Transformer substation fire alarm system and method

Abstract

The invention discloses a transformer substation fire alarm system and method. The system comprises a sensing layer, a network layer, a platform layer and an application layer. The sensing layer is used for monitoring fire in all directions, is responsible for collecting various fire signals in the transformer substation, and is composed of fixed monitoring equipment and a mobile inspection robot; the network layer is used for reliably transmitting data and is responsible for safely, reliably and stably transmitting the data acquired by the sensing layer to a decision center; the platform layer is used for intelligent analysis and decision making, and is responsible for processing data, making a judgment and sending an instruction; the application layer is used for remote monitoring and linkage processing and provides an interactive interface for the system and operation and maintenance personnel. The system has the advantages of comprehensive and sufficient monitoring data, good alarm effect, high alarm efficiency and convenience in early warning and maintenance, and can provide 7 * 24-hour online guard for fire safety of an unattended substation.

Description

Technical Field

[0001] This invention belongs to the field of substation fire alarm technology, specifically relating to a substation fire alarm system and method. Background Technology

[0002] The substation fire alarm system is an automated system specifically designed for the complex environment of substations. It is used to detect potential fire hazards at an early stage, issue alarms, and link and control fire extinguishing equipment. It features the characteristics of ensuring power grid safety, protecting critical equipment, preventing secondary disasters, and enabling unattended operation.

[0003] However, the existing substation fire alarm systems do not make reasonable and sufficient use of the Internet of Things, big data, and mobile inspection technologies, mainly in the following aspects: 1. Due to the susceptibility of a single sensor to interference or its fixed sensitivity, false alarms and missed alarms occur frequently. 2. Fixed detectors have physical blind spots, and the fire may have already spread by the time an alarm is triggered, resulting in a delayed response. 3. When equipment failures or communication terminal malfunctions occur at unmanned stations, they are difficult to detect in a timely manner, leading to maintenance difficulties. 4. Fire alarm, video surveillance and fire extinguishing systems often have poor linkage, and alarm information is isolated, which is not conducive to remote decision-making. To solve the above problems, it is necessary to develop a substation fire alarm system and method. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art and provide a substation fire alarm system and method with comprehensive and sufficient monitoring data, good alarm effect, high alarm efficiency, and convenient early warning and maintenance, which can provide 24 / 7 online protection for the fire safety of unattended substations.

[0005] The objective of this invention is achieved as follows: In a first aspect, a substation fire alarm system is provided, comprising a sensing layer, a network layer, a platform layer, and an application layer; The sensing layer is used for all-round fire monitoring and is responsible for collecting various fire signals in the substation. It consists of fixed monitoring equipment and mobile inspection robots. The network layer is used for reliable data transmission and is responsible for transmitting the data collected by the perception layer to the decision center securely, reliably, and stably. The platform layer is used for intelligent analysis and decision-making, and is responsible for processing data, making judgments and issuing instructions. The application layer is used for remote monitoring and coordinated response, and provides an interactive interface for the system and maintenance personnel.

[0006] Preferably, the fixed monitoring equipment is configured as follows: Main transformer area: Linear heat-sensing fire detectors with heat-sensing cables are used and wrapped around the transformer body and oil pipes. At the same time, flame detectors with rapid open flame alarm are used and placed in easily ignited areas. Switchgear room and control room: Use aspirating smoke detectors that can provide early warning, or use intelligent electronic constant temperature difference combination detectors that can simultaneously sense smoke and temperature, and place them near key precision equipment. Cable trenches and cable interlayers: Linear temperature detectors and / or aspirating smoke detectors are used, and they are laid at certain intervals along the cable trays. Battery compartment: Equipped with combustible gas detectors that can prevent explosion risks, and monitors hydrogen concentration.

[0007] Preferably, the mobile inspection robot integrates a smoke sensor, a flame sensor, and an infrared thermal imaging temperature measurement device, and is set to autonomously patrol along a preset route or under remote control to monitor the temperature of substation equipment and promptly alarm upon detecting abnormalities.

