Satellite communication earth station monitoring protocol design method based on atlas clustering

Abstract

The invention designs a satellite communication earth station monitoring protocol design method based on atlas clustering, which is suitable for the field of operation and maintenance management and control of satellite communication earth stations, classified processing of controlled equipment and parameters thereof and planning and design of a monitoring protocol. A multivariate statistical analysis and atlas clustering processing scheme of monitoring data is designed to reveal the relationship and mode between the monitoring data of the earth station so as to better understand and identify different characteristics and behaviors, and the inductive design of the monitoring protocol of the earth station is realized. The method has the advantages of being clear, easy to understand, good in continuity, high in expandability and the like, and particularly can solve the problems that a current satellite communication earth station monitoring protocol is not standard in design process, disordered in protocol content, poor in 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 the earth station, and specifically 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 communication has a history of more than half a century. Due to its global coverage, no restrictions on ground obstacles, and rapid deployment, it has become one of the irreplaceable core communication means. Satellite communication technology has also become an important indicator for measuring a country's core competitiveness.

[0003] The satellite communication earth station monitoring system is an important part of satellite communication system management. The system's task is to monitor, control and manage satellite communication earth station equipment. Depending on the communication capabilities of the earth station, the types and numbers of equipment assigned to the earth station are also different, mainly including antenna equipment, tracking equipment, transmitting equipment, receiving equipment, terminal equipment, management equipment, access equipment, etc. With the development of satellite communication technology and the improvement of the requirements for earth station communication capabilities, the types and numbers of equipment assigned to the earth station have increased significantly, bringing new challenges to earth station monitoring.

[0004] The monitoring protocol is used as the interaction specification between the in-station monitoring and the controlled equipment, and as the basis for the design and implementation of equipment monitoring. It is used to constrain the data interaction between the in-station monitoring and the controlled equipment. The monitoring protocol generally constrains: transmission mode, transmission protocol, working mode, frame format and other contents. The monitoring protocol should also clarify the parameter set and parameter grouping and other contents. In the design process of previous monitoring protocols, especially when summarizing parameter grouping, they relied on the experience of designers to make qualitative judgments and distinctions without quantitative processing, resulting in disordered content contained in the monitoring protocol, non-standard design process, large differences, and insufficient logical association and poor readability in actual use. The above-mentioned protocol, as the basis for the design and implementation of in-station monitoring in the earth station, 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 to quantitatively perform statistical analysis and graph segmentation processing on equipment data, support the induction, design and implementation of monitoring protocols, and solve the problems of non-standard design process, disordered content and poor continuity of current satellite communication earth station monitoring protocol design process. 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 difference, 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 comprises the following steps:

[0010] Step 1, collecting heterogeneous data of controlled devices of 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, applying the feature graph clustering algorithm to segment the data and identify the parameter set;

[0015] Step 6, summarize and design the monitoring protocol according to the parameter characteristics;

[0016] Step 7, testing and evaluating 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 size; static data of the equipment is collected through technical documents, including factory date, serial number, equipment type and software version; according to the equipment application scenarios, business processes 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 with different characteristics from the same type of device is considered as heterogeneous data;

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

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

[0024] Step 204, 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, use multivariate statistical methods 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 , principal component analysis is performed 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, constructing a weighted undirected graph through the extracted features, wherein nodes represent parameters and edges represent associations between parameters;

[0030] Step 402, assigning weights to edges according to 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, obtaining the aggregated result output, i.e., parameter grouping;

[0034] Step 503, analyzing the characteristics of the parameter groupings to identify the collection timing, conditions and mechanisms.

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

[0036] According to the results of graph clustering, different parameter sets are obtained and their characteristics are identified; according to the data characteristics, the transmission mode is determined, and the appropriate data transmission protocol, transmission channel, data type, frame format, etc. are selected to ensure reliable data transmission; according to the data characteristics, the monitoring interaction process is determined to clarify whether full query, group query, single parameter query or active reporting is supported; according to the data characteristics, the monitoring frequency is determined, and the sampling interval of each parameter or each group of parameters is specified, and the processing capacity of the controlled equipment is fully considered to ensure that the business process of the controlled equipment is not affected while ensuring timely acquisition of data; according to the data characteristics, the alarm threshold is determined to ensure that the abnormal status of the equipment is not missed or misreported; according to 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] The frame header and frame tail should be clearly defined when designing the monitoring protocol frame format. The frame header and frame tail should not conflict with the frame content. The verification method should be clearly defined, and multi-byte verification should be used for long frames 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, actually applying the formulated monitoring protocol to the monitoring interface specification between the earth station controlled equipment and the station monitoring;

[0040] Step 702, obtaining 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 according to the test and evaluation results, specifically:

