Satellite monitoring alarm method and device and medium

Abstract

The invention provides a satellite monitoring alarm method and device and a medium, and the method comprises the steps: obtaining target index data and a target index threshold value, enabling the target index threshold value to be associated with the target index data, enabling the target index threshold value to be obtained through calculation based on a pre-trained preset threshold value model, and enabling the target index threshold value to be associated with the target index data; the target index data at least comprises two of satellite telemetry data, test operation control data, core network performance data and terminal test data; performing alarm judgment on the target index data based on the target index threshold to obtain alarm information corresponding to the target index data; and performing alarm processing based on the alarm information corresponding to the target index data. Therefore, the technical problem of low accuracy of monitoring alarm in the prior art can be solved.

Description

Technical Field

[0001] This application relates to the field of satellite communication technology, specifically to a satellite monitoring and alarm method, device, and medium. Background Technology

[0002] With the rapid development of satellite communication technology, the satellite core network, as the core hub of the satellite communication system, undertakes functions such as data transmission, routing control, and resource scheduling between satellite nodes. Therefore, the satellite core network is crucial, and its stability and reliability directly affect the quality of global communication services. However, the operating environment of the satellite core network is highly dynamic, including changes in the satellite operating environment and terminal connections. When changes occur in the satellite core network environment, timely alerts and notifications to relevant personnel are necessary to understand the overall communication service status of the satellite.

[0003] Existing satellite network monitoring solutions rely on a large number of maintenance personnel to observe and collect relevant historical operational data. Threshold ranges are inferred from historical operational data and logs for monitoring and alarms. This approach is subject to uncontrollable human or experiential factors, resulting in low accuracy of monitoring and alarms. Summary of the Invention

[0004] In view of this, the embodiments of this application aim to provide a satellite monitoring and alarm method, device and medium that can solve the technical problem of low accuracy of monitoring and alarm in the prior art.

[0005] Firstly, this application provides a satellite monitoring alarm method, including: Acquire target indicator data and target indicator thresholds, wherein the target indicator thresholds are associated with the target indicator data, and the target indicator thresholds are calculated based on a pre-trained preset threshold model. The target indicator data includes at least two of the following: satellite telemetry data, telemetry and control data, core network performance data, and terminal test data. Based on the target indicator threshold, an alarm judgment is made on the target indicator data to obtain alarm information corresponding to the target indicator data; Alarm processing is performed based on the alarm information corresponding to the target indicator data.

[0006] In some embodiments, the step of performing alarm judgment on the target indicator data based on the target indicator threshold to obtain alarm information corresponding to the target indicator data includes: Based on a preset rule function, the target indicator data is combined to obtain the corresponding combined indicator data. Based on the target indicator threshold, the combined indicator data is used to make an alarm judgment to obtain the alarm information.

[0007] In some embodiments, the alarm processing based on the alarm information corresponding to the target indicator data includes: Based on the alarm information corresponding to the target indicator data, determine the alarm category and / or alarm method corresponding to the alarm information; Based on the alarm classification and / or the alarm method, the alarm information is processed. The alarm classification includes at least one of the following: information, minor, alarm, critical, and urgent. The alarm classification and the alarm method correspond one-to-one.

[0008] In some embodiments, before performing alarm processing based on the alarm information corresponding to the target indicator data, the method further includes: The alarm information is notified and suppressed; If the alarm information does not trigger the preset suppression rule corresponding to the notification suppression, the step of processing the alarm based on the alarm information corresponding to the target indicator data continues to be executed.

[0009] In some embodiments, the target indicator threshold is obtained by means of: Obtain a sample set, which includes a training set, a validation set, and a test set. The training set, the validation set, and the test set all include target multi-source data and alarm tag data corresponding to the target multi-source data. The target multi-source data is data after preprocessing the collected historical multi-source data. The preset threshold model is trained and validated based on the training set and the validation set to obtain the trained preset threshold model. The target index threshold is obtained by calculating the threshold of the test set based on the trained preset threshold model.

[0010] In some embodiments, the method further includes: Based on the target indicator data and the alarm information corresponding to the target indicator data, the preset threshold model is retrained to update the target indicator threshold.

[0011] In some embodiments, the target indicator data is obtained in the following ways: Acquire multi-source satellite data, wherein the multi-source satellite data corresponds one-to-one with the target indicator data; The target index data is obtained by fusing the multi-source satellite data.

[0012] In some embodiments, the fusion processing of the multi-source satellite data to obtain the target index data includes: The satellite multi-source data is spatiotemporally aligned to obtain the corresponding spatiotemporally aligned data; The spatiotemporal aligned data is analyzed and fused with correlation indicators to obtain the corresponding fused indicator data; The target indicator data is obtained by unifying the indicator structure of the fused indicator data.

