Sensor-based fire door status monitoring and warning system and method

Abstract

This invention relates to the field of fire door monitoring technology, and discloses a sensor-based fire door status monitoring and early warning system and method. The system includes a target sensor, an execution parameter generation module, an execution module, a protection module, a sensor status monitoring module, an internal information acquisition module for the protection module, an environmental information acquisition module, and an analysis module. The system analyzes external environmental information data, internal information data, and status information data from the protection module to obtain protection parameters, ensuring effective protection of the target sensor. Based on the analysis of the internal information data of the protection module, a reliability level is obtained. Then, based on the reliability level analysis, the working strategy of the execution module is determined. The system can automatically switch the execution module to manual adjustment mode when the reliability level of the target sensor is low due to fire damage, avoiding inappropriate or even dangerous actions by the execution module caused by erroneous data collected by the target sensor.

Description

Technical Field

[0001] This invention relates to the field of fire door monitoring technology, specifically to a sensor-based fire door status monitoring and early warning system and method. Background Technology

[0002] Fire is an extremely destructive disaster; in order to reduce the destructiveness of fire, we need to start with the key aspects of building fire protection design, among which the proper installation and effective management of fire doors are of paramount importance.

[0003] Chinese patent CN202510697745.6 discloses a fire door, a fire door sequencer intelligent monitoring device and method. It achieves high-precision monitoring of the door's spatial posture by embedding a nine-axis IMU sensor inside the door leaf, and dynamically adjusts the door closing strategy during a fire based on the detected posture of the door leaf space using a micro hydraulic cylinder, thereby improving the effectiveness of the escape route.

[0004] However, the aforementioned technologies still have significant drawbacks. As the fire gradually spreads to the fire door, its temperature gradually increases. The target sensor comes into direct contact with the fire door, and external heat is transferred to the target sensor through the outer casing. The temperature of the target sensor gradually rises, and the high temperature has a significant impact on the electronic components inside the target sensor, ultimately causing the data collected by the target sensor to drift and have large deviations. For example, inaccurate data such as linear acceleration and angular velocity obtained by a nine-axis IMU sensor can lead to errors in subsequent assessments of dynamic changes such as door tilt and vibration. This can cause the hydraulic cylinder to apply too much or too little compensation force when the door tilts, ultimately failing to restore the door to a vertical state. This may result in the fire door and the door frame not being able to close tightly. In this situation, dense smoke and toxic gases generated by the fire will rush in through the gap between the fire door and the door frame, quickly spreading to the originally relatively safe area and threatening the safety of people or property in the safe area inside the fire door. Summary of the Invention

[0005] The purpose of this invention is to provide a sensor-based fire door status monitoring and early warning system and method, solving the following technical problems:

[0006] How to prevent safety issues caused by inaccurate data collection from sensors on fire doors due to changes in the fire door and environment.

[0007] The objective of this invention can be achieved through the following technical solutions: A sensor-based fire door status monitoring and early warning system, comprising a target sensor, an execution parameter generation module, and an execution module, further comprising: A protection module, located outside the target sensor, is used to protect the target sensor. The sensor status monitoring module is used to monitor the target sensor and acquire the status information data of the target sensor; The protection module internal information acquisition module is used to acquire the internal information data of the protection module; The environmental information acquisition module is used to acquire external environmental information data of the protection module; The analysis module is used to analyze the external environmental information data, internal information data and status information data of the protection module to obtain the protection parameters of the protection module; it is also used to analyze the internal information data and status information data of the protection module to obtain the trust level of the target sensor; and then, based on the trust level of the target sensor, it determines the working strategy of the execution module.

[0008] As a further aspect of the present invention: the protection module includes: The temperature control module is used to control the temperature within the protection module; The filter module is used to filter the target substance in the protection module. The protection parameters include real-time temperature threshold and filtration intensity level.

[0009] As a further aspect of the present invention: the status information data includes the target sensor temperature and the surface resistance value of the sensor housing; the internal information data includes a first temperature inside the protection module and a first concentration of the target substance; the external environment information data includes a second temperature and a second concentration of the target substance.

[0010] As a further aspect of the present invention: the real-time temperature threshold determination process of the protection module is as follows: S11: By analyzing the target sensor temperature and the second temperature within a preset time period in the past, the external temperature influence index at the current time is obtained. In step S11, according to formula one: ; Calculate the external temperature influence index T at the current time. out ; Where f(X) is a judgment function, f(X) = X when X > 0; f(X) = 0 when X ≤ 0; T tag (t) represents the temperature change curve of the target sensor over time; T tag0 The preset target temperature value for the target sensor; T out (t) is the curve showing the change of the second temperature over time; T out0 The preset second temperature value; t s The current time; t is the duration of the preset time period; γ1 is the first weighting coefficient; γ2 is the second weighting coefficient; C1 is the first preset constant; C2 is the second preset constant; S12: Analyze the first temperature within a preset time period in the past to obtain the internal temperature deviation index at the current time; Through formula two: ; Calculate the internal temperature deviation index T at the current time. in ; Among them, T in (t) represents the curve of the first temperature change within the protection module over time; T high0 To protect the module from the preset maximum temperature threshold; t over The duration during which the first temperature exceeds the preset maximum temperature threshold within a preset time period; α1 is the first weighting coefficient; α2 is the second weighting coefficient; Z1 is the first preset constant; Z2 is the second preset constant; S13: Analyze the external temperature influence index and internal temperature deviation index at the current time to obtain the threshold adjustment coefficient; Through formula three: ; Calculate the threshold adjustment coefficient θ s ; Where ρ1 is the first adjustment weight coefficient; ρ2 is the second adjustment weight coefficient; D1 is the first adjustment preset constant; D2 is the second adjustment preset constant; C θ Preset adjustment constant S14: Determine the real-time temperature threshold of the protection module based on the threshold adjustment coefficient; Through formula four: ; Calculate the highest real-time temperature threshold T highs ; Therefore, the real-time temperature threshold is [T low0 ,T highs ]; Among them, T low0 To protect the module's preset minimum temperature threshold.

