Online monitoring method for industrial water digital pipe network of thermal power plant

Abstract

The invention relates to the technical field of power plant equipment operation and maintenance, and provides a thermal power plant industrial water digital pipe network on-line monitoring method which comprises the following steps: acquiring and preprocessing basic operation data, water quality index data and equipment operation state data of a thermal power plant; acquiring sensor information, and detecting the sensors meeting the standard parameters; real-time data are received and grouped, and sensor operation data in corresponding time periods are detected; when the memory is insufficient, backing up the data to the cloud server, and detecting the data by using a data detection model; qualified data are substituted into a preset monitoring model, and simulation monitoring and grouping storage are carried out; and constructing an online monitoring data knowledge base, comparing the real-time monitoring data with the knowledge base, marking abnormal data and generating early warning information. According to the method, the problem of system response delay or data loss caused by large data volume in the online monitoring process of the industrial water digital pipe network of the thermal power plant is effectively solved, and the monitoring efficiency and accuracy are improved.

Description

Technical Field

[0001] The invention relates to the technical field of power plant equipment operation and maintenance, and in particular to an online monitoring method for an industrial water digital pipe network of a thermal power plant. Background Art

[0002] As one of the main places for industrial water use, thermal power plants use a huge amount of water and have strict requirements on water quality and treatment efficiency. In order to improve the use efficiency of circulating cooling water, save water resources, and reduce equipment failures and safety hazards caused by improper water treatment, thermal power plants urgently need to introduce advanced online monitoring technology to monitor the operating status of industrial water systems in real time. The online monitoring system of the digital pipeline network for industrial water in thermal power plants usually includes the following main parts: Sensor network Sensors deployed at each node of the pipeline network are used to collect parameters such as water temperature, flow, pressure, and water quality in real time. The data acquisition and transmission system is responsible for summarizing and processing the data collected by the sensors, and transmitting it to the monitoring center through wired or wireless networks. The monitoring center platform receives and stores data from each sensor for real-time analysis, early warning, and display. The platform usually has functions such as data visualization, alarm management, and historical data query.

[0003] In the actual application process of online monitoring of the digital pipeline network for industrial water in thermal power plants, there are the following technical pain points: the online monitoring system needs to process a large amount of real-time data, including parameters such as water temperature, flow, pressure, and water quality. However, in the process of online monitoring data processing of the digital pipeline network for industrial water in thermal power plants, there are problems such as large data volume and slow processing speed, which lead to system response delay or data loss. In order to solve this problem, the present invention proposes an online monitoring method for the digital pipeline network for industrial water in thermal power plants. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides an online monitoring method for a digital pipeline network of industrial water in a thermal power plant, which solves the problem of system response delay or data loss due to a large amount of data during the online monitoring of a digital pipeline network of industrial water in a thermal power plant.

[0005] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0006] The present invention provides an online monitoring method for a digital pipe network of industrial water in a thermal power plant, comprising:

[0007] Step S101, obtaining basic operation data, water quality index data and equipment operation status data of a thermal power plant, preprocessing the basic operation data, water quality index data and equipment operation status data of the thermal power plant to obtain preprocessed basic operation data, water quality index data and equipment operation status data of the thermal power plant;

[0008] Step S102, collecting sensor information in the online monitoring system of the digital pipe network for industrial water of the thermal power plant, obtaining the operation information of the sensors used online in the online monitoring system of the digital pipe network for industrial water of the thermal power plant, determining the sensors in operation according to the operation information of the sensors used online in the online monitoring system of the digital pipe network for industrial water of the thermal power plant, detecting the sensors in operation according to preset standard parameters, and obtaining the sensor equipment information that meets the standard parameters;

[0009] Step S103, receiving the real-time thermal power plant industrial monitoring data collected by the sensor equipment that meets the standard parameters, grouping the real-time thermal power plant industrial monitoring data according to the data generation time, obtaining the grouped real-time thermal power plant industrial monitoring data, retrieving the operation data of the sensor in the corresponding time period of the grouped real-time thermal power plant industrial monitoring data, detecting whether the operation data of the sensor in the corresponding time period of the grouped real-time thermal power plant industrial monitoring data meets the preset standard, and using the operation data of the sensor that meets the preset standard as the usable monitoring data;

