Fire alarm control system in power industry

Abstract

The invention provides a power industry fire alarm control system which is provided with an environment monitoring module, a data processing module, a control module, a communication module and an alarm triggering module. Then the data is transmitted into a data processing module to be processed, and normalization processing, multi-parameter weighted fusion, fire risk index calculation and anomaly detection of the data are carried out; after power fire information is detected, related equipment is controlled through the control module, and the effect of extinguishing fire and protecting the equipment is achieved; the communication module transmits the system state and the alarm information to an external monitoring system or a remote control center; the alarm triggering module sends out an alarm signal to remind an operator on duty in time; according to the system, various environment monitoring sensors are integrated, and a weighted fusion algorithm, an anomaly detection mechanism and an automatic linkage control technology are adopted, so that efficient fire detection and emergency response functions are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of fire alarm control in the electric power industry, and in particular to a fire alarm control system in the electric power industry. Background Art

[0002] With the rapid development of the power industry, the safety of power facilities has attracted people's attention; fire accidents caused by high temperature, overload, short circuit and other reasons in power facilities occur from time to time, which not only causes huge economic losses, but also threatens personal safety; existing fire alarm systems usually use fixed temperature, smoke concentration and other thresholds to trigger alarms; however, the setting of such fixed thresholds often cannot adapt to changes in the dynamic environment of power facilities, such as temperature fluctuations, load changes, etc., resulting in insufficient alarm response speed and accuracy; in addition, the existing system still has problems such as complex operation and difficulty in realizing the linkage between fire and power facilities in actual application.

[0003] In actual applications in the power industry, operators usually need to respond quickly in emergency situations. However, the operating interface design of existing systems is not intuitive enough, which can easily lead to misoperation and increase the difficulty of emergency response. More importantly, existing fire alarm systems often lack automatic linkage with power facilities, which means that in the event of a fire, the system cannot automatically take emergency measures such as cutting off power or activating fire extinguishing devices, and must rely on manual intervention, which undoubtedly increases the risk of accidents expanding.

[0004] With the development of science and technology and the increase in the complexity of power facilities, users have higher and higher requirements for fire alarm systems, especially in terms of accuracy, response speed, ease of operation and system scalability; traditional fire alarm systems often cause false alarms or missed alarms due to their failure to respond to environmental changes in a timely manner, affecting the credibility of the system and the trust of users; therefore, how to improve the response speed and accuracy of the fire alarm system, simplify the operating process, and enhance the scalability of the system has become a technical problem that the power industry urgently needs to solve; for this reason, the applicant proposes a fire alarm control system for the power industry based on the fire prevention and control monitoring needs of the power industry, which can effectively improve the accuracy and response speed of fire monitoring in power facilities. Summary of the invention

[0005] In order to solve the above technical problems, the present invention proposes a fire alarm control system for the power industry. The system is provided with an environmental monitoring module, a data processing module, a control module, a communication module and an alarm trigger module. The working method collects data through the environmental monitoring module, and then transmits the data to the data processing module for processing, performs data normalization, multi-parameter weighted fusion, fire risk index calculation and anomaly detection; after detecting the power fire information, the control module controls the relevant equipment to play the role of fire extinguishing protection equipment; the communication module in the system transmits the system status and alarm information to the external monitoring system or the remote control center; the alarm trigger module sends an alarm signal to promptly remind the on-duty personnel, thereby realizing efficient fire detection and emergency response functions.

[0006] To achieve the above object, the technical solution adopted by the present invention is:

[0007] A fire alarm control system for the electric power industry, characterized in that: the fire alarm control system and working method for the electric power industry are provided with an environment monitoring module, a data processing module, a control module, a communication module and an alarm triggering module; specifically:

[0008] Environmental monitoring module: including temperature sensors, load sensors, humidity sensors and smoke sensors, which are used to collect key environmental parameters of power facilities in real time; sensors are distributed in various important locations of power facilities to ensure comprehensive monitoring of the environment and equipment operation status of the entire facility, and the collected data is transmitted to the data processing module through the sensor interface for processing;

[0009] Data processing module: the core of the system, responsible for receiving and processing data from the environmental monitoring module; its main functions include data normalization, multi-parameter weighted fusion, fire risk index calculation and anomaly detection; the data processing module uses advanced algorithms to perform fusion analysis on multiple parameters, and dynamically adjusts the weight of each parameter according to the changes in real-time data, thereby generating accurate fire risk assessment results; mainly includes data preprocessing module, multi-parameter weighted fusion module, anomaly detection analysis module, risk assessment and threshold processing module;

