Anti-false alarm fire-fighting smoke alarm method and system, and storage medium

Abstract

The invention relates to the technical field of smoke alarm, and particularly discloses an anti-false-alarm fire-fighting smoke alarm method and system and a storage medium, and the method comprises the steps: carrying out the deep analysis through the refined obtaining of the data collection process parameters of a fire-fighting smoke sensing device, obtaining the data collection sensitivity factors, and combining with the data analysis process parameters to obtain the false alarm of the fire-fighting smoke sensing device. The step is crucial for improving the accuracy of the fire-fighting smoke sensing device, a scientific basis is provided for judging whether the performance of the fire-fighting smoke sensing device is optimized or not, the false alarm rate is effectively reduced, and the overall efficiency of the fire-fighting smoke sensing device is improved. The environment parameters of the target area are collected in real time through the fire-fighting smoke sensing device, the smoke fire-fighting demand coefficient of the target area can be accurately evaluated in combination with the response precision factor, the coefficient directly guides whether false alarm prevention and early warning measures need to be carried out on the target area or not, and therefore the fire risk is effectively prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of smoke alarms, and in particular to a fire smoke alarm method, system and storage medium for preventing false alarms. Background Art

[0002] In modern buildings, fire safety is of vital importance. Early detection and alarm of fire are of great significance to reducing casualties and property losses. Fire smoke alarms, as key equipment for fire early warning, are widely used in various places. Traditional smoke alarms often face the problem of false alarms in practical applications, which not only brings inconvenience to people's lives, but also may cause unnecessary panic. In order to reduce false alarms and improve the accuracy and reliability of smoke alarms, the industry has conducted a lot of research and improvements to improve the accuracy and timeliness of fire early warnings.

[0003] For example, the invention patent with publication number CN117275165A discloses an artificial intelligence-based fire smoke treatment device, including: a data acquisition component for collecting environmental data of sensing nodes; an image acquisition component for collecting images of sensing nodes; a transmission component for sending the data collected by the data acquisition component and the images collected by the image acquisition component to a management server through a communication network; a management server for running the Internet of Things platform, receiving data uploaded by the transmission component, analyzing the data, identifying the fire point, and issuing instructions.

[0004] For example, the invention patent with publication number CN117037410A discloses an anti-false alarm smoke alarm, including an installation mechanism, which includes a shell, a threaded block fixedly connected to the outside of the shell, and a dust inlet pipe fixedly connected to the bottom end of the shell, the bottom end of the shell is provided with a bottom cavity, and the inner wall of the shell is adapted to be installed with a smoke sensor; through the design of the plug, when a fire occurs, the plug will slide up with the change of temperature, and the fan blades will rotate, so that smoke and dust can quickly enter the interior of the shell, causing the smoke sensor to alarm; and automatic dust falling will be carried out inside to ensure that the smoke sensor can alarm in time in case of fire.

[0005] However, in the process of implementing the embodiments of the present application, the present application discovered that the above-mentioned technology has at least the following technical problems: the prior art mainly focuses on reducing the probability of false alarms of smoke sensors through strategies such as improving environmental adaptability. However, in actual deployment and application, the false alarms of smoke sensors are not only affected by environmental factors, which greatly restricts the further improvement of the warning accuracy of smoke sensors. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a fire smoke alarm method, system and storage medium for preventing false alarms, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides a false alarm fire smoke alarm method, including: step one, obtaining data acquisition process parameters of the fire smoke sensor device, analyzing the data acquisition sensitivity factor of the fire smoke sensor device, and simultaneously obtaining the data analysis process parameters of the fire smoke sensor device, and comprehensively calculating the data acquisition sensitivity factor of the fire smoke sensor device to obtain the response accuracy factor of the fire smoke sensor device, thereby determining whether to optimize the performance of the fire smoke sensor device; step two, collecting environmental parameters of the target area through the fire smoke sensor device, and comprehensively calculating the response accuracy factor of the fire smoke sensor device to evaluate the smoke fire demand coefficient of the target area; step three, determining whether to implement false alarm warning measures for the smoke in the target area based on the smoke fire demand coefficient of the target area, and updating the smoke fire log of the target area.

[0008] As a further method, the determination of whether to optimize the performance of the fire smoke sensor device is as follows: extracting the response accuracy threshold of the fire smoke sensor device from the alarm database, and comparing the response accuracy factor of the fire smoke sensor device with the response accuracy threshold of the fire smoke sensor device. If the response accuracy factor of the fire smoke sensor device is greater than the response accuracy threshold of the fire smoke sensor device, it is determined that the performance of the fire smoke sensor device is not optimized; if the response accuracy factor of the fire smoke sensor device is less than or equal to the response accuracy threshold of the fire smoke sensor device, it is determined that the performance of the fire smoke sensor device is optimized. The specific performance optimization process is as follows: matching the response accuracy factor of the fire smoke sensor device with the optimization schemes corresponding to each response accuracy factor interval stored in the alarm database, thereby matching and executing the optimization scheme of the fire smoke sensor device, and updating the response accuracy factor of the fire smoke sensor device.

[0009] As a further method, the determination of whether to implement false alarm warning measures for the smoke in the target area is as follows: extracting the smoke fire demand threshold of the target area from the smoke fire log of the target area, comparing the smoke fire demand coefficient of the target area with the smoke fire demand threshold of the target area, if the smoke fire demand coefficient of the target area is less than or equal to the smoke fire demand threshold of the target area, then determining not to implement false alarm warning measures for the smoke in the target area; if the smoke fire demand coefficient of the target area is greater than the smoke fire demand threshold of the target area, then determining to implement false alarm warning measures for the smoke in the target area, the specific warning measures are as follows: matching the smoke fire demand coefficient of the target area with the smoke anomaly levels corresponding to each smoke fire demand coefficient interval stored in the alarm database, thereby deriving the smoke anomaly level of the target area, and implementing false alarm warning based on the smoke anomaly level of the target area.

[0010] As a further method, the smoke fire log of the target area is updated, and the specific updating process is: the execution result is stored in the smoke fire log as "resolved" or "false alarm", and the execution result of the anti-false alarm warning measures of the target area is obtained. If the execution result is "resolved", the smoke fire log of the target area will not be updated; if the execution result is "false alarm", the smoke fire log of the target area will be automatically updated.

[0011] The second aspect of the present invention provides a false alarm-proof fire smoke alarm system, comprising: a response accuracy analysis module, which is used to obtain data acquisition process parameters of a fire smoke sensor device, analyze the data acquisition sensitivity factor of the fire smoke sensor device, and simultaneously obtain the data analysis process parameters of the fire smoke sensor device, and comprehensively calculate the response accuracy factor of the fire smoke sensor device based on the data acquisition sensitivity factor of the fire smoke sensor device, thereby determining whether to optimize the performance of the fire smoke sensor device; a smoke fire demand evaluation module, which is used to collect environmental parameters of a target area through a fire smoke sensor device, and comprehensively calculate the response accuracy factor of the fire smoke sensor device to evaluate the smoke fire demand coefficient of the target area; an false alarm-proof warning implementation module, which is used to determine whether to implement false alarm-proof warning measures for the smoke in the target area according to the smoke fire demand coefficient of the target area, and update the smoke fire log of the target area.

[0012] A third aspect of the present invention provides a computer-readable storage medium for storing a program, wherein when the program is executed by a processor, the program implements the fire smoke alarm method for preventing false alarms as described above.

[0013] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides a fire smoke alarm method, system and storage medium for preventing false alarms. By obtaining the data collection process parameters of the fire smoke sensor device in a refined manner, the data collection sensitivity factor can be deeply analyzed and obtained. At the same time, the response accuracy factor can be obtained by comprehensive evaluation in combination with the data analysis process parameters. This step is crucial to improving the accuracy of the fire smoke sensor device and provides a scientific basis for determining whether the performance of the fire smoke sensor device is optimized. This not only ensures the high sensitivity and accuracy of the fire smoke sensor device in smoke detection, but also effectively reduces the false alarm rate and improves the overall efficiency of the fire smoke sensor device. Furthermore, the fire smoke sensor device is used to collect the environmental parameters of the target area in real time, and combined with the response accuracy factor, the smoke fire demand coefficient of the target area can be accurately evaluated. This coefficient directly guides whether it is necessary to implement false alarm warning measures for the target area, thereby effectively preventing fire risks. In addition, timely updating of the smoke fire log according to the evaluation results is conducive to realizing the intelligence and refinement of fire management and providing valuable data support and experience reference for fire safety work.