[0008] Preferably, the network layer includes an IoT gateway and a communication network. The IoT gateway is deployed at the substation site to be responsible for aggregating and protocol converting data collected by various detectors. The communication network is a ubiquitous power IoT composed of a dedicated fiber optic network, 4G / 5G, LoRa, and NB-IoT.

[0009] Preferably, the platform layer is a fire intelligent analysis platform deployed in a monitoring center or the cloud, which is responsible for receiving and storing all fire data sent by the network layer, and completing fire risk assessment, graded early warning mechanism, equipment management and system self-diagnosis based on big data analysis technology.

[0010] Preferably, the fire risk assessment workflow is as follows: (1) Data aggregation: Aggregating multi-dimensional, asynchronous data streams from all sensors; (2) Feature extraction and spatiotemporal correlation: Extract the features of each signal and correlate them with the time and space dimensions; (3) Intelligent algorithm model judgment: The platform has a built-in expert knowledge base and machine learning model. The multi-source data after association is input into the model for comprehensive calculation and outputs the judgment result: fire alarm confidence level.

[0011] Preferably, the tiered early warning mechanism initiates different levels of emergency response procedures based on the assessed fire alarm confidence level, as follows: (1) Fire alarm confidence level 0-30%, triggering Level 1 warning: status alert; (2) Fire alarm confidence level 30-60%, triggering Level II warning: early warning, notifying operation and maintenance personnel to pay close attention and analyze; (3) Fire alarm confidence level 60-95%, triggering level three warning: warning alarm, notify the person in charge and the scene, start video verification, and start emergency plan; (4) Fire alarm confidence level > 95% triggers Level 4 warning: confirm fire alarm, highest level sound and light alarm, automatic linkage fire extinguishing system, remote notification and start evacuation; After completing the corresponding emergency procedures, the system was restored to normal monitoring status.

[0012] Preferably, the device management and system self-diagnosis workflow is as follows: (1) Establish a full life cycle equipment file: The platform establishes an electronic file for each front-end device, recording its model, installation location, commissioning time, and maintenance history; (2) Real-time status monitoring and status report detection: The platform continuously conducts two-way communication with all devices, and the devices periodically send their status detection reports to the platform; (3) Predictive maintenance and automatic repair reporting: When the platform does not receive a status detection report of a certain device or receives a self-test failure report, it immediately generates a device fault alarm and automatically and accurately locates the specific device through the power file, and then automatically reports the repair; at the same time, the platform predicts the performance degradation trend of the device by analyzing the sensitivity change of the detector and the background noise level data. When it finds that the data is close to the threshold affecting its normal operation, it generates a predictive maintenance work order in advance and automatically dispatches the maintenance task to relevant personnel, forming a closed loop of operation and maintenance.

[0013] Preferably, the application layer includes a remote monitoring center and a linkage fire extinguishing device. In the regional monitoring center or through a mobile terminal, maintenance personnel can remotely and centrally monitor the status of the fire protection system of multiple unattended substations. Once a fire alarm occurs, the system accurately locates the fire and issues an audible and visual alert, while simultaneously pushing alarm information. After confirming the fire, the system automatically or remotely and manually activates the corresponding fire extinguishing device to complete the linkage fire extinguishing work.

[0014] Secondly, a substation fire alarm method is provided, applied to the aforementioned substation fire alarm system, comprising the following steps: S1, All-round data acquisition: Fixed detectors and mobile inspection robots work together to monitor all key areas in the station without blind spots, and collect data on temperature, smoke, open flame and gas concentration. S2, Reliable Data Transmission: The IoT gateway within the station collects data from all sensors and robots, and transmits the data stably and in real time to a remote fire intelligent analysis platform via fiber optic or 5G networks. S3, Intelligent Analysis and Judgment: The platform performs fusion analysis on the received multi-source data, uses algorithm models for cross-validation, and calculates the fire alarm confidence level; S4, graded early warning and linkage: activate the corresponding plan according to the fire alarm confidence level, and automatically link the on-site fire extinguishing device when the fire alarm is confirmed; S5, Remote Monitoring and Closed Loop: The monitoring center can remotely confirm the fire situation and intervene manually when necessary. At the same time, the platform continuously performs system self-diagnosis, monitors the health status of equipment, generates maintenance work orders, and forms an operation and maintenance closed loop.