[0011] As a further aspect of the present invention: the process for determining the filtration intensity level is as follows: S21: Based on the analysis of the first and second concentrations of the target substance and the surface resistance value of the sensor housing, the environmental particulate risk index is obtained; S22: The filtration intensity level is obtained by analyzing the environmental particulate risk index.

[0012] As a further aspect of the present invention: In step S21, formula five is used: ; Calculate the environmental particulate risk index K H ; Among them, C 1s The first concentration value at the current time; C 10 The preset first concentration value; C 2s The second concentration value at the current time; C 20 β1 is the preset second concentration value; β2 is the first concentration adjustment coefficient; β1, β2∈[0.2,1]; ρ1 is the preset weighting coefficient for the first concentration; ρ2 is the preset weighting coefficient for the second concentration; W1 is the preset constant for the first concentration; W2 is the preset constant for the second concentration; R s R0 is the current sensor housing surface resistance value; μ1 is the preset sensor housing surface resistance value; μ2 is the first preset adjustment coefficient; ε is the de-unit coefficient.

[0013] As a further aspect of the present invention: In step S22, the process of determining the filtration intensity level is as follows: the environmental particulate risk index K is... H Compare with the comparison thresholds [L1, L2]; When K H When L1 is ≤, the filtration intensity level is low; When L1 < K H When L2 is ≤, the filtration intensity level is medium. When L2 < K H At that time, the filtration intensity level was high.

[0014] As a further aspect of the present invention: the process for obtaining the confidence level of the target sensor is as follows: S31: By analyzing the target sensor temperature, the first temperature, and the surface resistance value of the sensor housing, the risk index of the target sensor is obtained; Through Formula Seven: ; Calculate the target sensor risk index U tag ; Among them, T tags The current temperature of the target sensor; T tagmax The preset maximum temperature for the target sensor; R max The maximum resistance value is preset for the sensor housing surface; T ins The first temperature value at the current time; T inmax The first temperature is the preset maximum value; σ1 is the sensor temperature weighting coefficient; σ2 is the sensor housing resistance weighting coefficient; σ3 is the protection module temperature weighting coefficient; Y1 is the sensor temperature preset constant; Y2 is the sensor housing resistance preset constant; Y3 is the protection module temperature preset constant. S32: Analyze the target sensor risk index to determine the trust level of the target sensor; The process for determining the reliability level of the target sensor is as follows: The target sensor risk index U tag Compare with the second preset comparison thresholds [U1, U2]; When 1≤U tag When the value is <U1, the confidence level of the target sensor is high. When U1≤U tag＜ At U2, the confidence level of the target sensor is medium. When U2≤U tag At that time, the confidence level of the target sensor is low.

[0015] As a further aspect of the present invention: the process for determining the working strategy of the execution module is as follows: When the target sensor's trust level is high, the execution module's operating strategy is automatic mode; When the confidence level of the target sensor is medium, the execution module remains in automatic mode. If the fire door shows obvious abnormalities, the personnel inside the fire door can switch to manual mode themselves. When the confidence level of the target sensor is low, the execution module's working strategy is to issue a low-level warning, and the execution module automatically switches to manual mode.

[0016] A sensor-based method for monitoring and early warning of fire door status, comprising the following steps: S1: A protection module is installed outside the target sensor to protect the target sensor; S2: Monitor the target sensor through the sensor status monitoring module and obtain the status information data of the target sensor; S3: Obtain internal information data of the protection module through the internal information acquisition module of the protection module; S4: Obtain external environmental information data of the protection module through the environmental information acquisition module; S5: The analysis module analyzes the external environmental information data, internal information data, and status information data of the protection module to obtain the protection parameters of the protection module; it is also used to analyze the internal information data and status information data of the protection module to obtain the trust level of the target sensor; and then, based on the trust level of the target sensor, it determines the working strategy of the execution module.