[0014] (2) The present invention obtains the response accuracy factor of the fire smoke sensor device by comprehensively combining the data analysis process parameters of the fire smoke sensor device with the data acquisition sensitivity factor of the fire smoke sensor device. Starting from the performance source of the fire smoke sensor device itself, the present invention realizes the accurate quantification of the early warning capability of the fire smoke sensor device. It not only fundamentally reduces the false alarm rate of the fire smoke sensor device, effectively avoids panic and unnecessary resource scheduling caused by false alarms, but also greatly improves the accuracy and timeliness of fire early warning. By continuously optimizing the response accuracy of the sensor device, it lays a solid foundation for building a more efficient and reliable fire safety system.

[0015] (3) The present invention intelligently determines whether to implement anti-false alarm warning measures based on the smoke fire demand coefficient of the target area and updates the smoke fire log in real time, thereby successfully realizing the adaptive management of the smoke fire protection system. This not only significantly enhances the pertinence and effectiveness of fire warnings and reduces the interference and waste caused by false alarms, but also promotes the close interaction and continuous optimization of the fire protection system and the use environment. By continuously learning and adapting to environmental changes, the emergency response capability of the fire smoke sensor device is further improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0017] Figure 1 The figure is a schematic flow chart of the method steps of the present invention.

[0018] Figure 2 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0020] Reference Figure 1 As shown, the first aspect of the present invention provides a fire smoke alarm method for preventing false alarms, including: step one, obtaining data acquisition process parameters of the fire smoke sensor device, analyzing the data acquisition sensitivity factor of the fire smoke sensor device, and simultaneously obtaining the data analysis process parameters of the fire smoke sensor device, and comprehensively considering the data acquisition sensitivity factor of the fire smoke sensor device to obtain the response accuracy factor of the fire smoke sensor device, thereby determining whether to optimize the performance of the fire smoke sensor device.

[0021] In a specific embodiment, the present invention obtains the response accuracy factor of the fire smoke sensor device by comprehensively analyzing the data analysis process parameters of the fire smoke sensor device and the data acquisition sensitivity factor of the fire smoke sensor device, and starts from the performance source of the fire smoke sensor device itself to achieve accurate quantification of the early warning capability of the fire smoke sensor device. It not only fundamentally reduces the false alarm rate of the fire smoke sensor device, effectively avoids panic and unnecessary resource scheduling caused by false alarms, but also greatly improves the accuracy and timeliness of fire warnings. By continuously optimizing the response accuracy of the sensor device, it lays a solid foundation for building a more efficient and reliable fire safety system.

[0022] Specifically, the response precision factor of the fire smoke sensor device is analyzed in the following steps: The data analysis process parameters of the fire smoke sensor device include the average response time of each sensor belonging to the fire smoke sensor device within the performance monitoring period, the minimum resolution of each sensor belonging to the fire smoke sensor device within the performance monitoring period, the smoke concentration change curve of the fire smoke sensor device within the performance monitoring period, and the signal strength change curve of the fire smoke sensor device within the performance monitoring period; the above-mentioned performance monitoring period represents the time period for analyzing the data collection and processing performance of the fire smoke sensor device, and the specific duration is determined by the equipment quality manager; the above-mentioned average response time represents the average value of the time from each sensor detecting a signal to outputting a signal within the performance monitoring period, which can be extracted from the timestamp log of each sensor; the above-mentioned minimum resolution represents the minimum signal strength change that can be detected by each sensor within the performance monitoring period, which can be obtained by analyzing the signal analysis software (such as Rohde & Schwarz CA210 signal analysis software); the above-mentioned smoke concentration change curve represents the smoke concentration detected by the fire smoke sensor device over time within the performance monitoring period The relationship curve of the change can be obtained by denoising the real-time smoke concentration detected by the fire smoke sensor device during the performance monitoring period and drawing it into a smooth curve through data processing software (such as matrix laboratory software). The above-mentioned signal strength change curve represents the relationship curve of the output signal strength of the fire smoke sensor device during the performance monitoring period changing with time, which can be obtained by denoising the real-time output signal strength of the fire smoke sensor device during the performance monitoring period and drawing it into a smooth curve through data processing software (such as matrix laboratory software). It should be explained that the output signal strength of the fire smoke sensor device during the performance monitoring period refers to the controller equipped in the fire smoke sensor device, which is used to receive signals from various sensors, and conduct comprehensive analysis and processing, integrate the signals from different sensors, and form a total signal. This total signal is the smoke fire demand coefficient of the target area, which can be used to trigger anti-false alarm warning measures. The signal strength of the total signal is the output signal strength of the fire smoke sensor device, and the output signal strength can be monitored by a signal strength meter.

[0023] The above sensors include but are not limited to temperature sensors, carbon dioxide concentration sensors and smoke concentration sensors.

[0024] The average response time of each sensor belonging to the fire smoke sensor device within the performance monitoring period is processed by standard deviation and marked as the time asynchrony of the sensors belonging to the fire smoke sensor device within the performance monitoring period, which indicates the degree of dispersion of the average response time of each sensor belonging to the fire smoke sensor device within the performance monitoring period.

[0025] Data processing is performed on the smoke density change curve and the signal strength change curve of the fire smoke sensor device during the performance monitoring period to obtain the smoke density-signal strength correlation coefficient of the fire smoke sensor device during the performance monitoring period. The specific data processing process is as follows: the smoke concentration at each performance monitoring time point is extracted from the smoke density change curve and marked as , Indicates the smoke concentration at the nth performance monitoring time point, It represents a set of smoke concentrations at each performance monitoring time point. The signal strength at each performance monitoring time point is extracted from the signal strength change curve and marked as , Indicates the signal strength at the nth performance monitoring time point, represents the set of signal strengths at each performance monitoring time point, then ,in express Collection and The covariance of the set, express The standard deviation of the set, express The standard deviation of the set, n represents the number of each performance monitoring time point, , m represents the total number of performance monitoring time points, It indicates the correlation coefficient between smoke density and signal strength of the fire smoke sensor during the performance monitoring period. If the correlation coefficient between smoke density and signal strength is high, it means that there is a strong positive correlation between the two. In the application of fire smoke sensor, a high positive correlation coefficient usually means that the sensor has a high sensitivity and accuracy to changes in smoke concentration. When the smoke concentration increases, the sensor can output a stronger signal accordingly, thereby triggering an alarm in time or taking corresponding countermeasures.

[0026] The data acquisition sensitivity factor of the fire smoke sensor device, the time asynchronism of the sensors belonging to the fire smoke sensor device within the performance monitoring period, the minimum resolution of each sensor belonging to the fire smoke sensor device within the performance monitoring period and the smoke concentration-signal strength correlation coefficient of the fire smoke sensor device within the performance monitoring period are comprehensively analyzed to obtain the response accuracy factor of the fire smoke sensor device. The response accuracy factor of the fire smoke sensor device is used to comprehensively quantify the accuracy of the fire smoke sensor device in the process of data collection and processing.

[0027] The specific analysis method of the response precision factor of the fire smoke sensor device is as follows: ; In the formula, is the response precision factor of the fire smoke sensor device, is the data collection sensitivity factor of the fire smoke sensor device, is the weight corresponding to the data collection sensitivity factor preset in the alarm database, It is the time asynchronism of the sensors of the fire smoke sensor device during the performance monitoring cycle. is the minimum resolution of the sth sensor of the fire smoke sensor device during the performance monitoring cycle, is the smoke density-signal strength correlation coefficient of the fire smoke sensor device during the performance monitoring period, Asynchronous degrees of defined time preset in the alarm database, The minimum resolution defined by default in the alarm database, is the smoke density-signal strength correlation coefficient preset in the alarm database, s is the number of each sensor, , q is the total number of sensors, The time asynchrony impact value preset in the alarm database, is the minimum resolution impact value preset in the alarm database, It is the influence value of the smoke density-signal strength correlation coefficient preset in the alarm database.

