A satellite communication earth station monitoring protocol design method based on graph clustering

Abstract

The application designs a satellite communication earth station monitoring protocol design method based on atlas clustering, which is suitable for the satellite communication earth station operation and maintenance control field, the classification processing and monitoring protocol planning and design of the controlled equipment and its parameters. The relationship and mode between the earth station monitoring data are revealed by mainly designing a multivariate statistical analysis and atlas clustering processing scheme of monitoring data, so as to better understand and identify different characteristics and behaviors, and realize the inductive design of the earth station monitoring protocol. The application has the characteristics of clear and easy to understand, good continuity, strong scalability and the like, and can especially solve the problems of non-standard satellite communication earth station monitoring protocol design process, disorder protocol content and poor continuity and the like.

Description

Technical Field

[0001] The present invention relates to the field of satellite communication earth station operation, maintenance and control, and particularly focuses on the design and summary of monitoring protocols within earth stations. Specifically, it involves data collection of controlled equipment within the earth station, preprocessing of heterogeneous and heterogeneous data, data feature extraction, relationship graph construction, graph clustering analysis, monitoring protocol formulation, protocol testing and evaluation, and protocol optimization. Background Art

[0002] Satellite communications have been around for over half a century. Due to its global coverage, freedom from ground obstacles, and rapid deployment, it has become an irreplaceable core communications technology. Satellite communications technology has also become a key indicator of a country's core competitiveness.

[0003] The satellite communication earth station monitoring system is a crucial component of satellite communication system management. This system's mission is to monitor, control, and manage satellite communication earth station equipment. The type and number of equipment assigned to an earth station vary depending on its communication capabilities, primarily including antennas, tracking equipment, transmitters, receivers, terminals, management equipment, and access devices. With the advancement of satellite communication technology and the increasing demands on earth station communication capabilities, the types and number of equipment assigned to earth stations have increased significantly, posing new challenges to earth station monitoring.

[0004] The monitoring protocol serves as the interaction specification between in-station monitoring and controlled equipment, and the basis for the design and implementation of equipment monitoring. It is used to constrain the data interaction between in-station monitoring and controlled equipment. The monitoring protocol generally constrains: transmission mode, transmission protocol, working mode, frame format, etc. The monitoring protocol should also clearly define parameter sets and parameter groupings. In the design process of previous monitoring protocols, especially when summarizing parameter groupings, they relied on the designer's experience to make qualitative judgments and distinctions without quantitative processing. This resulted in disordered content in the monitoring protocol, non-standard design processes, and large differences. In actual use, there are problems such as insufficient logical connections and poor readability. As the basis for the design and implementation of in-station monitoring in earth stations, the above-mentioned protocol will lead to problems such as unfriendliness to users and poor continuity.

[0005] Due to the above-mentioned drawbacks in the design of traditional earth station monitoring protocols, a satellite communication earth station monitoring protocol design method based on multivariate statistics and graph clustering was designed. The method quantitatively performed statistical analysis and graph segmentation processing on equipment data to support the induction, design and implementation of the monitoring protocol, and to solve the current problems of non-standard design process, disordered content and poor continuity of satellite communication earth station monitoring protocols. Summary of the Invention

[0006] In order to solve the problems of non-standard design process of traditional earth station monitoring protocol, disordered protocol content, insufficient logical association, large differences, poor readability and poor continuity, the present invention proposes a satellite communication earth station monitoring protocol design method based on multivariate statistics and graph clustering. Detailed Description of the Invention

[0008] The technical solution of the present invention is:

[0009] A satellite communication earth station monitoring protocol design method specifically includes the following steps:

[0010] Step 1: Collect heterogeneous data of controlled devices at the earth station;

[0011] Step 2: Preprocess the heterogeneous data to obtain standardized data;

[0012] Step 3, extract features from the standardized data;

[0013] Step 4: construct a feature map based on the proposed features;

[0014] Step 5: Apply the feature graph clustering algorithm to segment the data and identify the parameter set;

[0015] Step 6: Based on the parameter characteristics, design the monitoring protocol;

[0016] Step 7: Test and evaluate the monitoring protocol;

[0017] Step 8: Optimize the monitoring protocol based on the test and evaluation results.

[0018] Furthermore, step 1 is specifically as follows:

[0019] Through sensors and equipment boards, the parameters, status and indicator data of the controlled equipment are collected, including equipment temperature, voltage, current, alarm status, working status, communication quality and power level; static data of the equipment is collected through technical documents, including factory date, serial number, equipment type and software version; based on the equipment application scenario, business process and operating habits, the remote control parameters, remote monitoring parameters, alarm parameters, alarm thresholds, health parameters and working parameters of the controlled equipment are summarized.

