A text transmission method based on Beidou satellite and semantic communication in a smart grid

Abstract

The present application relates to the technical field of data transmission, and proposes a text transmission method based on Beidou satellite and semantic communication in a smart grid, comprising the following steps: S1, text generation and collection, generating text information related to power grid operation at each node of the smart grid, S2, text processing and encoding, performing semantic extraction and labeling on the collected text information through a semantic communication module, S3, data format conversion, converting the semantic encoded text into a signal format suitable for Beidou satellite communication, including modulating the data to convert it into a radio frequency signal for transmission in the satellite communication frequency band. Through the use of a semantic analysis model based on deep learning, after a large number of smart grid text connections, the complex semantic structure in the text can be deeply understood, and the data compressed by extracting the text keyword elements in real time is uploaded to the database as training sample data for the semantic analysis model, which is beneficial to the autonomous learning of the semantic analysis model.

Description

Technical Field

[0001] This invention relates to the field of data transmission technology, and in particular to a text transmission method based on BeiDou satellite and semantic communication in smart grids. Background Technology

[0002] Traditional power grid communication primarily relies on terrestrial communication networks. However, in remote areas, mountainous regions, or when natural disasters damage terrestrial communication infrastructure, the reliability and coverage of these networks face significant challenges. BeiDou satellite communication, with its advantages of wide coverage, lack of geographical limitations, and high communication stability, is gradually becoming an important supplementary means of remote communication for smart grids.

[0003] In text information transmission, traditional communication methods are mostly based on simple text format transmission without deeply exploring the semantic information of the text. This results in large data volumes and low transmission efficiency during transmission. Furthermore, the receiving end needs to consume a lot of resources for parsing and understanding the information, making it difficult to quickly and accurately obtain key information and respond. At the same time, existing satellite communication technologies often lack optimization for the characteristics of power grid text transmission in smart grid applications. For example, they cannot flexibly adjust transmission parameters according to the importance of the text and channel conditions, making it difficult to guarantee the reliability and efficiency of communication when facing complex and ever-changing power grid operating environments. Summary of the Invention

[0004] In view of the problems existing in the prior art, the purpose of this invention is to provide a text transmission method based on BeiDou satellite and semantic communication in smart grids, so as to solve the problems mentioned in the background art.

[0005] To address the above problems, the present invention adopts the following technical solution: a text transmission method based on BeiDou satellite and semantic communication in a smart grid, comprising the following steps:

[0006] S1. Text generation and collection: Generate text information related to the operation of the smart grid at each node and collect the text information, wherein the text information includes at least one of equipment operation status information, fault alarm information, and power load data information.

[0007] S2. Text processing and encoding: The semantic communication module extracts and annotates the collected text information, identifies key semantic elements and labels their semantic categories, then compresses and encodes the annotated semantic information to form semantically encoded text, and uses a deep learning semantic analysis model to analyze and process the text semantics.

[0008] S3. Data format conversion: converting semantically encoded text into a signal format suitable for BeiDou satellite communication, including modulating the data to convert it into radio frequency signals that can be transmitted in the satellite communication frequency band.

[0009] S4. Data transmission and adaptive power adjustment: The modulated radio frequency signal is transmitted to the Beidou satellite through the Beidou satellite communication terminal installed at the smart grid node. The Beidou satellite receives and forwards the signal to the Beidou satellite communication terminal at the receiving end. Dynamic adaptive transmission power control technology is used to dynamically adjust the transmission power according to the satellite signal strength, channel quality and the importance level of the text information.

[0010] S5. Data reception and decoding: The Beidou satellite communication terminal at the receiving end receives the signal and demodulates it into a digital signal. The semantic communication module decodes the semantic encoded text corresponding to the digital signal and restores the annotated semantic information.

[0011] S6. Text restoration and application: Restore the complete text content based on the decoded semantic information, and perform smart grid operation management based on the text content. The operation management operation includes at least one of equipment maintenance scheduling, power load regulation, and grid operation status assessment.

[0012] Preferably, in step S2, semantic extraction and annotation employ an algorithm based on natural language processing (NLP) technology. This algorithm identifies and annotates entities, attributes, and relationships in the text using a predefined semantic rule base. Furthermore, the deep learning semantic analysis model works in conjunction with this algorithm to supplement and analyze ambiguous semantics or newly emerging semantic expressions that are difficult for the algorithm to handle. The algorithm formula for the NLP technology is as follows: Where G is the probability of perceiving keyword elements, N is the number of training samples, and T is the probability of perceiving keyword elements. n The length of the nth target sentence. Let be the word of the nth target sentence at time t.