[0013] Secondly, this application provides a satellite monitoring alarm device, comprising: The acquisition module is used to acquire target indicator data and target indicator thresholds. The target indicator thresholds are associated with the target indicator data. The target indicator thresholds are calculated based on a pre-trained preset threshold model. The target indicator data includes at least two of the following: satellite telemetry data, telemetry and control data, core network performance data, and terminal test data. The processing module is used to perform alarm judgment on the target indicator data based on the target indicator threshold, and obtain alarm information corresponding to the target indicator data; The processing module is also used to perform alarm processing based on the alarm information corresponding to the target indicator data.

[0014] For any content not introduced or described in the embodiments of this application, please refer to the relevant descriptions in the foregoing method embodiments; they will not be repeated here.

[0015] Thirdly, this application provides another satellite monitoring and alarm device, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to execute the executable instructions to implement the steps of the above-described satellite monitoring and alarm method.

[0016] Fourthly, this application provides a computer-readable storage medium storing computer program instructions thereon, which, when executed by a processor, implement the steps of the above-described satellite monitoring and alarm method.

[0017] The technical solution provided in this application embodiment can include the following beneficial effects: This application acquires target indicator data and target indicator thresholds, wherein the target indicator thresholds are associated with the target indicator data, and the target indicator thresholds are calculated based on a pre-trained preset threshold model. The target indicator data includes at least two of the following: satellite telemetry data, telemetry, tracking and command data, core network performance data, and terminal test data. Alarm judgment is performed on the target indicator data based on the target indicator thresholds to obtain alarm information corresponding to the target indicator data. Alarm processing is performed based on the alarm information corresponding to the target indicator data. Thus, this application can combine multi-source target indicator data and dynamically adaptive target indicator thresholds for satellite monitoring alarm processing, which is beneficial to improving the accuracy and reliability of monitoring alarms, and can also solve the technical problem of low accuracy in existing monitoring alarms.

[0018] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0019] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings.

[0020] Figure 1 This is a schematic diagram of the structure of a satellite monitoring and alarm system provided in an embodiment of this application.

[0021] Figure 2 This is a flowchart illustrating a satellite monitoring and alarm method provided in an embodiment of this application.

[0022] Figure 3 This is a schematic diagram of a fusion process provided in an embodiment of this application.

[0023] Figure 4 This is a schematic diagram of the structure of a satellite monitoring and alarm device provided in an embodiment of this application.

[0024] Figure 5 This is a schematic diagram of another satellite monitoring and alarm device provided in an embodiment of this application.

[0025] Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Unless otherwise defined, the technical or scientific terms used in the embodiments of this specification shall have the ordinary meaning understood by one of ordinary skill in the art to which this specification pertains. The terms "first," "second," and similar terms used in the embodiments of this specification do not indicate any order, quantity, or importance, but are merely used to avoid confusion of constituent elements.

[0028] Unless the context otherwise requires, throughout this specification, "a plurality of" means "at least two," and "including" is interpreted as open-ended or encompassing, that is, "including, but not limited to." In the description of this specification, terms such as "one embodiment," "some embodiments," "exemplary embodiment," "example," "specific example," or "some examples" are intended to indicate that a particular feature, structure, material, or characteristic associated with that embodiment or example is included in at least one embodiment or example of this specification. The illustrative representations of the above terms do not necessarily refer to the same embodiment or example.

[0029] Exemplary embodiments of the present application will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present application are shown in the drawings, it should be understood that the present application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and will fully convey the scope of the present application to those skilled in the art.

[0030] In the process of submitting this application, the applicant also discovered the following problems in existing satellite network monitoring solutions: (1) The problem of data silos. Existing solutions support a single data source, such as only collecting satellite telemetry data or core network system operation index data, lacking multi-dimensional data correlation analysis, resulting in excessive reliance on manual work and a high misjudgment rate, making it difficult to provide effective alarms.

[0031] (2) Problems with static thresholds and simple judgments. Existing solutions use a single static threshold as the basis for alarms, such as a bit error rate greater than 0.1%. This only represents the current bit error rate of the satellite and cannot objectively reflect the average bit error rate at the time of satellite transit. It is easy to cause false alarms due to data at a certain moment. Moreover, the setting of the above-mentioned static thresholds relies on human experience and cannot be applied to the dynamic changes in the satellite environment. In addition, due to signal fluctuations caused by satellite orbital period, space electromagnetic interference caused by solar activity, and tidal effects of traffic volume, static thresholds are difficult to meet the constantly changing satellite operating conditions, resulting in a high false alarm rate.

