Digital converter station fire-fighting operation risk assessment system and method

Abstract

The invention discloses a digital converter station fire-fighting operation risk assessment system and method. The system comprises a data layer, a communication layer, a management layer and an application layer. The data layer comprises a fire-fighting facility Internet of Things acquisition module and a manual acquisition and input module; the data layer is used for collecting and inputting fire-fighting basic information; the communication layer is used for transmitting the fire-fighting basic information collected and recorded by the data layer to the management layer in a wired or wireless mode and linking an open interface of the management layer and model calling of the application layer; the management layer is used for performing unified definition and management on data, users, permissions, rules, protocols and applications in the system; and the application layer is used for risk assessment and monitoring. According to the fire-fighting operation risk assessment system and method for the digital converter station, the typical arrangement characteristics of the converter station are combined, risk assessment and monitoring early warning are carried out in a targeted mode, and safe transmission of important channels and key sections of a power grid can be practically guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of fire protection, and in particular relates to a fire protection operation risk assessment system and method for a digital converter station. Background Art

[0002] Firefighting is one of the important aspects of urban safety management. Once an accident occurs, it may cause huge losses to people's lives and property. At present, existing technologies have done a lot of research on how to effectively prevent and control fire safety risks. These studies have laid a theoretical foundation for urban fire safety management and risk assessment. High-voltage / UHV power transmission solves the problem of reverse distribution of energy load in my country. As an important asset of power grid companies, UHV converter stations have large equipment volume, high fire safety operation and maintenance requirements, and heavy tasks. However, there is currently a lack of a fire operation risk assessment system and method specifically for the risk characteristics of digital converter stations. Summary of the invention

[0003] In order to solve the problems in the prior art, the present invention aims to provide a digital converter station fire operation risk assessment system and method, which, combined with the typical layout characteristics of the converter station, carries out risk assessment and monitoring and early warning in a targeted manner, and can effectively ensure the safe transmission of important channels and key sections of the power grid.

[0004] In order to achieve the above-mentioned object, the present invention provides a digital converter station fire operation risk assessment system, comprising: a data layer, a communication layer, a management layer and an application layer;

[0005] The data layer includes a fire-fighting facility Internet of Things acquisition module and a manual acquisition and entry module; the data layer is used to collect and enter basic fire-fighting information;

[0006] The communication layer is used to transmit the basic firefighting information collected and entered by the data layer to the management layer by wire or wireless means, and to link the open interface of the management layer with the model call of the application layer;

[0007] The management layer is responsible for uniformly defining and managing the data, users, permissions, rules, protocols and applications in the system, performing verification, cleaning and regular processing on the basic fire protection information transmitted from the communication layer, and opening a unified calling interface to the application layer;

[0008] The application layer includes a state analysis model, a prediction model and a risk assessment model, which are used for risk assessment and monitoring.

[0009] As an implementation mode, the firefighting facility Internet of Things acquisition module is used to collect the operating status information and internal and external environment information of the target equipment of the firefighting facility Internet of Things of the target converter station in real time through sensors.

[0010] As an implementation method, the state analysis model is used to construct a fire-fighting equipment fault set, analyze the data collected by the sensor array according to the evolution law of characteristic parameters under typical fault conditions, compare the monitoring data of normal conditions and fault conditions, and identify typical fault conditions.

[0011] As an implementation method, the prediction model is used to integrate machine learning and deep learning using data processing and analysis methods, establish a mapping between faults and characteristic parameters by analyzing the changing patterns of the operating status of fire-fighting equipment within the characteristic parameter monitoring data set period, and realize the prediction and precise positioning of typical fault states.

[0012] As an implementation mode, the data processing and analysis method includes a trend analysis method, a time domain analysis method, a frequency domain analysis method, an acceleration envelope analysis method and a waterfall chart analysis method.

[0013] As an implementation mode, the risk assessment model is used to conduct quantitative analysis of defects and hidden dangers and classification of operational risks for the equipment, personnel and management elements of the fire protection facility Internet of Things of the target converter station based on the risk assessment indicator system module, the output of the state analysis model and the output of the prediction model.