[0017] The beneficial effects of this invention are: (1) This invention places the target sensor inside the protection module. By isolating the target sensor from the temperature changes of the fire door and the external environment, it avoids the data drift caused by the high temperature of the fire door. This ensures that the data collected by the target sensor is relatively accurate for a period of time after the fire occurs, so that the execution module can take effective actions according to the actual situation of the fire door. At the same time, it analyzes the external environmental information data, internal information data and status information data of the protection module to obtain the protection parameters of the protection module, ensuring that the protection module effectively protects the target sensor. Then, it analyzes the internal information data of the protection module to obtain the confidence level of the target sensor. Then, it analyzes the confidence level of the target sensor to determine the working strategy of the execution module. It can issue an early warning in time when the confidence level of the target sensor is low due to the fire, reminding the personnel in the safe area and the rescue personnel, and automatically switch the execution module to manual adjustment mode to avoid the execution module automatically making inappropriate or even dangerous actions due to the erroneous data collected by the target sensor, thus ensuring the overall reliability and safety of the fire door system. At the same time, it can let the rescue personnel understand the urgency of rescue in each area according to the confidence level of the target sensor, so as to facilitate the rescue personnel to formulate more reasonable rescue strategies. (2) This invention first analyzes the target sensor temperature and the second temperature within a preset time period in the past to obtain the external temperature influence index at the current time, which intuitively reflects the degree of influence of the external environment on the protection module; then, it analyzes the first temperature within a preset time period in the past to obtain the internal temperature deviation index at the current time, which intuitively reflects the severity of the temperature deviation within the protection module; next, it analyzes the external temperature influence index and the internal temperature deviation index at the current time to obtain the threshold adjustment coefficient and determine the adjustment degree of the highest temperature threshold in the real-time temperature threshold; finally, it determines the real-time temperature threshold of the protection module based on the threshold adjustment coefficient; this can effectively avoid inaccurate threshold setting due to a single factor, thereby improving the timeliness and effectiveness of temperature control of the protection module; thus ensuring that the target sensor will not have inaccurate data acquisition due to temperature within the protection module; and ensuring the overall reliability and safety of the fire door system; (3) The present invention analyzes the first concentration and second concentration of the target substance and the surface resistance value of the sensor housing, and intuitively quantifies the impact risk of the target substance in the protection module and the target substance in the external environment on the target sensor by calculating the environmental particle risk index; then, it analyzes the environmental particle risk index to obtain the filtration intensity level; it can slow down the speed of particles adhering to the surface of the target sensor as much as possible, thereby increasing the normal operating time of the target sensor and providing valuable rescue time for rescue. (4) When the confidence level of the target sensor is high, the execution module is in automatic mode; when the confidence level of the target sensor is medium, a corresponding warning is issued, and the execution module is still in automatic mode. If an abnormality occurs, the staff can switch to manual mode; when the confidence level of the target sensor is low, a corresponding warning is issued, and the execution module automatically switches to manual mode, so as to avoid the execution module automatically making inappropriate or even dangerous actions due to the erroneous data collected by the target sensor, and to ensure the overall reliability and safety of the fire door system; at the same time, it can let the rescuers understand the urgency of rescue in each area according to the confidence level of the target sensor, and facilitate the rescuers to formulate more reasonable rescue strategies. (5) This invention uses the target sensor risk index U tag It can accurately quantify the degree of abnormal risk of the target sensor caused by the target sensor temperature, particulate matter adhering to the sensor housing surface, and the temperature in the protected environment in real time, which facilitates the subsequent accurate determination of the trust level of the target sensor and provides a basis for determining the working strategy of the execution module. Attached Figure Description

[0018] The invention will now be further described with reference to the accompanying drawings.

[0019] Figure 1 This is a system module framework diagram of one embodiment of the present invention; Figure 2 This is a flowchart of a method according to an embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Please see Figure 1 As shown, in one embodiment, a sensor-based fire door status monitoring and early warning system is provided. The system includes a target sensor, an execution parameter generation module, and an execution module. The target sensor is used to collect status information data of the fire door; Specifically, the target sensor can be a nine-axis IMU sensor; the status information data can be the linear acceleration of the door in the X, Y, and Z axes, the angular velocity of the door around the X, Y, and Z axes, and the strength of the Earth's magnetic field around the door. The execution module may be a miniature hydraulic cylinder; The execution parameter generation module is used to analyze the status information data and generate the execution parameters of the execution module. The system also includes: A protection module, located outside the target sensor, is used to protect the target sensor. Specifically, placing the target sensor in the protection module can isolate the target sensor from the influence of temperature changes in the fire door and the external environment, and prevent the target sensor from drifting due to the high temperature of the fire door, resulting in low accuracy of the collected data. The sensor status monitoring module is used to monitor the target sensor and acquire the status information data of the target sensor; Specifically, the status information data includes the target sensor temperature and the surface resistance value of the sensor housing; The protection module internal information acquisition module is used to acquire the internal information data of the protection module; Specifically, the internal information data includes the first temperature within the protection module and the first concentration of the target substance (the target substance can be particulate matter or other substances that adhere to the target sensor and affect the accuracy of the sensor). The environmental information acquisition module is used to acquire external environmental information data of the protection module; Specifically, the external environmental information data includes the second temperature and the second concentration of the target substance; The analysis module is used to analyze the external environmental information data, internal information data and status information data of the protection module to obtain the protection parameters of the protection module; it is also used to analyze the internal information data and status information data of the protection module to obtain the trust level of the target sensor; and then, based on the trust level of the target sensor, it determines the working strategy of the execution module. Through the above technical solution, this embodiment places the target sensor within the protection module. By isolating the target sensor from the temperature changes of the fire door and the external environment, it avoids data drift caused by the high temperature of the fire door, ensuring that the data collected by the target sensor is relatively accurate for a period of time after a fire occurs. This allows the execution module to take effective actions based on the actual situation of the fire door. Simultaneously, by analyzing the external environmental information, internal information, and status information data of the protection module, the protection parameters of the protection module are obtained, ensuring effective protection of the target sensor. Furthermore, by analyzing the internal information data of the protection module, the reliability level of the target sensor is obtained. Based on the reliability level of the target sensor, the working strategy of the execution module is determined. This allows for timely warnings when the reliability level of the target sensor is low due to the fire, alerting personnel in safe areas and rescue personnel. It also automatically switches the execution module to manual adjustment mode, preventing inappropriate or even dangerous actions by the execution module due to erroneous data collected by the target sensor, ensuring the overall reliability and safety of the fire door system. Simultaneously, the reliability level of the target sensor allows rescue personnel to understand the urgency of rescue in each area, facilitating the development of more reasonable rescue strategies.