[0020] Furthermore, step 2 is specifically as follows:

[0021] Step 201: Data from devices of the same type with different characteristics are considered heterogeneous data.

[0022] Step 202: Clean the collected data and remove invalid and irrelevant data based on usage frequency, attention, and business relevance;

[0023] Step 203, filling in the logically missing data;

[0024] Step 204 is to standardize the data to ensure that data of different dimensions are comparable. The homogeneous attributes of the processed data include number, name, read-write attribute, change frequency, display format, range and unit.

[0025] Furthermore, in step 3, the features of the standardized data are extracted, specifically:

[0026] Step 301: Based on the standardized data obtained in step 2, a multivariate statistical method is used to analyze the data, read the data read and write and change frequency attributes, and calculate the query response time, control response time, average change time, and parameter update delay statistical characteristics;

[0027] Step 302 : Perform principal component analysis to reduce the dimension of the data and extract important features, including query response time, control response time, and average change time.

[0028] Furthermore, in step 4, a feature map is constructed, specifically:

[0029] Step 401: construct a weighted undirected graph using the extracted features, where nodes represent parameters and edges represent relationships between parameters;

[0030] Step 402 : assign weights to edges based on the degree of association, reflecting the similarity or correlation between nodes.

[0031] Furthermore, step 5 is as follows:

[0032] Step 501, applying a graph clustering algorithm to segment the graph;

[0033] Step 502: Get the aggregated result output, which is the parameter grouping;

[0034] Step 503: Analyze the characteristics of the parameter grouping and identify the collection timing, conditions and mechanism.

[0035] Furthermore, in step 6, a monitoring protocol is designed based on the parameter characteristics, specifically:

[0036] Based on the results of graph clustering, different parameter sets are obtained and their characteristics are identified; based on the data characteristics, the transmission method is determined, and the appropriate data transmission protocol, transmission channel, data type, frame format, etc. are selected to ensure reliable data transmission; based on the data characteristics, the monitoring interaction process is determined, and it is clarified whether full query, group query, single parameter query or active reporting is supported; based on the data characteristics, the monitoring frequency is determined, and the sampling interval for each parameter or each group of parameters is specified, fully considering the processing capacity of the controlled equipment, ensuring that the business process of the controlled equipment is not affected while ensuring timely data acquisition; based on the data characteristics, the alarm threshold is determined to ensure that abnormal status of the equipment is not missed or falsely reported; based on the data characteristics, the query response time and control response time are determined to ensure that users are not affected in actual application scenarios;

[0037] When designing the monitoring protocol frame format, the frame header and frame tail should be clearly defined, and the frame header and frame tail should not conflict with the frame content; the check method should be clearly defined, and long frames should use multi-byte check to improve the error frame detection rate; the data transmission byte order should be clearly defined.

[0038] Furthermore, in step 7, the monitoring protocol is tested and evaluated, specifically:

[0039] Step 701, applying the developed monitoring protocol to the monitoring interface specification between the earth station controlled equipment and the station monitoring;

[0040] Step 702: Obtain the parameters of the controlled device according to the data collection mechanism specified in the monitoring protocol;

[0041] Step 703: Evaluate the applicability of the protocol based on the data feedback, including frame error rate, false alarm rate, query response time, control response time, and parameter update delay indicators.

[0042] Furthermore, in step 8, the monitoring protocol is optimized based on the test and evaluation results, specifically:

[0043] Based on the test results, the monitoring protocol is iterated, optimized and adjusted; parameter groupings are adjusted, more efficient transmission methods are selected, query mechanisms are adjusted, monitoring frequencies are adjusted, or alarm thresholds are adjusted to improve the adaptability and effectiveness of the protocol.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] This method, combining multivariate statistics and graph clustering techniques, effectively addresses issues such as disorganized protocol content, unclear classifications, inaccurate data, and widely varying document styles, often caused by non-standardized monitoring protocol design processes. This method boasts clarity, broad applicability, and strong scalability. It effectively standardizes the design process and documented content of earth station monitoring protocols, even as the types and number of devices attached to earth stations increase significantly. This improves the adaptability and effectiveness of the protocols, allowing for optimization and expansion through iterative updates. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a flow chart provided by the implementation of the present invention;

[0047] Figure 2 This is a schematic diagram of the data collection and cleaning process provided by the present invention;

[0048] Figure 3 This is a schematic diagram of the principal component analysis process provided by the present invention;

[0049] Figure 4 It is a schematic diagram of the clustering algorithm results provided by the implementation of the present invention. DETAILED DESCRIPTION

[0050] In order to realize the present invention, an application scenario of satellite communication earth station monitoring protocol design is provided, which includes a station control computer, text editing software, etc.

