Fuel data analysis and intelligent alarm system
Through the real-time monitoring, analysis and alarm notification functions of fuel data analysis and intelligent alarm system, the problems of coal enterprises' data integration difficulties and existing systems cannot meet the user's alarm function needs are solved, and efficient data analysis and production safety guarantees are achieved.
Patent Information
- Application Number
- CN202411661859.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-20
- Publication Date
- 2025-04-11
AI Technical Summary
Coal enterprises have difficulty in integrating and integrating data due to multiple systems and data sources, resulting in inefficient data analysis and inability to detect problems and early warnings in time. The existing fuel data analysis and alarm systems cannot meet users' increasing alarm function needs, affecting production safety and efficiency.
It provides a fuel data analysis and intelligent alarm system, including an alarm configuration module, a data monitoring module, an alarm analysis module and an alarm notification module. Through the synergy of these modules, real-time monitoring, analysis and alarm notification of fuel data can be realized.
It improves the accuracy and efficiency of fuel data analysis, promptly detect abnormal situations and provide alarm notifications, prevent accidents, speed up system response speed, ensure production safety and optimize production efficiency.
Smart Images
Figure CN119807262A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of intelligent fuel analysis, and in particular to a fuel data analysis and intelligent alarm system. Background Art
[0002] The fuel data analysis and alarm system in the coal industry is of great significance and necessity in modern coal production. Through this system, the use and combustion status of fuel can be monitored in real time, abnormal situations can be discovered in time and early warnings can be issued, which helps prevent accidents and promote the sustainable development and competitiveness of the coal industry.
[0003] However, coal enterprises usually have multiple systems and data sources, which brings considerable difficulties and adjustments to data integration and consolidation, resulting in inefficient data analysis and the inability to detect problems and issue warnings in a timely manner. In addition, the current fuel data analysis and alarm systems have gradually failed to meet users' increasing demands for alarm functions, which may affect production safety and efficiency.
[0004] Therefore, the present invention provides a fuel data analysis and intelligent warning system. Summary of the invention
[0005] The present invention provides a fuel data analysis and intelligent alarm system, which is used to analyze and alarm fuel data according to user needs, improve the analysis efficiency and alarm efficiency of fuel data, timely discover and handle corresponding alarm events, and improve the safety of production operations.
[0006] The present invention provides a fuel data analysis and intelligent alarm system, comprising: An alarm configuration module, used to configure alarm parameters corresponding to the preset indicators in combination with the selected preset indicators and the obtained user configuration instructions; A data monitoring module, used to obtain the monitored fuel data related to the preset indicators in real time and output the data to be analyzed; An alarm analysis module is used to analyze the data to be analyzed by combining the alarm parameters and using a preset data analysis model, and output an alarm analysis result; The alarm notification module is used to select an alarm strategy and an alarm instruction under the corresponding strategy that match the alarm analysis result in the strategy-instruction database in combination with a preset result-strategy-instruction comparison table, and to perform an alarm notification based on the alarm strategy and alarm instruction.
[0007] Preferably, the alarm configuration module includes: The indicator selection submodule is used to obtain the indicator selection instruction input by the user, and select the corresponding preset indicator from the indicator database based on the indicator selection instruction to construct a preset indicator set; The parameter configuration submodule is used to obtain the user's configuration instructions and configure the alarm parameters corresponding to each preset indicator in the preset indicator set.
[0008] Preferably, the parameter configuration submodule includes: A field configuration unit, configured to configure the preset fields related to each preset indicator in the preset indicator set based on the configuration instruction, and output field configuration data; An alarm condition configuration unit, configured to edit an algorithm related to each preset indicator in the preset indicator set based on the configuration instruction, and output a preset alarm condition; An alarm rule configuration unit, configured to obtain, based on the configuration instruction, alarm rules matching the preset indicator set and the preset alarm condition in a rule database, and output alarm rule configuration data; The summarizing unit is used to output the alarm parameter configuration data based on the field configuration data, the preset alarm condition and the alarm detail configuration data.
[0009] Preferably, the alarm details configuration unit includes: A level-content configuration subunit, configured to obtain and configure alarm level information and alarm content information matching the preset indicator set and the preset alarm condition in the rule database, and output level-content configuration data; The policy configuration subunit is used to select and configure the alarm notification policy matching the level-content configuration data in the rule database.
[0010] Preferably, the data monitoring module includes: A data acquisition submodule, used to acquire real-time fuel data related to the preset index and output initial fuel data; A preprocessing submodule, used for preprocessing the initial fuel data and outputting it as first data; The data summary submodule is used to select historical fuel data matching the preset index from the historical database, and output the data in combination with the first data as data to be analyzed.
[0011] Preferably, the alarm analysis module includes: A model-algorithm matching submodule, used to select a preset data analysis model and a preset data analysis algorithm that match the preset indicator from the model-algorithm database; A statistical analysis submodule, used to perform statistical analysis on the data to be analyzed using a preset data analysis algorithm and output statistical analysis data; The alarm analysis submodule is used to perform alarm analysis on the data to be analyzed based on the alarm parameters and using the preset data analysis model, and summarize and output the alarm analysis results in combination with the statistical analysis data.