[0028] The above-mentioned time asynchrony influence value indicates the value of the influence of the time asynchrony unit value of the sensor belonging to the fire smoke sensor device within the performance monitoring period on the response precision factor of the fire smoke sensor device; the above-mentioned minimum resolution influence value indicates the value of the influence of the minimum resolution unit value of the sth sensor belonging to the fire smoke sensor device within the performance monitoring period on the response precision factor of the fire smoke sensor device; the above-mentioned smoke and fog-signal strength correlation coefficient influence value indicates the value of the influence of the smoke and fog-signal strength correlation coefficient unit value of the fire smoke sensor device within the performance monitoring period on the response precision factor of the fire smoke sensor device. The alarm database stores the corresponding relationship between the time asynchrony and its corresponding influence value, the corresponding relationship between the minimum resolution and its corresponding influence value, and the corresponding relationship between the smoke and fog-signal strength correlation coefficient and its corresponding influence value. For example, the time asynchrony, the minimum resolution and the smoke and fog-signal strength correlation coefficient are input into the alarm database, and the alarm database can match the time asynchrony influence value, the minimum resolution influence value and the smoke and fog-signal strength correlation coefficient influence value, and the value range is between 0 and 1.

[0029] It needs to be explained that the level of data acquisition sensitivity factor affects the fire smoke sensor device's ability to capture smoke and other signals, thereby determining the time asynchrony of the fire smoke sensor device within the performance monitoring cycle. Specifically, time asynchrony is an important indicator for measuring the response speed and timeliness of each sensor in the fire smoke sensor device. It reflects the time delay from the fire smoke sensor device sensing smoke and other signals to the final output signal. When the data acquisition sensitivity factor is at a low level, the reduction means that the fire smoke sensor device is not sensitive enough to changes in signals such as smoke concentration and temperature, which directly leads to the inability of each sensor in the fire smoke sensor device to quickly capture signals such as smoke concentration and temperature. Due to the lack of sensitivity, the fire smoke sensor device is slow to respond to or cannot sense slight changes in smoke concentration, thereby reducing the sensor. The minimum resolution of the sensor further prolongs the response time of each sensor. Due to various factors such as the performance differences of each sensor, different environmental conditions and changes in smoke concentration, the degree of increase in their response time is not consistent. This inconsistency leads to differences in response time between sensors, that is, it increases the time asynchrony between sensors. The increase in time asynchrony means that the real-time and accuracy of the fire smoke sensor device is reduced. Since the sensor cannot capture the smoke signal in a timely and accurate manner, the correlation between the captured signal and the smoke concentration is reduced. The weakening of this correlation means that the signal output by the fire smoke sensor device cannot accurately reflect the actual situation of the smoke concentration. Therefore, the mutual constraints between the parameters make the accuracy of the fire smoke sensor device in the data collection and processing process at a low level.

[0030] The weight corresponding to the above-mentioned data acquisition sensitivity factor represents the proportion of the data acquisition sensitivity factor of the fire smoke sensor device to the response accuracy factor of the fire smoke sensor device. The corresponding relationship between the data acquisition sensitivity factor and its corresponding weight is stored in the alarm database. For example, the data acquisition sensitivity factor of the fire smoke sensor device is input into the alarm database, and the alarm database can match the weight corresponding to the data acquisition sensitivity factor, and the value range is between 0 and 1; the above-mentioned time asynchrony is defined, which represents the maximum allowable value of the time asynchrony of the sensor belonging to the fire smoke sensor device within the performance monitoring cycle; the above-mentioned minimum resolution is defined, which represents the maximum allowable value of the minimum resolution of the sth sensor belonging to the fire smoke sensor device within the performance monitoring cycle; the above-mentioned smoke concentration-signal strength correlation coefficient is defined, which represents the minimum allowable value of the smoke concentration-signal strength correlation coefficient of the fire smoke sensor device within the performance monitoring cycle.

[0031] Specifically, the data acquisition sensitivity factor of the fire smoke sensor device is analyzed, and the specific analysis process is: the data acquisition process parameters of the fire smoke sensor device include the real-time bit depth of each sensor belonging to the fire smoke sensor device during the performance monitoring period, the sampling rate of each sensor belonging to the fire smoke sensor device during the performance monitoring period, the maximum signal strength of each sensor belonging to the fire smoke sensor device during the performance monitoring period, and the minimum signal strength of each sensor belonging to the fire smoke sensor device during the performance monitoring period; the above-mentioned real-time bit depth represents the number of data bits collected by each sensor belonging to the fire smoke sensor device at any time during the performance monitoring period, which determines the degree of signal detail that the sensor can capture. Generally, the bit depth of the sensor is fixed and can be extracted from the technical specification manual, but due to wear and aging of the sensor during use Factors such as accuracy and data loss lead to decreased accuracy and data loss, so the real-time bit depth in this embodiment can be analyzed by data analysis software (such as Matrix Lab); the above-mentioned sampling rate represents the average frequency of data collection of each sensor belonging to the fire smoke sensor device during the performance monitoring period, and the number of data collected by each sensor during the performance monitoring period can be extracted from the data log of each sensor belonging to the fire smoke sensor device, and divided by the duration corresponding to the performance monitoring period to obtain the sampling rate of each sensor during the performance monitoring period; the above-mentioned maximum signal strength represents the maximum level of the output signal strength of the fire smoke sensor device during the performance monitoring period, and the above-mentioned minimum signal strength represents the minimum level of the output signal strength of the fire smoke sensor device during the performance monitoring period, wherein the maximum signal strength and the minimum signal strength can be monitored by a signal strength meter.

[0032] The maximum value is extracted from the real-time bit depth of each sensor belonging to the fire smoke sensor device during the performance monitoring period, marked as the maximum bit depth of each sensor belonging to the fire smoke sensor device during the performance monitoring period, indicating the maximum level of the bit depth of each sensor belonging to the fire smoke sensor device during the performance monitoring period.

[0033] The maximum signal strength of each sensor belonging to the fire smoke sensor device within the performance monitoring period and the minimum signal strength of each sensor belonging to the fire smoke sensor device within the performance monitoring period are subjected to difference processing, and the processing result is marked as the signal strength change amplitude of each sensor belonging to the fire smoke sensor device within the performance monitoring period, indicating the difference between the maximum signal strength and the minimum signal strength of each sensor belonging to the fire smoke sensor device within the performance monitoring period, which can be obtained by monitoring the signal generator. This difference reflects the fluctuation range of the signal strength of the sensor during the monitoring process. During the normal operation of the fire smoke sensor device, the signal strength change amplitude of each sensor should be maintained at a relatively low level, which means that when there is no smoke or the smoke concentration is within the normal range, the output signal strength of the sensor remains stable and the fluctuation range is limited. This state reflects the high performance and stability of the sensor under normal conditions, ensuring its accurate monitoring and response to environmental conditions. Only when the smoke concentration and other abnormal conditions increase, the sensor will show a significant change in signal strength, thereby issuing an alarm in time and effectively playing its key role in fire early warning. Therefore, under normal environmental conditions, maintaining a low level of sensor signal strength change amplitude is an important prerequisite for ensuring the normal operation and accurate alarm of the fire smoke sensor device.

[0034] The maximum bit depth of each sensor belonging to the fire smoke sensor device during the performance monitoring period, the sampling rate of each sensor belonging to the fire smoke sensor device during the performance monitoring period, and the signal strength change amplitude of each sensor belonging to the fire smoke sensor device during the performance monitoring period are comprehensively analyzed to obtain the data acquisition sensitivity factor of the fire smoke sensor device. The data acquisition sensitivity factor of the fire smoke sensor device is used to comprehensively quantify the sensitivity of the fire smoke sensor device in the data acquisition process.

[0035] The data acquisition sensitivity factor of the fire smoke sensor device is specifically analyzed by: ; In the formula, is the data collection sensitivity factor of the fire smoke sensor device, s is the number of each sensor, , q is the total number of sensors, is the maximum bit depth of the sth sensor of the fire smoke sensor device during the performance monitoring cycle, is the sampling rate of the sth sensor of the fire smoke sensor device during the performance monitoring period, is the signal strength variation of the sth sensor of the fire smoke sensor device during the performance monitoring period, The impact value corresponding to the maximum bit depth unit value preset in the alarm database. The impact value corresponding to the sampling rate unit value preset in the alarm database, The impact value corresponding to the unit value of the signal strength change amplitude preset in the alarm database. Defines the maximum bit depth preset in the alarm database. The defined sampling rate is preset in the alarm database. It is the reference signal strength change range preset in the alarm database.

[0036] The above-defined maximum bit depth indicates the minimum allowable value of the maximum bit depth of the s-th sensor belonging to the fire smoke sensor device during the performance monitoring period; the above-defined sampling rate indicates the minimum allowable value of the sampling rate of the s-th sensor belonging to the fire smoke sensor device during the performance monitoring period; the above-mentioned reference signal strength variation range indicates the reference value of the signal strength variation range of the s-th sensor belonging to the fire smoke sensor device during the performance monitoring period.