[0051] The following is combined with Figure 1 , Attachment Figure 2 , Attachment Figure 3 , Attachment Figure 4 The present invention is further described.

[0052] The present invention illustrates a satellite communication earth station monitoring protocol design method based on multivariate statistics and graph clustering. The method collects data from controlled devices of the earth station and preprocesses the collected data. Feature extraction is performed on the processed standardized data to construct a feature graph. A graph clustering algorithm is applied to group the data and identify parameter sets. Based on the acquired parameter characteristics, a monitoring protocol is summarized and designed. The monitoring protocol is tested and evaluated, and it is iterated, optimized and adjusted. Finally, the design of the earth station monitoring protocol is completed.

[0053] This technology is used when it is necessary to design and formulate a satellite communication earth station monitoring protocol. The specific implementation method is as follows:

[0054] A. Data collection of controlled equipment at the earth station;

[0055] Among them, step A is specifically as follows:

[0056] A1, taking the frequency converter of the satellite communication earth station radio frequency equipment as an example, the attenuation, reference source state, crystal oscillator bias voltage and other data of the frequency converter can be read through the board card in the frequency converter case;

[0057] A2, through the technical document of the frequency converter, the factory date, factory number, software version and other information of the frequency converter can be obtained;

[0058] A3, according to the application scene, business process and operation habit of the frequency converter, the attenuation, reference source, crystal oscillator bias voltage, self-checking and other parameters are taken as remote control parameters, all data can be remotely monitored; the main module state, standby module state and alarm event are summarized as alarm data; the remote control state, main and standby state and working mode are summarized as working data; the factory date, terminal serial number and software version are summarized as static data.

[0059] B, preprocessing of the collected heterogeneous data;

[0060] Specifically, step B is:

[0061] B1, based on the data collected in step A, data with different characteristics are regarded as heterogeneous data;

[0062] B2, clean the collected data, and select the data according to the use scene and equipment technical requirements, among the collected data, the frequency, cold start, voltage value and redundancy mode are unnecessary data, which can be removed;

[0063] B3, in order to count the equipment working time and provide the life to life reminder, the cumulative power-on time parameter is added, the cumulative power-on time of the equipment is counted by the monitoring board, and the query interface of the data is provided;

[0064] B4, standardize the data to ensure the comparability of the data with different dimensions, and the homogenization attributes of the processed data include number, name, read-write attribute, change frequency, display format, range, unit, length, precision, etc.

[0065] C, feature extraction of standardized data;

[0066] Specifically, step C is:

[0067] C1, according to the preprocessing of the data in step B, the standardized data can be obtained;

[0068] C2, use multivariate statistical method to analyze the data, calculate the query response time, control response time, average change time, parameter update delay and other statistical characteristics of the data;

[0069] C3, principal component analysis (PCA) is performed to reduce the dimension of the data, and important features are extracted, including read-write attribute, change frequency, average change time, query response time, etc.

[0070] D. Construct feature maps;

[0071] Wherein, step D is specifically as follows:

[0072] D1. Use the data features extracted in step C to construct a weighted undirected graph, where nodes represent data and edges represent the relationships between data.

[0073] D2. Assign weights to edges based on the degree of association to reflect the similarity between nodes.

[0074] E. Apply feature graph clustering algorithm to segment the data;

[0075] Wherein, step E is specifically as follows:

[0076] E1, calculate the degree matrix and Laplace matrix;

[0077] E2. Select appropriate eigenvalues ​​and eigenvectors;

[0078] E3. Use K-means clustering algorithm to perform clustering in the selected feature vector space;

[0079] E4. Finally, the aggregation result is output and the graph is divided into three subgraphs. The subgraphs are parameter groups and the data points in the subgraphs are device parameters.

[0080] E5. Analyze the characteristics of parameter grouping, identify the collection timing, conditions and mechanisms, control parameter requirements before query instruction execution, refresh status parameters in real time, and query static information once the connection status changes.

[0081] F. According to the parameter characteristics, summarize and design the monitoring protocol;

[0082] Wherein, step F is specifically as follows:

[0083] F1. Based on the results of graph clustering, different parameter sets are obtained, including: device control parameters, device status parameters, and device static parameters;

[0084] F2. Based on the data characteristics, we know that the number of parameters is small, the content has high real-time requirements, the data format is relatively standardized, and it is suitable for simple short frame transmission. Therefore, we use Ethernet interface, UDP protocol, floating point number to integer transmission, and custom short frame format to ensure reliable data transmission;

[0085] F3. According to data characteristics, parameter reporting is divided into three categories: real-time parameters, static parameters, and event parameters. Therefore, a query reporting mechanism is adopted, supplemented by an event-driven active reporting mechanism for data collection. Static parameters are collected once each time the device is connected.

