Dangerous point pre-control management method in thermal power construction

Abstract

The invention relates to the technical field of thermal power construction, and provides a dangerous point pre-control management method in thermal power construction, which comprises the following steps of: acquiring historical dangerous point data, performing classification and feature extraction, analyzing potential influence by utilizing a virtual evolution technology, and training a dangerous point prediction model; according to the method, dangerous point prediction is carried out through the dangerous point prediction model, dangerous events are effectively prevented through graphical display and real-time pre-control instruction execution, meanwhile, through a continuous optimization and feedback mechanism, the dangerous point prediction precision and the pre-control effect are improved, the safety of a thermal power construction project is improved, and the safety of the thermal power construction project is improved. According to the invention, the problem of insufficient prevention of non-occurrence of dangerous points in the prior art is solved, and the accuracy and advancement of dangerous point pre-control are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of thermal power construction, and in particular to a method for pre-control management of dangerous points in thermal power construction. Background Art

[0002] Due to the large scale of thermal power construction, frequent overhead work, complex subcontracting, and numerous unsafe human factors, accidents, particularly personal injuries, are frequent in my country's thermal power plant construction. This phenomenon not only seriously threatens the lives of workers but also poses a major challenge to project progress and cost control. To fundamentally improve the safety management of thermal power construction and effectively curb the occurrence of various accidents, more scientific and systematic measures must be taken.

[0003] While existing thermal power plants can provide a certain degree of warning about dangerous areas based on historical accident data, they are significantly inadequate in preventing potential hazards before they occur, lacking the ability to proactively prevent and control them. This limitation reduces the accuracy and proactive nature of these risk-based prevention efforts, placing immense pressure on power construction companies facing potential safety risks and hindering safe construction. This not only impacts project progress but can also reduce construction efficiency and increase unnecessary costs. Therefore, there is an urgent need to develop and promote more advanced and comprehensive safety management technologies and methods to enhance the overall safety of thermal power projects. Summary of the Invention

[0004] In view of the shortcomings of the existing technology, the present invention provides a method for pre-control management of dangerous points in thermal power construction, which solves the obvious deficiencies of existing thermal power construction in preventing points where danger has not yet occurred and the lack of pre-emptive prevention and control capabilities. This limitation reduces the accuracy and pre-emptiveness of dangerous point pre-control, causing power construction companies to still bear tremendous pressure when facing potential safety risks and unable to achieve safe construction.

[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 a method for pre-control management of dangerous points in thermal power construction, comprising:

[0007] Step S101: Collect historical data of dangerous points in thermal power construction, where the historical data includes dangerous point type, dangerous point discovery frequency, and dangerous point discovery time;

[0008] Step S102: classify the historical dangerous point data in thermal power construction according to the dangerous point type to obtain a data set corresponding to each type of dangerous point, extract data features from the data set corresponding to each type of dangerous point, and obtain a dangerous feature factor;

[0009] Step S103: Using virtual evolution technology to analyze the potential impact of the hazard characteristic factors, evaluating and analyzing the consequences caused by the hazard characteristic factors based on historical hazard point data in thermal power construction, and obtaining an evaluation hazard analysis result;

[0010] Step S104: training a model based on the risk assessment analysis results and historical dangerous point data in thermal power construction to obtain a dangerous point prediction model. The dangerous point prediction model is used to predict dangerous points. Dangerous point prediction includes predicting the occurrence time of the dangerous point, the predicted location of the dangerous point, and the predicted impact range of the dangerous point.

[0011] Step S105: plotting a frequency curve of dangerous points with the time of discovery of the dangerous points as the horizontal axis and the number of times the dangerous points have occurred as the vertical axis. The frequency curve of dangerous points is displayed graphically. The graphical display information includes the predicted impact degree and danger level of the dangerous points, and is used to present the frequency of dangerous points at different dangerous points in the same period and the changing trend of the same dangerous point at different periods.