[0012] Preferably, the alarm analysis submodule includes: A demand acquisition unit, used to acquire the user's alarm demand information about fuel data in real time and output the alarm demand data; A feature extraction unit, used to extract features from the alarm demand information and construct a demand feature set based on the extracted features; An indicator selection unit, used to obtain a model evaluation indicator matching the required feature set in combination with a preset feature-indicator mapping table, and construct a model indicator set; A model selection unit, configured to perform model evaluation on a plurality of preset data analysis models based on the model indicator set, and output the preset data analysis models that meet the preset screening conditions as alarm analysis models; An alarm parameter input unit, used to input the alarm parameter into an alarm analysis model to generate an alarm rule; A data verification unit, configured to perform data verification on the data to be analyzed, and output the data to be analyzed that meets a preset threshold condition as second data; a format conversion unit, configured to obtain data format information of the second data and a format conversion requirement of the alarm analysis model, perform format conversion on the second data based on the format conversion requirement and using a preset data conversion method, and output third data; an alarm analysis unit, configured to perform an alarm analysis on the third data using the alarm analysis model and the alarm rule, and output a first analysis result; A result analysis unit, used for performing content analysis on the first analysis result and outputting result analysis data; A type analysis unit, used to perform type analysis on each warning information in the result analysis data and output a type analysis result; A process analysis unit, used to obtain process data of the alarm analysis result during the generation process, perform process analysis, and output the process analysis result; A source tracing analysis unit, configured to perform source tracing analysis on the result parsing data, and obtain source data corresponding to each type of alarm information in the type analysis result in combination with the third data, and output the source tracing analysis result; A summarizing unit is used to summarize the first analysis result, type analysis result, process analysis result and traceability analysis result, and output an alarm analysis result.
[0013] Preferably, the alarm notification module includes: A result analysis submodule is used to analyze the content of the alarm analysis result and construct warning analysis data based on the analyzed content; A list construction submodule, used for performing keyword matching on the warning analysis data, generating corresponding alarm events in combination with a preset keyword-event comparison table, and obtaining a first list based on the alarm events; The priority acquisition submodule is used to obtain the priority weight data corresponding to each keyword contained in each of the alarm events, and generate the priority of each of the alarm events using a preset algorithm; ; in, Indicates the priority corresponding to the i-th alarm event; represents the exponential function; Indicates the number of alarm events under the ith alarm event Error adjustment factor corresponding to each keyword; Indicates the total number of keywords contained in the i-th alarm event; represents the priority weight coefficient corresponding to the jth keyword in the i-th alarm event; Indicates the jth keyword in the i-th alarm event; Indicates the jth keyword in the i-th alarm event and other keywords except the j-th keyword The multiple correlation coefficient between keywords; A list adjustment submodule, used to sort the alarm events in the first list based on the priority corresponding to each of the alarm events, and output an alarm event list; A strategy matching submodule, used to obtain the alarm notification strategy and alarm notification instruction corresponding to each alarm event in the alarm event list in combination with a preset event-strategy-instruction comparison table; The alarm notification submodule is used to obtain the receiving terminal corresponding to the alarm notification instruction in combination with the preset instruction-terminal comparison table, and send the alarm information in the corresponding alarm event to the receiving terminal based on the alarm notification strategy and the alarm notification instruction; The alarm handling submodule is used to handle the corresponding alarm events based on the handling instructions of the preset supervision platform, and to provide real-time feedback on the alarm status change data of the alarm events, and output the alarm handling process data; The processing analysis submodule is used to analyze the effect of the alarm processing process data corresponding to each alarm event in combination with the obtained preset processing analysis indicators to obtain the processing analysis evaluation results; The alarm optimization submodule is used to optimize and adjust the preset data analysis model and the disposal instruction based on the alarm analysis result and the disposal analysis evaluation result.
[0014] The present invention provides a fuel data analysis and intelligent alarm system. The present invention realizes real-time monitoring, analysis and alarm notification of fuel data through the cooperation of an alarm configuration module, a data monitoring module, an alarm analysis module and an alarm notification module, so as to timely discover abnormal situations and take corresponding measures to ensure production safety and efficiency. The present invention can monitor fuel data in real time, improve the accuracy and efficiency of fuel data analysis, timely discover abnormal situations and issue alarm notifications, help prevent accidents, thereby speeding up the system response speed, ensuring production safety and optimizing production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.
[0016] Figure 1 It is a schematic diagram of the framework of a fuel data analysis and intelligent alarm system provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0017] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0018] like Figure 1 As shown, a fuel data analysis and intelligent alarm system provided by an embodiment of the present invention includes: An alarm configuration module is used to configure alarm parameters corresponding to the preset indicators in combination with the selected preset indicators and the obtained user configuration instructions; The data monitoring module is used to obtain the monitored fuel data related to the preset indicators in real time and output the data to be analyzed; The alarm analysis module is used to combine the alarm parameters and use the preset data analysis model to analyze the data to be analyzed and output the alarm analysis results; The alarm notification module is used to select the alarm strategy and the alarm instruction under the corresponding strategy that match the alarm analysis result in the strategy-instruction database in combination with the preset result-strategy-instruction comparison table, and to perform alarm notification based on the alarm strategy and alarm instruction.