[0013] Preferably, in step S2, the semantic encoding adopts a custom encoding format. This encoding format performs structured encoding based on semantic categories and data types to improve encoding efficiency and semantic expression accuracy. A check bit is introduced to quickly detect data errors during transmission at the receiving end and promptly request retransmission. It also detects erroneous or virus-infected codes in the encoded data to ensure the security of all data transmissions. The logical expression formula for the check bit is: Where, d i The information bits are encoded as text data to convey the meaning of the transmission. The sum of the number of "1"s in the information bits is modulo "2" and then inverted.

[0014] Preferably, in step S4, the modulation processing adopts the modulation method of binary phase shift keying (BPSK) satellite communication, and during the modulation process, low-density parity-check code (LDPC) encoding is combined to further enhance the signal's anti-interference capability.

[0015] Preferably, in step S6, equipment maintenance scheduling includes generating maintenance work orders based on equipment fault alarm information and assigning them to maintenance personnel; power load regulation includes adjusting the output power of power generation equipment based on power load data information; and power grid operation status assessment includes storing and analyzing text information to assess the stability and reliability of the power grid. In the analysis process, an artificial intelligence-based trend prediction algorithm is used to predictively assess the future operation status of the power grid based on historical text data and current text information, and to formulate response strategies in advance.

[0016] Preferably, the text transmission method includes a text transmission system, the text transmission system comprising:

[0017] A data acquisition unit is set up at each node of the smart network to generate and acquire text information about the operation of the power grid.

[0018] The analysis and encoding unit, connected to the generation and acquisition unit, is used to perform semantic processing steps, including a semantic extraction module, a semantic annotation module, a semantic compression module, and a semantic encoding module. The semantic extraction module and the semantic annotation module are used to extract and annotate keyword elements in the text data. They are both connected to the semantic rule base through Internet transmission technology to update the retrieval conditions and keyword elements in real time. The semantic compression module and the semantic encoding module are used to form a semantic codebook, which is used to analyze and process the semantics of the text and form a database. The sample data is used to train the semantic analysis model.

[0019] The BeiDou satellite communication unit includes a transmitting terminal and a receiving terminal installed at a smart grid node. The transmitting terminal is used to perform the BeiDou satellite transmission preparation steps and the BeiDou satellite transmission steps, and the receiving terminal is used to receive the signals relayed by the BeiDou satellite and demodulate them. Both the transmitting terminal and the receiving terminal are equipped with a dynamic power control module and a modem combined with channel coding technology.

[0020] The text restoration and application unit, connected to the semantic communication unit, is used to perform text restoration and application steps and to perform smart grid operation and management operations based on the decoded semantic information. This unit includes an artificial intelligence-based trend prediction module for power grid operation status assessment.

[0021] Preferably, the semantic extraction module includes a natural language processing engine and a semantic rule base, wherein the natural language processing engine performs semantic analysis on the text information based on the semantic rule base.

[0022] Preferably, the text restoration and application unit includes a text parsing module, an intelligent decision-making module, and a feedback optimization module. The text parsing module performs deep analysis on the decoded semantic information based on a semantic knowledge base, transforming it into structured data. The intelligent decision-making module uses a reinforcement learning algorithm to automatically generate optimal operation and management decisions based on the parsed structured data and a preset power grid operation strategy library. The feedback optimization module collects power grid operation data and human feedback information after the decision is executed, and dynamically updates and optimizes the semantic knowledge base and the operation strategy library.

[0023] The text transmission method based on BeiDou satellite and semantic communication in a smart grid provided by this invention has the following advantages:

[0024] 1. By adopting a deep learning-based semantic analysis model, after concatenating a large amount of smart grid text, it can deeply understand the complex semantic structure in the text and effectively process multilingual mixed text data. It can also compress and upload the extracted text keyword elements to the database in real time as training sample data for the semantic analysis model. This is conducive to the autonomous learning of the semantic analysis model, overcomes the limitations of traditional semantic processing algorithms when facing fuzzy semantics or new semantic expressions, and significantly improves the accuracy and adaptability of semantic extraction and annotation.

[0025] 2. By introducing a check bit into the semantic encoding format, the receiving end can quickly detect whether data errors occur during transmission. Once an error is detected, a retransmission can be requested in a timely manner, effectively avoiding errors in power grid operation and management decisions caused by data errors. Furthermore, it can identify error codes and virus codes in the encoded data, ensuring the security of all data transmissions and preventing problems such as power supply imbalances caused by data errors or virus codes, thus guaranteeing the safety and stability of power grid operation. Detailed Implementation

[0026] The specific embodiments of the present invention will be described in further detail below with reference to the examples. These examples are for illustrative purposes only and should not be construed as limiting the scope of the invention.

