Interactive hydropower station data analysis system based on large language model

Abstract

The invention discloses an interactive hydropower station data analysis system based on a large language model, and particularly relates to the technical field of hydroelectric generating set data analysis. The system comprises a language acquisition and recognition module, a user input analysis module, a speech recognition module, a speech recognition module, a speech recognition module, a speech recognition module, a speech recognition module and a speech recognition module, the natural language SQL generation module is used for extracting keywords to generate cue words and substituting the cue words into a large model for query; and the chart display module is used for displaying returned data in a chart form. According to the invention, through a natural language processing technology, a hydropower operator without a programming technology can easily carry out data query and analysis in a dialogue mode. The innovative mode not only simplifies the process of data analysis, but also enables more people to participate in the decision-making of data driving.

Description

Technical Field

[0001] The invention relates to the technical field of hydropower unit data analysis, and in particular to an interactive hydropower station data analysis system based on a large language model. Background Art

[0002] With the optimization of the global energy structure and the growth of clean energy demand, hydropower, as an important renewable energy, occupies an important position in the power system. Especially driven by UHV projects and smart grid technologies, the functions of hydropower units are no longer limited to traditional power generation tasks, but are gradually shifting to complex functions such as peak load regulation and frequency regulation. In order to adapt to the fluctuations in grid demand, the frequency and depth of regulation of hydropower units have increased significantly. This high-frequency and high-intensity operation mode makes the equipment more susceptible to factors such as erosion, wear, and fatigue.

[0003] Long-term operation leads to the gradual degradation of the performance of hydropower station equipment, and the aging of components may even cause serious accidents. How to use advanced technology to conduct efficient equipment monitoring and maintenance to ensure the stable operation of hydropower stations has become the focus of the hydropower industry. At present, the use of big data technology to analyze, predict and optimize the operation data of hydropower stations is an important means to achieve predictive maintenance of equipment. However, a large amount of heterogeneous monitoring data will be generated in the daily operation of hydropower stations, including hydrological data, mechanical data, hydraulic data and electrical data. How to quickly extract key information from these data and analyze them still faces many challenges.

[0004] At present, the computer monitoring system and online monitoring system of hydropower stations generate massive amounts of data every day, and the management and analysis of these data usually rely on a dedicated development team. Traditional data analysis methods usually require customized reports or programs to complete data management, processing and display. This method has the following major defects: 1. Every time a new demand or analysis dimension is added, additional development is required, which is time-consuming and labor-intensive, and it is difficult to flexibly respond to dynamic changes in the operating environment; 2. Traditional analysis tools have high technical requirements for users, and hydropower operators usually lack programming skills and cannot complete complex analysis tasks independently; 3. Hydropower station operation involves a variety of professional fields (such as hydrology, machinery, electrical, automation, etc.), and the data is scattered and complex in form, making it difficult to achieve efficient integration and utilization across fields 4. Traditional data analysis tools often lack immediacy and are difficult to meet the needs of hydropower stations in predictive maintenance and real-time regulation. To solve the above problems, we provide an interactive hydropower station data analysis system based on a large language model. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art and to propose an interactive hydropower station data analysis system based on a large language model.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] An interactive hydropower station data analysis system based on a large language model includes a language acquisition and recognition module for converting speech recognition into suitable text, a user input parsing module for converting user input information into a recognizable parsed language, a natural language SQL generation module for extracting keywords to generate prompt words and bringing them into the large model for query, and a chart display module for displaying the returned data in charts.

[0008] The present invention is further configured such that: the language collection and recognition module can deploy a highly sensitive voice receiving device at the hydropower station dispatching console, which can accurately capture the user's voice input.

[0009] The present invention is further configured as follows: the language acquisition and recognition module converts the voice signal into text through the ASR system voice recognition engine and further processes the recognized text content to filter out irrelevant words or modal particles and optimize the language structure.

[0010] The present invention is further configured such that: the user input parsing module analyzes the user's voice text through an integrated large language model to identify the user's query intention.

[0011] The present invention is further configured as follows: the model extracts core keywords in user input, including device name, data attributes, time context, query conditions, etc., and can identify additional conditions in user input to provide a basis for subsequent generation of SQL statements.

[0012] The present invention is further configured as follows: the natural language SQL generation module generates Prompt words according to user intentions and keywords, inputs the Prompt words into the fine-tuned large language model, and generates SQL statements that match the user query requirements.

[0013] The present invention is further configured as follows: the SQL statement generated by the natural language SQL generation module will be automatically submitted to the system's database for query, so as to obtain the data required by the user. If the query result does not meet the user's expectations, the system allows the user to perform multiple rounds of queries by adding questions or adjusting conditions, and the natural language SQL generation module will re-optimize the SQL statement based on the user's supplementary input to ensure that the final result meets the requirements.