[0019] In this embodiment, preset indicators: key indicators preset by the system for monitoring fuel data, such as temperature, pressure, flow rate, etc.; In this embodiment, user configuration instructions: alarm configuration instructions set by the user according to actual needs, used to guide the system on how to perform alarm configuration, such as setting thresholds, time intervals, etc.; In this embodiment, alarm parameters: parameters configured according to preset indicators and user configuration instructions for triggering alarms, such as exceeding a certain temperature threshold, falling below a certain pressure threshold, etc.; In this embodiment, monitoring fuel data: real-time acquired fuel data related to preset indicators for subsequent analysis and processing; In this embodiment, the data to be analyzed: the fuel data acquired by the monitoring module, the data to be analyzed for alarm; In this embodiment, the preset data analysis model: a model preset by the system for analyzing fuel data, which can analyze and generate results based on data characteristics; In this embodiment, the alarm analysis result: the result obtained after analyzing the data to be analyzed by the data analysis model, for example, used to determine whether to trigger an alarm and the alarm level, alarm category, etc.; In this embodiment, the preset result-strategy-instruction comparison table: a comparison table including the mapping relationship between the alarm analysis results and the alarm strategies and alarm instructions, is preset; In this embodiment, the strategy-instruction database: stores various alarm strategies and corresponding alarm instructions, and selects appropriate alarm strategies and alarm instructions for alarm notification according to actual conditions; In this embodiment, the alarm strategy refers to a specific strategy formulated according to the alarm analysis result, including but not limited to strategies such as how to handle the alarm, what measures to take, and how to notify the user; In this embodiment, the alarm instruction is a specific instruction formulated according to the alarm strategy, which is used to inform relevant personnel or systems to perform corresponding operations, such as sending an alarm, stopping production, etc.; Implementation principle and beneficial effects of this embodiment: The present invention realizes real-time monitoring, analysis and alarm notification of fuel data through the cooperation of the alarm configuration module, data monitoring module, alarm analysis module and alarm notification module, so as to timely discover abnormal situations and take corresponding measures to ensure production safety and efficiency. The present invention can monitor fuel data in real time, improve the accuracy and efficiency of fuel data analysis, and can timely discover abnormal situations and issue alarm notifications, which helps to prevent accidents, thereby speeding up the system response speed, ensuring production safety and optimizing production efficiency.
[0020] The embodiment of the present invention provides a fuel data analysis and intelligent alarm system, an alarm configuration module, including: The indicator selection submodule is used to obtain the indicator selection instruction input by the user, and select the corresponding preset indicator from the indicator database based on the indicator selection instruction to construct a preset indicator set; The parameter configuration submodule is used to obtain the user's configuration instructions and configure the corresponding alarm parameters of each preset indicator in the preset indicator set.
[0021] In this embodiment, the indicator selection instruction is an instruction input by the user for selecting a specific indicator. Through these instructions, the system can determine the specific indicators that need to be monitored and analyzed. For example, the user can input instructions such as "temperature" and "pressure" to select the corresponding monitoring indicators; In this embodiment, the indicator database: stores various indicator information available for selection by the system, including the name, unit, range, etc. of the indicator. The system matches the indicator selection instruction input by the user through the indicator database and selects the corresponding preset indicator from it; In this embodiment, the preset indicator set is a set of preset indicators selected from the indicator database according to the indicator selection instruction input by the user, which is used for subsequent parameter configuration and data analysis. For example, the preset indicator set may include indicators such as "temperature", "pressure", and "flow rate"; In this embodiment, configuration instructions: instructions input by the user for configuring alarm parameters, which set the alarm parameters of each indicator in the preset indicator set according to the user's needs. For example, the user can input configuration instructions such as "temperature exceeds 70 degrees Celsius" and "pressure is lower than 20psi".
[0022] The implementation principle and beneficial effects of this embodiment: The present invention cooperates with the indicator selection submodule and the parameter configuration submodule to enable users to specify monitoring indicators and configure corresponding alarm parameters, providing a basis for subsequent data monitoring and alarm analysis. The present invention can select the indicators that need to be monitored according to actual needs, and set the corresponding alarm parameters to achieve customized monitoring of specific indicators; it can achieve accurate alarm settings and detect abnormal situations in a timely manner; users can input indicator selection instructions and configuration instructions without having to deeply understand the internal operating mechanism of the system, which simplifies the operation process; according to the instructions entered by the user, the preset indicator set is quickly selected and the parameters are configured, which improves the efficiency of monitoring and alarm settings.
[0023] A fuel data analysis and intelligent alarm system provided by an embodiment of the present invention includes a parameter configuration submodule, including: A field configuration unit, configured to configure the preset fields related to each preset indicator in the preset indicator set based on the configuration instruction, and output the field configuration data; An alarm condition configuration unit, for editing the algorithm related to each preset indicator in the preset indicator set based on the configuration instruction, and outputting the preset alarm condition; An alarm rule configuration unit, used to obtain alarm rules matching a preset indicator set and a preset alarm condition in a rule database based on a configuration instruction, and output alarm rule configuration data; The summary unit is used to output alarm parameter configuration data based on field configuration data, preset alarm conditions and alarm detail configuration data.