[0012] Step S106: According to the predicted impact degree and hazard level of the dangerous point, pre-control instructions corresponding to the predicted impact degree and hazard level of the dangerous point are set, and the operating data of the thermal power construction is collected in real time. The operating data of the thermal power construction is substituted into the dangerous point prediction model to obtain the real-time dangerous point prediction result, and the real-time dangerous point prediction result is presented through a dangerous point occurrence frequency curve chart, and the predicted impact degree and hazard level of the dangerous point in the real-time dangerous point prediction result are extracted, and the corresponding pre-control instructions are matched according to the predicted impact degree and hazard level of the dangerous point in the real-time dangerous point prediction result.

[0013] Furthermore, the method for pre-control management of dangerous points in thermal power construction according to the present invention further includes, in step S106:

[0014] Send the pre-control instructions to the execution equipment end, which includes warning lights, warning speakers, power switches and fire-fighting equipment;

[0015] The execution device executes the pre-control instruction, collects the operating data of the thermal power construction after the execution device executes the pre-control instruction, obtains the real-time feedback data, substitutes the real-time feedback data into the dangerous point prediction model, obtains the dangerous point prediction result after the execution of the pre-control instruction, analyzes the dangerous point prediction result after the execution of the pre-control instruction, and obtains the dangerous point analysis result after the execution of the pre-control instruction.

[0016] Furthermore, the method for pre-control management of dangerous points in thermal power construction described in the present invention, in step S106, also includes: the dangerous point analysis result after the execution of the pre-control instruction includes no dangerous points and dangerous points; if the dangerous point analysis result after the execution of the pre-control instruction is that there is a dangerous point, then the dangerous point analysis result after the execution of the pre-control instruction continues to be matched with the pre-control instruction, and the matched pre-control instruction is sent to the execution device end for execution, and the dangerous point prediction is continued for the operating data in the thermal power construction after the execution of the pre-control instruction, until the dangerous point analysis result after the execution of the pre-control instruction is terminated when the dangerous point analysis result after the execution of the pre-control instruction is that there is no dangerous point.

[0017] Furthermore, the method for pre-control management of dangerous points in thermal power construction according to the present invention includes, in step 102:

[0018] Classify the dangerous points according to the type of historical dangerous point data. The dangerous point classification includes mechanical injury, high-altitude fall, electrical accident and fire. According to the dangerous point classification, the dangerous points are classified to obtain the data sets corresponding to mechanical injury, high-altitude fall, electrical accident and fire points;

[0019] For the data sets corresponding to mechanical injuries, falls from heights, electrical accidents, and fire points, data features reflecting the characteristics of such dangerous points are extracted, and the extracted features corresponding to mechanical injuries, falls from heights, electrical accidents, and fire points are used as dangerous feature factors.

[0020] Furthermore, the method for pre-control management of dangerous points in thermal power construction according to the present invention further includes, in step 102:

[0021] The features extracted from the mechanical injury dataset include: frequency of occurrence, injury type, injury location, equipment type, and operating environment;

[0022] The features extracted from the high-altitude fall data set include: high-altitude fall height, high-altitude fall cause, high-altitude fall injury site, high-altitude fall weather conditions, and high-altitude work type.

[0023] The features extracted from the electrical accident dataset include: electrical accident current type, electrical accident voltage level, electrical accident cause, electrical accident injury type, and electrical accident equipment status;

[0024] The features extracted from the fire dataset include: the cause of the fire, the size of the fire, the burning material of the fire, and the difficulty of extinguishing the fire.

[0025] Furthermore, the method for pre-control management of dangerous points in thermal power construction according to the present invention includes, in step 103:

[0026] Loading historical dangerous point data in thermal power construction from a database, the historical dangerous point data in thermal power construction including classified and extracted dangerous characteristic factors, and the historical dangerous point data in thermal power construction is used to set initial conditions for virtual evolution simulation;

[0027] Based on the specific scenarios of thermal power construction and the characteristics of hazard characteristic factors, a virtual evolution model is constructed to simulate the evolution process of different hazard points under different conditions;

[0028] Taking the hazard characteristic factors as input, the virtual evolution model is started to simulate the potential impact. Based on the input characteristic factors, the model will simulate the evolution of the hazard point under different time and conditions;

[0029] During the simulation process, the changes of nodes and parameters are recorded. The changes of nodes and parameters include the dangerous point influence range, dangerous point influence intensity, and dangerous point development trend.