[0043] According to the test results, the monitoring protocol is iterated, optimized and adjusted; parameter grouping is adjusted, a more efficient transmission method is selected, the query mechanism is adjusted, the monitoring frequency is adjusted or the alarm threshold is 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] The present invention combines multivariate statistics and graph clustering technology to effectively solve the problems of disordered protocol content, unclear classification, inaccurate data, and large differences in writing styles caused by the non-standard design process of the monitoring protocol. The method has the characteristics of clarity, wide application range, and strong scalability. It can effectively standardize the design process and writing content of the earth station monitoring protocol under the background of a substantial increase in the types and number of earth station-attached equipment, improve the adaptability and effectiveness of the protocol, and optimize and expand it 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 It is a schematic diagram of the data collection and cleaning process provided by the implementation of the present invention;

[0048] Figure 3 It is a schematic diagram of the principal component analysis process provided by the implementation of 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 a 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 of controlled equipment of the earth station and pre-processes the collected data; extracts features from the processed standardized data, constructs a feature graph, applies a graph clustering algorithm to group the data, and identifies parameter sets; summarizes and designs a monitoring protocol based on the acquired parameter characteristics; tests and evaluates the monitoring protocol, and iterates, optimizes, and adjusts it; and finally completes the design of the earth station monitoring protocol.

[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] Wherein, step A is specifically as follows:

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

[0057] A2. Through the inverter's technical documents, you can obtain the inverter's factory date, factory number, software version and other information;

[0058] A3. According to the application scenarios, business processes and operating habits of the inverter, attenuation, reference source, crystal bias voltage, self-test, etc. are remote control parameters, and all data can be remotely monitored; the main module status, standby module status, and alarm events are summarized as alarm data; the remote control status, main and standby status, 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 collected heterogeneous data;

[0060] Wherein, step B is specifically as follows:

[0061] B1. Based on the data collected in step A, data with different characteristics are considered heterogeneous data;

[0062] B2. Clean the collected data and filter the data according to the usage scenario and equipment technical requirements. Among the collected data, the frequency, cold start, voltage value, redundant mode and other data are non-essential data and can be cleared;

[0063] B3. In order to count the working time of the equipment and provide end-of-life reminder, the cumulative power-on time parameter is added. The monitoring board realizes the statistics of the cumulative power-on time of the equipment and provides a query interface for this data;

[0064] B4. Standardize the data to ensure that data of different dimensions are comparable. The homogeneous attributes of the processed data include number, name, read-write attributes, change frequency, display format, range, unit, length, precision, etc.

[0065] C. Feature extraction of standardized data;

[0066] Wherein, step C is specifically as follows:

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

[0068] C2. Analyze data using multivariate statistical methods to calculate statistical characteristics such as query response time, control response time, average change time, parameter update delay, etc.

[0069] C3. Perform principal component analysis (PCA) to reduce the dimension of data and extract important features, including read and write attributes, 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 relationship 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 Laplacian 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 output is obtained, and the graph is divided into three sub-graphs. The sub-graphs are parameter groups, and the data points in the sub-graphs 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, status parameter requirements are refreshed in real time, and static information needs to be queried 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. According to the results of graph clustering, different parameter sets are obtained, including: equipment control parameters, equipment status parameters, and equipment static parameters;

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

[0085] F3. According to the data characteristics, parameter reporting is divided into three categories: real-time parameters, static parameters and event parameters. Therefore, the query reporting mechanism is adopted, supplemented by the 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 parameters is in seconds. The computing power of the equipment can support the minimum query interval of 0.5 seconds for monitoring services. Therefore, the monitoring frequency is 1 second / time. While ensuring timely acquisition of data, the business process of the controlled equipment is not affected.

[0087] F5. According to the data characteristics, the BUC / BDC status and over-temperature alarm status in the device parameters are alarm parameters, which are enumeration parameters. Therefore, it is only necessary to determine whether the parameter value is equal to the threshold to ensure the device alarm status.

[0088] F6. According to the data characteristics, it can be seen that the query response time and control response time of all devices are completed within 100 milliseconds, which is much less than the query cycle of 1 second. Therefore, users will not feel it in actual application scenarios.

[0089] F7, monitoring protocol frame format starts with 7E and ends with 7E. Except for the start and end characters 7EH, the remaining bytes 7EH and 7DH need to be escaped. 7EH is escaped to 7DH and 5EH, and 7DH is escaped to 7DH and 5DH. Verification: the sum of all the bytes in the parameter body is accumulated, and the high bits are not carried. The data are all in byte units using network byte order. The parameter framing is performed using the keyword plus length method, and the keyword is the parameter number.

[0090] G. Test and evaluate monitoring protocols.

[0091] Wherein, step G is specifically as follows:

[0092] G1. The station control module of the inverter equipment and the monitoring software in the station are all programmed with monitoring interfaces in accordance with the protocol and are debugged and tested in parallel;

[0093] G2. The monitoring software in the station queries the parameters of the inverter. The static parameters are queried once when the inverter connection status changes. The event information generated by the inverter is reported to the monitoring software in the station through the event parameters.