[0024] In this embodiment, preset field: a pre-set field associated with each preset indicator in the preset indicator set, used to configure alarm parameters, for example, for the temperature indicator, the preset field may include "threshold", "unit", etc.; In this embodiment, field configuration data: data output after configuring the preset fields related to each preset indicator in the preset indicator set based on the configuration instruction, which data contains configuration information for each indicator and is used for subsequent alarm condition configuration and alarm rule configuration; In this embodiment, the preset alarm condition: the alarm condition set for each preset indicator in the preset indicator set, used to determine whether to trigger an alarm, for example, for the temperature indicator, the preset alarm condition may be "the temperature exceeds the set threshold"; In this embodiment, the rule database stores various possible alarm rule information, which is used to match corresponding alarm rules according to the preset indicator set and the preset alarm condition. For example, these rules may include specific alarm processing methods, notification objects, etc.; In this embodiment, the alarm details: specific alarm processing details obtained by matching the preset indicator set and the preset alarm condition, for example, the alarm level, notification method, processing flow, etc.; In this embodiment, the alarm rule configuration data: the alarm rule information obtained by matching the configuration instruction in the rule database, which is used for subsequent alarm parameter configuration, and these data include the alarm rule configuration information for each indicator; In this embodiment, the alarm parameter configuration data: the final alarm parameter configuration information obtained by summarizing the field configuration data, the preset alarm conditions and the alarm detail configuration data, includes the alarm conditions and alarm details of each indicator.
[0025] The implementation principle and beneficial effects of this embodiment: The present invention cooperates with each other through the field configuration unit, the alarm condition configuration unit, the alarm detail configuration unit and the summary unit to perform field configuration, alarm condition configuration and alarm detail configuration on each preset indicator in the preset indicator set, and finally outputs complete alarm parameter configuration data. The present invention can perform personalized field configuration, alarm condition configuration and alarm detail configuration on each preset indicator according to the configuration instructions input by the user, which can meet the different needs of users. Through the preset alarm conditions and alarm detail configuration, the system can make accurate alarm judgments, discover abnormal situations in time and take corresponding measures, thereby improving the accuracy and efficiency of alarms.
[0026] An embodiment of the present invention provides a fuel data analysis and intelligent alarm system, an alarm detail configuration unit, including: The level-content configuration subunit is used to obtain and configure the alarm level information and alarm content information matching the preset indicator set and the preset alarm condition in the rule database, and output the level-content configuration data; The policy configuration subunit is used to select and configure the alarm notification policy matching the level-content configuration data in the rule database.
[0027] In this embodiment, the alarm level information: different levels set for specific alarm situations, used to distinguish the importance and urgency of the alarm, for example, the alarm levels include "urgent", "important", "general", etc.; In this embodiment, alarm content information: a detailed description or information set for a specific alarm situation, used to explain the cause or content of the alarm. For example, for an alarm of a temperature exceeding a threshold, the alarm content information may be "The temperature exceeds the set threshold, please take immediate action"; In this embodiment, level-content configuration data: data of alarm level information and alarm content information matching the preset indicator set and the preset alarm condition acquired and configured in the rule database, which data is used for subsequent alarm notification strategy configuration; In this embodiment, the alarm notification strategy: the notification method and process set for different alarm levels and content information are used to notify relevant personnel or systems when an alarm occurs. The notification method may include email, text message, phone call, etc., and the notification process may include the notification object, notification frequency, etc.
[0028] The implementation principle and beneficial effects of this embodiment: The present invention obtains the alarm level information and alarm content information matching the preset indicator set and the preset alarm condition from the rule database through the coordinated action of the level-content configuration subunit and the policy configuration subunit, and configures the corresponding alarm notification strategy, so that relevant personnel or systems can be notified in a timely and effective manner when an alarm occurs. By setting the alarm level information and alarm content information, the present invention can clearly distinguish the importance and content of different alarm situations, which is conducive to rapid response and processing. At the same time, according to the level-content configuration data, the corresponding alarm notification strategy is configured, and the appropriate notification method and process can be flexibly selected to ensure that relevant personnel are informed of the alarm information in a timely manner.
[0029] The embodiment of the present invention provides a fuel data analysis and intelligent alarm system, a data monitoring module, including: The data acquisition submodule is used to acquire real-time fuel data related to preset indicators and output initial fuel data; A preprocessing submodule, used for preprocessing the initial fuel data and outputting it as first data; The data summary submodule is used to select historical fuel data matching the preset index in the historical database, and output it as data to be analyzed in combination with the first data.
[0030] In this embodiment, initial fuel data refers to real-time fuel data related to preset indicators acquired from the data acquisition submodule, that is, the original data initially acquired by the system, for example, including real-time data such as fuel temperature, pressure, flow rate, etc.; In this embodiment, preprocessing: cleaning, converting, standardizing, etc. of the initial fuel data are performed to prepare for subsequent data analysis and processing. The result of the preprocessing is the first data, and the processed data is easier to analyze and understand; In this embodiment, the first data: data obtained after being processed by the preprocessing submodule, which has been cleaned and converted, provides a basis for subsequent data analysis, for example, data obtained after denoising and data standardization of real-time fuel data; In this embodiment, the historical database: a database storing historical fuel data, including fuel data related to preset indicators collected in the past period of time, is used to analyze the change trend and historical information of the fuel data; In this embodiment, historical fuel data: past fuel data matching preset indicators selected from a historical database, used for comparison and analysis with real-time data to discover potential abnormalities or trends in fuel data; In this embodiment, the data to be analyzed is data obtained by the data summary submodule in combination with the historical fuel data and the first data, and is used for further data analysis and processing to discover regularities, trends or abnormal situations.
