Power monitoring data compression processing method based on Beidou short message transmission

Abstract

The invention relates to an electric power monitoring data compression processing method based on Beidou short message transmission, and the method comprises the following steps: collecting and preprocessing sensor data, and presetting the type of the sensor data; constructing a data analysis and processing model, and judging a compression strategy of each type of sensor data through the data analysis and processing model; compressing each type of sensor data according to a corresponding compression strategy to obtain each type of compressed sensor data; for any type of compressed sensor data, subpackaging the compressed sensor data according to the maximum capacity of a Beidou short message single packet to obtain a plurality of Beidou short message data packets; and sending the Beidou short message data packet.

Description

TECHNICAL FIELD

[0001] The application relates to a power monitoring data compression processing method based on Beidou short message transmission and belongs to the technical field of data compression. BACKGROUND

[0002] Power facilities are distributed everywhere, and for areas covered by ground network signals, power data return is performed through wired networks or ground 4G / 5G signals, while a large number of power facilities, such as power transmission lines, towers and substations, are located in remote areas without public network (such as 4G / 5G) signal coverage. Real-time monitoring of the operating state (such as current, voltage, temperature, inclination, image, etc.) of these facilities is an important means to ensure the safe and stable operation of the power grid.

[0003] At present, power data return in areas without public network signal coverage is realized through Beidou No. 3 short message communication. The short message communication service provided by the Beidou satellite navigation system has become an irreplaceable communication method in such scenarios due to its wide coverage and lack of geographical environment restrictions. However, the communication frequency and single-word communication capacity of Beidou No. 3 short message communication are limited. Traditional power monitoring data direct transmission methods have large data volumes and cannot be sent in a single short message. If multiple packets are used, the communication delay and cost will increase dramatically, making it difficult to meet real-time and economic requirements.

[0004] Some data compression algorithms exist in the prior art, such as LZW and Huffman encoding. However, these general compression algorithms have the following shortcomings when applied to power monitoring data: 1) They usually require large computing resources and memory, which is not suitable for resource-constrained embedded monitoring terminals; 2) They do not fully utilize the strong correlation of numerical sequences and the repetitiveness of state quantities in power monitoring data, leaving room for improvement in compression efficiency; and 3) They lack adaptive packetization and fault tolerance mechanisms closely integrated with the Beidou short message transmission protocol, resulting in insufficient data transmission reliability in harsh communication environments. SUMMARY

[0005] To solve the problems existing in the prior art, the application provides a power monitoring data compression processing method based on Beidou short message transmission.

[0006] The technical scheme of the application is as follows: On the one hand, the application provides a power monitoring data compression processing method based on Beidou short message transmission, including the following steps: Collecting sensor data and performing preprocessing, and presetting sensor data types; Building a data analysis and processing model to determine the compression strategy for each type of sensor data through the data analysis and processing model; According to the corresponding compression strategy, each type of sensor data is compressed to obtain compressed sensor data of each type; For any type of compressed sensor data, the compressed sensor data is divided into multiple Beidou short message data packets according to the maximum capacity of a single Beidou short message packet; The Beidou short message data packet is sent.

[0007] Preferably, the sensor data includes numerical data and state quantity data.

[0008] Preferably, the data analysis processing model is constructed based on a long short-term memory network.

[0009] Preferably, the compression strategy of the sensor data includes a compression algorithm and a compression ratio.

[0010] Preferably, for numerical data, a run-length encoding and Huffman encoding combined algorithm is used for compression, and the specific steps are as follows: The numerical data is run-length encoded, specifically: the characters in the numerical data that continuously appear more than a preset threshold are counted, and the number of continuous repeated appearances of the characters is counted. If a character d continuously appears n times, the original single character d that appears continuously n times is replaced by two characters nd; The run-length encoded numerical data is Huffman encoded, specifically: the frequency of each character in the numerical data is counted, all characters are sorted in descending order of appearance frequency, a Huffman tree is constructed based on the sorted characters, and the run-length encoded numerical data is encoded into the Huffman tree to obtain compressed numerical data.

