Among them, R is the remainder, M is the data to be checked, and G is the generating polynomial; The encoded data bits and error detection codes are arranged and combined according to the data frame structure, including the data field, control field, and check word.

4. The communication method between the online monitoring device of a power transmission line and a master station system according to claim 3, characterized in that: The step 3 comprises: According to the physical structure and connection relationship of the communication network, a network topology diagram is constructed. The network topology diagram includes nodes and edges. Nodes represent devices or routers in the network, and edges represent connections between nodes. For each node, the distance is initialized to infinity and the path is empty; for the source node, the distance is initialized to 0; Starting from the source node, for each node, calculate the shortest path to that node. The steps are as follows: For the current node, traverse all its neighboring nodes; For each neighbor node, calculate the distance from the source node to the neighbor node, that is, the distance of the current node plus the weight of the edge from the current node to the neighbor node; If the calculated distance is less than the distance currently recorded by the neighbor node, the distance and path of the neighbor node are updated; Mark the current node as visited; When all nodes have been visited, the shortest path from the source node to each node is obtained; Update the routing table based on the calculated shortest path.

5. The communication method between the online monitoring device of the power transmission line and the master station system according to claim 4, characterized in that: The step 4 comprises: The sender dynamically adjusts the size of the sending window based on the network load and congestion. The sender dynamically adjusts the size of the sending window based on the received ACK packets and network delay. The receiver detects network congestion signals based on the received data packets and network status. Once a congestion signal is detected, the receiver feeds the congestion signal back to the sender, triggering the sender's congestion control mechanism. The sender uses the congestion window adjustment algorithm to adjust the size of the sending window according to the received congestion signal and the current network status. The formula is as follows: Where W(t) is the adjustment amount of the congestion window size, e(t) is the error of the congestion signal, and K p , K i and K d are the proportional, integral and differential coefficients respectively.

6. The communication method between the online monitoring device of a power transmission line and a master station system according to claim 5, characterized in that: The step 5 comprises: Initialize a dictionary containing all possible characters and some initial phrases; Encode the data to be transmitted and convert the continuous character sequence into the corresponding code. The steps are as follows: Read the first character from the input data as the current character; Check if the string consisting of the current character and the previous character is in the dictionary; If it is in the dictionary, continue reading the next character until a string is found that is not in the dictionary; Output the encoding corresponding to the current string and add the string to the dictionary; Take the next character as the current character and continue the above steps; At the receiving end, the received compressed data is decoded to restore the original data; the specific steps are as follows: Read the first code from the compressed data and output the corresponding string; Use the output string as a new entry in the dictionary; Continue to read the next code and repeat the above steps.

7. The communication method between the online monitoring device of a power transmission line and a master station system according to claim 6, characterized in that: The step 6 comprises: Introducing a real-time performance monitoring module into the communication system to continuously monitor the real-time status and performance indicators of the network; Analyze and evaluate performance indicators based on real-time monitoring data, identify network bottlenecks and performance bottlenecks, and determine communication parameters and strategies that need to be adjusted; According to the results of performance indicator analysis, an adaptive adjustment strategy based on the following formula is adopted to dynamically adjust communication parameters and strategies. The formula is as follows: Q(s,a)=(1-α)·Q(s,a)+α·(R+γ·maxQ(s ′ ,a ′ )) Among them, Q(s,a) represents the value of executing action a in state s, α is the learning rate, R is the reward, γ is the discount factor, and s ′ is the next state, a ′ For the next action; According to the results of the adaptive adjustment strategy, the adjusted communication parameters and strategies are fed back to the communication system to implement real-time adjustment.

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