[0031] The implementation principle and beneficial effects of this embodiment: The present invention acquires, preprocesses and summarizes the data to be analyzed from the real-time data and historical data through the synergy of the data acquisition submodule, the preprocessing submodule and the data aggregation submodule, providing a basis for subsequent data analysis and intelligent alarm. The present invention can improve the accuracy and quality of the data by preprocessing the initial fuel data, providing a reliable data basis for subsequent analysis. At the same time, by comparing and analyzing the real-time data with the acquired historical data, potential abnormal conditions or trend changes in the fuel data can be discovered, providing support for subsequent intelligent alarms and decisions, and helping to discover problems and take measures in a timely manner.
[0032] The embodiment of the present invention provides a fuel data analysis and intelligent alarm system, an alarm analysis module, including: A model-algorithm matching submodule is used to select a preset data analysis model and a preset data analysis algorithm that match the preset indicators in the model-algorithm database; A statistical analysis submodule, used to perform statistical analysis on the data to be analyzed using a preset data analysis algorithm and output statistical analysis data; The alarm analysis submodule is used to perform alarm analysis on the data to be analyzed based on alarm parameters and using a preset data analysis model, and to summarize and output the alarm analysis results in combination with the statistical analysis data.
[0033] In this embodiment, the model-algorithm database stores various preset data analysis models and algorithms, such as a decision tree model, a support vector machine algorithm, etc. According to the characteristics of the fuel data, the system can select appropriate models and algorithms for data analysis; In this embodiment, the preset data analysis algorithm is an algorithm selected from the model-algorithm database for data analysis, such as cluster analysis, time series analysis, etc. These algorithms are selected and configured according to data characteristics and analysis requirements; In this embodiment, statistical analysis data: data obtained after processing by the statistical analysis submodule, including various statistical indicators and characteristics, used to describe the distribution and characteristics of the data. These data may include statistical indicators such as mean, standard deviation, correlation, etc., which are used to understand the distribution and characteristics of the data, for example, calculating the mean and variance of fuel temperature data, the mean value of fuel flow, the standard deviation of temperature, etc.
[0034] The implementation principle and beneficial effects of this embodiment: The present invention selects appropriate data analysis models and algorithms through the synergy of the model-algorithm matching submodule, the statistical analysis submodule and the alarm analysis submodule, performs statistical analysis and alarm analysis on the data to be analyzed, and outputs the alarm analysis results. The present invention can accurately discover potential problems or abnormal situations, improve the accuracy and timeliness of alarms, and at the same time, combined with statistical analysis data and preset algorithms, can conduct in-depth analysis of fuel data, discover the laws and trends hidden behind the data, and provide support for decision-making.
[0035] The fuel data analysis and intelligent alarm system provided by the embodiment of the present invention includes an alarm analysis submodule, which includes: A demand acquisition unit, used to acquire the user's alarm demand information about fuel data in real time and output the alarm demand data; A feature extraction unit, used to extract features from the alarm demand information and construct a demand feature set based on the extracted features; An indicator selection unit is used to obtain a model evaluation indicator that matches the required feature set in combination with a preset feature-indicator mapping table, and construct a model indicator set; A model selection unit, used to perform model evaluation on multiple preset data analysis models based on a model indicator set, and output the preset data analysis model that meets the preset screening conditions as an alarm analysis model; An alarm parameter input unit, used to input the alarm parameters into the alarm analysis model to generate alarm rules; A data verification unit, used to perform data verification on the data to be analyzed, and output the data to be analyzed that meets a preset threshold condition as second data; a format conversion unit, configured to obtain data format information of the second data and a format conversion requirement of the alarm analysis model, perform format conversion on the second data based on the format conversion requirement and using a preset data conversion method, and output third data; An alarm analysis unit, configured to perform an alarm analysis on the third data using the alarm analysis model and the alarm rule, and output a first analysis result; A result analysis unit, used to perform content analysis on the first analysis result and output result analysis data; A type analysis unit, used to perform type analysis on each alarm information in the result analysis data and output the type analysis result; The process analysis unit is used to obtain process data of the alarm analysis result during the generation process, perform process analysis, and output the process analysis result; A source tracing analysis unit, configured to perform source tracing analysis on the result parsing data, and obtain source data corresponding to each type of alarm information in the type analysis result in combination with the third data, and output the source tracing analysis result; The summarizing unit is used to summarize the first analysis result, the type analysis result, the process analysis result and the traceability analysis result, and output the alarm analysis result.