[0037] The influence value corresponding to the above-mentioned maximum bit depth unit value represents the influence degree of the maximum bit depth unit value on the data acquisition sensitivity factor, the influence value corresponding to the above-mentioned sampling rate unit value represents the influence degree of the sampling rate unit value on the data acquisition sensitivity factor, the influence value corresponding to the above-mentioned signal strength variation amplitude unit value represents the influence degree of the signal strength variation amplitude unit value on the data acquisition sensitivity factor, and the alarm database stores the correspondence between the maximum bit depth and its corresponding influence value, the correspondence between the sampling rate and its corresponding influence value, and the correspondence between the signal strength variation amplitude and its corresponding influence value. For example, the maximum bit depth, sampling rate and signal strength variation amplitude are input into the alarm database, and the alarm database can match the influence value corresponding to the maximum bit depth unit value, the influence value corresponding to the sampling rate unit value and the influence value corresponding to the signal strength variation amplitude unit value, and the value range is between 1 and 2.

[0038] It should be explained that a higher maximum bit depth means that the sensor can retain more information details when converting analog signals into digital signals, which indirectly improves the quality of the sampled data. The sampling rate, as the number of times the sensor collects data per second, is potentially affected by the maximum bit depth. Under the premise of maintaining data quality, a higher bit depth may require a higher sampling rate to make full use of the increased accuracy, thereby more accurately capturing the dynamic changes in smoke concentration. On the other hand, the amplitude of signal intensity change, an indicator reflecting the stability of sensor response, is also affected by the maximum bit depth and sampling rate. Under the premise of high maximum bit depth and sampling rate, the sensor can more accurately record small fluctuations in smoke concentration, so that when the smoke concentration begins to rise abnormally, the amplitude of signal intensity change can more keenly reflect this change. When the maximum bit depth is not enough to fully express the subtle differences in the signal, or the sampling rate is too low to fully capture the instantaneous characteristics of environmental changes. , which will directly restrict the sensor's ability to accurately reflect the actual environmental status. In this situation, the sensor's accuracy will inevitably be damaged, and its sensitivity to subtle changes in the environment will also be greatly reduced. This decrease in accuracy will in turn cause the sensor's signal strength change amplitude to perform abnormally, which may be manifested as a significant deviation of the signal strength change amplitude from the corresponding reference value. The signal strength change amplitude is not proportional to the actual smoke concentration change, and it cannot timely and accurately reflect the true change in signal strength, reducing the device's warning sensitivity to fire risks. In summary, a dynamic balance of mutual restraint and mutual promotion is formed between the maximum bit depth, sampling rate, and signal strength change amplitude. The increase in the maximum bit depth and sampling rate provides a basis for the sharp response of the signal strength change amplitude, while the stability and sensitivity of the signal strength change amplitude verify the effectiveness of the optimization of the first two parameters, which work together to improve the data acquisition sensitivity and fire warning accuracy of the fire smoke sensor device.

[0039] Furthermore, the determination of whether to optimize the performance of the fire smoke sensor device is as follows: extracting the response accuracy threshold of the fire smoke sensor device from the alarm database, and comparing the response accuracy factor of the fire smoke sensor device with the response accuracy threshold of the fire smoke sensor device. If the response accuracy factor of the fire smoke sensor device is greater than the response accuracy threshold of the fire smoke sensor device, it is determined that the fire smoke sensor device is not to be optimized for performance; if the response accuracy factor of the fire smoke sensor device is less than or equal to the response accuracy threshold of the fire smoke sensor device, it is determined that the fire smoke sensor device is to be optimized for performance. The specific performance optimization process is as follows: matching the response accuracy factor of the fire smoke sensor device with the optimization schemes corresponding to each response accuracy factor interval stored in the alarm database, thereby matching and executing the fire smoke sensor device. The optimization scheme of the fire smoke sensor device is updated at the same time; the response accuracy threshold of the fire smoke sensor device represents the minimum value of the reasonable range of the response accuracy factor of the fire smoke sensor device; in an example embodiment, assuming that the response accuracy factor of the fire smoke sensor device is PG, the optimization scheme of the fire smoke sensor device is specifically matched as follows: the response accuracy factor PG of the fire smoke sensor device belongs to the response accuracy factor interval [PG-19%, PG+11%) stored in the alarm database, and the optimization scheme corresponding to the response accuracy factor interval [PG-19%, PG+11%) includes: automatically calibrating each sensor and increasing the sampling rate of each sensor by 0.5 times; therefore, the optimization scheme of the fire smoke sensor device includes: automatically calibrating each sensor and increasing the sampling rate of each sensor by 0.5 times.

[0040] Step 2: Collect environmental parameters of the target area through the fire smoke sensor device, and evaluate the smoke fire demand coefficient of the target area by combining the response accuracy factor of the fire smoke sensor device.

[0041] In a specific embodiment, the present invention successfully realizes the adaptive management of the smoke fire protection system by intelligently determining whether to implement anti-false alarm warning measures based on the smoke fire protection demand coefficient of the target area and updating the smoke fire protection log in real time. It not only significantly enhances the pertinence and effectiveness of fire protection warnings, reduces the interference and waste caused by false alarms, but also promotes the close interaction and continuous optimization of the fire protection system and the use environment. By continuously learning and adapting to environmental changes, the emergency response capability of the fire smoke sensor device is further enhanced.

[0042] Specifically, the smoke fire demand coefficient of the target area is evaluated by: ; In the formula, is the smoke fire demand coefficient of the target area, is the response precision factor of the fire smoke sensor device, is the response accuracy threshold of the fire smoke sensor device, is the first response accuracy factor of the fire smoke sensor device, It is the smoke concentration growth-ambient temperature growth factor of the target area during the environmental detection cycle. is the ambient temperature growth-carbon dioxide concentration growth factor of the target area during the environmental detection period, It is the smoke concentration growth-carbon dioxide concentration growth factor of the target area during the environmental detection cycle. is the reference smoke concentration growth-ambient temperature growth factor of the target area, is the reference ambient temperature growth-carbon dioxide concentration growth factor of the target area, is the reference smoke concentration growth-carbon dioxide concentration growth factor for the target area, is the signal strength variation amplitude of the sth sensor of the fire smoke sensor device during the environmental detection cycle, s is the number of each sensor, , q is the total number of sensors, It is the signal strength change amplitude impact value preset in the alarm database. is the weight corresponding to the response precision factor preset in the alarm database, is the smoke fire demand factor correction value, It is the influence value of smoke concentration growth-ambient temperature growth factor preset in the alarm database. It is the impact value of the ambient temperature growth-carbon dioxide concentration growth factor preset in the alarm database. It is the influence value of smoke concentration growth-carbon dioxide concentration growth factor preset in the alarm database.

[0043] The above-mentioned smoke concentration growth-ambient temperature growth factor influence value indicates the influence degree of the unit value of the smoke concentration growth-ambient temperature growth factor on the smoke fire fighting demand coefficient of the target area; the above-mentioned ambient temperature growth-carbon dioxide concentration growth factor influence value indicates the influence degree of the unit value of the ambient temperature growth-carbon dioxide concentration growth factor on the smoke fire fighting demand coefficient of the target area; the above-mentioned smoke concentration growth-carbon dioxide concentration growth factor influence value indicates the influence degree of the unit value of the smoke concentration growth-carbon dioxide concentration growth factor on the smoke fire fighting demand coefficient of the target area, and the alarm database stores the corresponding relationship between the smoke concentration growth-ambient temperature growth factor and its corresponding influence value, the corresponding relationship between the ambient temperature growth-carbon dioxide concentration growth factor and its corresponding influence value, and the corresponding relationship between the smoke concentration growth-carbon dioxide concentration growth factor and its corresponding influence value. For example, the smoke concentration growth-ambient temperature growth factor, the ambient temperature growth-carbon dioxide concentration growth factor and the smoke concentration growth-carbon dioxide concentration growth factor are input into the alarm database, and the alarm database can match the smoke fog-signal strength correlation coefficient influence value, the smoke concentration growth-ambient temperature growth factor influence value, the ambient temperature growth-carbon dioxide concentration growth factor influence value and the smoke concentration growth-carbon dioxide concentration growth factor influence value, and the value range is between 0 and 1.