[0010] Step S104, detecting the remaining space of the real-time running memory of the local database, when the remaining space of the real-time running memory is lower than the preset minimum running memory space, backing up the available monitoring data and uploading it to the cloud server for storage to obtain the backup available monitoring data, using the preset data detection model to detect the backup available monitoring data, and obtaining the backup available monitoring data that has passed the detection, and determining the storage data corresponding to the qualified backup available monitoring data in the local database according to the attribute data of the qualified backup available monitoring data, and when the backup available monitoring data passes the detection, deleting the storage data corresponding to the qualified backup available monitoring data in the local database;

[0011] Step S105, substitute the backup available monitoring data into the preset online monitoring model of the digital pipeline network for industrial water of the thermal power plant to obtain the online simulation monitoring result of the digital pipeline network for industrial water of the thermal power plant; if the online simulation monitoring result of the digital pipeline network for industrial water of the thermal power plant is qualified, the backup available monitoring data is grouped and stored to obtain the backup available monitoring data grouping data; cluster analysis is performed on each backup available monitoring data grouping data to obtain the backup available monitoring data clustering analysis result data set; the backup available monitoring data clustering analysis result data set is used to construct an online monitoring data knowledge base; the real-time monitoring data is received; the real-time monitoring data is grouped according to the data generation time to obtain the grouped real-time monitoring data; cluster analysis is performed on the grouped real-time monitoring data to obtain the real-time monitoring data clustering analysis result data set; the real-time monitoring data clustering analysis result data set is compared with the online monitoring data knowledge base to obtain the approximate monitoring history data; if the approximate monitoring history data corresponding to the real-time monitoring data clustering analysis result data set has fault information, the real-time monitoring data corresponding to the real-time monitoring data clustering analysis result data set is marked as abnormal data, and an early warning information is generated.

[0012] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S102 comprises:

[0013] Filter out sensors that are currently in operation from the sensor information, and call up a preset standard parameter set, where the preset standard parameter set includes the accuracy, response time, and stability index of the sensor;

[0014] Compare the real-time operating parameters of each sensor in operation with the preset standard parameters to check whether the sensor meets the preset standard parameters and obtain a comparison test result;

[0015] According to the comparison test results, sensors that meet the preset standard parameters are screened out, and a qualified sensor device information list is generated. The qualified sensor device information list includes the operating sensor information.

[0016] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S103 comprises:

[0017] For each group of real-time thermal power plant industrial monitoring data, the sensor operation data of the corresponding time period is retrieved from the sensor operation record, and the sensor operation data of the corresponding time period includes the sensor status information, performance parameters and abnormal records;

[0018] Preprocess the retrieved operation data, including data cleaning and matching the time stamps of the time synchronization monitoring data with the operation data;

[0019] The preprocessed sensor operation data is compared with the preset standards to check whether the sensor's operating status, performance indicators, etc. meet the preset requirements, including the sensor's response time, to obtain the sensor's operation data that meets the preset standards.

[0020] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S104 comprises:

[0021] Receive data detection model and backup data storage path;

[0022] Use the joblib library to load the pre-trained data detection model, read the backup data file according to the backup data storage path, and pre-process the backup data to obtain the pre-processed backup data;

[0023] The preprocessed backup data is input into the data detection model to determine whether the preprocessed backup data is qualified, to obtain the qualified backup data, and to output the qualified backup data.

[0024] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S105 comprises:

[0025] Substitute the pre-processed and tested backup usable monitoring data into the preset online monitoring model of the industrial water digital pipe network of the thermal power plant;

[0026] In the online monitoring model of the digital pipe network for industrial water in thermal power plants, the backup data can be processed to obtain the online simulation monitoring results of the digital pipe network for industrial water in thermal power plants;

[0027] According to the preset standard value, judge whether the online simulation monitoring results of the digital pipe network of industrial water in the thermal power plant are qualified;

[0028] If the online simulation monitoring results of the digital pipe network for industrial water in thermal power plants are qualified, the available monitoring data will be backed up and stored in groups;

[0029] The backup availability monitoring data is divided into different groups according to the characteristics or attributes of the backup availability monitoring data grouping data, and the grouped backup availability monitoring data is stored in a designated location.