[0014] As an implementation mode, the risk assessment indicator system module includes a firefighting facility risk assessment module, a firefighting personnel risk assessment module, a firefighting management risk assessment module and a risk assessment indicator system table.

[0015] As an implementation method, the risk assessment indicator system table includes primary indicators, secondary indicators and tertiary indicators; each of the primary indicators corresponds to multiple secondary indicators; each of the secondary indicators corresponds to multiple tertiary indicators; and the analytic hierarchy process is used to determine the weights of the primary indicators, secondary indicators and tertiary indicators.

[0016] As an implementation mode, the risk assessment model calculates the fire operation risk value R of the target converter station according to formula (1):

[0017] R=∑w i q i (1);

[0018] Among them, w i To evaluate the weight of item i, q i is the specific score of assessment item i.

[0019] A digital converter station fire operation risk assessment method based on the digital converter station fire operation risk assessment system of the present invention comprises the following steps:

[0020] S1: Develop an overall plan for fire operation risk assessment;

[0021] S2: using the fire protection facility Internet of Things collection module to collect the basic fire protection information; calling the safety status information output by the state analysis model and the prediction model;

[0022] S3: Manually collect the basic fire information and enter the basic fire information through the manual collection and entry module;

[0023] S4: calculating the fire operation risk value of the target converter station using the risk assessment model according to the basic information and the safety status information, and giving a risk classification according to the fire operation risk value;

[0024] S5: Prepare an assessment report based on the fire operation risk value and the risk classification.

[0025] The present invention adopts the above technical solution, so it has the following beneficial effects:

[0026] 1. The fire operation risk assessment system of the digital converter station of the present invention can carry out risk assessment on the fire operation of the digital converter station with risk characteristics according to the risk characteristics of the digital converter station. Based on the risk management theory and combined with the typical layout characteristics of the converter station, the present invention carries out risk assessment and monitoring and early warning from three aspects: unsafe factors of people, unsafe conditions of things, and management defects, which can effectively improve the transmission capacity and intelligent level of important channels and key sections of the power grid.

[0027] 2. Through the adoption of the Internet of Things acquisition module for fire protection facilities, basic data acquisition automation is realized. The digital converter station fire operation risk assessment system of the present invention makes full use of the machine acquisition advantages of the Internet of Things system of fire protection facilities, installs sensors on the target equipment, and senses and collects its operating status attributes (such as working pressure, temperature, amplitude, frequency, water level, etc.) and internal and external environmental conditions (such as ambient air humidity, temperature, noise, etc.) in real time. And through these sensors with high distribution density, wide coverage, sensitivity and efficiency, a data layer is constructed to obtain data information from all directions and angles, thereby realizing accurate, fast and efficient risk assessment.

[0028] 3. Through the adoption of state analysis models and prediction models, the state perception and fault prediction of fire-fighting facilities in the target converter station can be realized. For the risk assessment of fire-fighting facilities, on the one hand, the existing equipment information is obtained through the perception of the Internet of Things system, and on the other hand, artificial intelligence technology is used. Based on the state analysis model, by analyzing the law of changes in the operating state of fire-fighting equipment within the characteristic parameter monitoring data set period, a fault and characteristic parameter mapping is established to achieve typical fault state prediction and precise positioning. The output of the state analysis model and the prediction model is also used as the input of the corresponding fire-fighting facility risk assessment item in the risk assessment model. This further improves the accuracy, practicality and scientificity of the risk assessment results. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0030] Figure 1 A schematic diagram of the architecture of a digital converter station fire operation risk assessment system according to an embodiment of the present application;

[0031] Figure 2 This is a schematic diagram of the architecture of the fire protection facility Internet of Things in an embodiment of the present application;

[0032] Figure 3 This is a schematic diagram of the architecture of the application layer of an embodiment of the present application;

[0033] Figure 4 This is a schematic diagram of the structure of the evaluation index system module of the embodiment of the present application;

[0034] Figure 5 This is a flow chart of a method for assessing fire operation risks in a digital converter station according to an embodiment of the present application.