[0032] (3) Problem of inefficient alarm response. Traditional alarm methods often adopt a broadcast notification strategy, lacking an alarm sorting and classification mechanism. It is impossible to push specific alarms to relevant stakeholders at the appropriate level or in the appropriate manner. Critical alarms are easily overwhelmed, resulting in a relatively long mean time between failures and repairs. When a problem occurs in the satellite system, it may trigger multiple alarms for multiple indicators, causing a notification avalanche.

[0033] To address the aforementioned problems, this application proposes a satellite monitoring and alarm method, device, and medium. Please refer to [link / reference]. Figure 1This is a schematic diagram of the structure of a satellite monitoring and alarm system provided in an embodiment of this application. Figure 1 The system 10 shown may include a satellite 100, a gateway station 200, and a terminal 300. The terminal 300 may be a device connecting the user and the satellite 100, responsible for transmitting, for example, test data and service data, and may generate or produce corresponding terminal test data. This terminal test data may include, but is not limited to, uplink / downlink message success rates, terminal activity time, response success rates, or other terminal test data; this application does not impose further limitations on this. The gateway station 200 may be a key ground facility connecting the satellite network and the terrestrial communication network. Specifically, it may include at least one earth station 201 and a gateway station control center 202. The illustration shows two earth stations 201 as an example, but this is not a limitation; the specific number can be set and adjusted according to actual conditions, and this application does not impose further limitations on this. The earth station 201 may refer to a communication terminal station located on Earth, primarily responsible for exchanging data with the satellite 100, such as exchanging satellite telemetry data, remote control data, and service data. The aforementioned gateway station control center 202 may include a telemetry, tracking, command and control system 2021, a core network system 2022, and a core network management system 2023. The telemetry, tracking, and command control system 2021 is primarily responsible for satellite status monitoring, orbit control, and data transmission, generating or creating satellite telemetry, tracking, and command data. The core network system 2022 is primarily responsible for functions such as user data management, session management, mobility management, data transmission, and signaling processing to ensure the normal operation of the communication network. The core network management system 2023 is primarily responsible for functions such as network status monitoring, fault diagnosis, resource scheduling, policy configuration, and security management. In this application, the core network management system 2023 can obtain relevant operational index data of satellite 100 through the earth station 201, the telemetry, tracking, and command control system 2021, and the core network system 2022 to facilitate subsequent work, such as monitoring and alarms. Details will be provided below in this application and will not be elaborated here.

[0034] Based on the above embodiments, please refer to Figure 2 This is a flowchart illustrating a satellite monitoring and alarm method provided in an embodiment of this application. Figure 2 The method shown can be applied to Figure 1 The system shown (e.g.) Figure 1 In the Core Network Management System (2023), this method may include the following implementation steps: S201. Obtain target indicator data and target indicator threshold, wherein the target indicator threshold is associated with the target indicator data, and the target indicator threshold is calculated based on a pre-trained preset threshold model. The target indicator data includes at least two of the following: satellite telemetry data, telemetry, tracking and command data, core network performance data, and terminal test data.

[0035] The target performance data mentioned above in this application can refer to data related to satellites or satellite core networks, which may include, but are not limited to, at least two of the following: satellite telemetry data, telemetry, tracking, command and control (TT&C) data, core network performance data, terminal test data (also known as routine terminal data), or other custom performance data. The aforementioned satellite telemetry data can refer to telemetry data acquired through sensors mounted on the satellite, which may include, but are not limited to, satellite status, bit error rate, carrier-to-noise ratio, data collection system (DCS) link status, chipspread spectrum (CSS) link status, inter-satellite link status, or other telemetry data. The aforementioned TT&C data can refer to data acquired through the TT&C system, which may include, but are not limited to, TT&C plan status, TT&C communication quality, etc. The aforementioned core network performance data can refer to key performance indicators that measure the efficiency and quality of core network operation, which may include, but are not limited to, service status, service load status, key interface throughput, external link status, etc. The aforementioned terminal test data may refer to the indicator data generated when testing and verifying the performance, function and security of satellite communication. It may include, but is not limited to, data such as uplink and downlink message success rate, terminal active time, and response success rate. This application does not impose further limitations or details on this.

[0036] S202. Based on the target indicator threshold, perform alarm judgment on the target indicator data to obtain alarm information corresponding to the target indicator data.

[0037] This application performs alarm judgment on the above target indicator data based on the above target indicator threshold and generates corresponding alarm information.

[0038] S203. Perform alarm processing based on the alarm information corresponding to the target indicator data.