[0022] As one embodiment of the present invention, the protection module includes: The temperature control module is used to control the temperature within the protection module; The filter module is used to filter the target substance in the protection module. The protection parameters include real-time temperature threshold and filtration intensity level; To address the challenges in real-world applications where fire doors experience a gradual temperature increase during a fire, while the surrounding environment on both sides of the fire door continuously changes, both of which directly and adversely affect the target sensor. This can lead to deviations in sensor measurements, disrupt normal operation, and ultimately reduce the reliability and safety of the entire system. This embodiment utilizes a temperature control module to regulate the temperature within the protection module. This ensures the temperature within the protection module remains within a suitable range for the target sensor's operation, effectively isolating it from the direct impact of fire door and ambient temperatures. This significantly reduces their direct influence on the target sensor, ensuring its continuous, stable, and accurate operation and providing a solid guarantee for the reliable operation of the entire system.

[0023] As one embodiment of the present invention, the real-time temperature threshold determination process of the protection module is as follows: S11: By analyzing the target sensor temperature and the second temperature within a preset time period in the past, the external temperature influence index at the current time is obtained. S12: Analyze the first temperature within a preset time period in the past to obtain the internal temperature deviation index at the current time; S13: Analyze the external temperature influence index and internal temperature deviation index at the current time to obtain the threshold adjustment coefficient; S14: Determine the real-time temperature threshold of the protection module based on the threshold adjustment coefficient; Through the above technical solution, this embodiment first analyzes the target sensor temperature and the second temperature within a preset time period in the past to obtain the external temperature influence index at the current time. This external temperature influence index can intuitively reflect the degree of influence of the external environment on the protection module. Then, based on the analysis of the first temperature within the preset time period in the past, the internal temperature deviation index at the current time is obtained. This internal temperature deviation index can intuitively reflect the severity of temperature deviation within the protection module. Next, based on the analysis of the external temperature influence index and the internal temperature deviation index at the current time, a threshold adjustment coefficient is obtained. This threshold adjustment coefficient is used to determine the adjustment degree of the highest temperature threshold in the real-time temperature threshold. Finally, the real-time temperature threshold of the protection module is determined based on the threshold adjustment coefficient. This dynamic threshold adjustment method can effectively avoid inaccurate threshold setting due to a single factor, thereby improving the timeliness and effectiveness of temperature control of the protection module. This ensures that the target sensor will not have inaccurate data acquisition due to temperature within the protection module, thus guaranteeing the overall reliability and safety of the fire door system.

[0024] As one embodiment of the present invention, in step S11, formula one is used: ; Calculate the external temperature influence index T at the current time. out ; Where f(X) is a judgment function, f(X) = X when X > 0; f(X) = 0 when X ≤ 0; T tag (t) represents the temperature change curve of the target sensor over time; T tag0 The preset target temperature value for the target sensor; T out (t) is the curve showing the change of the second temperature over time; T out0 The preset second temperature value; t s The current time; t is the duration of the preset time period; γ1 is the first weighting coefficient; γ2 is the second weighting coefficient; C1 is the first preset constant; C2 is the second preset constant; Formula 1 Explanation: This reflects the first cumulative value of the target sensor's temperature value exceeding the preset target temperature value within a preset time period past the current time. The higher the first cumulative value of the target sensor's temperature value exceeding the preset target temperature value within a preset time period past the previous time, the longer the target sensor is in a high-temperature state or the greater the temperature exceeds the preset target temperature value within that preset time period. This means that the target sensor itself is at a higher temperature, and it needs to dissipate more heat energy to maintain normal operation. Therefore, it has a greater impact on the temperature control of the protection module. This reflects the second cumulative value of the external environment temperature exceeding the preset second temperature value within the past preset time period of the current time. The higher the second cumulative value of the external environment temperature exceeding the preset second temperature value within the past preset time period of the current time, the longer the external environment is in a high-temperature state or the greater the temperature exceeds the preset second temperature value within that preset time period, and the greater the impact on the temperature of the protection module. Through the above technical solution, this embodiment reflects the comprehensive influence of external factors on the temperature control of the protection module by using the external temperature influence index at the current time. This effectively improves the rationality and accuracy of temperature control within the protection module, ensuring that the protection module is always maintained within a suitable temperature range. This ensures that the target sensor will not experience inaccurate data acquisition due to temperature within the protection module. As a key component of the fire door system, the rationality of the protection module's temperature control directly affects the performance of the entire system. Therefore, improving the accuracy of the protection module's temperature control can effectively enhance the overall reliability and safety of the fire door system. It should be noted that the preset target temperature value T of the target sensor tag0 Preset second temperature value T out0 , Duration of preset time period t, the first weighting coefficient γ1, the second weighting coefficient γ2, the first preset constant C1 and the second preset constant C2 are preset values, set according to empirical fitting, which is existing technology and will not be described in detail here.