[0015] Due to the adoption of the above technical solution, the beneficial effects of the present invention are: (1) The present invention adopts multi-sensor fusion and intelligent algorithm. The platform simultaneously receives data collected from multiple sensors. Detectors based on multiple principles serve as backups to compensate for the detection blind spots of a single technology. The algorithm performs multi-dimensional cross-verification, effectively eliminating false alarms while greatly reducing the false alarm rate. (2) The present invention adopts a combination of fixed point and mobile inspection. The mobile inspection robot can conduct a blind spot inspection without dead angles in the blind spots that are difficult to be fully covered by fixed detectors. The infrared thermal imaging temperature measurement device it is equipped with can perform general and precise temperature measurement on the equipment, discover overheating hazards, and trigger early warning. At the same time, the aspirating smoke detector can detect invisible combustion gas aerosol particles, realizing ultra-early warning of fire. (3) The present invention adopts full-system online monitoring and self-diagnosis. The Internet of Things gateway and intelligent analysis platform in the system can continuously monitor the working conditions of all front-end devices. The system can analyze the performance degradation trend of the equipment, achieve early maintenance, and the system can be online 24 / 7, eliminating the pain point of unattended operation. (4) The present invention adopts intelligent linkage and unified information platform to ensure that early warnings at all levels can be processed in a timely manner and facilitates operation and maintenance personnel to fully grasp the overall fire protection situation of the substation through the remote monitoring center; In summary, this invention has the advantages of comprehensive and sufficient monitoring data, good alarm effect, high alarm efficiency, and convenient early warning and maintenance, and can provide 24 / 7 online protection for the fire safety of unattended substations. Attached Figure Description

[0016] Figure 1 This is a schematic diagram illustrating the system composition and working principle of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will be further described in detail below through embodiments and in conjunction with the accompanying drawings.

[0018] like Figure 1 As shown, in a first aspect, the present invention provides a substation fire alarm system, including a sensing layer, a network layer, a platform layer and an application layer. The system integrates Internet of Things technology and smart devices, aiming to achieve comprehensive, accurate and rapid substation fire early warning and response.

[0019] The sensing layer is used for all-round fire monitoring and is responsible for collecting various fire signals within the substation. It consists of fixed monitoring equipment and mobile inspection robots.

[0020] Fixed monitoring equipment: Its deployment needs to be differentiated based on the characteristics of the substation's protected area, but should adhere to the following main principles: Main transformer area: Linear heat-sensing fire detectors with heat-sensing cables are used and wrapped around the transformer body and oil pipes. At the same time, flame detectors with rapid open flame alarm are used and placed in easily ignited areas. Switchgear room and control room: Use aspirating smoke detectors that can provide early alarms, or use intelligent electronic constant temperature difference combination detectors that can simultaneously sense smoke and temperature. They have a low false alarm rate and are placed near critical precision equipment. Cable trenches and cable interlayers: Linear temperature detectors and / or aspirating smoke detectors are used, and they are laid at certain intervals along the cable trays. Battery room: Equipped with combustible gas detectors that can prevent explosion risks, monitoring hydrogen concentration and preventing explosion risks.

[0021] Mobile inspection robots: As an effective supplement to fixed monitoring points, they can eliminate monitoring blind spots. They integrate smoke sensors, flame sensors, and infrared thermal imaging temperature measurement devices. They can autonomously patrol according to preset routes or under remote control to monitor the temperature of substation equipment and promptly alarm when abnormalities are detected.

[0022] The network layer is used for reliable data transmission and is responsible for transmitting the data collected by the perception layer to the decision center securely, reliably, and stably.