[0039] By implementing the embodiments of this application, this application obtains target indicator data and target indicator thresholds, wherein the target indicator thresholds are associated with the target indicator data, and the target indicator thresholds are calculated based on a pre-trained preset threshold model. The target indicator data includes at least two of the following: satellite telemetry data, telemetry, tracking, command and control data, core network performance data, and terminal test data. Alarm judgment is performed on the target indicator data based on the target indicator thresholds to obtain alarm information corresponding to the target indicator data. Alarm processing is then performed based on the alarm information corresponding to the target indicator data. In this way, this application can combine multi-source target indicator data and dynamically adaptive target indicator thresholds for satellite monitoring alarm processing, which is beneficial to improving the accuracy, efficiency, and reliability of monitoring alarms, while also solving the technical problem of low accuracy in existing monitoring alarms.

[0040] The following describes some specific and optional embodiments related to this application.

[0041] In step S201, this application does not limit the implementation method for obtaining the aforementioned target indicator data. For example, this application can first obtain multi-source satellite data, which corresponds one-to-one with the aforementioned target indicator data. Specifically, this data may include, but is not limited to, at least two of the following: satellite telemetry data, telemetry, tracking and command (TT&C) data, core network performance data, terminal test data, or other indicator data. This application also does not limit the implementation method for obtaining the aforementioned multi-source satellite data. For example, it can be actively collected using monitoring tools such as Prometheus or Metric, or it can receive multi-source satellite data from other devices (such as terminals or corresponding platform servers) via a network. This application does not impose further limitations or details on this. Next, this application can perform fusion processing on the aforementioned multi-source satellite data to obtain the aforementioned target indicator data. For example, please refer to... Figure 3 This is a schematic diagram of a fusion process provided in an embodiment of this application. For example... Figure 3 In this application, a data fusion engine can be used to fuse the aforementioned multi-source satellite data. This data fusion engine may include a spatiotemporal alignment module, a correlation analysis matrix, and a unified index model. Detailed implementation of these components is described below and will not be repeated here. Specifically, this application can use the spatiotemporal alignment module to perform spatiotemporal alignment on the aforementioned multi-source satellite data, thereby obtaining corresponding spatiotemporally aligned data. For example, this application can align the acquisition time of all multi-source satellite data to a reference time. This reference time can be system-defined or user-defined, such as using the acquisition time of satellite telemetry data as the reference time. For instance, the reference time for satellite telemetry data may include 2025-01-01 00:00:00 and 2025-01-01 00:10:00. The above-mentioned measurement and control data was collected at 00:04:00 on 2025-01-01. This application can process the above-mentioned measurement and control data to a reference time of 00:00:00 on 2025-01-01, which is closer in time. This application will not impose any restrictions or details on this.

[0042] Next, this application can analyze and fuse the aforementioned spatiotemporally aligned data using correlation indicators to obtain corresponding fused indicator data. Specifically, for example, this application can fuse correlated indicator data from these spatiotemporally aligned data using a pre-configured correlation analysis matrix. For instance, based on abnormally high bit error rate and abnormally high carrier-to-noise ratio indicators, this application can perform correlation analysis, inference, and fusion into satellite communication quality indicators; based on increased test terminal communication latency, core network throughput, and server load, it can infer that the core network has entered high-load operation and fuse it into corresponding core network high-load operation indicator data, etc. This application will not impose further limitations or details on these aspects.

[0043] Finally, this application can unify the indicator structure of the aforementioned fused indicator data to obtain the aforementioned target indicator data. Specifically, this application can input the aforementioned fused indicator data into a unified indicator model for structural unification, so that the aforementioned target indicator data has a unified preset structure. For example, each target indicator data includes the following field information: data source domain name, data source instance, and indicator details, etc. The indicator details may include indicator code, indicator details, indicator value, indicator type (original indicator, built-in indicator, custom indicator), benchmark collection time, and personalized information of the indicator, etc., which this application does not limit or elaborate on further. The aforementioned unified indicator model is an indicator processing model pre-configured by the system according to actual conditions, which this application does not limit or elaborate on further.

[0044] This application does not limit the implementation method for obtaining the aforementioned target indicator thresholds. For example, this application can first acquire historical multi-source data and label this historical multi-source data with corresponding alarm tags, such as manually fed-in or labeled data, like false alarms or missed alarms. The aforementioned historical multi-source data can be referred to in the foregoing introduction on satellite multi-source data or target indicator data, and this application does not impose further limitations or details. This application can store the aforementioned historical multi-source data and the corresponding alarm tag data in a historical data warehouse for convenient subsequent use. Next, this application can preprocess this historical multi-source data, such as linear missing value filling, normalization, feature processing, or other custom preprocessing, to obtain the corresponding aforementioned target multi-source data. This feature processing can include, but is not limited to, feature processing such as time features, alarm indicators, alarm thresholds, alarm feedback, etc., and can also include capturing / adding satellite-related features, such as satellite orbital altitude, transit elevation angle, terminal position, or other external environmental features, and this application does not impose further limitations on this.