[0025] As one embodiment of the present invention, in step S12, formula two is used: ; Calculate the internal temperature deviation index T at the current time. in ; Among them, T in (t) represents the curve of the first temperature change within the protection module over time; T high0 To protect the module from the preset maximum temperature threshold; t overThe duration during which the first temperature exceeds the preset maximum temperature threshold within a preset time period; α1 is the first weighting coefficient; α2 is the second weighting coefficient; Z1 is the first preset constant; Z2 is the second preset constant; Explanation of Formula 2: It reflects the third cumulative value of the first temperature value in the protection module exceeding the preset maximum temperature threshold within the preset time period past the current time; the higher the third cumulative value of the first temperature value in the protection module exceeding the preset maximum temperature threshold within the preset time period past the current time, the more serious the degree to which the temperature in the protection module exceeds the preset maximum temperature threshold within that preset time period. This reflects the ratio of the duration during which the first temperature exceeded the preset maximum temperature threshold within a preset time period to the preset duration of the preset time period. The larger the ratio, the longer the temperature in the protection module exceeded the preset maximum temperature threshold, indicating that the temperature in the protection module remained at a high temperature for an extended period, and that the temperature control of the protection module was unreasonable. Through the above technical solution, this embodiment uses the internal temperature deviation index T in Within a preset time period, the severity of the temperature exceeding the preset maximum temperature threshold within the protection module and the ratio of the duration of the first temperature exceeding the preset maximum temperature threshold within a past preset time period to the preset duration of the past preset time period are comprehensively evaluated and quantified to determine the degree of deviation between the current internal temperature of the protection module and the suitable operating temperature of the target sensor. This effectively improves the rationality and accuracy of temperature control within the protection module, ensuring that the protection module is always maintained within a suitable temperature range, and ensuring that the target sensor does not experience inaccurate data acquisition due to temperature within the protection module; thus guaranteeing the overall reliability and safety of the fire door system. It should be noted that the preset maximum temperature threshold T in the protection module high0 The first weight coefficient α1, the second weight coefficient α2, the first preset constant Z1, and the second preset constant Z2 are preset values, set based on empirical fitting, and are existing technologies, which will not be described in detail here.

[0026] As one embodiment of the present invention, in step S13, formula three is used: ; Calculate the threshold adjustment coefficient θ s ; Where ρ1 is the first adjustment weight coefficient; ρ2 is the second adjustment weight coefficient; D1 is the first adjustment preset constant; D2 is the second adjustment preset constant; C θ This is a preset adjustment constant; Formula 3 explains the external temperature influence index T at the current time. outThe larger the value, the more excess heat from the external temperature and the target sensor will affect the temperature control of the protection module. Therefore, to maintain the protection module at a suitable operating temperature for the target sensor, the maximum temperature threshold needs to be lowered significantly. Thus, the threshold adjustment coefficient θ... s The smaller the value, the lower the internal temperature deviation index T at the current time. in The larger the value, the greater the temperature deviation between the protection module's internal temperature and the target sensor's optimal operating temperature. Therefore, the higher the maximum temperature threshold needs to be adjusted, the greater the deviation. Thus, the threshold adjustment coefficient θ... s The smaller, Through the above technical solution, this embodiment adjusts the threshold coefficient θ s The quantification determines the extent to which the maximum temperature threshold needs to be lowered; this facilitates the subsequent acquisition of the real-time temperature threshold of the protection module, thereby preventing external temperature and excess heat from the target sensor from causing the temperature inside the protection module to exceed the appropriate operating temperature of the target sensor, ensuring that the target sensor will not cause inaccurate data acquisition due to temperature within the protection module; and guaranteeing the overall reliability and safety of the fire door system. It should be noted that the first adjustment weight coefficient ρ1, the second adjustment weight coefficient ρ2, the first adjustment preset constant D1, the second adjustment preset constant D2, and the preset adjustment constant C... θ These are preset values, set based on empirical fitting, and are existing technologies, which will not be described in detail here.

[0027] As one embodiment of the present invention, in step S14, formula four is used: ; Calculate the real-time temperature maximum threshold T highs ; Therefore, the real-time temperature threshold is [T low0 ,T highs ]; Among them, T low0 To protect the module's preset minimum temperature threshold; Through the above technical solution, this embodiment can effectively avoid inaccurate threshold settings due to a single factor by dynamically adjusting the threshold of the protection module after a fire warning occurs in the area, thereby improving the timeliness and effectiveness of temperature control of the protection module; thus ensuring that the target sensor will not have inaccurate data acquisition due to temperature within the protection module; and ensuring the overall reliability and safety of the fire door system. It should be noted that the preset minimum temperature threshold T low0 These are preset values, set based on empirical fitting, and are existing technologies, which will not be described in detail here.

[0028] As one embodiment of the present invention, the process for determining the filtration intensity level is as follows: S21: Based on the analysis of the first and second concentrations of the target substance and the surface resistance value of the sensor housing, the environmental particulate risk index is obtained; S22: Filtration intensity level is obtained based on the analysis of the environmental particulate risk index; Through the above technical solution, this embodiment analyzes the target substance's first and second concentrations and the sensor housing surface resistance value, and uses the calculated environmental particle risk index to intuitively quantify the impact risk level of the target substance within the protection module and the target substance in the external environment on the target sensor; then, based on the environmental particle risk index, the filtration intensity level is obtained; this can minimize the speed at which particles adhere to the surface of the target sensor, thereby increasing the duration of normal operation of the target sensor and providing valuable rescue time.