[0011] Preferably, for state quantity data, a coding algorithm based on a hash dictionary is used, specifically: Extract state description data in the state quantity data that is longer than a preset length, convert each state description data that is longer than the preset length into a fixed-length short hash value to obtain compressed state description data; A hash mapping dictionary is constructed, the hash mapping dictionary includes a plurality of entries, and for any entry, it stores a state description data that is longer than a preset length and a corresponding fixed-length short hash value; The hash mapping dictionary is transmitted to the data receiving side in advance, and the data receiving side restores the compressed state description data according to the hash mapping dictionary.

[0012] Preferably, when the sensor data is compressed, the actual compression ratio is calculated, and if the actual compression ratio is greater than the compression ratio in the compression strategy, the current sensor data is re-compressed.

[0013] Preferably, each Beidou short message data packet includes packet header information. The packet header information includes total packet number, current packet sequence, time stamp and CRC check code.

[0014] In another aspect, the present application also provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to the present application when executing the program.

[0015] In another aspect, the present application also provides a computer readable storage medium having a computer program stored thereon, wherein the program is executable on a processor to implement the method according to the present application.

[0016] The present application has the following beneficial effects: 1. The present application adopts differentiated compression strategies for different types of power monitoring sensor data (including numerical data and state quantity data), significantly reduces the transmission data volume of Beidou short messages, and enables the Beidou communication link originally limited by the maximum capacity of a single packet to efficiently carry more monitoring information.

[0017] 2. The data analysis processing model of the present application adopts a long short-term memory (LSTM) architecture, which can automatically learn the time characteristics and fluctuation rules of different types of sensor data, and realize intelligent matching of compression strategies. The model has self-adaptive learning ability and can automatically optimize the compression strategy as the distribution of sensor data changes. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 The present application is a method flowchart. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0020] It should be understood that the step numbers used herein are only for the convenience of description, and are not limited to the execution sequence of the steps.

[0021] It should be understood that the terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, unless otherwise clear from the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0022] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0023] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0024] See Figure 1 In some embodiments, a method for compressing power monitoring data based on BeiDou short message transmission is proposed, including the following steps: Collect sensor data and preprocess it, and preset the sensor data type; Construct a data analysis and processing model, and use the data analysis and processing model to determine the compression strategy for various types of sensor data; The data of each type of sensor is compressed according to the corresponding compression strategy to obtain the compressed data of each type of sensor. For any type of compressed sensor data, multiple BeiDou short message data packets are obtained by dividing the compressed sensor data into packets according to the maximum capacity of a single BeiDou short message packet. Send the BeiDou short message data packet.

[0025] In some embodiments, the sensor data includes numerical data and state data.

[0026] In one specific embodiment, the numerical data includes continuously changing analog quantities such as current, voltage, and temperature; The status data includes descriptive information such as switch on / off states and device alarms.

[0027] In some embodiments, the data analysis and processing model is built on a long short-term memory network.

[0028] In one specific embodiment, the data analysis and processing model is constructed based on a two-layer LSTM network, with 64 units in the first layer and 32 units in the second layer; a Dropout layer is added between the input layer and the fully connected layer to prevent overfitting; the weighted average absolute error (MAE) is used as the loss function, with different parameters assigned different weights; the Adam optimizer is used for training, with a learning rate of 0.001; an early stopping mechanism is implemented, terminating training when the validation set loss does not decrease for 5 consecutive epochs; The data analysis and processing model uses raw sensor data as training data.

[0029] In some embodiments, the compression strategy for sensor data includes a compression algorithm and a compression ratio.

[0030] In some embodiments, a combination of run-length encoding and Huffman coding is used to compress numerical data. The specific steps are as follows: Run-length encoding is performed on numerical data, specifically by counting characters that appear consecutively more than a preset threshold in the numerical data and counting the number of consecutive repetitions of that character. If the character d appears consecutively n times, then replace the single character d that appears consecutively n times with two characters nd. The numerical data after run-length encoding is subjected to Huffman encoding. Specifically, the frequency of each character in the numerical data is counted, all characters are sorted in descending order of frequency, a Huffman tree is constructed based on the sorted characters, and the numerical data after run-length encoding is encoded into the Huffman tree to obtain the compressed numerical data.

[0031] In one specific embodiment, the character sequence of the numerical data is [5,5,5,3,3]. At this time, the character "5" appears 3 times consecutively, which is more than the preset threshold of 2 times. Therefore, the character sequence is compressed to [3,5,2,3].

[0032] In one specific embodiment, the Huffman tree assigns short codes to high-frequency characters and long codes to low-frequency characters, thereby reducing the average code length.