[0027] This embodiment proposes a text transmission method based on BeiDou satellite and semantic communication in smart grids, including the following steps:

[0028] S1. Text generation and collection: Generate text information related to grid operation at each node of the smart grid and collect the text information. The text information includes at least one of the following: equipment operation status information, fault alarm information, and power load data information.

[0029] S2. Text processing and encoding: The semantic communication module extracts and annotates the collected text information, identifies key semantic elements and labels their semantic categories, then compresses and encodes the annotated semantic information to form semantically encoded text, and uses a deep learning semantic analysis model to analyze and process the text semantics.

[0030] S3. Data format conversion: converting semantically encoded text into a signal format suitable for BeiDou satellite communication, including modulating the data to convert it into radio frequency signals that can be transmitted in the satellite communication frequency band.

[0031] S4. Data transmission and adaptive power adjustment: The modulated radio frequency signal is transmitted to the Beidou satellite through the Beidou satellite communication terminal installed at the smart grid node. The Beidou satellite receives and forwards the signal to the Beidou satellite communication terminal at the receiving end. Dynamic adaptive transmission power control technology is used to dynamically adjust the transmission power according to the satellite signal strength, channel quality and the importance level of the text information.

[0032] S5. Data reception and decoding: The Beidou satellite communication terminal at the receiving end receives the signal and demodulates it into a digital signal. The semantic communication module decodes the semantic encoded text corresponding to the digital signal and restores the annotated semantic information.

[0033] S6. Text restoration and application: Restore the complete text content based on the decoded semantic information, and perform smart grid operation management operations based on the text content. The operation management operations include at least one of equipment maintenance scheduling, power load regulation, and grid operation status assessment.

[0034] In this embodiment, step S2 employs a natural language processing (NLP)-based algorithm for semantic extraction and annotation. This algorithm identifies and annotates entities, attributes, and relationships in the text using a predefined semantic rule base. Furthermore, a deep learning semantic analysis model works in conjunction with the algorithm to supplement and analyze ambiguous semantics or newly emerging semantic expressions that are difficult for the algorithm to handle. The algorithm formula for the NLP is as follows: Where G is the probability of perceiving keyword elements, N is the number of training samples, and T is the probability of perceiving keyword elements. n The length of the nth target sentence. Let be the word of the nth target sentence at time t.

[0035] In this embodiment, in step S2, semantic encoding adopts a custom encoding format. This encoding format performs structured encoding based on semantic categories and data types to improve encoding efficiency and semantic expression accuracy. A check bit is introduced to quickly detect data errors during transmission at the receiving end and promptly request retransmission. It also detects erroneous or malicious codes in the encoded data to ensure the security of all data transmissions. The logical expression formula for the check bit is: Where, d i The information bits are encoded as text data to convey the meaning of the transmission. The sum of the number of "1"s in the information bits is modulo "2" and then inverted.

[0036] In this embodiment, in step S4, the modulation processing adopts the modulation method of binary phase shift keying (BPSK) satellite communication, and during the modulation process, low density parity check code (LDPC) encoding is combined to further enhance the signal's anti-interference capability.

[0037] In this embodiment, in step S6, equipment maintenance scheduling includes generating maintenance work orders based on equipment fault alarm information and assigning them to maintenance personnel; power load regulation includes adjusting the output power of power generation equipment based on power load data information; and power grid operation status assessment includes storing and analyzing text information to assess the stability and reliability of the power grid. In the analysis process, an artificial intelligence-based trend prediction algorithm is used to predictively assess the future operation status of the power grid based on historical text data and current text information, and to formulate response strategies in advance.

[0038] In this invention, a deep learning-based semantic analysis model is adopted. After concatenating a large amount of smart grid text, it can deeply understand the complex semantic structure in the text and effectively process multilingual mixed text data. It also compresses and uploads the extracted text keyword elements to the database in real time as training sample data for the semantic analysis model. This is beneficial for the autonomous learning of the semantic analysis model, overcomes the limitations of traditional semantic processing algorithms when facing fuzzy semantics or new semantic expressions, and significantly improves the accuracy and adaptability of semantic extraction and annotation.

[0039] In this embodiment, the text transmission method includes a text transmission system, which includes:

[0040] A data acquisition unit is set up at each node of the smart network to generate and acquire text information about the operation of the power grid.