[0030] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S105 comprises:

[0031] The backup and available monitoring data is stored in the blockchain, and the hash value corresponding to the backup and available monitoring data is generated;

[0032] After the grouped backup avail- able monitoring data is stored in a designated location, the stored backup avail- able monitoring data is randomly retrieved at a preset time period;

[0033] The randomly retrieved backup can be used to monitor the data and the corresponding data stored in the blockchain. If the data comparison results are consistent, the grouped backup can be used to monitor the data successfully.

[0034] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S105 comprises:

[0035] Compare the data set of cluster analysis results of real-time monitoring data with the online monitoring data knowledge base to obtain historical data that matches the real-time monitoring data;

[0036] Use Euclidean distance to find the closest historical data point, perform fault detection on the similar historical data found, and determine whether there is fault information;

[0037] If there is fault information, the corresponding real-time monitoring data will be marked as abnormal data;

[0038] The warning information includes detailed information of abnormal data, fault type and suggested solutions, and outputs result warning information.

[0039] The beneficial effects of the present invention are mainly reflected in the following aspects:

[0040] By preprocessing and grouping the basic operation data, water quality index data and equipment operation status data of thermal power plants, the amount of data to be processed later is reduced, and the speed and accuracy of data processing are improved. Standard parameter detection is performed on sensors, and only sensors that meet the standards are used for data collection, which improves the reliability and accuracy of data.

[0041] When the local database memory is insufficient, the available monitoring data backup will be uploaded to the cloud server, avoiding the problem of data loss caused by insufficient memory. Using cloud servers and blockchain technology to store backup data enhances data security and integrity. Through cluster analysis of real-time monitoring data and comparison with the online monitoring data knowledge base, abnormal data can be quickly identified and early warning information can be generated, which helps operation and maintenance personnel take timely measures.

[0042] The backup can be used to build an online monitoring data knowledge base based on the cluster analysis results of the monitoring data, which provides a reference for the analysis and processing of real-time monitoring data. Through a series of data processing and monitoring steps, the stability and reliability of the online monitoring system of the digital pipe network for industrial water in thermal power plants are improved, and the safety hazards caused by system failures are reduced.

[0043] Deleting the qualified backup data in the local database frees up the storage space of the local database and improves resource utilization. The generated warning information includes detailed information of abnormal data, fault type and recommended solutions, providing powerful decision support for operation and maintenance personnel.

[0044] The present invention proposes a new online monitoring method for the digital pipe network of industrial water in thermal power plants, which promotes the innovation and development of equipment operation and maintenance technology in thermal power plants. It effectively solves the technical pain points faced in the online monitoring process of the digital pipe network of industrial water in thermal power plants, improves the efficiency and accuracy of the monitoring system, and provides a strong guarantee for the safe and stable operation of thermal power plants. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0046] Figure 1 A schematic diagram of an online monitoring method for a digital pipeline network of industrial water in a thermal power plant provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] 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 in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only 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. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0048] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0049] The present invention provides an online monitoring method for a digital pipe network of industrial water in a thermal power plant, comprising:

[0050] Step S101, obtaining basic operation data, water quality index data and equipment operation status data of a thermal power plant, preprocessing the basic operation data, water quality index data and equipment operation status data of the thermal power plant to obtain preprocessed basic operation data, water quality index data and equipment operation status data of the thermal power plant;

[0051] Obtaining basic operating data of a thermal power plant involves collecting the overall operating information of the thermal power plant, including parameters such as power generation, equipment load, and energy consumption, which provides a basis for subsequent analysis and processing and helps to understand the overall operating status and performance of the thermal power plant.

[0052] Obtain water quality index data, which covers water quality parameters such as water temperature, flow, pressure, water quality components (such as pH value, dissolved oxygen, etc.). Accurate acquisition of water quality data is essential for monitoring and evaluating the health of industrial water systems and helps to detect potential water quality problems in a timely manner.