[0033] In some embodiments, a hash dictionary-based encoding algorithm is used for the state data, specifically: Extract state description data that exceeds a preset length from the state quantity data, and convert each state description data that exceeds the preset length into a short hash value of fixed length to obtain compressed state description data; Construct a hash mapping dictionary, which includes multiple entries. For any entry, it stores a state description data exceeding a preset length and a corresponding short hash value of fixed length. The hash mapping dictionary is pre-transmitted to the data receiver, who then uses the hash mapping dictionary to reconstruct the compressed state description data.

[0034] In one specific embodiment, the state description data "insulator pollution level 1 alarm" exceeding the preset length is extracted from the extracted state quantity data and converted into a 2-byte hash code.

[0035] In some embodiments, after the sensor data is compressed, its actual compression ratio is calculated. If the actual compression ratio is greater than the compression ratio in the compression strategy, the current sensor data is recompressed.

[0036] In some embodiments, each BeiDou short message data packet includes header information; The packet header information includes the total number of packets, the current packet order, the timestamp, and the CRC checksum.

[0037] In some embodiments, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method as described in any embodiment of the present invention.

[0038] In some embodiments, a computer-readable storage medium is provided on which a computer program is stored, which, when executed by a processor, implements the method as described in any embodiment of the present invention.

[0039] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0040] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0041] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0042] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0043] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for compressing and processing power monitoring data based on BeiDou short message transmission, characterized in that, Includes the following steps: Collect sensor data and preprocess it, and preset the sensor data type; Construct a data analysis and processing model, and use the data analysis and processing model to determine the compression strategy for various types of sensor data; The data of each type of sensor is compressed according to the corresponding compression strategy to obtain the compressed data of each type of sensor. For any type of compressed sensor data, multiple BeiDou short message data packets are obtained by dividing the compressed sensor data into packets according to the maximum capacity of a single BeiDou short message packet. Send the BeiDou short message data packet.

2. The power monitoring data compression processing method based on BeiDou short message transmission according to claim 1, characterized in that, The sensor data includes numerical data and state data.

3. The method for compressing and processing power monitoring data based on BeiDou short message transmission according to claim 2, characterized in that, The data analysis and processing model is built on a long short-term memory network.

4. The power monitoring data compression processing method based on BeiDou short message transmission according to claim 3, characterized in that, The compression strategy for sensor data includes the compression algorithm and the compression ratio.

5. The power monitoring data compression processing method based on BeiDou short message transmission according to claim 4, characterized in that, For numerical data, a combination of run-length encoding and Huffman coding is used for compression. The specific steps are as follows: Run-length encoding is performed on numerical data, specifically by counting characters that appear consecutively more than a preset threshold in the numerical data and counting the number of consecutive repetitions of that character. If the character d appears consecutively n times, then replace the single character d that appears consecutively n times with two characters nd. The numerical data after run-length encoding is subjected to Huffman encoding. Specifically, the frequency of each character in the numerical data is counted, all characters are sorted in descending order of frequency, a Huffman tree is constructed based on the sorted characters, and the numerical data after run-length encoding is encoded into the Huffman tree to obtain the compressed numerical data.

6. The power monitoring data compression processing method based on BeiDou short message transmission according to claim 4, characterized in that, For state data, a hash dictionary-based encoding algorithm is used, specifically: Extract state description data that exceeds a preset length from the state quantity data, and convert each state description data that exceeds the preset length into a short hash value of fixed length to obtain compressed state description data; Construct a hash mapping dictionary, which includes multiple entries. For any entry, it stores a state description data exceeding a preset length and a corresponding short hash value of fixed length. The hash mapping dictionary is pre-transmitted to the data receiver, who then uses the hash mapping dictionary to reconstruct the compressed state description data.

7. The power monitoring data compression processing method based on BeiDou short message transmission according to claim 4, characterized in that, After the sensor data is compressed, its actual compression ratio is calculated. If the actual compression ratio is greater than the compression ratio in the compression strategy, the current sensor data is recompressed.

8. The method for compressing and processing power monitoring data based on BeiDou short message transmission according to claim 1, characterized in that, Each BeiDou short message data packet includes header information; The packet header information includes the total number of packets, the current packet order, the timestamp, and the CRC checksum.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 8.

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