[0023] IoT Gateway and Communication Network: An IoT gateway is deployed at the substation site to collect and convert data collected by various detectors. The communication network is a ubiquitous power IoT composed of fiber optic private network, 4G / 5G, LoRa, NB-IoT, etc., which can ensure the reliability and real-time performance of data transmission.

[0024] The platform layer is used for intelligent analysis and decision-making, and is responsible for processing data, making judgments, and issuing instructions.

[0025] Deploy a fire intelligent analysis platform in the monitoring center or cloud to receive and store all fire data sent from the network layer, and based on big data analysis technology, complete fire risk assessment, graded early warning mechanism, equipment management and system self-diagnosis.

[0026] 1. The fire risk assessment process is as follows: (1) Data collection: Collect multi-dimensional, asynchronous data streams from all sensors; such as the smoke concentration change curve of the smoke detector, the temperature value and heating rate of the heat detector, the specific ultraviolet / infrared spectral signal intensity of the fire and smoke detector, the hydrogen concentration value of the combustible gas detector, the infrared thermal image temperature spectrum and visible light video of the robot inspection, etc. (2) Feature extraction and spatiotemporal correlation: Extract the features of each signal and correlate them with the time and space dimensions; Examples of spatiotemporal correlation: Spatial correlation: If a smoke detector at point A alarms while a heat detector at point B also shows an increase in temperature, and A and B are located in the same cable channel, the platform will determine that these two events are spatially correlated, greatly increasing the likelihood of a fire alarm; Temporal correlation: The platform analyzes the sequence of events, such as if the heat detector first detects a slow temperature rise (early overheating), and the aspirating smoke detector only alarms a few minutes later (smoke is produced). This sequence of events conforms to the pattern of fire development and is highly reliable. (3) Intelligent algorithm model judgment: The platform has a built-in expert knowledge base and machine learning model. The multi-source data after association is input into the model for comprehensive calculation and outputs the judgment result: fire alarm confidence level.

[0027] 2. The tiered early warning mechanism activates different levels of emergency response procedures based on the assessed fire alarm confidence level, as follows: (1) Fire alarm confidence level 0-30%, triggering Level 1 warning: status alert; (2) Fire alarm confidence level 30-60%, triggering Level II warning: early warning, notifying operation and maintenance personnel to pay close attention and analyze; (3) Fire alarm confidence level 60-95%, triggering level three warning: warning alarm, notify the person in charge and the scene, start video verification, and start emergency plan; (4) Fire alarm confidence level > 95% triggers Level 4 warning: confirm fire alarm, highest level sound and light alarm, automatic linkage fire extinguishing system, remote notification and start evacuation; After completing the corresponding emergency procedures, the system was restored to normal monitoring status.

[0028] 3. The equipment management and system self-diagnosis workflow is as follows: (1) Establish a full life cycle equipment file: The platform establishes an electronic file for each front-end device, recording its model, installation location, commissioning time, and maintenance history; (2) Real-time status monitoring and status report detection: The platform continuously conducts two-way communication with all devices, and the devices periodically send their status detection reports to the platform; (3) Predictive maintenance and automatic repair reporting: When the platform does not receive a status detection report of a certain device or receives a self-test failure report, it immediately generates a device fault alarm and automatically and accurately locates the specific device through the power file, and then automatically reports the repair; at the same time, the platform predicts the performance degradation trend of the device by analyzing the sensitivity change of the detector and the background noise level data. When it finds that the data is close to the threshold affecting its normal operation, it generates a predictive maintenance work order in advance and automatically dispatches the maintenance task to relevant personnel, forming a closed loop of operation and maintenance.

[0029] The application layer is used for remote monitoring and coordinated response, and provides an interactive interface for the system and maintenance personnel. The application layer is implemented through a remote monitoring center and coordinated fire extinguishing devices.