[0014] The present invention is further configured such that: the chart display module supports a variety of data visualization forms such as line charts, bar charts, pie charts, heat maps, etc., and users can select a suitable display method according to their needs.

[0015] The present invention is further configured such that: the chart display module can dynamically refresh the chart of the real-time monitoring data to display the latest status.

[0016] The present invention is further configured such that: the chart display module allows the user to view detailed information or adjust the display range of the chart by clicking on a data point in the chart, and the chart display module supports exporting the chart in multiple formats.

[0017] The beneficial effects of the present invention are:

[0018] This invention uses natural language processing technology to enable hydropower operators who have no programming skills to easily query and analyze data in a conversational manner. This innovative approach not only simplifies the data analysis process, but also enables more people to participate in data-driven decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic diagram of the interactive data analysis module of the hydropower unit in the present invention.

[0020] Figure 2 Schematic diagram of the intent recognition process in the present invention. DETAILED DESCRIPTION

[0021] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments, and the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0022] It should be further explained that the drawings and implementation modes of the present invention mainly describe the concept of the present invention. On the basis of this concept, the specific forms and settings of some connection relationships, positional relationships, power mechanisms, power supply systems, hydraulic systems and control systems may not be fully described. However, on the premise that those skilled in the art understand the concept of the present invention, those skilled in the art can implement the above-mentioned specific forms and settings in a well-known manner.

[0023] When an element is referred to as being "fixed to" or "disposed on" another element, it may be directly on the other element or indirectly on the other element. When an element is referred to as being "connected to" another element, it may be directly connected to the other element or indirectly connected to the other element.

[0024] The directional words "inside and outside" refer to the inside and outside relative to the outline of each component itself. The directions or positional relationships indicated by the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" are based on the directions or positional relationships shown in the drawings and are only for the convenience of describing the present invention and simplifying the description. They do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as limiting the present invention.

[0025] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" may include both "above" and "below". The device may also be positioned in other different ways, and the spatially relative descriptions used here are interpreted accordingly.

[0026] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "multiple" means two or more, and "several" means one or more, unless otherwise clearly and specifically defined.

[0027] An interactive hydropower station data analysis system based on a large language model provided by the present invention is now described.

[0028] Example 1

[0029] like Figure 1-2 As shown, an interactive hydropower station data analysis system based on a large language model includes a language acquisition and recognition module for converting speech recognition into suitable text, a user input parsing module for converting user input information into a recognizable parsed language, a natural language SQL generation module for extracting keywords to generate prompt words and bringing them into the large model for query, and a chart display module for displaying the returned data in charts;

[0030] The language acquisition and recognition module can deploy a highly sensitive voice receiving device at the hydropower station dispatching station, which can accurately capture the user's voice input;

[0031] The language acquisition and recognition module converts the voice signal into text through the ASR system voice recognition engine and further processes the recognized text content to filter out irrelevant words or modal particles and optimize the language structure;

[0032] The user input parsing module analyzes the user's voice text through an integrated large language model to identify the query intention;

[0033] The model extracts core keywords from user input, including device name, data attributes, time context, query conditions, etc., and can identify additional conditions in user input to provide a basis for subsequent generation of SQL statements;

[0034] The natural language SQL generation module generates prompt words according to user intentions and keywords, inputs them into the fine-tuned large language model, and generates SQL statements that match the user's query requirements;

[0035] The SQL statement generated by the natural language SQL generation module will be automatically submitted to the system database for query, so as to obtain the data required by the user. If the query result does not meet the user's expectations, the system allows the user to perform multiple rounds of queries by adding questions or adjusting conditions, and the natural language SQL generation module will re-optimize the SQL statement according to the user's additional input to ensure that the final result meets the requirements;

[0036] The chart display module supports multiple data visualization forms such as line charts, bar charts, pie charts, heat maps, etc. Users can choose the appropriate display method according to their needs;

[0037] The chart display module can dynamically refresh the chart for real-time monitoring data to display the latest status;

[0038] The chart display module allows users to view detailed information or adjust the display range of the chart by clicking on data points in the chart. The chart display module also supports exporting charts in multiple formats.

[0039] In the above embodiment, the operator gives a description by voice, "At present, the upper guide bearing temperature alarm of #1 hydro-turbine generator set in XX power station has occurred. Please analyze the abnormal status and cause of the upper guide bearing temperature." The system pre-segmented the instruction, extracted the equipment keywords "XX power station", "#1 hydro-turbine generator set", "upper guide bearing", and completed the upper guide bearing to "upper guide bearing bearing". By comparing "alarm, analysis, abnormal status" with the vector library, the corresponding instruction intents of "year-on-year analysis" and "trend analysis" are obtained. The recognition time intent is one week, and the above intent and keywords are combined to generate prompt words:

[0040] Prompt 1: Please generate an SQL statement for year-on-year analysis of the aggregated results of the upper conductor temperature of the #1 hydro-turbine generator unit in the XX power station in the past week.

