CN-122020033-A - Automatic analysis and report generation method, equipment and medium for hydropower station operation data

CN122020033ACN 122020033 ACN122020033 ACN 122020033ACN-122020033-A

Abstract

The application discloses an automatic analysis and report generation method, equipment and medium for hydropower station operation data, which comprises the steps of S1, collecting and arranging hydropower station multi-type operation data, collecting various operation data, carrying out time sequence arrangement and synchronous processing on the collected data, S2, identifying and tracing the operation state and reasons, distinguishing the current operation state of each equipment in the hydropower station, aiming at state change, searching and combing out various reasons which cause the change, establishing a data-driven causal chain, S3, integrating and analyzing key indexes, carrying out integrated analysis on various performance indexes of each equipment and system, and self-adaptively adjusting various parameter weights according to actual operation conditions, S4, dynamically generating a report template, automatically judging the differentiated requirements of different users on report contents, and automatically selecting corresponding content modules, S5, generating and accurately pushing the report contents to users with different roles, and automatically pushing the corresponding report contents to the users with different roles.

Inventors

CHANG ZHANFENG
ZHANG QIAOFENG
ZHANG QIJUN
MAO WEIHAO
HU YANJING
HU DIE
WANG JINJIN

Assignees

三峡金沙江川云水电开发有限公司

Dates

Publication Date: 20260512
Application Date: 20260121

Claims (10)

1. The automatic analysis and report generation method for the hydropower station operation data is characterized by comprising the following steps of: S1, collecting and arranging multiple types of operation data of a hydropower station, and collecting various operation data by utilizing various existing monitoring equipment of the hydropower station; S2, identifying the running state and tracing the reasons, distinguishing the current running state of each device in the hydropower station, aiming at the state change, searching and combing out various reasons causing the change, and establishing a data-driven cause and effect chain; s3, integrating key indexes and finding out characteristics, carrying out integrated analysis on various performance indexes of various equipment and systems, and self-adaptively adjusting various parameter weights according to actual running conditions so that analysis results are more fit with current working conditions; s4, dynamically generating a report template, automatically judging the differentiated requirements of different users on report contents, and finishing key indexes focused on each user; and S5, generating and accurately pushing report contents, automatically writing report text conclusions and processing suggestions based on industry experience and historical cases and combining the analysis result, and automatically pushing corresponding report contents to users with different roles.
2. The method for automatically analyzing and reporting the operation data of hydropower station according to claim 1, wherein the step S1 of performing time sequence arrangement and synchronization processing on the collected data comprises the steps of counting the original sampling frequency of each type of equipment as follows The desired target uniform sampling frequency is And for all i satisfy Interpolation is carried out through a Lagrange interpolation method; For the following By a sliding window averaging method; For missing data, a double-domain-based autoregressive complement method is provided, namely an autoregressive model is respectively built in an original time domain and a characteristic transformation domain of acquired data, and any missing position is subjected to Determining an optimal value by combining a least square fitting method and an error minimization method; And for abnormal point detection and correction, calculating the mean value and standard deviation of each group of data under a unified window, and correcting the abnormal points by adopting a domain sliding median method.
3. The method for automatically analyzing and generating reports for hydropower station operation data according to claim 2, wherein the operation data collected in the step S1 comprises flow meters, pressure gauges, thermometers and video monitoring operation data.
4. The method for automatically analyzing and generating reports for hydropower station operation data according to claim 2, wherein the step S2 of identifying the operation state and tracing the cause comprises: For preset core performance parameters, calculating a sliding average value and a sliding standard deviation of the core performance parameters, setting a state judgment threshold value interval of each index by combining an equipment operation manual and a history threshold value, and defining the operation state at the current moment by a normal operation interval, an alarm interval and a fault interval ; And introducing a smooth discrimination mechanism of a historical state sequence, starting an automatic reason tracing flow once detecting that the equipment state is converted from normal to alarm or fault, and tracing and analyzing a change curve of a related index aiming at a state change section.
5. The method for automatic analysis and report generation of hydropower station operation data according to claim 4, wherein the step S2 of retrospectively analyzing the change curve of the related index comprises: Firstly, performing mutual information analysis on all preset core parameters, and measuring each variable Determining variables using time-lag cross-correlation analysis Whether the change of (a) precedes the state change in time , By traversing different time lags If in And is also provided with Reaching a significant peak, then it is considered that Pairs of variations of (2) Has causal guiding effect.
6. The method for automatically analyzing and reporting hydropower station operation data according to claim 5, wherein the step S3 of integrating key indexes and discovering features comprises: Setting m traditional performance indexes of each device D j , normalizing each index to a uniform scale through a maximum and minimum normalization method, and introducing an adaptive weight adjustment algorithm based on working condition clustering: Firstly, classifying historical data by using a K-means clustering method to obtain different working condition categories, counting the volatility and fault contribution degree of each index in each category, and recording the importance weight of the kth index under a certain working condition as ; The running data of the equipment at the current moment is dynamically attributed to the nearest working condition category through cluster center distance or Bayesian probability discrimination And adopts the index weight corresponding to the current category Weighting integration is carried out; designing a mechanism based on history-real-time hybrid feature generation, and mapping a multi-dimensional original index to a new low-dimensional feature space by using a principal component analysis or variation self-coding dimension reduction method to obtain a group of innovative health features considering correlation and information quantity; Dynamic statistics, slope and fluctuation novel indexes under a sliding window are adopted.
7. The method for automatically analyzing and generating reports for hydropower station operation data according to claim 1, wherein the step S4 of dynamically generating a report template comprises: According to different user identity information and historical use habits thereof, the focus of attention of the user is automatically judged, a dedicated attention subject library is established according to the user category, and according to the actual result of each analysis, a related content module is automatically matched, the report structure and the display sequence are dynamically adjusted, charts, text descriptions and key data are flexibly inserted, and the generation of a modularized and reorganizable report template is realized so as to meet the differentiated requirements of different users on report contents.
8. The method for automatically analyzing and generating reports for hydropower station operation data according to claim 1, wherein the step S5 of generating report contents and accurately pushing the report contents comprises: Based on an industry knowledge base and historical operation and maintenance cases, analysis results are summarized, text conclusion and processing suggestions are automatically generated, and corresponding report contents are accurately and timely pushed to users through mails, app notices or information system integration modes according to user roles, contact modes and configuration preferences, so that personalized information transmission and task response are realized.
9. An electronic device comprising at least one processor, and a memory communicatively coupled to the at least one processor; Wherein the memory stores instructions executable by the at least one processor, by executing the instructions stored by the memory, causing the at least one processor to perform the method of any one of claims 1 to 8.
10. A computer readable storage medium for storing instructions that, when executed, cause the method of any one of claims 1 to 8 to be implemented.