[0010] Control module: Executes corresponding emergency operations according to the fire risk assessment results provided by the data processing module; the control module can automatically cut off the power supply of the power facilities and activate the fire extinguishing device when the fire risk index reaches the preset threshold; in addition, the control module can also provide operators with the option of manual intervention through the human-computer interaction interface to ensure that the system can respond quickly and effectively in emergency situations;

[0011] Communication module: responsible for transmitting system status and alarm information to the external monitoring system or remote control center; the communication module communicates data with the external system through wireless and wired networks to ensure that operators can grasp the safety status of power facilities in real time and take corresponding emergency measures when necessary;

[0012] Alarm trigger module: connected to the data processing module, used to send out a fire alarm signal when the fire risk index exceeds the preset threshold; the alarm trigger module provides a variety of alarm methods, including sound and light alarm, remote alarm, etc., to ensure that the fire alarm can be transmitted to relevant personnel in the first time, and start the linkage control module to perform subsequent operations;

[0013] Furthermore, the data processing of the data preprocessing module in the data processing module of the power industry fire alarm control system adopts a normalized processing formula, which is specifically:

[0014]

[0015] Where: X(t) is the raw data collected by the sensor at a certain time t;

[0016] X min The minimum value in the sensor's historical data

[0017] X max The maximum value in the sensor's historical data;

[0018] X norm (t) is normalized to the interval [0, 1].

[0019] Furthermore, the anomaly detection and analysis module of the data processing module in the fire alarm control system of the power industry determines whether the current sensor data deviates from the normal range through the analysis of historical data, helping the system to quickly respond to potential emergencies; the principle of anomaly detection is based on the sliding window technology, and the system averages the historical data of each sensor μ X and standard deviation σ X Statistics are collected and the current data is compared with the historical data. The conditional formula for anomaly detection is:

[0020] |X(t)-μ X |>3·σ X

[0021] When the current data of the sensor exceeds three standard deviations compared with the historical mean, the system considers that the parameter has abnormal fluctuations. At this time, the system automatically increases the weight of the parameter in the weighted fusion to ensure that potential fire risks can be quickly identified.

[0022] Furthermore, the risk assessment and threshold processing module of the data processing module in the power industry fire alarm control system adopts a risk index calculation formula when performing fire risk assessment, specifically:

[0023] R(t)=ω T (t)·T norm (t)+ω I (t)·I morm (t)+ω S (t)·S morm (t)+ω H (t)·H morm (t)

[0024] Where: T (t) represents the weight of temperature;

[0025] ω I (t) represents the weight of load current;

[0026] ω S (t) represents the weight of smoke concentration;

[0027] ω H (t)Weight of humidity.

[0028] Furthermore, the risk assessment and threshold processing module in the data processing module of the power industry fire alarm control system uses the following adjustment formulas for adjusting the temperature and load current alarm thresholds during the threshold adjustment:

[0029] T threshold (t) = T base ·(1-γ T ·R(t))

[0030] I threshold (t) = I base ·(1-γ I ·R(t))

[0031] Where: T base is the initial temperature alarm threshold;

[0032] I base is the initial load current alarm threshold;

[0033] γ T and γ I is the adjustment coefficient;

[0034] When the fire risk index R(t) increases, the system will automatically lower the alarm thresholds of temperature and load current, making it easier for the system to trigger an alarm; if the monitored temperature T(t) or load current I(t) exceeds the dynamically adjusted threshold, the system will immediately trigger an alarm; after the alarm is triggered, the system will issue corresponding emergency instructions through the control module, such as cutting off the power supply, starting the fire extinguishing device, etc.

[0035] Furthermore, the risk assessment and threshold processing module in the power industry fire alarm control system adopts the weight adjustment formula in the risk index calculation formula as follows:

[0036]

[0037] in: α j is the sensitivity coefficient corresponding to each sensor.