[0094] G3. Count the frame loss rate and frame error rate of monitoring data between the inverter and the monitoring software in the station; count the refresh frequency difference and data display delay between the parameters on the monitoring software interface in the station and the parameters on the inverter equipment panel; count the query response time and control response time; observe whether there is any delay or freeze when the inverter equipment performs business tasks, and verify whether the monitoring function affects the normal operation of the equipment;

[0095] H. Optimize monitoring protocols based on test and evaluation results

[0096] Wherein, step H is specifically as follows:

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

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

[0099] Record the above design content into the document according to the format requirements to complete the monitoring protocol design.

[0100] The above embodiments of the present invention have created a satellite communication earth station monitoring protocol design method based on multivariate statistics and graph clustering, which solves 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 adaptability, effectiveness and continuity of the protocol are improved.

[0101] A person skilled in the art will understand that a method for designing a satellite communication earth station monitoring protocol based on multivariate statistics and graph clustering can be implemented through file editing software, auxiliary software and related hardware. When the method is executed, the steps of the above-mentioned method embodiment are performed.

[0102] Finally, it should be noted that the above is only a preferred example of the present invention. Although the present invention is described in detail with reference to the above embodiments, the technical solution of the present invention is not limited to this. For those skilled in the art, the technical solution of the aforementioned embodiments can still be modified, or other parts of the technical features can be replaced by equivalents. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A satellite communication earth station monitoring protocol design method based on graph clustering, characterized in that: The specific steps include: Step 1, collecting heterogeneous data of controlled devices of 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, applying the feature graph clustering algorithm to segment the data and identify the parameter set; Step 6, summarize and design the monitoring protocol according to the parameter characteristics; Step 7, testing and evaluating the monitoring protocol; Step 8: Optimize the monitoring protocol based on the test and evaluation results.

2. According to the satellite communication earth station monitoring protocol design method based on graph clustering described in claim 1, it is 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 size; static data of the equipment is collected through technical documents, including factory date, serial number, equipment type and software version; according to the equipment application scenarios, business processes 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. According to the satellite communication earth station monitoring protocol design method based on graph clustering described in claim 1, it is characterized in that: Step 2 is as follows: Step 201, data with different characteristics from the same type of device is considered as heterogeneous data; Step 202, cleaning the collected data, eliminating invalid and irrelevant data based on usage frequency, attention, and business relevance; Step 203, filling in the logically missing data; Step 204, 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. According to the satellite communication earth station monitoring protocol design method based on graph clustering described in claim 1, it is 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, use multivariate statistical methods 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 , principal component analysis is performed to reduce the dimension of the data and extract important features, including query response time, control response time and average change time.

5. According to the satellite communication earth station monitoring protocol design method based on graph clustering described in claim 1, it is characterized in that: In step 4, construct a feature map, specifically: Step 401, constructing a weighted undirected graph through the extracted features, wherein nodes represent parameters and edges represent associations between parameters; Step 402, assigning weights to edges according to the degree of association, reflecting the similarity or correlation between nodes.

6. According to the satellite communication earth station monitoring protocol design method based on graph clustering described in claim 1, it is characterized in that: Step 5 is as follows: Step 501, applying a graph clustering algorithm to segment the graph; Step 502, obtaining the aggregated result output, i.e., parameter grouping; Step 503, analyzing the characteristics of the parameter groupings to identify the collection timing, conditions and mechanisms.

7. According to the satellite communication earth station monitoring protocol design method based on graph clustering described in claim 1, it is characterized in that: In step 6, the monitoring protocol is designed based on the parameter characteristics, specifically: According to the results of graph clustering, different parameter sets are obtained and their characteristics are identified; according to the data characteristics, the transmission mode is determined, and the appropriate data transmission protocol, transmission channel, data type, frame format, etc. are selected to ensure reliable data transmission; according to the data characteristics, the monitoring interaction process is determined to clarify whether full query, group query, single parameter query or active reporting is supported; according to the data characteristics, the monitoring frequency is determined, and the sampling interval of each parameter or each group of parameters is specified, and the processing capacity of the controlled equipment is fully considered to ensure that the business process of the controlled equipment is not affected while ensuring timely acquisition of data; according to the data characteristics, the alarm threshold is determined to ensure that the abnormal status of the equipment is not missed or misreported; according to 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 frame tail are clearly defined when the monitoring protocol frame format is designed. The frame header and frame 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. According to the satellite communication earth station monitoring protocol design method based on graph clustering described in claim 1, it is characterized in that: In step 7, the monitoring protocol is tested and evaluated, specifically: Step 701, actually applying the formulated monitoring protocol to the monitoring interface specification between the earth station controlled equipment and the station monitoring; Step 702, obtaining 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. According to the satellite communication earth station monitoring protocol design method based on graph clustering described in claim 1, it is characterized in that: In step 8, based on the test and evaluation results, the monitoring protocol is optimized, specifically: According to the test results, the monitoring protocol is iterated, optimized and adjusted; parameter grouping is adjusted, a more efficient transmission method is selected, the query mechanism is adjusted, the monitoring frequency is adjusted or the alarm threshold is adjusted to improve the adaptability and effectiveness of the protocol.

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