[0086] F4, According to the data characteristics, the real-time requirement of the parameter is in seconds, the operation ability of the device can support the minimum query interval of the monitoring service to be 0.5 seconds, therefore, the monitoring frequency of 1 second / time is adopted, while ensuring the timely acquisition of data, the business process of the controlled device is not affected;

[0087] F5, According to the data characteristics, it can be known that the BUC / BDC state and the over-temperature alarm state in the device parameter are alarm parameters, which are all enumeration type parameters, therefore, it is only necessary to judge whether the parameter value is equal to the threshold value, so as to ensure the alarm state of the device;

[0088] F6, According to the data characteristics, it can be known that the query response time and the control response time of all devices are completed within 100 milliseconds, which is far less than the query period of 1 second, therefore, in the actual application scene, the user is not sensitive;

[0089] F7, The starting symbol of the monitoring protocol frame format is 7E, and the ending symbol is 7E, in addition to the starting symbol and the ending symbol being 7EH, 7EH and 7DH in the remaining bytes need to be escaped, 7EH is escaped as 7DH and 5EH, and 7DH is escaped as 7DH and 5DH; Check: The cumulative sum of all content bytes in the parameter body is not carried over; Data is in byte units using network byte order; The parameter group framing is performed in the keyword plus length mode, and the keyword is the parameter number.

[0090] G, Test and evaluate the monitoring protocol.

[0091] Among them, step G is specifically:

[0092] G1, The station control module and the station monitoring software of the frequency converter device are programmed according to the protocol to monitor the interface, and are debugged and tested in parallel;

[0093] G2, The station monitoring software queries the parameters of the frequency converter, wherein the static parameters are queried once when the connection state of the frequency converter changes, and the event information generated by the frequency converter is reported to the station monitoring software through the event parameters;

[0094] G3, The frame loss rate and the frame error rate of the monitoring data between the frequency converter and the station monitoring software are counted; the difference in refresh frequency and data display delay between the parameters on the interface of the station monitoring software and the parameters on the panel of the frequency converter device are counted; the query response time and the control response time are counted; whether there is delay or lag when the frequency converter device performs business tasks is observed, and whether the monitoring function affects the normal work of the device is verified;

[0095] H, According to the test and evaluation results, optimize the monitoring protocol

[0096] Among them, step H is specifically:

[0097] H1, According to the test results, the control response of "self-checking" may exceed the estimated waiting time;

[0098] H2, therefore, is marked in the protocol, and a "self-check result" parameter is added. After the "self-check" control instruction is issued, the device returns a control response immediately, indicating that the instruction is executed. The value of the "self-check result" parameter is monitored in real time to determine whether the self-check is completed. Through the above changes, the protocol is iteratively updated to improve the adaptability and effectiveness of the protocol.

[0099] The above design content is recorded in the document according to the format requirements, and the monitoring protocol design is completed.

[0100] The above embodiments of the present application creatively provide a satellite communication earth station monitoring protocol design method based on multivariate statistics and atlas clustering, solve the problems of the non-standard design process of the traditional earth station monitoring protocol, the disorder of the protocol content, the insufficient logical association, the large difference, the poor readability, and the poor continuity, and improve the adaptability, effectiveness, and continuity of the protocol.

[0101] Those skilled in the art can understand that the implementation of the satellite communication earth station monitoring protocol design method based on multivariate statistics and atlas clustering can be completed by using file editing software, auxiliary software, and related hardware. When the method is executed, the steps of the above method embodiments are executed.

[0102] Finally, it should be noted that: the above only for the preferred examples of the present application, although the present application is described in detail with reference to the above embodiments, the technical solutions of the present application are not limited to this. For those skilled in the art, the technical solutions of the above embodiments can still be modified, or other parts of the technical features can be replaced. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A satellite communication earth station monitoring protocol design method based on graph clustering, characterized in that: The specific steps include: Step 1: Collect heterogeneous data of controlled devices at the earth station; Step 2: Preprocess the heterogeneous data to obtain standardized data; Step 3, extract features from the standardized data; Step 4: construct a feature map based on the proposed features; Step 5: Apply the feature graph clustering algorithm to segment the data and identify the parameter set; Step 6: Based on the parameter characteristics, design the monitoring protocol; Step 7: Test and evaluate the monitoring protocol; Step 8: Optimize the monitoring protocol based on the test and evaluation results.