[0038] A working method of a fire alarm control system in the electric power industry, characterized in that it comprises the following steps:

[0039] Step 1: The sensors installed at the power facilities of the environmental monitoring module collect relevant data on site and transmit the data to the data processing module;

[0040] Step 2: After receiving the data collected by the environmental monitoring module, the data processing module processes the data, performs noise filtering and data standardization on the original data;

[0041] Step 3: The data processing module performs data fusion on the processed data;

[0042] Step 4: The data processing module performs anomaly detection on the fused data;

[0043] Step 5: The data processing module evaluates the fire risk of the power facility by using the parameters after abnormal detection, and adjusts the threshold during the evaluation process;

[0044] Step 6: After the data processing module conducts a fire risk assessment, it links the control module, communication module and alarm trigger module to trigger an alarm, promptly control related equipment and notify on-duty personnel to handle the exception.

[0045] The benefits of this application are:

[0046] 1. The fire alarm control system and working method of the power industry can accurately assess the fire risk level in complex power environment facilities;

[0047] 2. The fire alarm control system and working method of the power industry can automatically start the fire extinguishing system to control the fire as quickly as possible. Operators can also manually intervene through the human-computer interaction module to perform power outage or fire extinguishing operations, further ensuring the flexibility and reliability of fire extinguishing response;

[0048] 3. Fire alarm control system and working method in the power industry Through comprehensive analysis and dynamic adjustment of sensor data, the system can quickly respond to potential fire risks and ensure the timeliness and reliability of fire alarms;

[0049] 4. Fire alarm control system and working methods in the power industry When the fire risk is confirmed to be high, the system sends an alarm to the remote monitoring platform or fire center through the communication module to ensure that external operators are informed in time and respond to emergencies. It can also share environmental monitoring data with other external safety systems to facilitate the comprehensive safety management of power facilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the system architecture of the present invention;

[0051] Figure 2 It is a schematic diagram of the working data flow of the present invention. DETAILED DESCRIPTION

[0052] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments:

[0053] like Figure 1-2 As shown, a fire alarm control system for the power industry is shown. Figure 1 As shown, the fire alarm control system and working method of the power industry are provided with an environmental monitoring module, a data processing module, a control module, a communication module and an alarm triggering module; specifically:

[0054] Environmental monitoring module: including temperature sensors, load sensors, humidity sensors and smoke sensors, which are used to collect key environmental parameters of power facilities in real time; sensors are distributed in various important locations of power facilities to ensure comprehensive monitoring of the environment and equipment operation status of the entire facility, and the collected data is transmitted to the data processing module through the sensor interface for processing;

[0055] Temperature sensor: monitors temperature changes within the facility in real time to detect overheating or fire risks;

[0056] Load current sensor: detects the load current of the equipment to determine whether there is overload or power abnormality;

[0057] Smoke sensor: monitors the smoke concentration in the air. When the concentration exceeds the limit, it may indicate the occurrence of fire.

[0058] Humidity sensor: used to monitor the humidity inside the facility, especially important in scenarios where gas fire extinguishing systems or fire and moisture protection need to be monitored;

[0059] Data processing module: the core of the system, responsible for receiving and processing data from the environmental monitoring module; its main functions include data normalization, multi-parameter weighted fusion, fire risk index calculation and anomaly detection; the data processing module uses advanced algorithms to perform fusion analysis on multiple parameters, and dynamically adjusts the weight of each parameter according to the changes in real-time data, thereby generating accurate fire risk assessment results; mainly includes data preprocessing module, multi-parameter weighted fusion module, anomaly detection analysis module, risk assessment and threshold processing module;

[0060] Control module: Executes corresponding emergency operations according to the fire risk assessment results provided by the data processing module; the control module can automatically cut off the power supply of the power facilities and activate the fire extinguishing device when the fire risk index reaches the preset threshold; in addition, the control module can also provide operators with the option of manual intervention through the human-computer interaction interface to ensure that the system can respond quickly and effectively in emergency situations;

[0061] Communication module: responsible for transmitting system status and alarm information to the external monitoring system or remote control center; the communication module communicates data with the external system through wireless and wired networks to ensure that operators can grasp the safety status of power facilities in real time and take corresponding emergency measures when necessary;

[0062] Alarm trigger module: connected to the data processing module, used to send out a fire alarm signal when the fire risk index exceeds the preset threshold; the alarm trigger module provides a variety of alarm methods, including sound and light alarm, remote alarm, etc., to ensure that the fire alarm can be transmitted to relevant personnel in the first time, and start the linkage control module to perform subsequent operations;

[0063] The data processing of the data preprocessing module in the data processing module of the fire alarm control system in the power industry shown in the figure adopts the normalization processing formula, which is:

[0064]