[0030] Furthermore, the method for pre-control management of dangerous points in thermal power construction according to the present invention includes, in step 103:

[0031] The output results of the virtual evolution model include casualties and equipment damage;

[0032] The output results of the virtual evolution model are evaluated and analyzed, and based on the evaluation results, the evaluation risk analysis results are generated. The evaluation hazard analysis results include the impact range of the hazard characteristic factors, the impact degree of the hazard characteristic factors, the development trend of the hazard characteristic factors and the chain reaction of the hazard characteristic factors.

[0033] Furthermore, the method for pre-control management of dangerous points in thermal power construction according to the present invention further includes, in step 103:

[0034] Identification of chain reactions. When evaluating hazard analysis results, if the impact of a certain hazard characteristic factor triggers other hazard points or exacerbates the severity of other hazard points, a chain reaction occurs. Chain reactions include electrical accidents causing fires, which further affect the operating status of other equipment.

[0035] The operation data of equipment in the chain reaction and the operation data in the thermal power construction are collected to obtain the chain reaction danger point data.

[0036] Furthermore, the method for pre-controlling and managing dangerous points in thermal power construction according to the present invention further includes:

[0037] Processing and analyzing the chain reaction danger point data using a danger point prediction model to obtain a chain reaction danger point prediction result, the chain reaction danger point prediction result including a first danger point prediction result, a second danger point prediction result, and a third danger point prediction result;

[0038] The first danger point prediction result, the second danger point prediction result, and the third danger point prediction result are sequentially plotted as danger point occurrence frequency curves to obtain a first plotted danger point occurrence frequency curve graph, a second plotted danger point occurrence frequency curve graph, and a third plotted danger point occurrence frequency curve graph;

[0039] According to the first, second and third plotted frequency curves of dangerous point occurrence, pre-control instructions corresponding to the predicted impact degree and danger level of the dangerous point are matched.

[0040] Beneficial effects of the present invention:

[0041] Improve the accuracy and preemptiveness of dangerous point pre-control: By collecting historical dangerous point data in thermal power construction and conducting detailed classification and feature extraction, the present invention can more accurately identify and analyze various dangerous points and their characteristics. Combined with virtual evolution technology, it can simulate the evolution process of dangerous points under different conditions and predict their potential impact, thereby improving the accuracy of dangerous point pre-control. At the same time, the dangerous point prediction model is used to provide advance warning of future dangerous points, allowing power construction companies to take preventive measures in advance and effectively avoid or reduce the occurrence of dangerous events.

[0042] Improve safety management: The hazard point pre-control management method provided by the present invention provides a scientific basis and effective tools for the safety management of thermal power construction projects. Through real-time data collection, model prediction, graphical display and pre-control instruction execution, safety management is made more systematic and intelligent, which not only helps to reduce the probability of accidents, but also enables rapid response when accidents occur, reducing the losses caused by accidents.

[0043] Securing the life safety of workers: Thermal power construction projects involve a variety of high-risk operations such as aerial work and electrical work. Frequent accidents pose a serious threat to the life safety of workers. The implementation of the present invention can significantly reduce the possibility of accidents, thereby ensuring the life safety of workers.

[0044] Improved project progress and cost control: By effectively pre-controlling dangerous points, this invention can avoid project delays and additional costs caused by accidents. This helps power construction companies improve construction efficiency, reduce costs, and enhance economic benefits.

[0045] Promoting technological innovation and industrial upgrading: The successful application of this invention not only provides new ideas and methods for safety management in thermal power construction, but also promotes the innovation and development of related technologies. This will help improve the safety level and competitiveness of the entire thermal power construction industry and promote industrial upgrading.

[0046] In summary, the present invention significantly improves the safety management level of thermal power construction projects through an innovative hazard point pre-control management method, ensures the life safety of workers, accelerates project progress and cost control efficiency, and promotes technological innovation and industrial upgrading. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to 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 any creative work.

[0048] Figure 1 A schematic diagram of a method flow chart provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. The technical solutions provided by each embodiment of the present invention are described in detail below in conjunction with the drawings.