[0053] Acquiring equipment operating status data includes operating status information of pumps, valves, sensors, etc. Real-time collection of equipment status data helps to detect equipment failures or abnormalities in a timely manner and provide decision support for equipment maintenance and repair.

[0054] Data preprocessing involves cleaning, formatting, and standardizing the collected basic operating data, water quality index data, and equipment operating status data. Data preprocessing is a step to improve data quality and availability, and helps improve the accuracy and efficiency of subsequent analysis and processing.

[0055] Step S102, collecting sensor information in the online monitoring system of the digital pipe network for industrial water of the thermal power plant, obtaining the operation information of the sensors used online in the online monitoring system of the digital pipe network for industrial water of the thermal power plant, determining the sensors in operation according to the operation information of the sensors used online in the online monitoring system of the digital pipe network for industrial water of the thermal power plant, detecting the sensors in operation according to preset standard parameters, and obtaining the sensor equipment information that meets the standard parameters;

[0056] Filter out the sensors that are currently in operation from the sensor information, and call up the preset standard parameter set (including the accuracy, response time, and stability index of the sensor). Compare the real-time operating parameters of each sensor in operation with the preset standard parameters to check whether the sensor meets the preset standard parameters and obtain the comparison test results.

[0057] Based on the comparative test results, sensors that meet the preset standard parameters are screened out, and a list of qualified sensor equipment information (including operating sensor information) is generated.

[0058] Step S102 allows only sensors that are in operation and meet the performance standards to be used for data collection, thereby improving the accuracy and reliability of the data. Through the preset standard parameter detection, sensors with poor performance or failure can be discovered and eliminated in a timely manner to avoid affecting the accuracy and stability of the entire monitoring system. A list of qualified sensor equipment information is generated to provide a basis for subsequent data collection and analysis, and to improve the reliability and effectiveness of the monitoring data source.

[0059] Step S103, receiving the real-time thermal power plant industrial monitoring data collected by the sensor equipment that meets the standard parameters, grouping the real-time thermal power plant industrial monitoring data according to the data generation time, obtaining the grouped real-time thermal power plant industrial monitoring data, retrieving the operation data of the sensor in the corresponding time period of the grouped real-time thermal power plant industrial monitoring data, detecting whether the operation data of the sensor in the corresponding time period of the grouped real-time thermal power plant industrial monitoring data meets the preset standard, and using the operation data of the sensor that meets the preset standard as the usable monitoring data;

[0060] Real-time industrial monitoring data of thermal power plants is collected by sensor equipment that meets standard parameters, including water temperature, flow, pressure, water quality and other parameters.

[0061] The received real-time data will be grouped according to the time it was generated to facilitate subsequent data processing and analysis. Data grouping helps to organize data from related time periods for easy comparison and analysis. For each data group, the system will retrieve the operating data of the sensor in the corresponding time period, including the sensor's status information, performance parameters, and any abnormal records.

[0062] The retrieved sensor operation data will be compared with the preset standards to check whether the sensor's operating status, performance indicators, etc. meet the preset requirements. This step is to improve the accuracy and reliability of the data. Only the sensor operation data that meets the preset standards will be screened out as usable monitoring data. This ensures that the subsequent analysis is based on high-quality data.

[0063] By strictly testing and screening the sensor operation data, step S103 improves the quality and accuracy of the monitoring data used. Data grouping and subsequent processing steps enable a large amount of real-time data to be processed in an orderly and efficient manner, avoiding data confusion and loss. Through automated and standardized data processing procedures, step S103 improves the efficiency and accuracy of online monitoring of the digital pipe network of industrial water in thermal power plants, and helps to promptly discover and deal with potential problems.

[0064] Step S104, detecting the remaining space of the real-time running memory of the local database, when the remaining space of the real-time running memory is lower than the preset minimum running memory space, backing up the available monitoring data and uploading it to the cloud server for storage to obtain the backup available monitoring data, using the preset data detection model to detect the backup available monitoring data, and obtaining the backup available monitoring data that has passed the detection, and determining the storage data corresponding to the qualified backup available monitoring data in the local database according to the attribute data of the qualified backup available monitoring data, and when the backup available monitoring data passes the detection, deleting the storage data corresponding to the qualified backup available monitoring data in the local database;

[0065] Detect the remaining space of the local database's real-time running memory. The system will first check the remaining space of the local database's real-time running memory to evaluate whether data backup is needed. This improves the system's ability to detect insufficient memory in a timely manner and provide a basis for subsequent data backup operations.