[0065] Where: X(t) is the raw data collected by the sensor at a certain time t;

[0066] X min The minimum value in the sensor's historical data

[0067] X max The maximum value in the sensor's historical data;

[0068] X norm (t) is normalized to the interval [0, 1];

[0069] The anomaly detection and analysis module of the data processing module in the fire alarm control system of the power industry shown in the figure determines whether the current sensor data deviates from the normal range through the analysis of historical data, helping the system to quickly respond to potential emergencies; the principle of anomaly detection is based on the sliding window technology, and the system averages the historical data of each sensor X and standard deviation σ X Statistics are collected and the current data is compared with the historical data. The conditional formula for anomaly detection is:

[0070] |X(t)-μ X |>3·σ X

[0071] When the current data of the sensor exceeds three standard deviations compared with the historical mean, the system considers that the parameter has abnormal fluctuations. At this time, the system will automatically increase the weight of the parameter in the weighted fusion to ensure that potential fire risks can be quickly identified;

[0072] The risk assessment and threshold processing module of the data processing module in the fire alarm control system of the power industry shown in the figure adopts the risk index calculation formula when performing fire risk assessment, which is specifically:

[0073] R(t)=ω T (t)·T norm (t)+ω I (t)·I morm (t)+ω S (t)·S morm (t)+ω H (t)·H morm (t)

[0074] Where: T (t) represents the weight of temperature;

[0075] ω I (t) represents the weight of load current;

[0076] ω S (t) represents the weight of smoke concentration;

[0077] ω H (t)Weight of humidity;

[0078] The adjustment formula of the temperature and load current alarm thresholds in the risk assessment and threshold processing module in the data processing module of the fire alarm control system in the power industry shown in the figure is:

[0079] T threshold (t) = T base ·(1-γ T ·R(t))

[0080] I threshold (t) = I base ·(1-γ I ·R(t))

[0081] Where: T base is the initial temperature alarm threshold;

[0082] I base is the initial load current alarm threshold;

[0083] γ T and γ I is the adjustment coefficient;

[0084] When the fire risk index R(t) increases, the system will automatically lower the alarm thresholds of temperature and load current, making it easier for the system to trigger an alarm; if the monitored temperature T(t) or load current I(t) exceeds the dynamically adjusted threshold, the system will immediately trigger an alarm; after the alarm is triggered, the system will issue corresponding emergency instructions through the control module, such as cutting off the power supply, starting the fire extinguishing device, etc.

[0085] The weight adjustment formula used in the risk index calculation formula in the risk assessment and threshold processing module in the fire alarm control system of the power industry is as follows:

[0086]

[0087] Where: α j is the sensitivity coefficient corresponding to each sensor

[0088] The working method of the fire alarm control system in the power industry shown in the figure has the following working steps:

[0089] Step 1: The sensors installed at the power facilities of the environmental monitoring module collect relevant data on site and transmit the data to the data processing module;

[0090] Step 2: After receiving the data collected by the environmental monitoring module, the data processing module processes the data, performs noise filtering and data standardization on the raw data; data processing is performed by the data preprocessing module, which first preprocesses the data of different physical quantities; since the data from the environmental monitoring module involves different physical quantities, such as temperature, load current, smoke concentration and humidity, the system first performs standardization on these data; data from different sensors may be in different numerical ranges, for example, temperature is usually in degrees Celsius, while load current is in amperes, and direct calculation of these data may lead to result deviation; therefore, the data processing module first normalizes the data, and data normalization can ensure that data from various sensors can be fairly calculated and compared;

[0091] Step 3: The data processing module performs data fusion on the processed data; the data fusion is performed through a multi-parameter weighted fusion module;

[0092] Step 4: The data processing module performs anomaly detection on the fused data. The anomaly detection mechanism determines whether the current sensor data deviates from the normal range by analyzing historical data, helping the system to quickly respond to potential emergencies. The principle of anomaly detection is based on the sliding window technology. The system averages the historical data of each sensor. X and standard deviation σ X The system will collect statistics and compare the current data with the historical data. When the current data of the sensor exceeds three standard deviations from the historical mean, the system will consider that the parameter has abnormal fluctuations. At this time, the system will automatically increase the weight of the parameter in the weighted fusion to ensure that potential fire risks can be quickly identified; for example, if the current data of the smoke sensor is significantly higher than the historical mean, the system will mark the data as abnormal through the anomaly detection mechanism and increase the weight of the smoke concentration in the fire risk index to ensure that the assessment of the fire risk index is more sensitive;