[0044] The above-mentioned signal strength variation amplitude influence value represents the numerical value of the influence degree of the unit value of the signal strength variation amplitude on the smoke fire demand coefficient. The weight corresponding to the above-mentioned response precision factor represents the proportion of the response precision factor of the fire smoke sensor device to the smoke fire demand coefficient. The alarm database stores the correspondence between the signal strength variation amplitude and its corresponding influence value and the correspondence between the response precision factor and its corresponding weight. For example, the signal strength variation amplitude and the response precision factor are input into the alarm database, and the alarm database can match the signal strength variation amplitude influence value and the weight corresponding to the response precision factor, and the value range is between 0 and 1.

[0045] The smoke fire demand coefficient correction value above indicates the degree of correction of the smoke fire demand coefficient of the target area, where The smoke fire demand coefficient correction value is set to prevent abnormal smoke in the target area when the response accuracy factor of the fire smoke sensor device is less than the response accuracy threshold of the fire smoke sensor device. The data collected by the fire smoke sensor device will deviate from the actual situation. Therefore, the smoke fire demand coefficient of the target area needs to be personalized. Although the probability of this situation is relatively low, it still needs to be considered.

[0046] It should be explained that, under normal conditions, these growth factors should be maintained within a range close to their corresponding reference values, which reflects the natural fluctuation and equilibrium state of environmental parameters. Under this equilibrium state, the change in signal strength is relatively small, indicating that the smoke fire fighting demand in the target area is low, and the result of comprehensive data processing will not reach the preset smoke fire fighting demand threshold, so the fire alarm will not be triggered. However, when the environmental parameters change, the behavior of these growth factors will change. First, consider the case of a single parameter growth, such as smoking behavior will only cause the growth rate of smoke concentration to increase rapidly, while the growth rates of carbon dioxide concentration and ambient temperature are relatively slight relative to the growth rate of smoke concentration. At this time, the smoke concentration growth-ambient temperature growth factor and the smoke concentration growth-carbon dioxide concentration growth factor will significantly deviate from their reference values, because the change in smoke concentration is not synchronized with the changes in the other two parameters. Nevertheless, since the change in signal strength is still at a low level, the result of comprehensive data processing will still not reach the smoke fire fighting demand threshold. Next, consider the case where two parameters grow at the same time. For example, during cooking, the generation of oil smoke will not only increase the growth rate of smoke concentration, but also increase the growth rate of ambient temperature. Since the growth directions of these two parameters are consistent, the smoke concentration growth-ambient temperature growth factor will not will deviate significantly from its reference value. However, since the growth rate of carbon dioxide concentration remains unchanged, the ambient temperature growth-carbon dioxide concentration growth factor and the smoke concentration growth-carbon dioxide concentration growth factor will still deviate significantly from their reference values. Despite this deviation, the change in signal strength is still not enough to trigger a fire alarm, and the result of comprehensive data processing still does not reach the smoke fire demand threshold. Finally, we consider the environmental anomaly caused by fire. In the case of fire, the growth rates of smoke concentration, ambient temperature and carbon dioxide concentration will all increase significantly. This comprehensive growth trend causes the relative relationship between the three growth factors (smoke concentration growth-ambient temperature growth factor, ambient temperature growth-carbon dioxide concentration growth factor and smoke concentration growth-carbon dioxide concentration growth factor) to remain stable, that is, they will not deviate significantly from their reference values ​​based on fire conditions. At this time, the change in signal strength will be at a high level, because fire, as a strong external interference, has an impact far exceeding the natural fluctuation range between environmental parameters. Therefore, the fire smoke sensor will sense this high level of signal strength change and trigger a smoke fire demand alarm. In summary, through a detailed analysis of the growth factors of smoke concentration, ambient temperature and carbon dioxide concentration, we can more accurately grasp the environmental dynamics of the target area and identify potential safety hazards in a timely manner.

[0047] It needs to be explained that in a complex and changing environment, the fire smoke sensor device may be interfered by various non-fire factors, such as cooking fumes and water vapor. Although these factors may also cause changes in signal strength, the amplitude of the change is usually much smaller than the change caused by the fire. Therefore, expanding the influence of the signal strength change amplitude in the smoke fire demand coefficient in the target area can more effectively distinguish between fire signals and non-fire signals, thereby improving the anti-interference ability of the fire smoke sensor device.

[0048] Furthermore, the smoke fire demand coefficient of the target area is evaluated, and the specific evaluation process is as follows: The environmental parameters of the target area include the real-time smoke concentration of the target area within the environmental detection cycle, the real-time ambient temperature of the target area within the environmental detection cycle, and the real-time carbon dioxide concentration of the target area within the environmental detection cycle; the above-mentioned environmental detection cycle refers to the time period for detecting the environment of the target area, and the specific duration is determined by the fire data administrator; the above-mentioned real-time smoke concentration means the smoke concentration of the target area at any time within the environmental detection cycle, which is measured by the smoke concentration sensor in the fire smoke sensing device; the above-mentioned real-time ambient temperature means the ambient temperature of the target area at any time within the environmental detection cycle, which is measured by the temperature sensor in the fire smoke sensing device; the above-mentioned real-time carbon dioxide concentration means the carbon dioxide concentration of the target area at any time within the environmental detection cycle, which is measured by the carbon dioxide concentration sensor in the fire smoke sensing device.

[0049] The signal strength variation amplitude of each sensor belonging to the fire smoke sensor device during the environmental detection cycle is obtained, which represents the difference between the maximum signal strength and the minimum signal strength of each sensor belonging to the fire smoke sensor device during the environmental detection cycle, which can be monitored by a signal strength measuring instrument.

[0050] The data acquisition sensitivity factor of the fire smoke sensor device is multiplied by the data acquisition sensitivity factor influence value to obtain the data acquisition sensitivity factor influence result of the fire smoke sensor device. The response accuracy factor of the fire smoke sensor device is multiplied by the response accuracy factor influence value to obtain the response accuracy factor influence result of the fire smoke sensor device. The response accuracy factor of the fire smoke sensor device is accumulated with the data acquisition sensitivity factor influence result of the fire smoke sensor device to obtain the data accuracy influence value of the fire smoke sensor device. The first response accuracy factor of the fire smoke sensor device is matched from the alarm database. The above-mentioned data acquisition sensitivity factor influence value indicates that the data acquisition sensitivity factor of the fire smoke sensor device accounts for the response accuracy factor of the fire smoke sensor device. The proportion of the data accuracy influence value of the device is obtained from the alarm database; the above-mentioned response accuracy factor influence value, which represents the proportion of the response accuracy factor of the fire smoke sensor device to the data accuracy influence value of the fire smoke sensor device, is obtained from the alarm database, and the alarm database stores the corresponding relationship between the data acquisition sensitivity factor and its corresponding influence value and the corresponding relationship between the response accuracy factor and its corresponding influence value. For example, the data acquisition sensitivity factor of the fire smoke sensor device and the response accuracy factor of the fire smoke sensor device are input into the alarm database, and the alarm database can match the data acquisition sensitivity factor influence value and the response accuracy factor influence value, and the value range is between 0 and 1.

[0051] The data accuracy impact value of the above-mentioned fire smoke sensor device is used to quantify the influence of the fire smoke sensor device on the smoke fire demand coefficient during the data collection and processing process; the data collection sensitivity factor influence result of the above-mentioned fire smoke sensor device represents the specific influence quantitative value of the data collection sensitivity factor of the fire smoke sensor device on the data accuracy impact value; the response accuracy factor influence result of the above-mentioned fire smoke sensor device represents the specific influence quantitative value of the response accuracy factor of the fire smoke sensor device on the data accuracy influence value.

[0052] The first response accuracy factor of the above-mentioned fire smoke sensor device has a specific matching process as follows: the alarm database stores the first response accuracy factor corresponding to each data accuracy impact value interval, and the data accuracy impact value interval stored in the alarm database to which the data accuracy impact value of the fire smoke sensor device belongs is queried. The first response accuracy factor corresponding to the data accuracy impact value interval is the first response accuracy factor of the fire smoke sensor device, which is used to determine whether the fire smoke sensor device will have an adverse effect on the smoke fire demand coefficient during the data collection and processing process. Specifically, when the response accuracy factor of the fire smoke sensor device is less than or equal to the first response accuracy factor, it indicates that its response accuracy has reached the established use requirements. However, in this case, it should be noted that there may still be certain deviations in the response accuracy of the sensor device. Therefore, in order to more comprehensively evaluate the smoke fire fighting demand, when the response accuracy factor of the fire smoke sensor device satisfies that the response accuracy factor of the fire smoke sensor device is less than or equal to the first response accuracy factor, the response accuracy factor is included in the smoke fire fighting demand coefficient of the target area for comprehensive analysis. When the response accuracy factor of the fire smoke sensor device is greater than the first response accuracy factor, it indicates that the response accuracy of the sensor device is high enough so that it will not cause any deviation or adverse effect on the smoke fire fighting demand coefficient. Therefore, in this case, there is no need to further comprehensively analyze the response accuracy factor and the smoke fire fighting demand coefficient.