[0045] Next, this application can construct a corresponding sample set based on these target multi-source data and the corresponding alarm tag data. Further, this application can divide the above sample set into corresponding training, validation, and test sets according to a preset ratio, for example, dividing 70% of the sample set into the training set, 15% into the validation set, and 15% into the test set according to time sequence. Further, this application can use the above training set and validation set to train and validate the preset threshold model to be trained, thereby obtaining a trained preset threshold model. This application does not limit the above preset threshold model, which may include, but is not limited to, models such as Long Short-Term Memory (LSTM) networks, Gated Recurrent Unit (GRU) models, Transformer self-attention mechanisms, or other custom deep learning models; this application does not impose further limitations on this. Taking the LSTM model as an example, this application can use the deep learning framework PyTorch to construct the LSTM model to be trained, train the LSTM model using the aforementioned training set, and then monitor the training process using a validation set. The accuracy of the trained LSTM model is verified by statistically analyzing the false positive rate and the false negative rate. The goal is to minimize the false positive rate while ensuring a low false negative rate, thereby obtaining a well-trained LSTM model. This application does not impose further limitations or details on this aspect. Furthermore, this application calculates the threshold for the aforementioned test set based on the pre-trained preset threshold model to obtain the aforementioned target indicator threshold. In practical applications, for example, this application can use historical satellite data from the past 48 hours as the aforementioned sample set and input it into the preset threshold model to predict the target indicator threshold for the next hour, etc. This application does not impose further limitations or details on this aspect.

[0046] In step S202, this application does not limit the specific implementation of the above alarm judgment. For example, this application can use a rule engine to call the corresponding preset rule function (such as a custom function) to flexibly combine the above target indicator data to obtain the corresponding combined indicator data; then, alarm judgment is performed based on the above combined indicator data and the above target indicator threshold. Specifically, this application can combine the target indicator threshold to perform alarm judgment on the above combined indicator data, thereby obtaining alarm information corresponding to the above target indicator data. The rule engine can be a custom rule expression formed by using the JEXL expression language engine, such as indicator fusion judgment, historical data aggregation judgment, and periodic rule indicator support. The preset rule function is a rule function pre-defined by the system according to the actual situation, which may include, but is not limited to, total, avg, max, min, rate, increase, h_sum, h_rate, or other custom or extended functions.

[0047] For example, `f.h_increase('err_rate', '5m')>0.1&f.h_avg('plan_success_rate', '5m')<0.9999` indicates that the bit error rate has increased by more than 0.1 in the past 5 minutes, and the telemetry, tracking, and command (TT&C) communication success rate within the past 5 minutes is less than 0.9999. This application uses the `increase` function and corresponding thresholds to combine and judge the bit error rate and TT&C communication success rate to obtain corresponding alarm information, such as abnormal power supply link quality. This power supply link can refer to the communication link between the satellite and the earth station; however, this application does not impose further limitations or details on this.

[0048] In an optional embodiment, to ensure model accuracy or reduce threshold error, this application may periodically or periodically retrain the aforementioned preset threshold model (such as an LSTM model) to correct the aforementioned target indicator threshold in real time and obtain an adaptive threshold with better accuracy. Specifically, for example, this application may retrain the aforementioned preset threshold model based on / utilizing the aforementioned target indicator data and the alarm information corresponding to the aforementioned target indicator data to synchronously update the aforementioned target indicator threshold, etc., and this application will not impose further limitations or descriptions on this.

[0049] In step S203, before performing alarm processing, this application can first suppress the alarm information through a notification suppression node. This notification suppression node can be pre-configured with corresponding preset suppression rules based on the actual needs of the system or user, such as configuring a threshold for alarms issued per minute. If the alarm information meets / triggers the corresponding preset suppression rules (e.g., exceeds the corresponding alarm threshold), this application can automatically perform alarm circuit breaking to prevent notification avalanche effects caused by system abnormalities / faults. Conversely, if the alarm information does not meet / not trigger the corresponding preset suppression rules, alarm processing can be performed on the alarm information.