[0093] Step 5: The data processing module evaluates the fire risk of the power facility by using the parameters after abnormal detection and adjusts the threshold during the evaluation process; the fire risk assessment adopts the risk index calculation formula. Through this weighting mechanism, the system can flexibly respond to changes in sensor data and provide a more accurate fire risk assessment based on current environmental conditions;

[0094] When the fire risk index R(t) increases, the system will automatically lower the alarm thresholds of temperature and load current, making it easier for the system to trigger an alarm; if the monitored temperature T(t) or load current I(t) exceeds the dynamically adjusted threshold, the system will immediately trigger an alarm; after the alarm is triggered, the system will issue corresponding emergency instructions through the control module, such as cutting off the power supply, starting the fire extinguishing device, etc.

[0095] Step 6: After the data processing module conducts a fire risk assessment, it links the control module, communication module and alarm trigger module to trigger an alarm, promptly control related equipment and notify on-duty personnel to handle the exception.

[0096] The data processing module shown ensures that the system can accurately assess fire risks in complex power facility environments. Through comprehensive analysis and dynamic adjustment of sensor data, the system can quickly respond to potential fire risks and ensure the timeliness and reliability of fire alarms.

[0097] The working method of the fire alarm control system in the power industry shown in the figure is that the control module is set to perform necessary emergency operations when a fire occurs; when the fire risk index R(t) exceeds a certain threshold, the control module automatically sends a power-off command to the power facilities to cut off the power supply to the affected area to prevent the spread of fire and damage to equipment; the control module can automatically start the fire extinguishing system, such as the gas fire extinguishing system or the automatic sprinkler system, according to the fire assessment result of the processing module to control the fire as quickly as possible; the operator can also manually intervene through the human-computer interaction module to perform power-off or fire extinguishing operations, further ensuring the flexibility and reliability of the system response.

[0098] The working method of the fire alarm control system in the power industry shown in the figure, the communication module is responsible for the communication between the fire alarm controller and the external system; through a wired or wireless network, the system can transmit real-time data, fire alarms and operating instructions to the remote monitoring system or fire center; when the fire risk is confirmed to be high, the system sends an alarm to the remote monitoring platform or fire center through the communication module to ensure that external operators are informed in time and respond to emergencies. The environmental monitoring data can also be shared with other external safety systems to facilitate the comprehensive safety management of power facilities.

[0099] The working method of the fire alarm control system in the power industry shown in the figure is that the alarm trigger module set up is the front-line protection mechanism of the system. When the fire risk assessment exceeds the safety threshold, the module will immediately send out an alarm signal, including sound and light alarm and remote alarm; when a fire occurs, the system sends a signal through the sound and light alarm to notify on-site personnel to evacuate or take emergency response measures. Combined with the communication module, the alarm trigger module will also send an alarm signal to the remote monitoring system at the same time to ensure that the emergency response can be carried out in a timely manner.

[0100] The above description is only a preferred embodiment of the present invention and does not constitute any other form of limitation to the present invention. Any modification or equivalent change made based on the technical essence of the present invention still falls within the scope of protection required by the present invention.

Claims

1. A fire alarm control system for the power industry, characterized by: The fire alarm control system of the power industry includes an environment monitoring module, a data processing module, a control module, a communication module and an alarm triggering module; specifically: Environmental monitoring module: including temperature sensors, load sensors, humidity sensors and smoke sensors, which are used to collect key environmental parameters of power facilities in real time; sensors are distributed in various important locations of power facilities to ensure comprehensive monitoring of the environment and equipment operation status of the entire facility, and the collected data is transmitted to the data processing module through the sensor interface for processing; Data processing module: the core of the system, responsible for receiving and processing data from the environmental monitoring module; its main functions include data normalization, multi-parameter weighted fusion, fire risk index calculation and anomaly detection; the data processing module uses advanced algorithms to perform fusion analysis on multiple parameters, and dynamically adjusts the weight of each parameter according to the changes in real-time data, thereby generating accurate fire risk assessment results; including data preprocessing module, multi-parameter weighted fusion module, anomaly detection analysis module, risk assessment and threshold processing module; Control module: performs corresponding emergency operations according to the fire risk assessment results provided by the data processing module; the control module can automatically cut off the power supply of the power facility and activate the fire extinguishing device when the fire risk index reaches the preset threshold; In addition, the control module can also provide operators with the option of manual intervention through the human-machine interface, ensuring that the system can respond quickly and effectively in emergency situations; Communication module: responsible for transmitting system status and alarm information to the external monitoring system or remote control center; the communication module communicates data with the external system through wireless and wired networks to ensure that operators can grasp the safety status of power facilities in real time and take corresponding emergency measures when necessary; Alarm trigger module: connected to the data processing module, used to send out a fire alarm signal when the fire risk index exceeds the preset threshold; the alarm trigger module provides a variety of alarm methods, including sound and light alarms, remote alarms, etc., to ensure that the fire alarm can be transmitted to relevant personnel in the first time, and start the linkage control module to perform subsequent operations.