[0050] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0051] The present invention provides a method for pre-control management of dangerous points in thermal power construction, comprising:

[0052] Step S101: Collect historical data of dangerous points in thermal power construction, where the historical data includes dangerous point type, dangerous point discovery frequency, and dangerous point discovery time;

[0053] Hazard point data is collected from historical records of thermal power plant construction. This data includes, but is not limited to, the type of hazard point (e.g., mechanical injury, falls from height, electrical accidents, fires, etc.), the frequency of hazard point discovery, and the time of hazard point discovery. This collected historical hazard point data is preprocessed, including data cleaning, formatting, and necessary standardization, to ensure data quality for subsequent analysis.

[0054] Step S102: classify the historical dangerous point data in thermal power construction according to the dangerous point type to obtain a data set corresponding to each type of dangerous point, extract data features from the data set corresponding to each type of dangerous point, and obtain a dangerous feature factor;

[0055] Step S102 categorizes the preprocessed historical hazard point data by hazard point type, generating a dataset corresponding to each hazard point type. Data feature extraction is performed on each hazard point dataset. For example, features extracted from a mechanical injury dataset might include frequency, injury type, injury location, equipment type, and operating environment; while a high-altitude fall dataset might include features such as fall height, cause of fall, injury location, weather conditions, and operation type.

[0056] Step S103: Using virtual evolution technology to analyze the potential impact of the hazard characteristic factors, evaluating and analyzing the consequences caused by the hazard characteristic factors based on historical hazard point data in thermal power construction, and obtaining an evaluation hazard analysis result;

[0057] Step S103: Analyze the potential impact of the extracted risk characteristic factors using virtual evolution technology. First, load historical risk point data in thermal power construction from the database as initial conditions for simulation.

[0058] Based on the specific scenarios of thermal power construction and the characteristics of hazard characteristic factors, a virtual evolution model is constructed. This model can simulate the evolution process of different hazard points under different conditions.

[0059] Using the hazard characteristic factors as input, a virtual evolution model is launched to simulate potential impacts. Changes in nodes and parameters during the simulation process are recorded, including the impact range, impact intensity, and development trend of the hazard point.

[0060] Evaluate and analyze the output results of the virtual evolution model to generate risk analysis results, including the impact scope, impact degree, development trend and possible chain reactions of the hazardous characteristic factors.

[0061] Step S104: training a model based on the evaluation and hazard analysis results and historical hazard point data in thermal power construction to obtain a hazard point prediction model. The hazard point prediction model is used to predict hazard points. The hazard point prediction includes the predicted hazard point occurrence time, the predicted hazard point location, and the predicted impact range of the hazard point.

[0062] Step S104 trains a prediction model based on the hazard analysis results and historical hazard point data. The hazard point prediction model can predict the time, location, and impact range of future hazard points. Real-time operational data from thermal power plants is collected and substituted into the trained hazard point prediction model for real-time hazard point prediction.

[0063] Step S105: plotting a frequency curve of dangerous points with the time of discovery of the dangerous points as the horizontal axis and the number of times the dangerous points have occurred as the vertical axis. The frequency curve of dangerous points is displayed graphically. The graphical display information includes the predicted impact degree and danger level of the dangerous points, and is used to present the frequency of dangerous points at different dangerous points in the same period and the changing trend of the same dangerous point at different periods.

[0064] Step S106: According to the predicted impact degree and hazard level of the dangerous point, pre-control instructions corresponding to the predicted impact degree and hazard level of the dangerous point are set, and the operating data of the thermal power construction is collected in real time. The operating data of the thermal power construction is substituted into the dangerous point prediction model to obtain the real-time dangerous point prediction result, and the real-time dangerous point prediction result is presented through a dangerous point occurrence frequency curve chart, and the predicted impact degree and hazard level of the dangerous point in the real-time dangerous point prediction result are extracted, and the corresponding pre-control instructions are matched according to the predicted impact degree and hazard level of the dangerous point in the real-time dangerous point prediction result.

[0065] Step S105 plots a frequency curve of dangerous points with the time of dangerous point discovery as the horizontal axis and the number of dangerous point occurrences as the vertical axis. Through graphical display, the frequency of occurrence of different dangerous points in the same period and the changing trend of the same dangerous point in different periods are presented.

[0066] Step S106 sets corresponding pre-control instructions based on the predicted impact and danger level of the dangerous point in the real-time dangerous point prediction result, and sends the pre-control instructions to the execution device end (such as warning lights, warning speakers, power switches and fire fighting equipment, etc.).