[0029] As one embodiment of the present invention, in step S21, formula five is used: ; Calculate the environmental particulate risk index K H ; Among them, C 1s The first concentration value at the current time; C 10 The preset first concentration value; C 2s The second concentration value at the current time; C 20 β1 is the preset second concentration value; β2 is the first concentration adjustment coefficient; β1, β2∈[0.2,1]; ρ1 is the preset weighting coefficient for the first concentration; ρ2 is the preset weighting coefficient for the second concentration; W1 is the preset constant for the first concentration; W2 is the preset constant for the second concentration; R s R0 is the current sensor housing surface resistance value; μ1 is the first preset adjustment coefficient; μ2 is the second preset adjustment coefficient; ε is the de-unit coefficient. Formula 5 Explanation: The surface resistance value R of the sensor housing at the current time. s The larger the value, the more particulate matter adheres to the exterior of the target sensor, indicating a poorer surface condition and a greater impact on the accuracy of data acquisition. By adjusting the first concentration threshold within the protection module and the second concentration threshold of the external environment using the first concentration adjustment coefficient β1 and the second concentration adjustment coefficient β2, the accuracy of data acquisition is improved. Calculated environmental particulate risk index K H The larger; Through the above technical solution, this embodiment uses the environmental particulate risk index K H It intuitively reflects the degree of risk of target substances within the protection module and in the external environment on the target sensor; through the environmental particulate risk index K. HThis allows for a more reasonable determination of the filtration intensity level of the protection module; It should be noted that the preset first concentration value C 10 Preset second concentration value C 20 The preset weighting coefficients ρ1 and ρ2 for the first concentration, W1 and W2 for the first and second concentrations, R0 for the surface resistance of the sensor housing, ε for removing the unit, μ1 for the first, and μ2 for the second are preset values, set based on empirical fitting, and are existing technologies, which will not be described in detail here.

[0030] In one embodiment of the present invention, in step S22, the process of determining the filtration intensity level is as follows: the environmental particulate risk index K is... H Compare with the first preset comparison thresholds [L1, L2]; When K H When L1 is ≤, the filtration intensity level is low; When L1 < K H When L2 is ≤, the filtration intensity level is medium. When L2 < K H At that time, the filtration intensity level is high; Through the above technical solution, in this embodiment when K H When L1 ≤ K, it indicates a low level of particulate matter risk within the protection module. In this case, the filter module uses a low filtration intensity level to filter the gas entering the protection module; when L1 < K H When L2 ≤ K, it indicates a high level of particulate matter risk within the protection module. In this case, the filter module uses a medium filtration intensity level to filter the gas entering the protection module; when L2 < K H When the risk level of particulate matter within the protection module is extremely high, the filter module uses a high filtration intensity level to filter the gas entering the protection module, thereby slowing down the rate at which particulate matter adheres to the surface of the target sensor, thus increasing the duration of normal operation of the target sensor and providing valuable rescue time. It should be noted that the first preset comparison thresholds [L1, L2] are preset values, set based on empirical fitting, and are existing technologies, which will not be described in detail here.

[0031] As one embodiment of the present invention, the process for obtaining the reliability level of the target sensor is as follows: S31: By analyzing the target sensor temperature, the first temperature, and the surface resistance value of the sensor housing, the risk index of the target sensor is obtained; S32: Analyze the target sensor risk index to determine the trust level of the target sensor; Through the above technical solution, this embodiment first analyzes the target sensor temperature, first temperature, and surface resistance value of the sensor housing to obtain the target sensor risk index. The target sensor risk index can intuitively reflect the abnormal risk of the target sensor at the current time. Then, based on the analysis of the target sensor risk index, the reliability level of the target sensor can be accurately determined, providing a basis for determining the working strategy of the execution module. It can promptly issue an early warning when the reliability level of the target sensor is low due to the impact of fire, reminding personnel in the safe area and rescue personnel, and automatically switch the execution module to manual adjustment mode. This avoids the execution module from automatically making inappropriate or even dangerous actions due to erroneous data collected by the target sensor, ensuring the overall reliability and safety of the fire door system. At the same time, it can also allow rescue personnel to understand the urgency of rescue in each area based on the reliability level of the target sensor, facilitating the development of more reasonable rescue strategies.

[0032] As one embodiment of the present invention, in step S31, formula seven is used: ; Calculate the target sensor risk index U tag ; Among them, T tags The current temperature of the target sensor; T tagmax The preset maximum temperature for the target sensor; R max The maximum resistance value is preset for the sensor housing surface; T ins The first temperature value at the current time; T inmax The first temperature is the preset maximum value; σ1 is the sensor temperature weighting coefficient; σ2 is the sensor housing resistance weighting coefficient; σ3 is the protection module temperature weighting coefficient; Y1 is the sensor temperature preset constant; Y2 is the sensor housing resistance preset constant; Y3 is the protection module temperature preset constant. Formula 7 Explanation: The greater the current temperature of the target sensor exceeds its preset maximum temperature, the greater the risk of target sensor malfunction due to temperature. If the current temperature does not exceed the preset maximum temperature, the risk of target sensor malfunction due to temperature is minimal. Similarly, the greater the current resistance value of the sensor housing surface exceeds its preset maximum resistance value, the greater the risk of target sensor malfunction due to particulate matter adhering to the sensor housing surface. If the current resistance value does not exceed the preset maximum resistance value, the risk of target sensor malfunction due to particulate matter adhering to the sensor housing surface is minimal. Furthermore, the greater the current temperature value exceeds its preset maximum value, the greater the risk of target sensor malfunction due to the temperature within the protected environment. If the current temperature value does not exceed its preset maximum value, the risk of target sensor malfunction due to the temperature within the protected environment is minimal. Through the above technical solution, this embodiment uses the target sensor risk index U tag It can accurately quantify the degree of risk of target sensor anomalies caused by target sensor temperature, particulate matter adhering to the sensor housing surface, and the temperature within the protected environment in real time, facilitating the accurate determination of the target sensor's reliability level. This provides a basis for determining the subsequent working strategy of the execution module. It can also promptly issue early warnings when the target sensor's reliability level is low due to fire, alerting personnel in safe areas and rescue personnel, and automatically switching the execution module to manual adjustment mode. This prevents the execution module from automatically taking inappropriate or even dangerous actions due to erroneous data collected by the target sensor, ensuring the overall reliability and safety of the fire door system. Furthermore, it can allow rescue personnel to understand the urgency of rescue efforts in different areas based on the target sensor's reliability level, facilitating the development of more reasonable rescue strategies. It should be noted that the preset maximum temperature T of the target sensor tagmax The sensor housing surface has a preset maximum resistance value R. max The first preset maximum temperature T inmax The sensor temperature weighting coefficient σ1, the sensor housing resistance weighting coefficient σ2, the protection module temperature weighting coefficient σ3, the sensor temperature preset constant Y1, the sensor housing resistance preset constant Y2, and the protection module temperature preset constant Y3 are preset values, set based on empirical fitting, and are existing technologies, which will not be described in detail here.