2. A fire alarm control system for the electric power industry according to claim 1, characterized in that: The data processing of the data preprocessing module in the data processing module of the power industry fire alarm control system adopts a normalized processing formula, which is specifically: Where: X(t) is the raw data collected by the sensor at a certain time t; X min The minimum value in the sensor's historical data X max The maximum value in the sensor's historical data; X norm (t) is normalized to the interval [0,1].

3. A fire alarm control system for the electric power industry according to claim 1, characterized in that: The anomaly detection and analysis module of the data processing module in the power industry fire alarm control system determines whether the current sensor data deviates from the normal range through the analysis of historical data, helping the system to quickly respond to potential emergencies; The principle of anomaly detection is based on the sliding window technology. The system averages the historical data of each sensor. X and standard deviation σ X Statistics are collected and the current data is compared with the historical data. The conditional formula for anomaly detection is: |X(t)-μ X |>3·s X When the current data of the sensor exceeds three standard deviations compared with the historical mean, the system considers that the parameter has abnormal fluctuations. At this time, the system automatically increases the weight of the parameter in the weighted fusion to ensure that potential fire risks can be quickly identified.

4. The fire alarm control system for the electric power industry according to claim 1, characterized in that: The risk assessment and threshold processing module of the data processing module in the power industry fire alarm control system adopts the risk index calculation formula when performing fire risk assessment, specifically: R(t)=ω T (t)·T norm (t)+ω I (t)·I morm (t)+ω S (t)·S morm (t)+ω H (t)·H morm (t) Where: ωT(t) represents the weight of temperature; ωI(t) represents the weight of load current; ωs(t) represents the weight of smoke concentration; ωH(t) is the weight of humidity.

5. The fire alarm control system for the electric power industry according to claim 1, characterized in that: The adjustment formula of the temperature and load current alarm thresholds in the threshold adjustment of the risk assessment and threshold processing module in the data processing module of the power industry fire alarm control system is: T threshold (t)=T base ·(1-γ T ·R(t)) I threshold (t)=I base ·(1-γ I ·R(t)) Where: T base is the initial temperature alarm threshold; I base is the initial load current alarm threshold; γ T and γ I is the adjustment coefficient; When the fire risk index R(t) increases, the system will automatically lower the alarm thresholds of temperature and load current, making it easier for the system to trigger an alarm; if the monitored temperature T(t) or load current I(τ) exceeds the dynamically adjusted threshold, the system will immediately trigger an alarm; after the alarm is triggered, the system will issue corresponding emergency instructions through the control module, such as cutting off the power supply, starting the fire extinguishing device, etc.

6. A fire alarm control system for the electric power industry according to claim 4, characterized in that: The weight adjustment formula in the risk index calculation formula used by the risk assessment and threshold processing module in the power industry fire alarm control system is: Where: α j is the sensitivity coefficient corresponding to each sensor.

7. A working method of a fire alarm control system in the power industry, characterized in that: The following steps are involved: Step 1: The sensors installed at the power facilities of the environmental monitoring module collect relevant data on site and transmit the data to the data processing module; Step 2: After receiving the data collected by the environmental monitoring module, the data processing module processes the data, performs noise filtering and data standardization on the original data; Step 3: The data processing module performs data fusion on the processed data; Step 4: The data processing module performs anomaly detection on the fused data; Step 5: The data processing module evaluates the fire risk of the power facility by using the parameters after abnormal detection, and adjusts the threshold during the evaluation process; Step 6: After the data processing module conducts a fire risk assessment, it links the control module, communication module and alarm trigger module to trigger an alarm, promptly control related equipment and notify on-duty personnel to handle the exception.

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