[0066] When the remaining space of the local database real-time running memory is lower than the preset minimum running memory space, the system will back up the available monitoring data and upload it to the cloud server for storage. Through cloud storage, the system can effectively release the storage pressure of the local database and improve the security and reliability of data.

[0067] Use the preset data detection model to detect the backup data. The system will use the preset data detection model to detect the backup monitoring data to improve the accuracy and completeness of the data. This step is an important part of data quality control, which can filter out data that does not meet the requirements and improve the accuracy of subsequent data analysis.

[0068] Determine the storage data of the qualified backup data in the local database. For the qualified backup data, the system will determine its corresponding storage data in the local database. This step provides a basis for subsequent data deletion operations and improves the consistency and integrity of the data.

[0069] Delete the storage data of the qualified backup data in the local database. After the backup data has been successfully uploaded to the cloud server and passed the inspection, the system will delete the corresponding storage data in the local database. By deleting the local data, the system can further free up storage space and improve the operating efficiency of the system.

[0070] Step S104 implements data backup, detection, storage and deletion through a series of operations, thereby improving data security and reliability, and at the same time improving system operation efficiency and storage space utilization.

[0071] Step S105, substitute the backup available monitoring data into the preset online monitoring model of the digital pipeline network for industrial water of the thermal power plant to obtain the online simulation monitoring result of the digital pipeline network for industrial water of the thermal power plant; if the online simulation monitoring result of the digital pipeline network for industrial water of the thermal power plant is qualified, the backup available monitoring data is grouped and stored to obtain the backup available monitoring data grouping data; cluster analysis is performed on each backup available monitoring data grouping data to obtain the backup available monitoring data clustering analysis result data set; the backup available monitoring data clustering analysis result data set is used to construct an online monitoring data knowledge base; the real-time monitoring data is received; the real-time monitoring data is grouped according to the data generation time to obtain the grouped real-time monitoring data; cluster analysis is performed on the grouped real-time monitoring data to obtain the real-time monitoring data clustering analysis result data set; the real-time monitoring data clustering analysis result data set is compared with the online monitoring data knowledge base to obtain the approximate monitoring history data; if the approximate monitoring history data corresponding to the real-time monitoring data clustering analysis result data set has fault information, the real-time monitoring data corresponding to the real-time monitoring data clustering analysis result data set is marked as abnormal data, and an early warning information is generated.

[0072] The backup usable monitoring data that has been preprocessed and tested is substituted into the preset online monitoring model of the industrial water digital pipeline network of the thermal power plant to simulate and predict the actual operating status of the pipeline network.

[0073] After executing the online monitoring model of the digital pipeline network for industrial water in thermal power plants, the backup can be processed using the monitoring data to obtain simulated monitoring results, and the qualification of the results can be judged according to the preset standard values, thereby verifying the accuracy of the data and the reliability of the model.

[0074] If the simulation monitoring results are qualified, the backup usable monitoring data will be grouped and stored, and cluster analysis will be performed on it to form a cluster analysis result data set. This helps to discover the correlation and rules between data, and provides a basis for subsequent data analysis and fault prediction.

[0075] The cluster analysis result data set is used to build an online monitoring data knowledge base, which contains historical data and experience of pipeline network operation and can be used for comparison and analysis with real-time monitoring data.

[0076] Receive real-time monitoring data, perform grouping and cluster analysis, and obtain a data set of cluster analysis results of real-time monitoring data. This step is to reflect the current operating status of the pipeline network in real time. Compare the cluster analysis results of real-time monitoring data with the online monitoring data knowledge base to find out whether there is a failure mode similar to historical data. If there is failure information, it indicates that there is a problem with the current pipeline network.