[0067] The execution device performs corresponding operations according to the received pre-control instructions, and collects the thermal power construction and operation data after execution to obtain real-time feedback data.

[0068] Real-time feedback data is fed into the prediction model to analyze the danger points after the pre-control instructions are executed and evaluate the pre-control effect. If the danger point still exists, new pre-control instructions are matched and executed until the danger point is completely eliminated.

[0069] Throughout the implementation process, we continuously collect feedback data to optimize and adjust the forecasting model and pre-control instructions to improve forecast accuracy and pre-control effectiveness. We regularly review and summarize implementation results, and make necessary improvements and updates based on the actual situation of thermal power construction and safety management needs.

[0070] Specifically, the method for pre-control management of dangerous points in thermal power construction according to the present invention further includes, in step S106:

[0071] Send the pre-control instructions to the execution equipment end, which includes warning lights, warning speakers, power switches and fire-fighting equipment;

[0072] The execution device executes the pre-control instruction, collects the operating data of the thermal power construction after the execution device executes the pre-control instruction, obtains the real-time feedback data, substitutes the real-time feedback data into the dangerous point prediction model, obtains the dangerous point prediction result after the execution of the pre-control instruction, analyzes the dangerous point prediction result after the execution of the pre-control instruction, and obtains the dangerous point analysis result after the execution of the pre-control instruction.

[0073] Specifically, the method for pre-control management of dangerous points in thermal power construction described in the present invention, in step S106, also includes: the dangerous point analysis result after the execution of the pre-control instruction includes no dangerous points and dangerous points. If the dangerous point analysis result after the execution of the pre-control instruction is that there is a dangerous point, then the dangerous point analysis result after the execution of the pre-control instruction continues to be matched with the pre-control instruction, and the matched pre-control instruction is sent to the execution device end for execution, and the dangerous point prediction is continued for the operating data in the thermal power construction after the execution of the pre-control instruction, until the dangerous point analysis result after the execution of the pre-control instruction is terminated when the dangerous point analysis result after the execution of the pre-control instruction is that there is no dangerous point.

[0074] Specifically, the method for pre-control management of dangerous points in thermal power construction according to the present invention includes, in step 102:

[0075] Classify the dangerous points according to the type of historical dangerous point data. The dangerous point classification includes mechanical injury, high-altitude fall, electrical accident and fire. According to the dangerous point classification, the dangerous points are classified to obtain the data sets corresponding to mechanical injury, high-altitude fall, electrical accident and fire points;

[0076] For the data sets corresponding to mechanical injuries, falls from heights, electrical accidents, and fire points, data features reflecting the characteristics of such dangerous points are extracted, and the extracted features corresponding to mechanical injuries, falls from heights, electrical accidents, and fire points are used as dangerous feature factors.

[0077] Specifically, the method for pre-control management of dangerous points in thermal power construction according to the present invention further includes, in step 102:

[0078] The features extracted from the mechanical injury dataset include: frequency of occurrence, injury type, injury location, equipment type, and operating environment;

[0079] The features extracted from the high-altitude fall data set include: high-altitude fall height, high-altitude fall cause, high-altitude fall injury site, high-altitude fall weather conditions, and high-altitude work type.

[0080] The features extracted from the electrical accident dataset include: electrical accident current type, electrical accident voltage level, electrical accident cause, electrical accident injury type, and electrical accident equipment status;

[0081] The features extracted from the fire dataset include: the cause of the fire, the size of the fire, the burning material of the fire, and the difficulty of extinguishing the fire.

[0082] Specifically, the method for pre-control management of dangerous points in thermal power construction according to the present invention includes, in step 103:

[0083] Loading historical dangerous point data in thermal power construction from a database, the historical dangerous point data in thermal power construction including classified and extracted dangerous characteristic factors, and the historical dangerous point data in thermal power construction is used to set initial conditions for virtual evolution simulation;

[0084] Based on the specific scenarios of thermal power construction and the characteristics of hazard characteristic factors, a virtual evolution model is constructed to simulate the evolution process of different hazard points under different conditions;

[0085] Taking the hazard characteristic factors as input, the virtual evolution model is started to simulate the potential impact. Based on the input characteristic factors, the model will simulate the evolution of the hazard point under different time and conditions;

[0086] During the simulation process, the changes of nodes and parameters are recorded. The changes of nodes and parameters include the dangerous point influence range, dangerous point influence intensity, and dangerous point development trend.