[0050] This application does not limit the specific implementation method of the above-mentioned alarm processing. For example, this application can determine the alarm category and / or alarm method corresponding to the alarm information based on the alarm information corresponding to the above-mentioned target indicator data. Specifically, this application can classify or grade alarms based on information such as the corresponding target indicator data, the urgency of the alarm information, and the business type corresponding to the alarm information to obtain the alarm category corresponding to the above-mentioned alarm information, and then determine the corresponding alarm method (also known as alarm notification method or strategy) based on the alarm category. The above-mentioned alarm category is a category that is pre-defined by the system or user according to the actual situation. It can include, but is not limited to, any one or more of the following categories, such as information, minor, alarm, serious, urgent, or other custom alarm categories / gradings. The above-mentioned alarm categories and alarm methods correspond one-to-one, and different alarm categories correspond to different alarm methods. For example, for information and minor, alarms can be issued through platform messages and / or DingTalk notifications. For alarm, serious, and urgent, alarms can be issued in a timely manner through media such as WeChat Work, DingTalk, email, and SMS to ensure the timeliness and timeliness of alarms. Optionally, this application can also classify and determine the corresponding target maintenance personnel according to the business type corresponding to the alarm information, such as test and control maintenance personnel, core network maintenance personnel, and routine maintenance personnel; and then promptly notify the relevant maintenance personnel of the alarm information based on the above alarm methods (such as corresponding media) to carry out fault repair and dimensioning work, etc. This application does not impose too many limitations or details on this.

[0051] As can be seen, the proposed solution employs a multi-source data fusion engine that can flexibly access satellite telemetry data, telemetry and control data, core network performance data, terminal test data, etc. Through spatiotemporal alignment, it integrates data from various sources, breaking down data barriers between multiple systems, forming a correlation analysis matrix, and ultimately outputting a unified indicator model, providing a powerful data foundation for the satellite core network monitoring system. The application utilizes a rule-based engine-driven dynamic adaptive threshold scheme, which flexibly correlates real-time indicator data, historical indicator data, and manually annotated data from multiple sources to achieve adaptive iterative updates of thresholds. This significantly reduces the reliance on manual experience when setting thresholds for corresponding indicators, thereby effectively reducing the false alarm rate. Furthermore, through alarm classification and a multi-level alarm method / alarm notification mechanism, this application accurately delivers alarm information to relevant maintenance personnel through multiple channels based on business type and urgency severity, greatly improving alarm response efficiency. The circuit breaker strategy for notification suppression effectively prevents notification avalanche caused by massive alarms. In a specific embodiment, this application acquires target indicator data and target indicator thresholds, wherein the target indicator thresholds are associated with the target indicator data. The target indicator thresholds are calculated based on a pre-trained preset threshold model. The target indicator data includes at least two of the following: satellite telemetry data, telemetry, tracking and command data, core network performance data, and terminal test data. Alarm judgment is performed on the target indicator data based on the target indicator thresholds to obtain alarm information corresponding to the target indicator data. Alarm processing is then performed based on the alarm information corresponding to the target indicator data. Thus, this application can combine multi-source target indicator data and dynamically adaptive target indicator thresholds for satellite monitoring alarm processing, which is beneficial for improving the accuracy, efficiency, and reliability of monitoring alarms, while also solving the technical problem of low accuracy in existing monitoring alarms.

[0052] Based on the foregoing embodiments, please refer to Figure 4 This is a schematic diagram of the structure of a satellite monitoring and alarm device provided in an embodiment of this application. Figure 4 The apparatus 400 shown may include an acquisition module 401 and a processing module 402, wherein: The acquisition module 401 is used to acquire target indicator data and target indicator threshold. The target indicator threshold is associated with the target indicator data. The target indicator threshold is calculated based on a pre-trained preset threshold model. The target indicator data includes at least two of the following: satellite telemetry data, telemetry and control data, core network performance data, and terminal test data. The processing module 402 is used to perform alarm judgment on the target indicator data based on the target indicator threshold, and obtain alarm information corresponding to the target indicator data. The processing module 402 is also used to perform alarm processing based on the alarm information corresponding to the target indicator data.

[0053] In some embodiments, the processing module 402 is specifically used for: Based on a preset rule function, the target indicator data is combined to obtain the corresponding combined indicator data. Based on the target indicator threshold, the combined indicator data is used to make an alarm judgment to obtain the alarm information.

[0054] In some embodiments, the processing module 402 is specifically used for: Based on the alarm information corresponding to the target indicator data, determine the alarm category and / or alarm method corresponding to the alarm information; Based on the alarm classification and / or the alarm method, the alarm information is processed. The alarm classification includes at least one of the following: information, minor, alarm, critical, and urgent. The alarm classification and the alarm method correspond one-to-one.

[0055] In some embodiments, before performing alarm processing based on the alarm information corresponding to the target indicator data, the processing module 402 is specifically used for: The alarm information is notified and suppressed; If the alarm information does not trigger the preset suppression rule corresponding to the notification suppression, the step of processing the alarm based on the alarm information corresponding to the target indicator data continues to be executed.

[0056] In some embodiments, the acquisition module 401 is specifically used for: Obtain a sample set, which includes a training set, a validation set, and a test set. The training set, the validation set, and the test set all include target multi-source data and alarm tag data corresponding to the target multi-source data. The target multi-source data is data after preprocessing the collected historical multi-source data. The preset threshold model is trained and validated based on the training set and the validation set to obtain the trained preset threshold model. The target index threshold is obtained by calculating the threshold of the test set based on the trained preset threshold model.