[0035] Description of Figure Numbers:

[0036] 1-Data layer;

[0037] 2-Communication layer;

[0038] 3- Management;

[0039] 4- Application layer;

[0040] 41-Status analysis model; 42-Prediction model; 43-Risk assessment model. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 making creative work are within the scope of protection of the present invention.

[0042] In the description of the present invention, it should be noted that the terms "upper", "lower", "left", "right", "center", "vertical", "horizontal", "inner", "outer", etc. indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, which are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", "third", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0043] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installation", "setting", "connection", "connection" and the like should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0044] See also Figure 1 to Figure 5 , the digital converter station fire operation risk assessment system of the embodiment of the present invention comprises: a data layer 1, a communication layer 2, a management layer 3 and an application layer 4;

[0045] The data layer 1 includes a firefighting facility Internet of Things acquisition module and a manual acquisition and entry module; the data layer 1 is used to collect and enter basic firefighting information;

[0046] The communication layer 2 is used to transmit the basic fire protection information collected and entered by the data layer 1 to the management layer 3 via wired or wireless means, and link the open interface of the management layer 3 with the model call of the application layer 4;

[0047] The management layer 3 is responsible for uniformly defining and managing the data, users, permissions, rules, protocols and applications in the system, performing verification, cleaning and regularization processing on the basic fire protection information transmitted from the communication layer 2, and opening a unified calling interface to the application layer 4;

[0048] The application layer 4 includes a state analysis model 41, a prediction model 42 and a risk assessment model 43, which are used for risk assessment and monitoring.

[0049] In this embodiment, data layer 1 is the basic layer of the evaluation method and the main source of object data of application layer 4. Data layer 1 includes the Internet of Things acquisition module for fire protection facilities and the manual acquisition and entry module. Data is divided into two categories: machine acquisition and manual acquisition. Machine acquisition is mainly completed by the Internet of Things acquisition module for fire protection facilities. By installing sensors on the target equipment, its operating status attributes (such as working pressure, temperature, amplitude, frequency, water level, etc.) and internal and external environmental conditions (such as ambient air humidity, temperature, noise, etc.) are sensed and collected in real time. Data layer 1 obtains data information from all directions and angles through these sensors with high distribution density, wide coverage, sensitivity and efficiency, providing sufficient data resources for application layer 4, thereby realizing online calculation and unified control of various information. Manual collection is data entered into the system by staff or on-site inspectors in combination with the dynamic lines of fire protection work content.

[0050] The firefighting facility IoT acquisition module is used to collect the operating status information and internal and external environmental information of the target equipment of the firefighting facility IoT of the target converter station in real time through sensors. The operating status information includes working pressure, temperature, amplitude, frequency and water level; the internal and external environmental information includes: ambient air humidity, temperature and noise.

[0051] In this embodiment, the fire-fighting facility Internet of Things includes an automatic fire alarm system, a fire-fighting water supply and fire hydrant system, an automatic sprinkler system, and a compressed air foam system. In other embodiments, the fire-fighting facility Internet of Things can also adjust its components as needed.

[0052] The communication layer 2 is mainly responsible for data transmission. On the one hand, it transmits the basic fire protection information collected and identified by the data layer 1 to the management layer 3 through wired or wireless means. On the other hand, it links the open interface of the management layer 3 with the model call of the application layer 4.

[0053] The management layer 3 is responsible for the unified definition and management of the data, users, permissions, rules, protocols, applications, etc. in the entire system, plays the role of the operating system middleware, verifies and cleans the original data transmitted from the communication layer 2, and opens a unified calling interface to the application layer 4.

[0054] The application layer 4 is the top layer of the system. It uses time series, mathematical statistics, neural networks, machine learning, data mining and other methods to build state analysis models 41, prediction models 42 and risk assessment models 43, call data interfaces, and carry out risk assessment and monitoring.

[0055] The state analysis model 41 is used to construct a fire-fighting equipment fault set, analyze the data collected by the sensor array according to the evolution law of characteristic parameters under typical fault conditions, compare the monitoring data of normal conditions and fault conditions, and identify typical fault conditions.