[0087] Specifically, the method for pre-control management of dangerous points in thermal power construction according to the present invention includes, in step 103:

[0088] The output results of the virtual evolution model include casualties and equipment damage;

[0089] The output results of the virtual evolution model are evaluated and analyzed, and based on the evaluation results, the evaluation risk analysis results are generated. The evaluation hazard analysis results include the impact range of the hazard characteristic factors, the impact degree of the hazard characteristic factors, the development trend of the hazard characteristic factors and the chain reaction of the hazard characteristic factors.

[0090] Specifically, the method for pre-control management of dangerous points in thermal power construction according to the present invention further includes, in step 103:

[0091] Identification of chain reactions. When evaluating hazard analysis results, if the impact of a certain hazard characteristic factor triggers other hazard points or exacerbates the severity of other hazard points, a chain reaction occurs. Chain reactions include electrical accidents causing fires, which further affect the operating status of other equipment.

[0092] The operation data of equipment in the chain reaction and the operation data in the thermal power construction are collected to obtain the chain reaction danger point data.

[0093] Specifically, the method for pre-control management of dangerous points in thermal power construction according to the present invention further includes:

[0094] Processing and analyzing the chain reaction danger point data using a danger point prediction model to obtain a chain reaction danger point prediction result, the chain reaction danger point prediction result including a first danger point prediction result, a second danger point prediction result, and a third danger point prediction result;

[0095] The first danger point prediction result, the second danger point prediction result, and the third danger point prediction result are sequentially plotted as danger point occurrence frequency curves to obtain a first plotted danger point occurrence frequency curve graph, a second plotted danger point occurrence frequency curve graph, and a third plotted danger point occurrence frequency curve graph;

[0096] According to the first, second and third plotted frequency curves of dangerous point occurrence, pre-control instructions corresponding to the predicted impact degree and danger level of the dangerous point are matched.

[0097] The technical solution of the present invention effectively solves the shortcomings of existing thermal power construction in preventing dangerous points before they occur, improves the accuracy and preemptiveness of dangerous point pre-control, and thus helps power construction companies better deal with potential safety risks and achieve safe construction. The specific solution is as follows:

[0098] Data collection and feature extraction: By collecting historical dangerous point data in thermal power construction, and conducting detailed classification and data feature extraction, dangerous characteristic factors reflecting the characteristics of various dangerous points are obtained.

[0099] Virtual evolution analysis: Use virtual evolution technology to analyze the potential impact of hazard characteristic factors, simulate the evolution process of different hazard points under different conditions, predict the consequences and impact range that may be caused by hazard points, and provide a scientific basis for the formulation of preventive measures.

[0100] Model training and prediction: Based on the evaluation of hazard analysis results and historical hazard point data, a hazard point prediction model is trained. The hazard point prediction model can predict the time, location and impact range of future hazard points, achieving advanced warning of hazard points.

[0101] Real-time collection of operational data from thermal power construction and substitution into the prediction model for real-time prediction of dangerous points ensures the timeliness and accuracy of the prediction.

[0102] Graphical Display and Preventive Control Instructions: By plotting a frequency curve for hazardous points, the system graphically displays the frequency of occurrence of different hazardous points over the same period, as well as the changing trends of the same hazardous point over time, improving the intuitiveness and operability of safety management. Based on the predicted impact and hazard level of the hazardous point in real-time hazardous point prediction results, corresponding pre-control instructions are set. Real-time intervention is then implemented through execution devices such as warning lights, warning speakers, power switches, and firefighting equipment, effectively preventing the occurrence of hazardous events.

[0103] Continuous Monitoring and Feedback: After executing pre-control instructions, operational data from the thermal power plant continues to be collected and analyzed using models to predict and evaluate the effectiveness of the pre-control instructions. If any danger points still exist, pre-control instructions will continue to be matched and executed until the danger points are completely eliminated.