[0041] The analysis and encoding unit, connected to the generation and acquisition unit, is used to perform semantic processing steps, including a semantic extraction module, a semantic annotation module, a semantic compression module, and a semantic encoding module. The semantic extraction module and the semantic annotation module are used to extract and annotate keyword elements in text data. They are both connected to the semantic rule base through Internet transmission technology to update the retrieval conditions and keyword elements in real time. The semantic compression module and the semantic encoding module are used to form a semantic encoding book, which is used to analyze and process the semantics of the text and form a database. The sample data used for the semantic analysis model is used to train the semantic analysis model.

[0042] The BeiDou satellite communication unit includes a transmitting terminal and a receiving terminal installed at a smart grid node. The transmitting terminal is used to perform the BeiDou satellite transmission preparation steps and the BeiDou satellite transmission steps, and the receiving terminal is used to receive the signals relayed by the BeiDou satellite and demodulate them. Both the transmitting terminal and the receiving terminal are equipped with a dynamic power control module and a modem combined with channel coding technology.

[0043] The text restoration and application unit, connected to the semantic communication unit, is used to perform text restoration and application steps and to perform smart grid operation and management operations based on the decoded semantic information. This unit includes an artificial intelligence-based trend prediction module for power grid operation status assessment.

[0044] In this embodiment, the semantic extraction module includes a natural language processing engine and a semantic rule base. The natural language processing engine performs semantic analysis on the text information based on the semantic rule base.

[0045] In this embodiment, the text restoration and application unit includes a text parsing module, an intelligent decision-making module, and a feedback optimization module. The text parsing module performs deep analysis on the decoded semantic information based on the semantic knowledge base, transforming it into structured data. The intelligent decision-making module uses a reinforcement learning algorithm to automatically generate the optimal operation management decision based on the parsed structured data and the preset power grid operation strategy library. The feedback optimization module collects power grid operation data and human feedback information after the decision is executed, and dynamically updates and optimizes the semantic knowledge base and the operation strategy library.

[0046] In this invention, a check bit is introduced into the semantic encoding format, which enables the receiving end to quickly detect whether data errors occur during transmission. Once an error is detected, a retransmission can be requested in a timely manner, effectively avoiding errors in power grid operation and management decisions caused by data errors. Furthermore, it can identify error codes and virus codes in the encoded data, ensuring the security of all data transmissions and preventing problems such as power supply imbalances caused by data errors or virus codes, thus guaranteeing the safety and stability of power grid operation.

[0047] The above embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Although the invention has been described in detail with reference to the embodiments, those skilled in the art should understand that various combinations, modifications, or equivalent substitutions of the technical solutions of the invention do not depart from the spirit and scope of the invention and should be covered within the scope of the claims of the invention.

Claims

1. A text transmission method based on BeiDou satellite and semantic communication in a smart grid, characterized in that, Includes the following steps: S1. Text generation and collection: Generate text information related to the operation of the smart grid at each node and collect the text information, wherein the text information includes at least one of equipment operation status information, fault alarm information, and power load data information. S2. Text processing and encoding: The semantic communication module extracts and annotates the collected text information, identifies key semantic elements and labels their semantic categories, then compresses and encodes the annotated semantic information to form semantically encoded text, and uses a deep learning semantic analysis model to analyze and process the text semantics. S3. Data format conversion: converting semantically encoded text into a signal format suitable for BeiDou satellite communication, including modulating the data to convert it into radio frequency signals that can be transmitted in the satellite communication frequency band. S4. Data transmission and adaptive power adjustment: The modulated radio frequency signal is transmitted to the Beidou satellite through the Beidou satellite communication terminal installed at the smart grid node. The Beidou satellite receives and forwards the signal to the Beidou satellite communication terminal at the receiving end. Dynamic adaptive transmission power control technology is used to dynamically adjust the transmission power according to the satellite signal strength, channel quality and the importance level of the text information. S5. Data reception and decoding: The Beidou satellite communication terminal at the receiving end receives the signal and demodulates it into a digital signal. The semantic communication module decodes the semantic encoded text corresponding to the digital signal and restores the annotated semantic information. S6. Text restoration and application: Restore the complete text content based on the decoded semantic information, and perform smart grid operation management based on the text content. The operation management operation includes at least one of equipment maintenance scheduling, power load regulation, and grid operation status assessment.