[0033] In one embodiment of the present invention, the process of determining the confidence level of the target sensor in step S32 is as follows: The target sensor risk index U tag Compare with the second preset comparison thresholds [U1, U2]; When 1≤U tagWhen the value is <U1, the confidence level of the target sensor is high. When U1≤U tag＜ At U2, the confidence level of the target sensor is medium. When U2≤U tag At that time, the confidence level of the target sensor is low; Through the above technical solution, in this embodiment, when 1≤U tag When U1 < U1, it indicates that the target sensor is in good condition with a low risk of anomalies; therefore, the target sensor's reliability level is high, and the execution module is in automatic mode. When U1 ≤ U1, the target sensor's reliability level is low. tag＜ When U2 is reached, it indicates that the target sensor is in poor condition with a moderate level of anomaly risk; therefore, the reliability level of the target sensor is medium. A medium-level warning is issued at this time, and the execution module remains in automatic mode. If a significant anomaly occurs in the fire door, personnel inside can manually switch to manual mode. When U2 ≤ U... tag If the target sensor is in a very poor state, indicating a very high risk of anomaly, its reliability level is low. At this point, a low-level warning is issued, and the execution module automatically switches to manual mode. This prevents the execution module from taking inappropriate or even dangerous actions due to erroneous data collected by the target sensor, ensuring the overall reliability and safety of the fire door system. Simultaneously, the reliability level of the target sensor allows rescue personnel to understand the urgency of rescue efforts in each area, facilitating the development of more appropriate rescue strategies.

[0034] As one embodiment of the present invention, the process for determining the working strategy of the execution module is as follows: When the target sensor's trust level is high, the execution module's operating strategy is automatic mode; When the confidence level of the target sensor is medium, the execution module remains in automatic mode. If the fire door shows obvious abnormalities, the personnel inside the fire door can switch to manual mode themselves. When the confidence level of the target sensor is low, the execution module's working strategy is to issue a low-level warning, and the execution module automatically switches to manual mode.

[0035] Through the above technical solution, in this embodiment, when the reliability level of the target sensor is high, it indicates that the sensor data is accurate and reliable. At this time, the execution module's working strategy is set to automatic mode, ensuring that the fire door automatically reacts based on real-time and accurate environmental data without manual intervention. This improves the timeliness and accuracy of the fire door's response, effectively protecting personnel safety. When the reliability level of the target sensor is medium, it means that the sensor data is basically reliable but still has some uncertainty. At this time, the execution module remains in automatic mode to maintain basic automatic response capability. Simultaneously, if the fire door exhibits obvious abnormalities, such as failing to close with the door frame and having gaps, the fire door... Personnel can switch to manual mode themselves; this method retains the convenience of automatic mode while giving personnel autonomous control in emergency situations, enhancing the system's flexibility and reliability. When the target sensor's reliability level is low, it indicates that the sensor data may have significant errors or be unreliable. At this time, the execution module's working strategy is to issue a low-level warning, reminding relevant personnel to pay attention to the potential problems with the sensor data, and automatically switch to manual mode. The warning mechanism avoids misoperation caused by inaccurate sensor data, while the manual mode allows personnel to make judgments and operations based on the actual situation, ensuring the safe operation of the fire door when sensor data is unreliable.

[0036] Please see Figure 2 As shown, a sensor-based method for monitoring and warning the status of fire doors includes the following steps: S1: A protection module is installed outside the target sensor to protect the target sensor; S2: Monitor the target sensor through the sensor status monitoring module and obtain the status information data of the target sensor; S3: Obtain internal information data of the protection module through the internal information acquisition module of the protection module; S4: Obtain external environmental information data of the protection module through the environmental information acquisition module; S5: The analysis module analyzes the external environmental information data, internal information data, and status information data of the protection module to obtain the protection parameters of the protection module; it is also used to analyze the internal information data and status information data of the protection module to obtain the trust level of the target sensor; and then, based on the trust level of the target sensor, it determines the working strategy of the execution module.

[0037] Through the above technical solution, this embodiment first sets up a protection module outside the target sensor to isolate the target sensor from the influence of the fire door and the temperature changes of the external environment. This prevents the data collected by the target sensor from drifting due to the high temperature of the fire door, ensuring that the data collected by the target sensor is relatively accurate for a period of time after a fire occurs. This allows the execution module to take effective actions based on the actual situation of the fire door. Then, the sensor status monitoring module monitors the target sensor and obtains its status information data. Next, the internal information acquisition module of the protection module obtains the internal information data of the protection module. Then, the environmental information acquisition module obtains the external environmental information data of the protection module. Finally, the analysis module analyzes the external environmental information data, internal information data, and status information data of the protection module. The system obtains protection parameters from the protection module, ensuring effective protection of the target sensor. It also analyzes the internal and status data of the protection module to determine the target sensor's reliability level. Based on this reliability level, it determines the execution module's operating strategy. The system can issue timely warnings when the target sensor's reliability level is low due to fire, alerting personnel in safe areas and rescue workers. It automatically switches the execution module to manual adjustment mode to prevent inappropriate or dangerous actions caused by erroneous data from the target sensor, ensuring the overall reliability and safety of the fire door system. Furthermore, the system allows rescue personnel to understand the urgency of rescue efforts in different areas based on the target sensor's reliability level, facilitating the development of more appropriate rescue strategies.