[0053] It needs to be explained that the first response accuracy factor of the fire smoke sensor device is greater than the response accuracy threshold of the fire smoke sensor device.

[0054] The maximum and minimum values ​​are located from the real-time smoke concentration in the target area within the environmental detection cycle, and difference processing is performed. The processing result is ratio processed with the duration corresponding to the environmental detection cycle, and finally the smoke concentration growth rate of the target area within the environmental detection cycle is obtained, which represents the growth rate of the smoke concentration in the target area within the environmental detection cycle.

[0055] The maximum and minimum values ​​are located from the real-time ambient temperature of the target area within the environmental detection cycle, and difference processing is performed. The processing result is ratio processed with the duration corresponding to the environmental detection cycle, and finally the ambient temperature growth rate of the target area within the environmental detection cycle is obtained, which indicates the growth rate of the ambient temperature of the target area within the environmental detection cycle.

[0056] The maximum and minimum values ​​are located from the real-time carbon dioxide concentration in the target area during the environmental detection period, and difference processing is performed. The processing result is ratio processed with the duration corresponding to the environmental detection period, and finally the carbon dioxide concentration growth rate in the target area during the environmental detection period is obtained, which represents the growth rate of the carbon dioxide concentration in the target area during the environmental detection period.

[0057] The smoke concentration growth rate in the target area during the environmental detection period is ratioed with the ambient temperature growth rate in the target area during the environmental detection period to obtain the smoke concentration growth-ambient temperature growth factor in the target area during the environmental detection period, which is used to quantify the proportional relationship between the smoke concentration growth rate and the ambient temperature growth rate in the target area during the environmental detection period.

[0058] The growth rate of ambient temperature in the target area during the environmental detection period is ratio-processed with the growth rate of carbon dioxide concentration in the target area during the environmental detection period to obtain the growth factor of ambient temperature - carbon dioxide concentration in the target area during the environmental detection period, which is used to quantify the proportional relationship between the growth rate of ambient temperature and the growth rate of carbon dioxide concentration in the target area during the environmental detection period.

[0059] The growth rate of smoke concentration in the target area during the environmental detection period is ratio-processed with the growth rate of carbon dioxide concentration in the target area during the environmental detection period to obtain the smoke concentration growth-carbon dioxide concentration growth factor in the target area during the environmental detection period; this factor is used to quantify the proportional relationship between the growth rate of smoke concentration in the target area during the environmental detection period and the growth rate of carbon dioxide concentration.

[0060] The reference smoke concentration growth-ambient temperature growth factor, the reference ambient temperature growth-carbon dioxide concentration growth factor and the reference smoke concentration growth-carbon dioxide concentration growth factor of the target area are extracted from the smoke fire log of the target area; the reference smoke concentration growth-ambient temperature growth factor of the target area indicates the reference value of the smoke concentration growth-ambient temperature growth factor of the target area during the environmental detection period; the reference ambient temperature growth-carbon dioxide concentration growth factor of the target area indicates the reference value of the ambient temperature growth-carbon dioxide concentration growth factor of the target area during the environmental detection period; the reference smoke concentration growth-carbon dioxide concentration growth factor of the target area indicates the reference value of the smoke concentration growth-carbon dioxide concentration growth factor of the target area during the environmental detection period. Under normal conditions, that is, when the environment is in a stable state and there is no external interference (such as fire), the smoke concentration growth-ambient temperature growth factor, the ambient temperature growth-carbon dioxide concentration growth factor and the smoke concentration growth-carbon dioxide concentration growth factor will approach the corresponding reference values. These reference values ​​are based on long-term monitoring data and reflect the natural balance between these parameters under normal environmental conditions.

[0061] Comprehensively evaluate the signal strength change amplitude of each sensor belonging to the fire smoke sensor device within the environmental detection period, the smoke concentration growth-ambient temperature growth factor of the target area within the environmental detection period, the ambient temperature growth-carbon dioxide concentration growth factor of the target area within the environmental detection period, the smoke concentration growth-carbon dioxide concentration growth factor of the target area within the environmental detection period, the reference smoke concentration growth-ambient temperature growth factor of the target area, the reference ambient temperature growth-carbon dioxide concentration growth factor of the target area, the reference smoke concentration growth-carbon dioxide concentration growth factor of the target area, the response accuracy threshold of the fire smoke sensor device, the response accuracy factor of the fire smoke sensor device, the first response accuracy factor of the fire smoke sensor device and the data acquisition sensitivity factor of the fire smoke sensor device to obtain the smoke fire fighting demand coefficient of the target area, which is used to comprehensively quantify the specific demand degree of the target area for smoke prevention and control in terms of fire safety.

[0062] Step 3: According to the smoke fire demand coefficient of the target area, determine whether to implement false alarm warning measures for the smoke in the target area, and update the smoke fire log of the target area.

[0063] Specifically, the determination of whether to implement false alarm warning measures for smoke in the target area is as follows: extract the smoke fire demand threshold of the target area from the smoke fire log of the target area, compare the smoke fire demand coefficient of the target area with the smoke fire demand threshold of the target area, if the smoke fire demand coefficient of the target area is less than or equal to the smoke fire demand threshold of the target area, then determine not to implement false alarm warning measures for the smoke in the target area; if the smoke fire demand coefficient of the target area is greater than the smoke fire demand threshold of the target area, then determine to implement false alarm warning measures for the smoke in the target area, the specific warning measures are as follows: match the smoke fire demand coefficient of the target area with the smoke anomaly level corresponding to each smoke fire demand coefficient interval stored in the alarm database, thereby deriving the smoke anomaly level of the target area, and perform false alarm warning based on the smoke anomaly level of the target area; the above-mentioned target The smoke fire demand threshold of the area represents the maximum value of the reasonable range of the smoke fire demand coefficient of the target area; the specific matching process of the smoke anomaly level of the above-mentioned target area is as follows: the smoke anomaly level corresponding to each smoke fire demand coefficient interval is stored in the alarm database, and the smoke fire demand coefficient interval stored in the alarm database to which the smoke fire demand coefficient of the target area belongs is queried, then the smoke anomaly level corresponding to the smoke fire demand coefficient interval is the smoke anomaly level of the target area; in an example embodiment, assuming that the smoke anomaly level of the target area is level three, an anti-false alarm warning is performed based on the smoke anomaly level of the target area, and the specific warning is: sending an anti-false alarm warning log to the fire management personnel, and at the same time the fire smoke sensor device emits a sound corresponding to the third level of smoke anomaly, wherein the anti-false alarm warning log includes: "Level three smoke anomaly occurs in the target area, there may be a risk of fire, please deal with it as soon as possible."

[0064] Furthermore, the smoke fire log of the target area is updated, and the specific updating process is as follows: The execution result stored in the smoke fire log is "solved" or "false alarm", and the execution result of the anti-false alarm warning measure of the target area is obtained. If the execution result is "solved", the smoke fire log of the target area is not updated; if the execution result is "false alarm", the smoke fire log of the target area is automatically updated; the execution result of the anti-false alarm warning measure of the target area is used to indicate whether the anti-false alarm warning measure of the target area has effectively warned the potential fire risk, and is confirmed and uploaded by the fire management personnel. If the execution result is "false alarm", the smoke fire log of the target area is automatically updated. In an example embodiment, the specific automatic update process is: the smoke fire log of the target area The smoke fire demand threshold of the target area is automatically increased by k%, and the reference smoke concentration growth-ambient temperature growth factor of the target area, the reference ambient temperature growth-carbon dioxide concentration growth factor of the target area and the reference smoke concentration growth-carbon dioxide concentration growth factor of the target area are automatically increased by 2*k% respectively; this adjustment is aimed at improving the sensitivity of the warning, ensuring that the anti-false alarm warning measures can flexibly adapt to the current changing usage environment, and can effectively improve the anti-interference ability of the warning. The specific value of k% is formulated by the fire management personnel based on comprehensive consideration of historical data, on-site conditions, system performance and other factors to ensure that the adjusted threshold can effectively reduce false alarms without affecting the timely warning of real fire risks.