[0041] Prompt 2: Please generate an SQL statement for trend analysis of the upper guide rail temperature of the #1 hydro-turbine generator unit in XX Power Station in the past week.

[0042] After obtaining the above prompt words, the large language model generates SQL1 and SQL2 respectively, and substitutes them into the relationship database for query and return results to generate a chart.

[0043] Working principle: When used, the present invention provides an efficient and convenient solution for hydropower station data analysis through voice input, natural language processing, automatic SQL generation and data visualization. The system first uses voice recognition technology to convert the user's natural voice input into text, and parses the user's intention through a large language model to extract core keywords (such as device name, query attributes, time context and additional conditions). Prompt words are generated by keywords and intentions, and the system automatically generates SQL statements and executes queries in the database to achieve fast and accurate data acquisition. Users can also perform multiple rounds of queries by adding questions or adjusting conditions to ensure that the results meet complex business needs.

[0044] The query results are presented in a variety of visual forms through the system's chart display module, such as line charts, bar charts, heat maps, etc., supporting real-time dynamic refresh and interactive operations to help users quickly gain insights into key data. Users can click on chart data points to view detailed information, adjust the display range, or export data for report production. This design greatly improves the user's data analysis efficiency and experience, and provides a clear and intuitive support tool for hydropower station scheduling and management.

[0045] The system is suitable for scenarios such as abnormal status analysis, trend monitoring and decision support. For example, when processing abnormal alarms, the system can generate SQL statements for year-on-year analysis and trend analysis, quickly locate the cause of the abnormality and generate visual analysis results; in trend monitoring, the system can dynamically display the change curve of equipment operating efficiency and update the latest status in real time. This modular design not only improves the efficiency of data query and analysis, but also has high flexibility and scalability, and can be widely used in various aspects of intelligent management of hydropower stations.

[0046] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0047] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0048] Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values ​​of the parts and steps described in these embodiments do not limit the scope of the present application. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship. The technology, methods and equipment known to ordinary technicians in the relevant field may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be regarded as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

Claims

1. An interactive hydropower station data analysis system based on a large language model, characterized in that: It includes a language collection and recognition module for converting voice recognition into appropriate text, a user input parsing module for converting user input information into recognizable and parsed language, a natural language SQL generation module for extracting keywords to generate prompt words and bringing them into the large model for query, and a chart display module for displaying the returned data in charts.

2. The interactive hydropower station data analysis system based on a large language model according to claim 1 is characterized in that: The language collection and recognition module can deploy a highly sensitive voice receiving device at the hydropower station dispatching console, and can accurately capture the user's voice input.

3. The interactive hydropower station data analysis system based on a large language model according to claim 1 is characterized in that: The language acquisition and recognition module converts the voice signal into text through the ASR system voice recognition engine and further processes the recognized text content to filter out irrelevant words or modal particles and optimize the language structure.

4. The interactive hydropower station data analysis system based on a large language model according to claim 1, characterized in that: The user input parsing module analyzes the user's voice text through an integrated large language model to identify the user's query intention.

5. The interactive hydropower station data analysis system based on a large language model according to claim 1, characterized in that: The model extracts core keywords in user input, including device name, data attributes, time context, query conditions, etc., and can identify additional conditions in user input to provide a basis for subsequent generation of SQL statements.

6. The interactive hydropower station data analysis system based on a large language model according to claim 1, characterized in that: The natural language SQL generation module generates prompt words according to user intentions and keywords, inputs them into the fine-tuned large language model, and generates SQL statements that match the user's query requirements.

7. The interactive hydropower station data analysis system based on a large language model according to claim 1, characterized in that: The SQL statement generated by the natural language SQL generation module will be automatically submitted to the system's database for query to obtain the data required by the user. If the query result does not meet the user's expectations, the system allows the user to perform multiple rounds of queries by adding questions or adjusting conditions, and the natural language SQL generation module will re-optimize the SQL statement based on the user's additional input to ensure that the final result meets the requirements.

8. The interactive hydropower station data analysis system based on a large language model according to claim 1, characterized in that: The chart display module supports multiple data visualization forms such as line charts, bar charts, pie charts, heat maps, etc. Users can choose the appropriate display method according to their needs.

9. The interactive hydropower station data analysis system based on a large language model according to claim 1, characterized in that: The chart display module can dynamically refresh the chart for real-time monitoring data to display the latest status.

10. The interactive hydropower station data analysis system based on a large language model according to claim 1, characterized in that: The chart display module allows users to view detailed information or adjust the display range of the chart by clicking on data points in the chart. The chart display module also supports exporting charts in multiple formats.

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