[0030] Remote monitoring center: From the regional monitoring center or through mobile terminals, maintenance personnel can remotely and centrally monitor the status of fire protection systems in multiple unattended substations. Once a fire alarm occurs, the system can accurately locate the fire and issue audible and visual alerts, while also pushing alarm information.

[0031] Linked fire suppression system: After confirming a fire, the system can automatically or remotely manually activate the corresponding fire suppression devices to complete the linked fire suppression work. For example, for a main transformer, a water spray fire suppression system or a foam system is usually linked; for a switch cabinet room, a gas fire suppression system (such as heptafluoropropane) is usually linked.

[0032] Secondly, the present invention provides a substation fire alarm method, applied to the aforementioned substation fire alarm system, comprising the following steps: S1, all-round data acquisition: Fixed detectors (temperature, smoke, flame, gas) and mobile inspection robots (supplementing data + eliminating blind spots) work together to monitor all key areas in the station without dead angles and collect data such as temperature, smoke, open flame, and gas concentration. S2, Reliable Data Transmission: The IoT gateway within the station collects data from all sensors and robots, and transmits the data stably and in real time to a remote fire intelligent analysis platform via fiber optic or 5G networks. S3, Intelligent Analysis and Judgment: The platform performs fusion analysis on the received multi-source data, uses algorithm models for cross-validation, and calculates the fire alarm confidence level; S4, graded early warning and linkage: activate the corresponding plan according to the fire alarm confidence level, and automatically link the on-site fire extinguishing device when the fire alarm is confirmed; S5, Remote Monitoring and Closed Loop: The monitoring center can remotely confirm the fire situation and intervene manually when necessary. At the same time, the platform continuously performs system self-diagnosis, monitors the health status of equipment, generates maintenance work orders, and forms an operation and maintenance closed loop.

[0033] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.

Claims

1. A substation fire alarm system, characterized in that: It includes the perception layer, network layer, platform layer, and application layer; The sensing layer is used for all-round fire monitoring and is responsible for collecting various fire signals in the substation. It consists of fixed monitoring equipment and mobile inspection robots. The network layer is used for reliable data transmission and is responsible for transmitting the data collected by the perception layer to the decision center securely, reliably, and stably. The platform layer is used for intelligent analysis and decision-making, and is responsible for processing data, making judgments and issuing instructions. The application layer is used for remote monitoring and coordinated response, and provides an interactive interface for the system and maintenance personnel.

2. The substation fire alarm system according to claim 1, characterized in that: The fixed monitoring equipment is configured as follows: Main transformer area: Linear heat-sensing fire detectors with heat-sensing cables are used and wrapped around the transformer body and oil pipes. At the same time, flame detectors with rapid open flame alarm are used and placed in easily ignited areas. Switchgear room and control room: Use aspirating smoke detectors that can provide early warning, or use intelligent electronic constant temperature difference combination detectors that can simultaneously sense smoke and temperature, and place them near key precision equipment. Cable trenches and cable interlayers: Linear temperature detectors and / or aspirating smoke detectors are used, and they are laid at certain intervals along the cable trays. Battery compartment: Equipped with combustible gas detectors that can prevent explosion risks, and monitors hydrogen concentration.

3. The substation fire alarm system according to claim 1, characterized in that: The mobile inspection robot integrates a smoke sensor, a flame sensor, and an infrared thermal imaging temperature measurement device. It is set to autonomously patrol along a preset route or under remote control to monitor the temperature of substation equipment and promptly alarm if any abnormalities are detected.

4. The substation fire alarm system according to claim 1, characterized in that: The network layer includes an IoT gateway and a communication network. The IoT gateway is deployed at the substation site and is responsible for aggregating and protocol converting data collected by various detectors. The communication network is a ubiquitous power IoT composed of a dedicated fiber optic network, 4G / 5G, LoRa, and NB-IoT.

5. The substation fire alarm system according to claim 1, characterized in that: The platform layer is a fire intelligent analysis platform deployed in a monitoring center or cloud. It is responsible for receiving and storing all fire data sent by the network layer, and based on big data analysis technology, it completes fire risk assessment, graded early warning mechanism, equipment management and system self-diagnosis.