[0065] In a specific embodiment, the present invention provides a fire smoke alarm method for preventing false alarms. By finely acquiring the data acquisition process parameters of the fire smoke sensor device, it is possible to deeply analyze and obtain its data acquisition sensitivity factor. At the same time, combined with the data analysis process parameters, a comprehensive evaluation is performed to obtain the response accuracy factor. This step is crucial to improving the accuracy of the fire smoke sensor device and provides a scientific basis for determining whether the performance of the fire smoke sensor device is optimized. This not only ensures the high sensitivity and accuracy of the fire smoke sensor device in smoke detection, but also effectively reduces the false alarm rate and improves the overall efficiency of the fire smoke sensor device. Furthermore, the fire smoke sensor device is used to collect the environmental parameters of the target area in real time, and combined with the response accuracy factor, the smoke fire demand coefficient of the target area can be accurately evaluated. This coefficient directly guides whether it is necessary to implement false alarm warning measures for the target area, thereby effectively preventing fire risks. In addition, timely updating of the smoke fire log according to the evaluation results helps to realize the intelligence and refinement of fire management and provide valuable data support and experience reference for fire safety work.

[0066] Reference Figure 2 As shown, the second aspect of the present invention provides a false alarm-proof fire smoke alarm system, comprising: a response accuracy analysis module, a smoke fire demand assessment module and a false alarm-proof warning implementation module.

[0067] A second aspect of the present invention provides a fire smoke alarm system for preventing false alarms, and also includes an alarm database, wherein the alarm database is used to store an influence value corresponding to a maximum bit depth unit value, an influence value corresponding to a sampling rate unit value, an influence value corresponding to a signal strength variation unit value, define a maximum bit depth, define a sampling rate, a reference signal strength variation, a weight corresponding to a data acquisition sensitivity factor, define a time asynchrony, define a minimum resolution, define a smoke and fog-signal strength correlation coefficient, a response accuracy threshold of a fire smoke sensor device, an optimization scheme corresponding to each response accuracy factor interval, a first response accuracy factor of a fire smoke sensor device, an influence value of a signal strength variation, a weight corresponding to a response accuracy factor, a smoke anomaly level corresponding to each smoke fire demand coefficient interval, an influence value of a data acquisition sensitivity factor, an influence value of a response accuracy factor, an influence value of a time asynchrony, an influence value of a minimum resolution, an influence value of a smoke and fog-signal strength correlation coefficient, an influence value of a smoke concentration growth-ambient temperature growth factor, an influence value of an ambient temperature growth-carbon dioxide concentration growth factor, and an influence value of a smoke concentration growth-carbon dioxide concentration growth factor.

[0068] The response accuracy analysis module is connected to the smoke fire demand assessment module, the smoke fire demand assessment module is connected to the anti-false alarm warning implementation module, and the response accuracy analysis module, the smoke fire demand assessment module and the anti-false alarm warning implementation module are all connected to the alarm database.

[0069] The response accuracy analysis module is used to obtain the data acquisition process parameters of the fire smoke sensor device, analyze the data acquisition sensitivity factor of the fire smoke sensor device, and simultaneously obtain the data analysis process parameters of the fire smoke sensor device, and comprehensively consider the data acquisition sensitivity factor of the fire smoke sensor device to obtain the response accuracy factor of the fire smoke sensor device, thereby determining whether to optimize the performance of the fire smoke sensor device.

[0070] The smoke fire demand assessment module is used to collect environmental parameters of the target area through the fire smoke sensor device, and evaluate the smoke fire demand coefficient of the target area by integrating the response precision factor of the fire smoke sensor device.

[0071] The anti-false alarm warning implementation module is used to determine whether to implement anti-false alarm warning measures for the smoke in the target area according to the smoke fire demand coefficient of the target area, and update the smoke fire log of the target area.

[0072] A third aspect of the present invention provides a computer-readable storage medium for storing a program, wherein when the program is executed by a processor, the program implements the fire smoke alarm method for preventing false alarms as described above.

[0073] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A fire smoke alarm method for preventing false alarms, characterized in that: include: Step 1: obtaining data acquisition process parameters of the fire smoke sensor device, analyzing the data acquisition sensitivity factor of the fire smoke sensor device, and obtaining data analysis process parameters of the fire smoke sensor device, and comprehensively considering the data acquisition sensitivity factor of the fire smoke sensor device to obtain the response accuracy factor of the fire smoke sensor device, so as to determine whether to optimize the performance of the fire smoke sensor device; Step 2: Collect environmental parameters of the target area through the fire smoke sensor device, and evaluate the smoke fire demand coefficient of the target area by combining the response precision factor of the fire smoke sensor device; Step 3: According to the smoke fire demand coefficient of the target area, determine whether to implement false alarm warning measures for the smoke in the target area, and update the smoke fire log of the target area.

2. A fire smoke alarm method for preventing false alarms according to claim 1, characterized in that: The data acquisition sensitivity factor of the fire smoke sensor device is analyzed, and the specific analysis process is: The data collection process parameters of the fire smoke sensor device include the real-time bit depth of each sensor of the fire smoke sensor device during the performance monitoring period, the sampling rate of each sensor of the fire smoke sensor device during the performance monitoring period, the maximum signal strength of each sensor of the fire smoke sensor device during the performance monitoring period, and the minimum signal strength of each sensor of the fire smoke sensor device during the performance monitoring period; Extracting a maximum value from the real-time bit depth of each sensor belonging to the fire smoke sensor device during the performance monitoring period, and marking it as the maximum bit depth of each sensor belonging to the fire smoke sensor device during the performance monitoring period; Perform difference processing on the maximum signal strength of each sensor belonging to the fire smoke sensor device within the performance monitoring period and the minimum signal strength of each sensor belonging to the fire smoke sensor device within the performance monitoring period, and mark the processing result as the signal strength change amplitude of each sensor belonging to the fire smoke sensor device within the performance monitoring period; The maximum bit depth of each sensor belonging to the fire smoke sensor device during the performance monitoring period, the sampling rate of each sensor belonging to the fire smoke sensor device during the performance monitoring period, and the signal strength change amplitude of each sensor belonging to the fire smoke sensor device during the performance monitoring period are comprehensively analyzed to obtain the data acquisition sensitivity factor of the fire smoke sensor device. The data acquisition sensitivity factor of the fire smoke sensor device is used to comprehensively quantify the sensitivity of the fire smoke sensor device in the data acquisition process.

3. The fire smoke alarm method for preventing false alarms according to claim 1, characterized in that: The specific analysis process of the response precision factor of the fire smoke sensor device is as follows: The data analysis process parameters of the fire smoke sensor device include the average response time of each sensor of the fire smoke sensor device during the performance monitoring period, the minimum resolution of each sensor of the fire smoke sensor device during the performance monitoring period, the smoke and fog change curve of the fire smoke sensor device during the performance monitoring period, and the signal strength change curve of the fire smoke sensor device during the performance monitoring period; The average response time of each sensor of the fire smoke sensor device in the performance monitoring period is processed by standard deviation, and marked as the time asynchronism of the sensor of the fire smoke sensor device in the performance monitoring period; Data processing is performed on the smoke density change curve of the fire smoke sensor device during the performance monitoring period and the signal strength change curve of the fire smoke sensor device during the performance monitoring period to obtain the smoke density-signal strength correlation coefficient of the fire smoke sensor device during the performance monitoring period; The data acquisition sensitivity factor of the fire smoke sensor device, the time asynchronism of the sensors belonging to the fire smoke sensor device within the performance monitoring period, the minimum resolution of each sensor belonging to the fire smoke sensor device within the performance monitoring period and the smoke concentration-signal strength correlation coefficient of the fire smoke sensor device within the performance monitoring period are comprehensively analyzed to obtain the response accuracy factor of the fire smoke sensor device. The response accuracy factor of the fire smoke sensor device is used to comprehensively quantify the accuracy of the fire smoke sensor device in the process of data collection and processing.