[0036] In this embodiment, alarm requirement information: alarm requirement information about fuel data provided by the user in real time, including the user's specific requirements for data analysis and alarms. For example, the user may require the system to issue an alarm when the fuel temperature exceeds a certain threshold; In this embodiment, alarm demand data: data output from the demand acquisition unit, including alarm demand information proposed by the user, which will serve as the basis for subsequent alarm analysis; In this embodiment, the demand feature set is a feature set obtained by extracting the alarm demand information through the feature extraction unit, which is used to describe the characteristics of the user's alarm demand. For example, the alarm demand information may include characteristics such as fuel flow and pressure; In this embodiment, a feature-indicator mapping table is preset: a table that maps features to specific model evaluation indicators. Through this mapping table, the system can convert demand features into model evaluation indicators; In this embodiment, model evaluation indicators: model evaluation indicators matched according to the required feature set, used to evaluate the performance of the data analysis model, for example, indicators such as accuracy and recall rate; In this embodiment, the model indicator set: a model indicator set obtained by combining the model evaluation indicator and the preset screening condition, which is used to select a preset data analysis model that meets the condition; In this embodiment, the preset screening condition: the screening condition used to select the alarm analysis model from the plurality of preset data analysis models is preset, for example, the preset data analysis model with the best comprehensive performance is selected as the subsequent alarm analysis model; In this embodiment, the alarm analysis model: a data analysis model for alarm analysis selected by the model selection unit, a model constructed according to user requirements and data characteristics; In this embodiment, the alarm rule: a rule generated according to the alarm parameter input by the alarm parameter input unit and the model indicator set, used to perform alarm analysis on the data to be analyzed; In this embodiment, the preset threshold conditions are conditions for the data verification unit to verify the data to be analyzed, and when the data meets these conditions, it will be output as the second data; In this embodiment, the second data: data that meets the preset threshold condition after verification by the data verification unit, is used as input data for alarm analysis; In this embodiment, data format information: format information of the second data, including information such as structure, type, and encoding of the data, to help the system understand how to process and parse the second data. For example, the data format information may include a data field name, a data type, etc.; In this embodiment, format conversion requirements: format requirements of the alarm analysis model for the second data, including data format conversion rules and requirements, for example, converting a timestamp into a specific time format; In this embodiment, the preset data conversion method: a data conversion method preset by the system, used to convert the second data according to the format conversion requirement, for example, converting the date format from "YYYY-MM-DD" to "MM / DD / YYYY"; In this embodiment, the third data: the data processed by the format conversion unit, has met the format requirements of the alarm analysis model and can be used for subsequent alarm analysis; In this embodiment, the first analysis result: the result obtained after the alarm analysis unit performs alarm analysis on the third data, including possible alarm information, abnormal conditions, etc.; In this embodiment, result analysis data: data obtained after content analysis of the first analysis result, to help the user understand and interpret the result of the alarm analysis; In this embodiment, the type analysis result: the result obtained after classifying and analyzing various alarm information in the result analysis data can help users understand different types of alarm situations; In this embodiment, the process analysis result: the analysis result of each step and link in the alarm analysis process helps the user understand the whole alarm analysis process and key information in the process; In this embodiment, source tracing analysis: tracing and analyzing the alarm information to find out the source and cause of the alarm information in order to better understand and handle the alarm situation; In this embodiment, source data: the original data corresponding to each type of alarm information in the type analysis result, used to support source tracing analysis and further data analysis; In this embodiment, the source tracing analysis result: the result obtained after the source data is analyzed by the source tracing analysis unit, helps the user understand the source and evolution process of the alarm information.
[0037] The implementation principle and beneficial effects of this embodiment: The present invention completes the intelligent analysis process of alarm analysis through the synergy of various sub-units, from user demand information to model selection to alarm analysis, and finally outputs the alarm analysis results. The present invention can customize the generation of alarm rules and analysis models suitable for user needs based on the alarm demand information provided by the user, thereby improving the accuracy and practicality of the alarm. At the same time, through the automated processing of various sub-units, the system can automatically provide comprehensive alarm analysis results from user needs to model selection to data analysis, helping users to better understand data status and trends, and improving the efficiency and accuracy of data analysis.
[0038] A fuel data analysis and intelligent alarm system and an alarm notification module provided by an embodiment of the present invention include: The result analysis submodule is used to analyze the content of the alarm analysis results and construct the warning analysis data based on the analyzed content; A list construction submodule is used to perform keyword matching on the warning analysis data, generate corresponding alarm events in combination with a preset keyword-event comparison table, and obtain a first list based on the alarm events; The priority acquisition submodule is used to obtain the priority weight data corresponding to each keyword contained in each alarm event, and generate the priority of each alarm event using a preset algorithm; ; in, Indicates the priority corresponding to the i-th alarm event; represents the exponential function; Indicates the number of alarm events under the ith alarm event Error adjustment factor corresponding to each keyword; Indicates the total number of keywords contained in the i-th alarm event; represents the priority weight coefficient corresponding to the jth keyword in the i-th alarm event; Indicates the jth keyword in the i-th alarm event; Indicates the jth keyword in the i-th alarm event and other keywords except the j-th keyword The multiple correlation coefficient between keywords; A list adjustment submodule, used to sort the alarm events in the first list based on the priority corresponding to each alarm event, and output the alarm event list; The strategy matching submodule is used to obtain the alarm notification strategy and alarm notification instruction corresponding to each alarm event in the alarm event list by combining the preset event-strategy-instruction comparison table; The alarm notification submodule is used to obtain the receiving terminal corresponding to the alarm notification instruction in combination with the preset instruction-terminal comparison table, and send the alarm information in the corresponding alarm event to the receiving terminal based on the alarm notification strategy and the alarm notification instruction; The alarm handling submodule is used to handle the corresponding alarm events based on the handling instructions of the preset supervision platform, and to provide real-time feedback on the alarm status change data of the alarm events, and output the alarm handling process data; The disposal analysis submodule is used to analyze the effect of the alarm disposal process data corresponding to each alarm event in combination with the obtained preset disposal analysis indicators to obtain the disposal analysis evaluation results; The alarm optimization submodule is used to optimize and adjust the preset data analysis model and disposal instructions based on the alarm analysis results and disposal analysis and evaluation results.