6. The substation fire alarm system according to claim 5, characterized in that: The fire risk assessment workflow is as follows: (1) Data aggregation: Aggregating multi-dimensional, asynchronous data streams from all sensors; (2) Feature extraction and spatiotemporal correlation: Extract the features of each signal and correlate them with the time and space dimensions; (3) Intelligent algorithm model judgment: The platform has a built-in expert knowledge base and machine learning model. The multi-source data after association is input into the model for comprehensive calculation and outputs the judgment result: fire alarm confidence level.

7. The substation fire alarm system according to claim 6, characterized in that: The tiered early warning mechanism activates different levels of emergency response procedures based on the assessed fire alarm confidence level, as follows: (1) Fire alarm confidence level 0-30%, triggering Level 1 warning: status alert; (2) Fire alarm confidence level 30-60%, triggering Level II warning: early warning, notifying operation and maintenance personnel to pay close attention and analyze; (3) Fire alarm confidence level 60-95%, triggering level three warning: warning alarm, notify the person in charge and the scene, start video verification, and start emergency plan; (4) Fire alarm confidence level > 95% triggers Level 4 warning: confirm fire alarm, highest level sound and light alarm, automatic linkage fire extinguishing system, remote notification and start evacuation; After completing the corresponding emergency procedures, the system was restored to normal monitoring status.

8. The substation fire alarm system according to claim 7, characterized in that: The equipment management and system self-diagnosis workflow is as follows: (1) Establish a full life cycle equipment file: The platform establishes an electronic file for each front-end device, recording its model, installation location, commissioning time, and maintenance history; (2) Real-time status monitoring and status report detection: The platform continuously conducts two-way communication with all devices, and the devices periodically send their status detection reports to the platform; (3) Predictive maintenance and automatic repair reporting: When the platform does not receive a status detection report of a certain device or receives a self-test failure report, it immediately generates a device fault alarm and automatically and accurately locates the specific device through the power file, and then automatically reports the repair; at the same time, the platform predicts the performance degradation trend of the device by analyzing the sensitivity change of the detector and the background noise level data. When it finds that the data is close to the threshold affecting its normal operation, it generates a predictive maintenance work order in advance and automatically dispatches the maintenance task to relevant personnel, forming a closed loop of operation and maintenance.

9. The substation fire alarm system according to claim 1, characterized in that: The application layer includes a remote monitoring center and a coordinated fire extinguishing device. At the regional monitoring center or via mobile terminal, maintenance personnel can remotely and centrally monitor the status of the fire protection systems of multiple unattended substations. Once a fire alarm occurs, the system accurately locates the fire and issues an audible and visual alert, while simultaneously pushing alarm information. After confirming the fire, the system automatically or remotely and manually activates the corresponding fire extinguishing device to complete the coordinated fire extinguishing work.

10. A substation fire alarm method, applied to the substation fire alarm system according to any one of claims 1 to 9, characterized in that, Includes the following steps: S1, All-round data acquisition: Fixed detectors and mobile inspection robots work together to monitor all key areas in the station without blind spots, and collect data on temperature, smoke, open flame and gas concentration. S2, Reliable Data Transmission: The IoT gateway within the station collects data from all sensors and robots, and transmits the data stably and in real time to a remote fire intelligent analysis platform via fiber optic or 5G networks. S3, Intelligent Analysis and Judgment: The platform performs fusion analysis on the received multi-source data, uses algorithm models for cross-validation, and calculates the fire alarm confidence level; S4, graded early warning and linkage: activate the corresponding plan according to the fire alarm confidence level, and automatically link the on-site fire extinguishing device when the fire alarm is confirmed; S5, Remote Monitoring and Closed Loop: The monitoring center can remotely confirm the fire situation and intervene manually when necessary. At the same time, the platform continuously performs system self-diagnosis, monitors the health status of equipment, generates maintenance work orders, and forms an operation and maintenance closed loop.

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