[0056] In this embodiment, the state analysis model 41 collects monitoring signals such as pressure, vibration, and action signals of the normal standby operating state and typical fault state of the fire water system, compressed air foam fire extinguishing system, etc. through the sensor array. By constructing a fire equipment fault set and based on the evolution law of characteristic parameters under typical fault conditions, the data collected by the sensor array is analyzed, the monitoring data of normal conditions and fault conditions are compared, and typical fault conditions are identified.

[0057] The prediction model 42 is used to integrate machine learning and deep learning by using data processing and analysis methods, establish fault and characteristic parameter mapping by analyzing the change law of the fire equipment operation status within the characteristic parameter monitoring data set period, and realize typical fault status prediction and accurate positioning. The data processing and analysis methods include trend analysis method, time domain analysis method, frequency domain analysis method, acceleration envelope analysis method and waterfall chart analysis method.

[0058] The risk assessment model 43 is used to conduct quantitative analysis of defects and hidden dangers and classification of operational risks for the equipment, personnel and management elements of the fire protection facility Internet of Things of the target converter station based on the risk assessment indicator system module, the output of the state analysis model 41 and the output of the prediction model 42, and in accordance with national and industry standards and specifications.

[0059] In this embodiment, the risk assessment indicator system module includes a firefighting facility risk assessment module, a firefighting personnel risk assessment module, a firefighting management risk assessment module and a risk assessment indicator system table.

[0060] The fire protection facility risk assessment module assesses the fire protection facility Internet of Things of the converter station.

[0061] Among them, in this embodiment, the main buildings in the converter station include the valve hall, converter transformer and control building.

[0062] The valve hall is composed of the extreme I high-end, extreme I low-end, extreme II high-end, and extreme II low-end valve halls. The main body of the valve hall is a steel structure painted with steel structure fire retardant paint, and the main internal component is the flow control valve. The fire protection system equipped with the Internet of Things for fire protection facilities includes early suction smoke fire alarms, ultraviolet flame detectors and automatic fire alarm systems, and mechanical smoke exhaust systems. The patrol corridor is equipped with cart-type dry powder fire extinguishers, point smoke detectors, emergency lighting and evacuation indication systems, etc.

[0063] The converter transformer is installed in a BOX-IN structure. An oil collection pit is set up below and the leaked oil is discharged to the accident oil pool through a water seal well. The weight of the oil stored in the converter transformer ranges from tens to hundreds of tons. The fire protection system equipped with the Internet of Fire Facilities is composed of a cable-type linear temperature-sensing fire detection system, a water spray fire extinguishing system, a compressed air foam fire extinguishing system, a converter transformer firewall, an accident oil pool and a water seal well.

[0064] The control building is mainly equipped with a main control room, battery room, equipment room, air conditioning room, office room, etc. The host of the automatic fire alarm system of the fire protection facility Internet of Things is generally located in the main control room. The main steel structure of the control building is painted with steel structure fire retardant paint for protection. The fire protection facilities equipped include indoor fire hydrant system, automatic fire alarm system, fire emergency broadcast system, emergency lighting and evacuation indication system, etc.

[0065] Flame-retardant cables are installed in layers in the cable trench, and fireproof covers are installed on the top. There are fireproof isolation zones every 60 meters in the cable trench. In the main cable trench and square cable trench of the UHV converter station, the interval is reduced to 30 meters. Temperature-sensitive cables are wrapped around the cable surface, and suspended dry powder fire extinguishers are installed.

[0066] In this embodiment, the firefighter risk assessment module assesses objects including firefighters.

[0067] Firefighters refer to the personnel who are engaged in fire-related management, work and rescue in the converter station, mainly including fire safety responsible person managers, fire safety management staff and emergency rescue personnel.