4. The fire smoke alarm method for preventing false alarms according to claim 1, characterized in that: The specific determination process of whether to optimize the performance of the fire smoke sensor device is as follows: Extracting a response accuracy threshold of the fire smoke sensor device from the alarm database, and comparing the response accuracy factor of the fire smoke sensor device with the response accuracy threshold of the fire smoke sensor device, if the response accuracy factor of the fire smoke sensor device is greater than the response accuracy threshold of the fire smoke sensor device, then determining not to perform performance optimization on the fire smoke sensor device; If the response precision factor of the fire smoke sensor device is less than or equal to the response precision threshold of the fire smoke sensor device, it is determined that the performance of the fire smoke sensor device is optimized. The specific performance optimization process is: The response precision factor of the fire smoke sensor device is matched with the optimization scheme corresponding to each response precision factor interval stored in the alarm database, thereby matching and executing the optimization scheme of the fire smoke sensor device, and updating the response precision factor of the fire smoke sensor device.

5. The fire smoke alarm method for preventing false alarms according to claim 1, characterized in that: The smoke fire demand coefficient of the target area is evaluated, and the specific evaluation process is as follows: The environmental parameters of the target area include the real-time smoke concentration of the target area within the environmental detection period, the real-time ambient temperature of the target area within the environmental detection period, and the real-time carbon dioxide concentration of the target area within the environmental detection period; Obtain the signal strength variation range of each sensor of the fire smoke sensor device within the environmental detection cycle; The data acquisition sensitivity factor of the fire smoke sensor device is multiplied by the data acquisition sensitivity factor influence value to obtain the data acquisition sensitivity factor influence result of the fire smoke sensor device; the response accuracy factor of the fire smoke sensor device is multiplied by the response accuracy factor influence value to obtain the response accuracy factor influence result of the fire smoke sensor device; and the response accuracy factor of the fire smoke sensor device is accumulated with the data acquisition sensitivity factor influence result of the fire smoke sensor device to obtain the data accuracy influence value of the fire smoke sensor device, thereby matching the first response accuracy factor of the fire smoke sensor device from the alarm database; The maximum and minimum values ​​are located from the real-time smoke concentration of the target area within the environmental detection cycle, and difference processing is performed. The processing result is ratio-processed with the duration corresponding to the environmental detection cycle, and finally the smoke concentration growth rate of the target area within the environmental detection cycle is obtained; The maximum and minimum values ​​are located from the real-time ambient temperature of the target area within the environmental detection period, and difference processing is performed. The processing result is ratio processed with the duration corresponding to the environmental detection period, and finally the ambient temperature growth rate of the target area within the environmental detection period is obtained; The maximum and minimum values ​​are located from the real-time carbon dioxide concentration of the target area within the environmental detection period, and difference processing is performed. The processing result is ratio-processed with the duration corresponding to the environmental detection period, and finally the carbon dioxide concentration growth rate of the target area within the environmental detection period is obtained; Ratio processing is performed on the growth rate of smoke concentration in the target area during the environmental detection period with the growth rate of ambient temperature in the target area during the environmental detection period to obtain the growth factor of smoke concentration - ambient temperature in the target area during the environmental detection period; Ratio processing is performed on the growth rate of ambient temperature in the target area during the environmental detection period with the growth rate of carbon dioxide concentration in the target area during the environmental detection period to obtain the growth factor of ambient temperature - carbon dioxide concentration in the target area during the environmental detection period; Ratio processing is performed on the growth rate of smoke concentration in the target area during the environmental detection period with the growth rate of carbon dioxide concentration in the target area during the environmental detection period to obtain the growth factor of smoke concentration - carbon dioxide concentration in the target area during the environmental detection period; Extract the reference smoke concentration growth-ambient temperature growth factor of the target area, the reference ambient temperature growth-carbon dioxide concentration growth factor of the target area, and the reference smoke concentration growth-carbon dioxide concentration growth factor of the target area from the smoke fire log of the target area; Comprehensively evaluate the signal strength change amplitude of each sensor belonging to the fire smoke sensor device within the environmental detection period, the smoke concentration growth-ambient temperature growth factor of the target area within the environmental detection period, the ambient temperature growth-carbon dioxide concentration growth factor of the target area within the environmental detection period, the smoke concentration growth-carbon dioxide concentration growth factor of the target area within the environmental detection period, the reference smoke concentration growth-ambient temperature growth factor of the target area, the reference ambient temperature growth-carbon dioxide concentration growth factor of the target area, the reference smoke concentration growth-carbon dioxide concentration growth factor of the target area, the response accuracy threshold of the fire smoke sensor device, the response accuracy factor of the fire smoke sensor device, the first response accuracy factor of the fire smoke sensor device and the data acquisition sensitivity factor of the fire smoke sensor device to obtain the smoke fire fighting demand coefficient of the target area, which is used to comprehensively quantify the specific demand degree of the target area for smoke prevention and control in terms of fire safety.

6. A fire smoke alarm method for preventing false alarms according to claim 5, characterized in that: The smoke fire demand coefficient of the target area is evaluated by the following specific method: ； In the formula, is the smoke fire demand coefficient of the target area, is the response precision factor of the fire smoke sensor device, is the response accuracy threshold of the fire smoke sensor device, is the first response accuracy factor of the fire smoke sensor device, It is the smoke concentration growth-ambient temperature growth factor of the target area during the environmental detection cycle. is the ambient temperature growth-carbon dioxide concentration growth factor of the target area during the environmental detection period, It is the smoke concentration growth-carbon dioxide concentration growth factor of the target area during the environmental detection cycle. is the reference smoke concentration growth-ambient temperature growth factor of the target area, is the reference ambient temperature growth-carbon dioxide concentration growth factor of the target area, is the reference smoke concentration growth-carbon dioxide concentration growth factor for the target area, is the signal strength variation amplitude of the sth sensor of the fire smoke sensor device during the environmental detection cycle, s is the number of each sensor, , q is the total number of sensors, It is the signal strength change amplitude impact value preset in the alarm database. is the weight corresponding to the response precision factor preset in the alarm database, is the smoke fire demand factor correction value, It is the influence value of smoke concentration growth-ambient temperature growth factor preset in the alarm database. It is the impact value of the ambient temperature growth-carbon dioxide concentration growth factor preset in the alarm database. It is the influence value of smoke concentration growth-carbon dioxide concentration growth factor preset in the alarm database.

7. The fire smoke alarm method for preventing false alarms according to claim 1, characterized in that: The specific determination process of whether to implement the false alarm warning measures for the smoke in the target area is as follows: Extract the smoke fire demand threshold of the target area from the smoke fire log of the target area, compare the smoke fire demand coefficient of the target area with the smoke fire demand threshold of the target area, and if the smoke fire demand coefficient of the target area is less than or equal to the smoke fire demand threshold of the target area, it is determined that no false alarm warning measures will be implemented for the smoke in the target area; If the smoke fire demand coefficient of the target area is greater than the smoke fire demand threshold of the target area, it is determined that the smoke in the target area will be subject to false alarm warning measures. The specific warning measures are as follows: The smoke fire demand coefficient of the target area is matched with the smoke anomaly level corresponding to each smoke fire demand coefficient interval stored in the alarm database, thereby obtaining the smoke anomaly level of the target area, and an anti-false alarm warning is performed based on the smoke anomaly level of the target area.

8. A fire smoke alarm method for preventing false alarms according to claim 7, characterized in that: The smoke fire log of the target area is updated, and the specific updating process is as follows: The execution result stored in the smoke fire log is "solved" or "false alarm", and the execution result of the false alarm prevention warning measures in the target area is obtained. If the execution result is "solved", the smoke fire log of the target area will not be updated; If the execution result is "false alarm", the smoke fire log of the target area will be automatically updated.

9. A system using a fire smoke alarm method for preventing false alarms as claimed in any one of claims 1 to 8, characterized in that: include: The response accuracy analysis module is used to obtain the data acquisition process parameters of the fire smoke sensor device, analyze the data acquisition sensitivity factor of the fire smoke sensor device, and simultaneously obtain the data analysis process parameters of the fire smoke sensor device, and comprehensively calculate the response accuracy factor of the fire smoke sensor device based on the data acquisition sensitivity factor of the fire smoke sensor device, so as to determine whether to optimize the performance of the fire smoke sensor device; The smoke fire demand assessment module is used to collect environmental parameters of the target area through the fire smoke sensor device, and evaluate the smoke fire demand coefficient of the target area by integrating the response accuracy factor of the fire smoke sensor device; The anti-false alarm warning implementation module is used to determine whether to implement anti-false alarm warning measures for the smoke in the target area according to the smoke fire demand coefficient of the target area, and to update the smoke fire log of the target area.

10. A computer-readable storage medium for storing a program, wherein when the program is executed by a processor, the fire smoke alarm method for preventing false alarms according to any one of claims 1 to 8 is implemented.

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