2. The text transmission method based on BeiDou satellite and semantic communication in a smart grid according to claim 1, characterized in that, In step S2, semantic extraction and annotation employ an algorithm based on natural language processing (NLP) technology. This algorithm identifies and annotates entities, attributes, and relationships in the text using a predefined semantic rule base. Furthermore, the deep learning semantic analysis model works in conjunction with this algorithm to supplement and analyze ambiguous semantics or newly emerging semantic expressions that are difficult for the algorithm to handle. The algorithm formula for the NLP technology is as follows: ,in, To perceive the probability of keyword elements. The number of training samples. For the first The length of the target sentence, For the first The target sentence is The word for time, For the first The input text content corresponding to each target sentence.

3. A text transmission method based on BeiDou satellite and semantic communication in a smart grid according to claim 1, characterized in that, In step S2, semantic encoding adopts a custom encoding format. This format performs structured encoding based on semantic categories and data types to improve encoding efficiency and semantic accuracy. A check bit is introduced to quickly detect data errors during transmission at the receiving end and promptly request retransmission. It also detects erroneous or malicious codes in the encoded data to ensure the security of all data transmissions. The logical expression formula for the check bit is: ,in, The text data information bits are encoded to convey the meaning of the transmission. The sum of the number of "1"s in the information bits is modulo 2 and then inverted. This refers to the total number of bits of transmitted data, including the parity bit. This is the sequence number of the information bit.

4. A text transmission method based on BeiDou satellite and semantic communication in a smart grid according to claim 1, characterized in that, In step S4, the modulation process adopts the modulation method of binary phase shift keying (BPSK) satellite communication, and during the modulation process, low-density parity-check code (LDPC) encoding is combined to further enhance the signal's anti-interference capability.

5. A text transmission method based on BeiDou satellite and semantic communication in a smart grid according to claim 1, characterized in that, In step S6, equipment maintenance scheduling includes generating maintenance work orders based on equipment fault alarm information and assigning them to maintenance personnel; power load regulation includes adjusting the output power of power generation equipment based on power load data information; and power grid operation status assessment includes storing and analyzing text information to assess the stability and reliability of the power grid. In the analysis process, an artificial intelligence-based trend prediction algorithm is used to predictively assess the future operation status of the power grid based on historical text data and current text information, and to formulate response strategies in advance.

6. A text transmission method based on BeiDou satellite and semantic communication in a smart grid according to claim 1, characterized in that, The text transmission method includes a text transmission system, the text transmission system comprising: A data acquisition unit is set up at each node of the smart network to generate and acquire text information about the operation of the power grid. The analysis and encoding unit, connected to the generation and acquisition unit, is used to perform semantic processing steps, including a semantic extraction module, a semantic annotation module, a semantic compression module, and a semantic encoding module. The semantic extraction module and the semantic annotation module are used to extract and annotate keyword elements in the text data. They are both connected to the semantic rule base through Internet transmission technology to update the retrieval conditions and keyword elements in real time. The semantic compression module and the semantic encoding module are used to form a semantic codebook, which is used to analyze and process the semantics of the text and form a database. The sample data is used to train the semantic analysis model. The BeiDou satellite communication unit includes a transmitting terminal and a receiving terminal installed at a smart grid node. The transmitting terminal is used to perform the BeiDou satellite transmission preparation steps and the BeiDou satellite transmission steps, and the receiving terminal is used to receive the signals relayed by the BeiDou satellite and demodulate them. Both the transmitting terminal and the receiving terminal are equipped with a dynamic power control module and a modem combined with channel coding technology. The text restoration and application unit, connected to the semantic communication unit, is used to perform text restoration and application steps and to perform smart grid operation and management operations based on the decoded semantic information. This unit includes an artificial intelligence-based trend prediction module for power grid operation status assessment.

7. A text transmission method based on BeiDou satellite and semantic communication in a smart grid according to claim 6, characterized in that, The semantic extraction module includes a natural language processing engine and a semantic rule base. The natural language processing engine performs semantic analysis on the text information based on the semantic rule base.

8. A text transmission method based on BeiDou satellite and semantic communication in a smart grid according to claim 1, characterized in that, The text restoration and application unit includes a text parsing module, an intelligent decision-making module, and a feedback optimization module. The text parsing module performs deep analysis on the decoded semantic information based on a semantic knowledge base, transforming it into structured data. The intelligent decision-making module uses a reinforcement learning algorithm to automatically generate optimal operation and management decisions based on the parsed structured data and a preset power grid operation strategy library. The feedback optimization module collects power grid operation data and human feedback information after the decision is executed, and dynamically updates and optimizes the semantic knowledge base and operation strategy library.