[0057] In some embodiments, the processing module 402 is further configured to: Based on the target indicator data and the alarm information corresponding to the target indicator data, the preset threshold model is retrained to update the target indicator threshold.

[0058] In some embodiments, the acquisition module 401 is specifically used for: Acquire multi-source satellite data, wherein the multi-source satellite data corresponds one-to-one with the target indicator data; The target index data is obtained by fusing the multi-source satellite data.

[0059] In some embodiments, the acquisition module 401 is specifically used for: The satellite multi-source data is spatiotemporally aligned to obtain the corresponding spatiotemporally aligned data; The spatiotemporal aligned data is analyzed and fused with correlation indicators to obtain the corresponding fused indicator data; The target indicator data is obtained by unifying the indicator structure of the fused indicator data.

[0060] Please see Figure 5 This is a schematic diagram of another satellite monitoring and alarm device provided in an embodiment of this application. For example... Figure 5 The device shown can be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc. This electronic device can be applied to various types of computer equipment.

[0061] Reference Figure 5 The device 500 may include one or more of the following components: processing component 502, memory 504, power supply component 506, multimedia component 508, audio component 510, input / output interface 512, sensor component 514, and communication component 516.

[0062] Processing component 502 typically controls the overall operation of device 500, including operations associated with display, telephone calls, data communication, camera operation, and recording. Processing component 502 may include one or more processors 520 to execute instructions to complete all or part of the steps of the aforementioned satellite monitoring and alarm method. Furthermore, processing component 502 may include one or more modules to facilitate interaction between processing component 502 and other components. For example, processing component 502 may include a multimedia module to facilitate interaction between multimedia component 508 and processing component 502.

[0063] Memory 504 is configured to store various types of data to support the operation of device 500. Examples of such data include instructions for any application or method operating on device 500, contact data, phonebook data, messages, pictures, videos, etc. Memory 504 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0064] Power supply component 506 provides power to various components of device 500. Power supply component 506 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to device 500.

[0065] Multimedia component 508 includes a screen that provides an output interface between the device 500 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 508 includes a front-facing camera and / or a rear-facing camera. When the device 500 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0066] Audio component 510 is configured to output and / or input audio signals. For example, audio component 510 includes a microphone (MIC) configured to receive external audio signals when device 500 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 504 or transmitted via communication component 516. In some embodiments, audio component 510 also includes a speaker for outputting audio signals.

[0067] Input / output interface 512 provides an interface between processing component 502 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, start buttons, and lock buttons.

[0068] Sensor assembly 514 includes one or more sensors for providing status assessments of various aspects of device 500. For example, sensor assembly 514 may detect the on / off state of device 500, the relative positioning of components such as the display and keypad of device 500, changes in the position of device 500 or a component of device 500, the presence or absence of user contact with device 500, the orientation or acceleration / deceleration of device 500, and temperature changes of device 500. Sensor assembly 514 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 514 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 514 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0069] Communication component 516 is configured to facilitate wired or wireless communication between device 500 and other devices. Device 500 can access wireless networks based on communication standards, such as WiFi, 2G, or 3G, or combinations thereof. In one exemplary embodiment, communication component 516 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 516 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0070] In an exemplary embodiment, the apparatus 500 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the satellite monitoring and alarm method described above.

[0071] Understandably, the processor 520 in this application embodiment can be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method embodiment can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor described above can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0072] Understandably, the memory 504 in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous linked dynamic random access memory (SLDRAM), and direct rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0073] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 504 including instructions, which can be executed by the processor 520 of the device 500 to complete the above-described upper-level satellite monitoring and alarm method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0074] The aforementioned device can be a standalone electronic device or a part of a standalone electronic device. For example, in one embodiment, the device can be an integrated circuit (IC) or a chip, wherein the integrated circuit can be a single IC or a collection of multiple ICs. The chip can include, but is not limited to, the following types: GPU (Graphics Processing Unit), CPU (Central Processing Unit), FPGA (Field Programmable Gate Array), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), and SoC (System on Chip). The aforementioned integrated circuit or chip can be used to execute executable instructions (or code) to implement the aforementioned satellite monitoring and alarm method. The executable instructions can be stored in the integrated circuit or chip or obtained from other devices or equipment. For example, the integrated circuit or chip includes a processor, memory, and an interface for communicating with other devices. The executable instruction can be stored in the memory, and when the executable instruction is executed by the processor, it implements the above-mentioned satellite monitoring and alarm method; or, the integrated circuit or chip can receive the executable instruction through the interface and transmit it to the processor for execution to implement the above-mentioned satellite monitoring and alarm method.