[0104] Chain Reaction Identification and Response: Identify chain reactions within the hazard analysis results—that is, how the impact of a particular hazard characteristic may trigger or exacerbate other hazards. By building a chain reaction hazard prediction model, chain reactions can be predicted and analyzed, and corresponding preventive measures can be developed to prevent further spread.

[0105] In summary, the technical solution of the present invention effectively improves the accuracy and pre-emptiveness of dangerous point pre-control in thermal power construction through comprehensive data collection and analysis, model prediction, intuitive graphical display, real-time pre-control instruction execution, and continuous monitoring and feedback mechanism, helping power construction companies to better deal with potential safety risks and achieve the goal of safe construction.

[0106] Obviously, those skilled in the art may make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if such modifications and variations fall within the scope of the claims and their equivalents, the present invention is intended to encompass such modifications and variations, and the above-described embodiments of the present invention do not constitute limitations on the scope of protection of the present invention.

Claims

1. A method for pre-control management of dangerous points in thermal power construction, characterized in that: include: Step S101, collecting historical dangerous point data in thermal power construction, the historical dangerous point data including dangerous point type, dangerous point discovery frequency and dangerous point discovery time; Step S102, classifying the historical dangerous point data in thermal power construction according to the dangerous point type, obtaining a data set corresponding to each type of dangerous point, extracting data features from the data set corresponding to each type of dangerous point, and obtaining a dangerous feature factor; Step S103, using virtual evolution technology to analyze the potential impact of the dangerous characteristic factors, evaluating and analyzing the consequences caused by the dangerous characteristic factors based on the historical dangerous point data in the thermal power construction, and obtaining the evaluation and danger analysis results; Step S104, training the model according to the evaluation hazard analysis results and the historical hazard point data in thermal power construction to obtain a hazard point prediction model, which is used to predict the hazard point, including the predicted hazard point occurrence time, the predicted hazard point location and the predicted impact range of the hazard point; Step S105, with the time of discovery of the dangerous point as the horizontal axis and the number of times the dangerous point occurs as the vertical axis, a dangerous point occurrence frequency curve is drawn, and the dangerous point occurrence frequency curve is displayed graphically. The graphical display information includes the predicted impact degree and danger level of the dangerous point, which is used to present the frequency of dangerous occurrence of different dangerous points in the same period and the change trend of the same dangerous point in different periods; Step S106, according to the predicted impact degree and hazard level of the dangerous point, set the pre-control instructions corresponding to the predicted impact degree and hazard level of the dangerous point, collect the operating data of the thermal power construction in real time, substitute the operating data of the thermal power construction into the dangerous point prediction model, obtain the real-time dangerous point prediction result, present the real-time dangerous point prediction result through the dangerous point occurrence frequency curve chart, and extract the predicted impact degree and hazard level of the dangerous point in the real-time dangerous point prediction result, and match the corresponding pre-control instructions according to the predicted impact degree and hazard level of the dangerous point in the real-time dangerous point prediction result.

2. The method for pre-controlling dangerous points in thermal power construction according to claim 1, characterized in that: In step S106, it also includes: The pre-control instructions are sent to the execution equipment end, which includes the warning light, the warning speaker, the power off switch and the fire fighting equipment; The execution device executes the pre-control instruction, collects the operating data of the thermal power construction after the execution device executes the pre-control instruction, obtains the real-time feedback data, substitutes the real-time feedback data into the dangerous point prediction model, obtains the dangerous point prediction result after the execution of the pre-control instruction, analyzes the dangerous point prediction result after the execution of the pre-control instruction, and obtains the dangerous point analysis result after the execution of the pre-control instruction.

3. The method for pre-controlling dangerous points in thermal power construction according to claim 2, characterized in that: In step S106, it also includes: the dangerous point analysis result after the execution of the pre-control instruction includes no dangerous point and dangerous point. If the dangerous point analysis result after the execution of the pre-control instruction is that there is a dangerous point, the dangerous point analysis result after the execution of the pre-control instruction continues to be matched with the pre-control instruction, and the matched pre-control instruction is sent to the execution device for execution, and the dangerous point prediction is continued for the operating data in the thermal power construction after the execution of the pre-control instruction, until the dangerous point analysis result after the execution of the pre-control instruction is that there is no dangerous point.