2. The satellite communication earth station monitoring protocol design method based on graph clustering according to claim 1, characterized in that: Step 1 is as follows: Through sensors and equipment boards, the parameters, status and indicator data of the controlled equipment are collected, including equipment temperature, voltage, current, alarm status, working status, communication quality and power level; static data of the equipment is collected through technical documents, including factory date, serial number, equipment type and software version; based on the equipment application scenario, business process and operating habits, the remote control parameters, remote monitoring parameters, alarm parameters, alarm thresholds, health parameters and working parameters of the controlled equipment are summarized.

3. The satellite communication earth station monitoring protocol design method based on graph clustering according to claim 1, characterized in that: Step 2 is as follows: Step 201: Data from devices of the same type with different characteristics are considered heterogeneous data. Step 202: Clean the collected data and remove invalid and irrelevant data based on usage frequency, attention, and business relevance; Step 203, filling in the logically missing data; Step 204 is to standardize the data to ensure that data of different dimensions are comparable. The homogeneous attributes of the processed data include number, name, read-write attribute, change frequency, display format, range and unit.

4. The satellite communication earth station monitoring protocol design method based on graph clustering according to claim 1, characterized in that: In step 3, the features of the standardized data are extracted, specifically: Step 301: Based on the standardized data obtained in step 2, a multivariate statistical method is used to analyze the data, read the data read and write and change frequency attributes, and calculate the query response time, control response time, average change time, and parameter update delay statistical characteristics; Step 302 : Perform principal component analysis to reduce the dimension of the data and extract important features, including query response time, control response time, and average change time.

5. The satellite communication earth station monitoring protocol design method based on graph clustering according to claim 1, characterized in that: In step 4, construct a feature map, specifically: Step 401: construct a weighted undirected graph using the extracted features, where nodes represent parameters and edges represent relationships between parameters; Step 402 : assign weights to edges based on the degree of association, reflecting the similarity or correlation between nodes.

6. The method for designing a satellite communication earth station monitoring protocol based on graph clustering according to claim 1, characterized in that: Step 5 is as follows: Step 501, applying a graph clustering algorithm to segment the graph; Step 502: Get the aggregated result output, which is the parameter grouping; Step 503: Analyze the characteristics of the parameter grouping and identify the collection timing, conditions and mechanism.

7. The method for designing a satellite communication earth station monitoring protocol based on graph clustering according to claim 1, characterized in that: In step 6, the monitoring protocol is designed based on the parameter characteristics, specifically: Based on the results of graph clustering, different parameter sets are obtained and their characteristics are identified; based on the data characteristics, the transmission method is determined, and the appropriate data transmission protocol, transmission channel, data type, and frame format are selected to ensure reliable data transmission; based on the data characteristics, the monitoring interaction process is determined, and it is clarified whether full query, group query, single parameter query, or active reporting is supported; based on the data characteristics, the monitoring frequency is determined, and the sampling interval for each parameter or each group of parameters is specified, fully considering the processing capacity of the controlled equipment to ensure that the business process of the controlled equipment is not affected while ensuring timely data acquisition; based on the data characteristics, the alarm threshold is determined to ensure that abnormal status of the equipment is not missed or falsely reported; based on the data characteristics, the query response time and control response time are determined to ensure that users are not affected in actual application scenarios; The frame header and tail are clearly defined when the monitoring protocol frame format is designed. The frame header and tail should not conflict with the frame content. Clarify the verification method, use multi-byte verification for long frames to improve the error frame detection rate; the data transmission byte order should be clarified.

8. The method for designing a satellite communication earth station monitoring protocol based on graph clustering according to claim 1, characterized in that: In step 7, the monitoring protocol is tested and evaluated, specifically: Step 701, actually applying the developed monitoring protocol to the monitoring interface specification between the earth station controlled equipment and the station monitoring; Step 702: Obtain the parameters of the controlled device according to the data collection mechanism specified in the monitoring protocol; Step 703: Evaluate the applicability of the protocol based on the data feedback, including frame error rate, false alarm rate, query response time, control response time, and parameter update delay indicators.

9. The method for designing a satellite communication earth station monitoring protocol based on graph clustering according to claim 1, characterized in that: In step 8, based on the test and evaluation results, the monitoring protocol is optimized, specifically: Based on the test results, the monitoring protocol is iterated, optimized and adjusted; parameter groupings are adjusted, more efficient transmission methods are selected, query mechanisms are adjusted, monitoring frequencies are adjusted, or alarm thresholds are adjusted to improve the adaptability and effectiveness of the protocol.

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