[0038] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A sensor-based fire door status monitoring and early warning system, the system comprising a target sensor, an execution parameter generation module, and an execution module, characterized in that, The system also includes: A protection module, located outside the target sensor, is used to protect the target sensor. The sensor status monitoring module is used to monitor the target sensor and acquire the status information data of the target sensor; The protection module internal information acquisition module is used to acquire the internal information data of the protection module; The environmental information acquisition module is used to acquire external environmental information data of the protection module; The analysis module is used to analyze the external environmental information data, internal information data and status information data of the protection module to obtain the protection parameters of the protection module; it is also used to analyze the internal information data and status information data of the protection module to obtain the trust level of the target sensor; and then, based on the trust level of the target sensor, it determines the working strategy of the execution module.

2. The sensor-based fire door status monitoring and early warning system according to claim 1, characterized in that, The protection module includes: The temperature control module is used to control the temperature within the protection module; The filter module is used to filter the target substance in the protection module. The protection parameters include real-time temperature threshold and filtration intensity level.

3. The sensor-based fire door status monitoring and early warning system according to claim 2, characterized in that, The status information data includes the target sensor temperature and the surface resistance value of the sensor housing; the internal information data includes the first temperature inside the protection module and the first concentration of the target substance; the external environment information data includes the second temperature and the second concentration of the target substance.

4. The sensor-based fire door status monitoring and early warning system according to claim 3, characterized in that, The process for determining the real-time temperature threshold of the protection module is as follows: S11: By analyzing the target sensor temperature and the second temperature within a preset time period in the past, the external temperature influence index at the current time is obtained. S12: Analyze the first temperature within a preset time period in the past to obtain the internal temperature deviation index at the current time; S13: Analyze the external temperature influence index and internal temperature deviation index at the current time to obtain the threshold adjustment coefficient; S14: Determine the real-time temperature threshold of the protection module based on the threshold adjustment coefficient.

5. The sensor-based fire door status monitoring and early warning system and method according to claim 4, characterized in that, The process for determining the filtration intensity level is as follows: S21: Based on the analysis of the first and second concentrations of the target substance and the surface resistance value of the sensor housing, the environmental particulate risk index is obtained; S22: The filtration intensity level is obtained by analyzing the environmental particulate risk index.

6. The sensor-based fire door status monitoring and early warning system according to claim 5, characterized in that, In step S21, according to formula five: ； Computing environment particle risk index K H ; Among them, C 1s The first concentration value at the current time; C 10 The preset first concentration value; C 2s The second concentration value at the current time; C 20 β1 is the preset second concentration value; β2 is the first concentration adjustment coefficient; β1, β2∈[0.2,1]; ρ1 is the preset weighting coefficient for the first concentration; ρ2 is the preset weighting coefficient for the second concentration; W1 is the preset constant for the first concentration; W2 is the preset constant for the second concentration; R s R0 is the current sensor housing surface resistance value; μ1 is the preset sensor housing surface resistance value; μ2 is the first preset adjustment coefficient; ε is the de-unit coefficient.

7. The sensor-based fire door status monitoring and early warning system according to claim 6, characterized in that, In step S22, the process of determining the filtration intensity level is as follows: The environmental particulate risk index K... H Compare with the comparison thresholds [L1, L2]; When K H When L1 is ≤, the filtration intensity level is low; When L1 < K H When L2 is ≤, the filtration intensity level is medium. When L2 < K H At that time, the filtration intensity level was high.

8. The sensor-based fire door status monitoring and early warning system according to claim 7, characterized in that, The process for obtaining the confidence level of the target sensor is as follows: S31: By analyzing the target sensor temperature, the first temperature, and the surface resistance value of the sensor housing, the risk index of the target sensor is obtained; S32: Analyze the target sensor risk index to determine the trust level of the target sensor.

9. The sensor-based fire door status monitoring and early warning system according to claim 8, characterized in that, The process for determining the working strategy of the execution module is as follows: When the target sensor's trust level is high, the execution module's operating strategy is automatic mode; When the confidence level of the target sensor is medium, the execution module remains in automatic mode. If the fire door shows obvious abnormalities, the personnel inside the fire door can switch to manual mode themselves. When the confidence level of the target sensor is low, the execution module's working strategy is to issue a low-level warning, and the execution module automatically switches to manual mode.

10. A sensor-based method for monitoring and warning the status of fire doors, applicable to the sensor-based fire door status monitoring and warning system according to any one of claims 1-9, characterized in that, The method includes the following steps: S1: A protection module is installed outside the target sensor to protect the target sensor; S2: Monitor the target sensor through the sensor status monitoring module and obtain the status information data of the target sensor; S3: Obtain internal information data of the protection module through the internal information acquisition module of the protection module; S4: Obtain external environmental information data of the protection module through the environmental information acquisition module; S5: The analysis module analyzes the external environmental information data, internal information data, and status information data of the protection module to obtain the protection parameters of the protection module; it is also used to analyze the internal information data and status information data of the protection module to obtain the trust level of the target sensor; and then, based on the trust level of the target sensor, it determines the working strategy of the execution module.

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