[0068] The legal representative, principal person in charge or actual controller of the converter station is the person responsible for fire safety and is fully responsible for the fire safety of the converter station. The person responsible for fire safety should coordinate the fire protection work in the station, approve and implement the annual fire protection work plan, provide necessary funds and organizational guarantees for fire safety, organize fire prevention inspections, supervise the implementation of fire hazard rectification, promptly handle major issues involving fire safety, organize the formulation of fire extinguishing and emergency evacuation plans that meet the actual situation of the converter station, and implement drills. The person responsible for fire safety should also determine the fire safety manager, who will organize and implement the fire safety management work of the converter station.

[0069] Fire safety management staff are mainly responsible for formulating and implementing fire safety responsibilities of various positions, fire safety operating procedures, fire facility operation and maintenance procedures and other systems, and formulating fire extinguishing and emergency evacuation plans for important places and key areas; doing a good job in fire control room duty and fire protection facilities, fire protection facilities, equipment configuration, inspection, maintenance, and other management work to ensure they are in good condition and effective; carrying out monthly fire prevention inspections and daily fire prevention patrols, establishing inspection and patrol records, and promptly eliminating fire safety hazards.

[0070] Emergency rescue personnel include volunteer firefighters and professional firefighters in the station. They are important participants in fire fighting and emergency evacuation. They should be familiar with relevant fire fighting and emergency evacuation plans, and be able to skillfully extinguish initial fires, organize and guide personnel to evacuate safely, and conduct emergency rescue when a fire occurs. Volunteer firefighters are also the main force in fire safety monitoring work at the fire scene.

[0071] In this embodiment, the assessment object of the fire management risk assessment module includes fire management.

[0072] Fire management mainly includes the implementation of the fire safety responsibility system, fire management, publicity, education and training, and fire extinguishing and emergency evacuation plans and drills. A sound fire archive management system should be established, and fire archives should include basic fire safety information and fire safety management information. Identify key fire safety areas, set up fire prevention signs, and implement strict management. Establish and improve the fire safety education and training system, clarify the organization and personnel, and ensure the funding for education and training. Fire extinguishing and emergency evacuation plans should be formulated in light of actual conditions, and drills should be conducted at least once every six months, so as to summarize experience in a timely manner and continuously improve the plans. Divide the fire level and fire area, and implement fire safety organizational measures, including fire work permits, work permits, supervision, interruptions and terminations.

[0073] In this embodiment, the risk assessment index system table is shown in Table 1.

[0074] The risk assessment indicator system table includes primary indicators, secondary indicators and tertiary indicators; each of the primary indicators corresponds to multiple secondary indicators; each of the secondary indicators corresponds to multiple tertiary indicators; the analytic hierarchy process is used to determine the weights of the primary indicators, secondary indicators and tertiary indicators.

[0075]

[0076]

[0077]

[0078] Table 1. Risk assessment indicator system

[0079] In this embodiment, the risk assessment model 43 calculates the fire operation risk value R of the target converter station according to formula (1):

[0080] R=∑w i q i (1);

[0081] Among them, w i To evaluate the weight of item i, q i It is the specific score of the assessment item i. The larger the score, the higher the risk.

[0082] The risk assessment model 43 also divides the risk assessment results of all assessment objects within the assessment scope into four levels according to the risk data distribution, statistical characteristics and differences of the assessment objects: high risk, relatively high risk, general risk and relatively low risk; and marks each risk level with red, orange, yellow and blue respectively.

[0083] The digital converter station fire operation risk assessment system of the present invention is targeted at the risk characteristics of digital converter stations and can carry out risk assessment on the fire operation of digital converter stations with risk characteristics. Based on the risk management theory and combined with the typical layout characteristics of converter stations, the present invention carries out risk assessment and monitoring and early warning from three aspects: unsafe factors of people, unsafe conditions of objects, and management defects, which can effectively improve the transmission capacity and intelligent level of important channels and key sections of the power grid.