[0077] If the real-time monitoring data is marked as abnormal data, the system will generate an early warning message, including the details of the abnormal data, the type of fault, and the recommended solution. This helps operation and maintenance personnel to promptly discover and deal with potential safety hazards.

[0078] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S102 comprises:

[0079] Filter out sensors that are currently in operation from the sensor information, and call up a preset standard parameter set, where the preset standard parameter set includes the accuracy, response time, and stability index of the sensor;

[0080] Compare the real-time operating parameters of each sensor in operation with the preset standard parameters to check whether the sensor meets the preset standard parameters and obtain a comparison test result;

[0081] According to the comparison test results, sensors that meet the preset standard parameters are screened out, and a qualified sensor device information list is generated. The qualified sensor device information list includes the operating sensor information.

[0082] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S103 comprises:

[0083] For each group of real-time thermal power plant industrial monitoring data, the sensor operation data of the corresponding time period is retrieved from the sensor operation record, and the sensor operation data of the corresponding time period includes the sensor status information, performance parameters and abnormal records;

[0084] Preprocess the retrieved operation data, including data cleaning and matching the time stamps of the time synchronization monitoring data with the operation data;

[0085] The preprocessed sensor operation data is compared with the preset standards to check whether the sensor's operating status, performance indicators, etc. meet the preset requirements, including the sensor's response time, to obtain the sensor's operation data that meets the preset standards.

[0086] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S104 comprises:

[0087] Receive data detection model and backup data storage path;

[0088] Use the joblib library to load the pre-trained data detection model, read the backup data file according to the backup data storage path, and pre-process the backup data to obtain the pre-processed backup data;

[0089] The preprocessed backup data is input into the data detection model to determine whether the preprocessed backup data is qualified, to obtain the qualified backup data, and to output the qualified backup data.

[0090] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S105 comprises:

[0091] Substitute the pre-processed and tested backup usable monitoring data into the preset online monitoring model of the industrial water digital pipe network of the thermal power plant;

[0092] In the online monitoring model of the digital pipe network for industrial water in thermal power plants, the backup data can be processed to obtain the online simulation monitoring results of the digital pipe network for industrial water in thermal power plants;

[0093] According to the preset standard value, judge whether the online simulation monitoring results of the digital pipe network of industrial water in the thermal power plant are qualified;

[0094] If the online simulation monitoring results of the digital pipe network for industrial water in thermal power plants are qualified, the available monitoring data will be backed up and stored in groups;

[0095] The backup availability monitoring data is divided into different groups according to the characteristics or attributes of the backup availability monitoring data grouping data, and the grouped backup availability monitoring data is stored in a designated location.

[0096] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S105 comprises:

[0097] The backup and available monitoring data is stored in the blockchain, and the hash value corresponding to the backup and available monitoring data is generated;

[0098] After the grouped backup avail- able monitoring data is stored in a designated location, the stored backup avail- able monitoring data is randomly retrieved at a preset time period;

[0099] The randomly retrieved backup can be used to monitor the data and the corresponding data stored in the blockchain. If the data comparison results are consistent, the grouped backup can be used to monitor the data successfully.

[0100] Furthermore, the method for online monitoring of the digital pipe network of industrial water in a thermal power plant provided by the present invention, step S105 comprises:

[0101] Compare the data set of cluster analysis results of real-time monitoring data with the online monitoring data knowledge base to obtain historical data that matches the real-time monitoring data;

[0102] Use Euclidean distance to find the closest historical data point, perform fault detection on the similar historical data found, and determine whether there is fault information;

[0103] If there is fault information, the corresponding real-time monitoring data will be marked as abnormal data;

[0104] The warning information includes detailed information of abnormal data, fault type and suggested solutions, and outputs result warning information.

[0105] The technical solution of the present invention solves the problem of system response delay or data loss due to large amount of data during the online monitoring of the digital pipe network of industrial water in thermal power plants through the following steps:

[0106] Acquire and pre-process the basic operation data of thermal power plants, water quality index data, and equipment operation status data to reduce the amount of data to be processed later and improve processing efficiency. Collect sensor information, identify sensors in operation, and perform tests based on preset standard parameters to improve the accuracy and reliability of sensor data.