Description

Automatic analysis and report generation method, equipment and medium for hydropower station operation data Technical Field The application belongs to the field of hydropower station data processing, and particularly relates to a hydropower station operation data-oriented automatic analysis and report generation method, equipment and medium. Background With the continuous improvement of the level of intellectualization and informatization in the power industry, hydropower stations are used as important clean energy production units, and the operation safety and the economy of the hydropower stations are widely concerned. The existing hydropower station is commonly provided with a large amount of automatic and monitoring equipment, and can realize real-time acquisition of various operation data such as flow, pressure, temperature, electrical parameters and the like. However, because various devices have various sources, different data acquisition frequencies and heterogeneous data formats, time sequence alignment and comprehensive analysis of operation data have certain difficulty. In practical application, operation and maintenance personnel often need to rely on manual data arrangement and analysis, and equipment operation abnormality and reasons thereof are difficult to timely and accurately find, so that efficiency of fault response and scientificity of decision are influenced. In addition, the running reports for different users (such as operation and maintenance personnel, managers, experts and the like) are generally single in format and fixed in content, and are difficult to meet the differentiated requirements of different roles on key indexes and analysis depths. Aiming at the problems, an advanced method capable of automatically collecting and arranging multi-source heterogeneous operation data, intelligently identifying the operation state and tracing the abnormal reasons and simultaneously realizing automatic generation and pushing of personalized reports is needed so as to improve the intelligent operation and scientific management level of the hydropower station. Disclosure of Invention The invention aims to solve the technical problems of various sources, non-uniform data types and frequencies, high difficulty in information synchronization and fusion analysis, incapacitation of identifying abnormal states and tracing reasons, single report content format, difficulty in meeting different user differentiation requirements and the like of the traditional hydropower station operation data, and provides an automatic analysis and report generation method, equipment and medium for hydropower station operation data, which realize automatic acquisition and synchronous processing of multiple types of operation data, intelligently identify the operation states and abnormal reasons of the equipment, dynamically integrate key indexes and characteristics, automatically generate and accurately push personalized reports according to user identities and requirements, so as to improve the intelligent and scientific level of hydropower station operation management. On the one hand, the aim of the application is achieved by the following technical scheme: An automatic analysis and report generation method for hydropower station operation data, the automatic analysis and report generation method for hydropower station operation data comprises the following steps: S1, collecting and arranging multiple types of operation data of a hydropower station, and collecting various operation data by utilizing various existing monitoring equipment of the hydropower station; S2, identifying the running state and tracing the reasons, distinguishing the current running state of each device in the hydropower station, aiming at the state change, searching and combing out various reasons causing the change, and establishing a data-driven cause and effect chain; s3, integrating key indexes and finding out characteristics, carrying out integrated analysis on various performance indexes of various equipment and systems, and self-adaptively adjusting various parameter weights according to actual running conditions so that analysis results are more fit with current working conditions; s4, dynamically generating a report template, automatically judging the differentiated requirements of different users on report contents, and finishing key indexes focused on each user; and S5, generating and accurately pushing report contents, automatically writing report text conclusions and processing suggestions based on industry experience and historical cases and combining the analysis result, and automatically pushing corresponding report contents to users with different roles. According to a preferred embodiment, step S1 of performing a time-sequential sorting and synchronizing process on the acquired data comprises counting the original sampling frequency of each type of device asThe desired target uniform sampling frequency isAnd for all i sat