[0084] The basic data collection automation is realized by adopting the Internet of Things acquisition module of fire protection facilities. The digital converter station fire operation risk assessment system of the present invention makes full use of the machine acquisition advantages of the Internet of Things system of fire protection facilities, installs sensors on the target equipment, and senses and collects its operating status attributes (such as working pressure, temperature, amplitude, frequency, water level, etc.) and internal and external environmental conditions (such as ambient air humidity, temperature, noise, etc.) in real time. And through these sensors with high distribution density, wide coverage, sensitivity and efficiency, the data layer 1 is constructed to obtain data information from all directions and angles, thereby realizing accurate, fast and efficient risk assessment.

[0085] By adopting the state analysis model 41 and the prediction model 42, the state perception and fault prediction of the fire-fighting facilities in the target converter station are realized. For the risk assessment of fire-fighting facilities, on the one hand, the existing equipment information is obtained through the perception of the Internet of Things system, and on the other hand, artificial intelligence technology is used. Based on the state analysis model 41, by analyzing the law of changes in the operating state of the fire-fighting equipment within the characteristic parameter monitoring data set period, a fault and characteristic parameter mapping is established to achieve typical fault state prediction and precise positioning. The output of the state analysis model 41 and the prediction model 42 is also used as the input of the corresponding fire-fighting facility risk assessment item in the risk assessment model 43. The accuracy, practicality and scientificity of the risk assessment results are further improved. Among them, the typical fault state prediction and precise positioning are realized through the state analysis model 41 and the prediction model 42 of the application layer 4, and serve as the input of the risk assessment model 43.

[0086] A digital converter station fire operation risk assessment method based on the digital converter station fire operation risk assessment system of the present invention comprises the following steps:

[0087] S1: Develop an overall plan for fire operation risk assessment;

[0088] Understand the comprehensive fire safety management work of the assessment object, investigate the building distribution, working conditions and operation plan of the converter station to be assessed, formulate an overall plan for fire operation risk assessment, clarify the purpose, principles and scope of the assessment, formulate a work schedule and roadmap, break down tasks, and implement guarantees.

[0089] S2: using the fire protection facility Internet of Things collection module to collect the fire protection basic information; calling the safety status information output by the state analysis model 41 and the prediction model 42;

[0090] S3: Manually collect the basic fire information and enter the basic fire information through the manual collection and entry module;

[0091] For basic data information that needs to be collected manually, the inspectors will conduct a comprehensive and in-depth assessment of each area of ​​the object, and obtain it through on-site visits, investigations, inspections, etc. The aforementioned collected data will also be spot-checked and reviewed to ensure the authenticity, accuracy and completeness of the data.

[0092] S4: Calculating the fire operation risk value of the target converter station using the risk assessment model 43 according to the basic information and the safety status information, and giving a risk classification according to the fire operation risk value;

[0093] According to the assessment indicators and assessment models, the risk scores of the risk items involved in the assessment object are calculated one by one, and the total score of its fire operation risk is automatically summarized. A risk grade is given to quantify the overall fire safety level of the assessment object.

[0094] S5: Prepare an assessment report based on the fire operation risk value and the risk classification.

[0095] In this embodiment, by conducting statistical descriptions such as the maximum value, minimum value, average value, mode, median, and quantile of each risk indicator score and drawing risk classification maps, the overall fire safety risk classification distribution and ranking of the assessed scope are mastered. By drawing visual auxiliary analysis such as frequency distribution maps and radar maps, the fire safety hazards and risk points of each digital converter station are accurately identified. Finally, targeted countermeasures and suggestions are comprehensively proposed and an assessment report is written.

[0096] It should be noted that the preferred embodiments of the present invention are given in the specification and drawings of the present invention. However, the present invention can be implemented in many different forms and is not limited to the embodiments described in this specification. These embodiments are not intended to be additional limitations on the content of the present invention. The purpose of providing these embodiments is to make the understanding of the disclosure of the present invention more thorough and comprehensive. In addition, the above-mentioned technical features continue to be combined with each other to form various embodiments not listed above, which are all considered to be within the scope of the present invention; further, for ordinary technicians in this field, they can be improved or transformed according to the above description, and all these improvements and transformations should belong to the scope of protection of the claims attached to the present invention.