[0107] Receive real-time data collected by sensor devices that meet standard parameters, group them according to the time when the data was generated, and then detect whether the operating data of the sensors in the corresponding time period meets the preset standards, so as to filter out usable monitoring data.

[0108] Detect the remaining space in the local database real-time running memory. When the space is insufficient, back up the available monitoring data and upload it to the cloud server for storage to improve data security and integrity. Use the preset data detection model to detect the backup available monitoring data to improve data quality. Then substitute the qualified data into the preset online monitoring model of the industrial water digital pipeline network of the thermal power plant to obtain the online simulation monitoring results.

[0109] The backup available monitoring data is grouped and stored, and clustered to build an online monitoring data knowledge base. This helps to quickly identify and process abnormal data. Receive real-time monitoring data, perform grouping and cluster analysis, and compare it with the online monitoring data knowledge base. If fault information is found in the similar monitoring historical data, the real-time monitoring data is marked as abnormal data and an early warning message is generated.

[0110] Through the above steps, the present invention effectively solves the problem of system response delay or data loss caused by large data volume during the online monitoring of the industrial water digital pipeline network of a thermal power plant, and improves the efficiency and accuracy of the monitoring system.

[0111] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations, and the above-described embodiments of the present invention do not constitute a limitation on the scope of protection of the present invention.

Claims

1. A method for online monitoring of digital pipe network of industrial water in thermal power plant, characterized in that: include: Step S101, obtaining basic operation data, water quality index data and equipment operation status data of a thermal power plant, preprocessing the basic operation data, water quality index data and equipment operation status data of the thermal power plant to obtain preprocessed basic operation data, water quality index data and equipment operation status data of the thermal power plant; Step S102, collecting sensor information in the online monitoring system of the digital pipe network for industrial water of the thermal power plant, obtaining the operation information of the sensors used online in the online monitoring system of the digital pipe network for industrial water of the thermal power plant, determining the sensors in operation according to the operation information of the sensors used online in the online monitoring system of the digital pipe network for industrial water of the thermal power plant, detecting the sensors in operation according to preset standard parameters, and obtaining the sensor equipment information that meets the standard parameters; Step S103, receiving the real-time thermal power plant industrial monitoring data collected by the sensor equipment that meets the standard parameters, grouping the real-time thermal power plant industrial monitoring data according to the data generation time, obtaining the grouped real-time thermal power plant industrial monitoring data, retrieving the operation data of the sensor in the corresponding time period of the grouped real-time thermal power plant industrial monitoring data, detecting whether the operation data of the sensor in the corresponding time period of the grouped real-time thermal power plant industrial monitoring data meets the preset standard, and using the operation data of the sensor that meets the preset standard as the usable monitoring data; Step S104, detecting the remaining space of the real-time running memory of the local database, when the remaining space of the real-time running memory is lower than the preset minimum running memory space, backing up the available monitoring data and uploading it to the cloud server for storage to obtain the backup available monitoring data, using the preset data detection model to detect the backup available monitoring data, and obtaining the backup available monitoring data that has passed the detection, and determining the storage data corresponding to the qualified backup available monitoring data in the local database according to the attribute data of the qualified backup available monitoring data, and when the backup available monitoring data passes the detection, deleting the storage data corresponding to the qualified backup available monitoring data in the local database; Step S105, substitute the backup available monitoring data into the preset online monitoring model of the digital pipeline network for industrial water of the thermal power plant to obtain the online simulation monitoring result of the digital pipeline network for industrial water of the thermal power plant; if the online simulation monitoring result of the digital pipeline network for industrial water of the thermal power plant is qualified, the backup available monitoring data is grouped and stored to obtain the backup available monitoring data grouping data; cluster analysis is performed on each backup available monitoring data grouping data to obtain the backup available monitoring data clustering analysis result data set; the backup available monitoring data clustering analysis result data set is used to construct an online monitoring data knowledge base; the real-time monitoring data is received; the real-time monitoring data is grouped according to the data generation time to obtain the grouped real-time monitoring data; cluster analysis is performed on the grouped real-time monitoring data to obtain the real-time monitoring data clustering analysis result data set; the real-time monitoring data clustering analysis result data set is compared with the online monitoring data knowledge base to obtain the approximate monitoring history data; if the approximate monitoring history data corresponding to the real-time monitoring data clustering analysis result data set has fault information, the real-time monitoring data corresponding to the real-time monitoring data clustering analysis result data set is marked as abnormal data, and an early warning information is generated.