[0039] In this embodiment, warning analysis data: data obtained by content analysis of the alarm analysis result by the result analysis submodule, which contains key information and content, and is helpful for subsequent processing and analysis; In this embodiment, the keyword matching: list building submodule matches keywords in the warning parsing data to identify and generate corresponding alarm events, which helps the system automatically identify and classify alarm information; In this embodiment, a preset keyword-event comparison table: a correspondence table between keywords and events preset by the system, used to assist keyword matching and generate corresponding alarm events, for example, the keyword "fault" corresponds to the event "equipment failure"; In this embodiment, alarm event: a specific alarm event identified and generated by the system, including alarm-related information and content, used to notify users or relevant personnel to take corresponding measures; In this embodiment, the first list: the alarm event list sorted by the list adjustment submodule is sorted according to priority for subsequent processing and notification; In this embodiment, priority weight data: priority weight coefficients corresponding to each keyword in each alarm event, used to calculate the priority of each alarm event, these weight data affect the order and processing priority of the alarm event; In this embodiment, the preset algorithm: an algorithm set according to system requirements and specific circumstances, used to calculate the priority of each alarm event. In this example, a given formula is used to calculate the priority of the alarm event; In this embodiment, the alarm event list: a set of alarm events processed by the priority acquisition submodule and the list adjustment submodule, a list arranged in order of priority, for subsequent notification and processing; In this embodiment, the alarm notification strategy refers to the notification method and rules formulated for a specific alarm event, including the object of notification, the method of notification, the frequency of notification, etc. For example, for a high-priority alarm event, the notification strategy may require that the relevant engineer be notified immediately; In this embodiment, the alarm notification instruction: a specific notification instruction for each alarm event determined according to a preset event-strategy-instruction comparison table, which is used to inform the notification submodule to send the corresponding alarm information. For example, for an equipment failure alarm, the notification instruction may include sending a text message to notify relevant personnel; In this embodiment, receiving terminal: a device or terminal that receives the alarm notification, which may be a mobile phone, a computer, a monitoring system, etc. The alarm notification submodule determines which terminals to send the alarm information to according to the preset instruction-terminal comparison table; In this embodiment, the preset supervision platform: a platform or system preset by the system for supervising and managing the alarm handling process, used to guide and supervise the processing and handling of alarm events; In this embodiment, the handling instructions: according to the specific instructions or steps for handling alarm events set by the preset supervision platform, the alarm handling submodule handles the corresponding alarm events according to these instructions; In this embodiment, alarm handling process data: data and records generated during the processing and handling of each alarm event, including processing steps, processing time, processing results and other information; In this embodiment, the preset handling analysis indicators are: indicators and standards for evaluating the effect of the alarm handling process, and for judging whether the handling is effective, timely and accurate; In this embodiment, the treatment analysis evaluation result: the evaluation result obtained based on the analysis of the treatment process data and preset indicators by the treatment analysis submodule, which is used to evaluate the effect and improvement of the treatment process.
[0040] The implementation principle and beneficial effects of this embodiment: The present invention realizes the identification, sorting and notification processing of alarm events through the synergy of a series of sub-modules, and provides a comprehensive alarm notification function. The present invention can quickly identify and sort alarm events according to priority, improve the processing efficiency and timeliness of alarm events, and at the same time, through priority weight data and preset algorithms, the system can accurately calculate the priority of each alarm event to ensure the accuracy and importance of notifications. The alarm handling process data is also analyzed through the handling analysis submodule. The system can evaluate the effect of the processing results, help optimize and improve the subsequent alarm processing process, and provide users with powerful alarm management and notification functions.
[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A fuel data analysis and intelligent warning system, characterized in that: include: An alarm configuration module, used to configure alarm parameters corresponding to the preset indicators in combination with the selected preset indicators and the obtained user configuration instructions; A data monitoring module, used to obtain the monitored fuel data related to the preset indicators in real time and output the data to be analyzed; An alarm analysis module is used to analyze the data to be analyzed by combining the alarm parameters and using a preset data analysis model, and output an alarm analysis result; The alarm notification module is used to select an alarm strategy and an alarm instruction under the corresponding strategy that match the alarm analysis result in the strategy-instruction database in combination with a preset result-strategy-instruction comparison table, and to perform an alarm notification based on the alarm strategy and alarm instruction.
2. A fuel data analysis and intelligent warning system according to claim 1, characterized in that: The alarm configuration module includes: The indicator selection submodule is used to obtain the indicator selection instruction input by the user, and select the corresponding preset indicator from the indicator database based on the indicator selection instruction to construct a preset indicator set; The parameter configuration submodule is used to obtain the user's configuration instructions and configure the alarm parameters corresponding to each preset indicator in the preset indicator set.
3. A fuel data analysis and intelligent warning system according to claim 2, characterized in that: The parameter configuration submodule includes: A field configuration unit, configured to configure the preset fields related to each preset indicator in the preset indicator set based on the configuration instruction, and output field configuration data; An alarm condition configuration unit, configured to edit an algorithm related to each preset indicator in the preset indicator set based on the configuration instruction, and output a preset alarm condition; An alarm rule configuration unit, configured to obtain, based on the configuration instruction, alarm rules matching the preset indicator set and the preset alarm condition in a rule database, and output alarm rule configuration data; The summarizing unit is used to output the alarm parameter configuration data based on the field configuration data, the preset alarm condition and the alarm detail configuration data.