[0097] The present invention is described in detail above in conjunction with the embodiments of the accompanying drawings. A person skilled in the art can make various variations of the present invention according to the above description. Therefore, certain details in the embodiments should not constitute a limitation of the present invention, and the scope of protection of the present invention shall be defined by the scope of the attached claims.

Claims

1. A digital converter station fire operation risk assessment system, characterized in that: include: Data layer, communication layer, management layer and application layer; The data layer includes a firefighting facility Internet of Things collection module and a manual collection and entry module; The data layer is used to collect and input basic firefighting information; The communication layer is used to transmit the basic firefighting information collected and entered by the data layer to the management layer by wire or wireless means, and to link the open interface of the management layer with the model call of the application layer; The management layer is responsible for uniformly defining and managing the data, users, permissions, rules, protocols and applications in the system, performing verification, cleaning and regular processing on the basic fire protection information transmitted from the communication layer, and opening a unified calling interface to the application layer; The application layer includes a state analysis model, a prediction model and a risk assessment model, which are used for risk assessment and monitoring.

2. The digital converter station fire operation risk assessment system according to claim 1 is characterized in that: The firefighting facility Internet of Things acquisition module is used to collect the operating status information and internal and external environment information of the target equipment of the firefighting facility Internet of Things of the target converter station in real time through sensors.

3. The digital converter station fire operation risk assessment system according to claim 2 is characterized in that: The state analysis model is used to construct a fire equipment fault set, analyze the data collected by the sensor array according to the evolution law of characteristic parameters under typical fault conditions, compare the monitoring data of normal conditions and fault conditions, and identify typical fault conditions.

4. The digital converter station fire operation risk assessment system according to claim 2 is characterized in that: The prediction model is used to integrate machine learning and deep learning by adopting data processing and analysis methods, establish a mapping between faults and characteristic parameters by analyzing the changing rules of the operating status of fire-fighting equipment within the period of the characteristic parameter monitoring data set, and realize the prediction and precise positioning of typical fault states.

5. The digital converter station fire operation risk assessment system according to claim 4 is characterized in that: The data processing and analysis methods include trend analysis method, time domain analysis method, frequency domain analysis method, acceleration envelope analysis method and waterfall chart analysis method.

6. The digital converter station fire operation risk assessment system according to claim 2 is characterized in that: The risk assessment model is used to conduct quantitative analysis of defects and hidden dangers and classification of operational risks for the equipment, personnel and management elements of the fire protection facility Internet of Things of the target converter station based on the risk assessment indicator system module, the output of the state analysis model and the output of the prediction model.

7. The digital converter station fire operation risk assessment system according to claim 6 is characterized in that: The risk assessment indicator system module includes a firefighting facility risk assessment module, a firefighting personnel risk assessment module, a firefighting management risk assessment module and a risk assessment indicator system table.

8. The digital converter station fire operation risk assessment system according to claim 7 is characterized in that: The risk assessment indicator system table includes primary indicators, secondary indicators and tertiary indicators; each of the primary indicators corresponds to multiple secondary indicators; each of the secondary indicators corresponds to multiple tertiary indicators; the analytic hierarchy process is used to determine the weights of the primary indicators, secondary indicators and tertiary indicators.

9. The digital converter station fire operation risk assessment system according to claim 8 is characterized in that: The risk assessment model calculates the fire operation risk value R of the target converter station according to formula (1): R=∑w i q i (1); Among them, w i To evaluate the weight of item i, q i is the specific score of assessment item i.

10. A method for assessing fire operation risk of a digital converter station based on the fire operation risk assessment system of a digital converter station according to claim 9, comprising the steps of: S1: Develop an overall plan for fire operation risk assessment; S2: Collect the basic fire protection information using the fire protection facility Internet of Things collection module; Calling the security status information output by the status analysis model and the prediction model; S3: Manually collect the basic fire information and enter the basic fire information through the manual collection and entry module; S4: calculating the fire operation risk value of the target converter station using the risk assessment model according to the basic information and the safety status information, and giving a risk classification according to the fire operation risk value; S5: Prepare an assessment report based on the fire operation risk value and the risk classification.

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