2. The method for online monitoring of industrial water digital pipe network in thermal power plant according to claim 1, characterized in that: The step S102 includes: Filter out sensors that are currently in operation from the sensor information, and call up a preset standard parameter set, where the preset standard parameter set includes the accuracy, response time, and stability index of the sensor; Compare the real-time operating parameters of each sensor in operation with the preset standard parameters to check whether the sensor meets the preset standard parameters and obtain a comparison test result; According to the comparison test results, sensors that meet the preset standard parameters are screened out, and a qualified sensor device information list is generated. The qualified sensor device information list includes the operating sensor information.

3. The method for online monitoring of industrial water digital pipe network in thermal power plant according to claim 1, characterized in that: The step S103 includes: For each group of real-time thermal power plant industrial monitoring data, the sensor operation data of the corresponding time period is retrieved from the sensor operation record, and the sensor operation data of the corresponding time period includes the sensor status information, performance parameters and abnormal records; Preprocess the retrieved operation data, including data cleaning and matching the time stamps of the time synchronization monitoring data with the operation data; The preprocessed sensor operation data is compared with the preset standards to check whether the sensor's operating status, performance indicators, etc. meet the preset requirements, including the sensor's response time, to obtain the sensor's operation data that meets the preset standards.

4. The method for online monitoring of industrial water digital pipe network in thermal power plant according to claim 1, characterized in that: The step S104 includes: Receive data detection model and backup data storage path; Use the joblib library to load the pre-trained data detection model, read the backup data file according to the backup data storage path, and pre-process the backup data to obtain the pre-processed backup data; The preprocessed backup data is input into the data detection model to determine whether the preprocessed backup data is qualified, to obtain the qualified backup data, and to output the qualified backup data.

5. The method for online monitoring of digital pipe network of industrial water in thermal power plant according to claim 1, characterized in that: The step S105 includes: Substitute the pre-processed and tested backup usable monitoring data into the preset online monitoring model of the industrial water digital pipe network of the thermal power plant; In the online monitoring model of the digital pipe network for industrial water in thermal power plants, the backup data can be processed to obtain the online simulation monitoring results of the digital pipe network for industrial water in thermal power plants; According to the preset standard value, judge whether the online simulation monitoring results of the digital pipe network of industrial water in the thermal power plant are qualified; If the online simulation monitoring results of the digital pipe network for industrial water in thermal power plants are qualified, the available monitoring data will be backed up and stored in groups; The backup availability monitoring data is divided into different groups according to the characteristics or attributes of the backup availability monitoring data grouping data, and the grouped backup availability monitoring data is stored in a designated location.

6. The method for online monitoring of digital pipe network for industrial water in thermal power plants according to claim 5, characterized in that: The step S105 includes: The backup and available monitoring data is stored in the blockchain, and the hash value corresponding to the backup and available monitoring data is generated; After the grouped backup avail- able monitoring data is stored in a designated location, the stored backup avail- able monitoring data is randomly retrieved at a preset time period; The randomly retrieved backup can be used to monitor the data and the corresponding data stored in the blockchain. If the data comparison results are consistent, the grouped backup can be used to monitor the data successfully.

7. The method for online monitoring of digital pipe network of industrial water in thermal power plant according to claim 6, characterized in that: The step S105 includes: Compare the data set of cluster analysis results of real-time monitoring data with the online monitoring data knowledge base to obtain historical data that matches the real-time monitoring data; Use Euclidean distance to find the closest historical data point, perform fault detection on the similar historical data found, and determine whether there is fault information; If there is fault information, the corresponding real-time monitoring data will be marked as abnormal data; The warning information includes detailed information of abnormal data, fault type and suggested solutions, and outputs result warning information.

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