4. A fuel data analysis and intelligent warning system according to claim 3, characterized in that: The alarm details configuration unit includes: A level-content configuration subunit, configured to obtain and configure alarm level information and alarm content information matching the preset indicator set and the preset alarm condition in the rule database, and output level-content configuration data; The policy configuration subunit is used to select and configure the alarm notification policy matching the level-content configuration data in the rule database.
5. A fuel data analysis and intelligent warning system according to claim 1, characterized in that: The data monitoring module comprises: A data acquisition submodule, used to acquire real-time fuel data related to the preset index and output initial fuel data; A preprocessing submodule, used for preprocessing the initial fuel data and outputting it as first data; The data summary submodule is used to select historical fuel data matching the preset index from the historical database, and output the data in combination with the first data as data to be analyzed.
6. A fuel data analysis and intelligent warning system according to claim 1, characterized in that: The alarm analysis module comprises: A model-algorithm matching submodule, used to select a preset data analysis model and a preset data analysis algorithm that match the preset indicator from the model-algorithm database; A statistical analysis submodule, used to perform statistical analysis on the data to be analyzed using a preset data analysis algorithm and output statistical analysis data; The alarm analysis submodule is used to perform alarm analysis on the data to be analyzed based on the alarm parameters and using the preset data analysis model, and summarize and output the alarm analysis results in combination with the statistical analysis data.
7. A fuel data analysis and intelligent warning system according to claim 1, characterized in that: The alarm analysis submodule includes: A demand acquisition unit, used to acquire the user's alarm demand information about fuel data in real time and output the alarm demand data; A feature extraction unit, used to extract features from the alarm demand information and construct a demand feature set based on the extracted features; An indicator selection unit, used to obtain a model evaluation indicator matching the required feature set in combination with a preset feature-indicator mapping table, and construct a model indicator set; A model selection unit, configured to perform model evaluation on a plurality of preset data analysis models based on the model indicator set, and output the preset data analysis models that meet the preset screening conditions as alarm analysis models; An alarm parameter input unit, used to input the alarm parameter into an alarm analysis model to generate an alarm rule; A data verification unit, configured to perform data verification on the data to be analyzed, and output the data to be analyzed that meets a preset threshold condition as second data; a format conversion unit, configured to obtain data format information of the second data and a format conversion requirement of the alarm analysis model, perform format conversion on the second data based on the format conversion requirement and using a preset data conversion method, and output third data; an alarm analysis unit, configured to perform an alarm analysis on the third data using the alarm analysis model and the alarm rule, and output a first analysis result; A result parsing unit, used for performing content parsing on the first analysis result and outputting result parsing data; A type analysis unit, used to perform type analysis on each warning information in the result analysis data and output a type analysis result; A process analysis unit, used to obtain process data of the alarm analysis result during the generation process, perform process analysis, and output the process analysis result; A source tracing analysis unit, configured to perform source tracing analysis on the result parsing data, and obtain source data corresponding to each type of alarm information in the type analysis result in combination with the third data, and output the source tracing analysis result; A summarizing unit is used to summarize the first analysis result, type analysis result, process analysis result and traceability analysis result, and output an alarm analysis result.
8. A fuel data analysis and intelligent warning system according to claim 1, characterized in that: Alarm notification module, including: A result analysis submodule is used to analyze the content of the alarm analysis result and construct warning analysis data based on the analyzed content; A list construction submodule, used for performing keyword matching on the warning analysis data, generating corresponding alarm events in combination with a preset keyword-event comparison table, and obtaining a first list based on the alarm events; The priority acquisition submodule is used to obtain the priority weight data corresponding to each keyword contained in each of the alarm events, and generate the priority of each of the alarm events using a preset algorithm; ； in, Indicates the priority corresponding to the i-th alarm event; represents the exponential function; Indicates the number of alarm events under the ith alarm event Error adjustment factor corresponding to each keyword; Indicates the total number of keywords contained in the i-th alarm event; represents the priority weight coefficient corresponding to the jth keyword in the i-th alarm event; Indicates the jth keyword in the i-th alarm event; Indicates the jth keyword in the i-th alarm event and other keywords except the j-th keyword The multiple correlation coefficient between keywords; A list adjustment submodule, used for sorting the alarm events in the first list based on the priority corresponding to each of the alarm events, and outputting an alarm event list; A strategy matching submodule, used to obtain the alarm notification strategy and alarm notification instruction corresponding to each alarm event in the alarm event list in combination with a preset event-strategy-instruction comparison table; The alarm notification submodule is used to obtain the receiving terminal corresponding to the alarm notification instruction in combination with the preset instruction-terminal comparison table, and send the alarm information in the corresponding alarm event to the receiving terminal based on the alarm notification strategy and the alarm notification instruction; The alarm handling submodule is used to handle the corresponding alarm events based on the handling instructions of the preset supervision platform, and to provide real-time feedback on the alarm status change data of the alarm events, and output the alarm handling process data; The processing analysis submodule is used to analyze the effect of the alarm processing process data corresponding to each alarm event in combination with the obtained preset processing analysis indicators to obtain the processing analysis evaluation results; The alarm optimization submodule is used to optimize and adjust the preset data analysis model and the disposal instruction based on the alarm analysis result and the disposal analysis evaluation result.