[0075] Please see Figure 6 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. For example, as shown... Figure 6 As shown, the computer device 600 includes a memory 601 and a processor 602. The memory 601 stores executable program code 6011, and the processor 602 is used to call and execute the executable program code 6011 to perform a satellite monitoring alarm method.

[0076] This application embodiment can divide a computer device into functional modules according to the above method embodiment. For example, each module can correspond to a specific function, or two or more functions can be integrated into a processing module. The integrated module can be implemented in hardware. It should be noted that the module division in this embodiment is illustrative and only represents one logical functional division. In actual implementation, there may be other division methods. When dividing each functional module according to a specific function, the computer device may include: a processing module and a communication module, etc.

[0077] It should be noted that all relevant content of each step involved in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here. The computer device provided in this embodiment is used to execute the above-described satellite monitoring and alarm method, and therefore can achieve the same effect as the above-described implementation method.

[0078] In another exemplary embodiment, a computer program product is also provided, the computer program product comprising a computer program executable by a programmable device, the computer program having a code portion for performing the above-described satellite monitoring alarm method when executed by the programmable device.

[0079] It should be noted that the descriptions of the above embodiments of storage media, devices, and equipment are similar to the descriptions of the above method embodiments, and have similar beneficial effects. For technical details not disclosed in the embodiments of storage media, devices, and equipment of this application, please refer to the descriptions of the method embodiments of this application for understanding.

[0080] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of this application. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed in this application. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0081] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications or equivalent substitutions made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A satellite monitoring and alarm method, characterized in that, include: Acquire target indicator data and target indicator thresholds, wherein the target indicator thresholds are associated with the target indicator data, and the target indicator thresholds are calculated based on a pre-trained preset threshold model. The target indicator data includes at least two of the following: satellite telemetry data, telemetry and control data, core network performance data, and terminal test data. Based on the target indicator threshold, an alarm judgment is made on the target indicator data to obtain alarm information corresponding to the target indicator data; Alarm processing is performed based on the alarm information corresponding to the target indicator data.

2. The method according to claim 1, characterized in that, The step of performing alarm judgment on the target indicator data based on the target indicator threshold to obtain alarm information corresponding to the target indicator data includes: Based on a preset rule function, the target indicator data is combined to obtain the corresponding combined indicator data. Based on the target indicator threshold, the combined indicator data is used to make an alarm judgment to obtain the alarm information.

3. The method according to claim 1, characterized in that, The alarm processing based on the alarm information corresponding to the target indicator data includes: Based on the alarm information corresponding to the target indicator data, determine the alarm category and / or alarm method corresponding to the alarm information; Based on the alarm classification and / or the alarm method, the alarm information is processed. The alarm classification includes at least one of the following: information, minor, alarm, critical, and urgent. The alarm classification and the alarm method correspond one-to-one.

4. The method according to claim 3, characterized in that, Before performing alarm processing based on the alarm information corresponding to the target indicator data, the method further includes: The alarm information is notified and suppressed; If the alarm information does not trigger the preset suppression rule corresponding to the notification suppression, the step of processing the alarm based on the alarm information corresponding to the target indicator data continues to be executed.

5. The method according to claim 1, characterized in that, The methods for obtaining the target indicator threshold include: Obtain a sample set, which includes a training set, a validation set, and a test set. The training set, the validation set, and the test set all include target multi-source data and alarm tag data corresponding to the target multi-source data. The target multi-source data is data after preprocessing the collected historical multi-source data. The preset threshold model is trained and validated based on the training set and the validation set to obtain the trained preset threshold model. The target index threshold is obtained by calculating the threshold of the test set based on the trained preset threshold model.

6. The method according to claim 5, characterized in that, The method further includes: Based on the target indicator data and the alarm information corresponding to the target indicator data, the preset threshold model is retrained to update the target indicator threshold.

7. The method according to any one of claims 1-6, characterized in that, The methods for obtaining the target indicator data include: Acquire multi-source satellite data, wherein the multi-source satellite data corresponds one-to-one with the target indicator data; The target index data is obtained by fusing the multi-source satellite data.

8. The method according to claim 7, characterized in that, The process of fusing the multi-source satellite data to obtain the target index data includes: The satellite multi-source data is spatiotemporally aligned to obtain the corresponding spatiotemporally aligned data; The spatiotemporal aligned data is analyzed and fused with correlation indicators to obtain the corresponding fused indicator data; The target indicator data is obtained by unifying the indicator structure of the fused indicator data.

9. A satellite monitoring and alarm device, characterized in that, include: processor; A memory for storing processor-executable instructions; wherein the processor is configured to execute the executable instructions to implement the steps of the method according to any one of claims 1 to 8.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 8.

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