4. The method for pre-controlling dangerous points in thermal power construction according to claim 1, characterized in that: In step 102, it includes: Dangerous point classification is performed according to the type of historical dangerous point data. Dangerous point classification includes mechanical injury, high-altitude fall, electrical accident and fire. Dangerous point classification is performed according to the dangerous point classification to obtain data sets corresponding to mechanical injury, high-altitude fall, electrical accident and fire points; For the data sets corresponding to mechanical injuries, falls from heights, electrical accidents, and fire points, the data features reflecting the characteristics of such dangerous points are extracted, and the extracted features corresponding to mechanical injuries, falls from heights, electrical accidents, and fire points are used as dangerous feature factors.

5. The method for pre-controlling dangerous points in thermal power construction according to claim 4, characterized in that: In step 102, it also includes: The features extracted from the mechanical injury dataset include: frequency of occurrence, injury type, injury location, equipment type, and operating environment; The features extracted from the high-altitude fall dataset include: high-altitude fall height, high-altitude fall cause, high-altitude fall injury site, high-altitude fall weather conditions, and high-altitude work type. The features extracted from the electrical accident dataset include: electrical accident current type, electrical accident voltage level, electrical accident cause, electrical accident injury type, and electrical accident equipment status; The features extracted from the fire dataset include: the cause of the fire, the size of the fire, the burning material of the fire, and the difficulty of extinguishing the fire.

6. The method for pre-controlling dangerous points in thermal power construction according to claim 1, characterized in that: In step 103, it includes: Loading historical dangerous point data in thermal power construction from a database, the historical dangerous point data in thermal power construction including classified and extracted dangerous characteristic factors, the historical dangerous point data in thermal power construction is used for setting initial conditions of virtual evolution simulation; According to the specific scenarios of thermal power construction and the characteristics of dangerous characteristic factors, a virtual evolution model is constructed to simulate the evolution process of different dangerous points under different conditions; Taking the hazard characteristic factors as input, the virtual evolution model is started to simulate the potential impact. The model will simulate the evolution process of the hazard point under different time and conditions based on the input characteristic factors; During the simulation process, the changes of nodes and parameters are recorded. The changes of nodes and parameters include the influence range of dangerous points, the influence intensity of dangerous points, and the development trend of dangerous points.

7. The method for pre-controlling dangerous points in thermal power construction according to claim 6, characterized in that: In step 103, it includes: The output results of the virtual evolution model include casualties and equipment damage; The output results of the virtual evolution model are evaluated and analyzed, and based on the evaluation results, the evaluation risk analysis results are generated. The evaluation hazard analysis results include the impact range of hazardous characteristic factors, the impact degree of hazardous characteristic factors, the development trend of hazardous characteristic factors and the chain reaction of hazardous characteristic factors.

8. The method for pre-controlling dangerous points in thermal power construction according to claim 7, characterized in that: In step 103, it also includes: Identification of chain reactions. In the evaluation of hazard analysis results, if the influence of a certain hazard characteristic factor leads to the triggering of other hazard points or aggravates the severity of other hazard points, a chain reaction occurs. Chain reactions include electrical accidents causing fires, which further affect the operating status of other equipment. The operation data of equipment in the chain reaction and the operation data in the thermal power construction are collected to obtain the chain reaction danger point data.

9. The method for pre-controlling dangerous points in thermal power construction according to any one of claims 1 to 8, characterized in that: Also includes: The chain reaction danger point data are processed and analyzed by the danger point prediction model to obtain the chain reaction danger point prediction results, which include the first danger point prediction results, the second danger point prediction results and the third danger point prediction results; The first danger point prediction result, the second danger point prediction result and the third danger point prediction result are sequentially plotted into danger point occurrence frequency curve graphs to obtain a first plotted danger point occurrence frequency curve graph, a second plotted danger point occurrence frequency curve graph and a third plotted danger point occurrence frequency curve graph; According to the first drawn dangerous point occurrence frequency curve graph, the second drawn dangerous point occurrence frequency curve graph and the third drawn dangerous point occurrence frequency curve graph, pre-control instructions corresponding to the predicted impact degree and the dangerous level of the dangerous point are matched.

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