A multi-objective optimization adaptive waveform switching acoustic wave extinguishing method and system

Abstract

This invention discloses a multi-objective optimized adaptive waveform switching acoustic fire extinguishing method and system, relating to the field of acoustic fire extinguishing technology. The invention sets a waveform switching objective function. This objective function includes, on the one hand, the sound pressure level at the target flame when the composite waveform reaches the flame, which characterizes the fire extinguishing effectiveness of each waveform combination; on the other hand, it includes the waveform effectiveness sensitivity of the composite waveform, which guides the selection of the composite waveform combination; and thirdly, it includes the total weighted sound pressure level of the environment, which limits the sound pressure level of the composite waveform in the current environment. Thus, in the overall optimization, this invention can adaptively optimize the selection of waveform combinations by utilizing the unique advantages of different waveforms according to the dynamically changing fire situation and complex environmental constraints. This achieves deep coupling decision-making between waveform combination, noise control, and fire extinguishing effectiveness, ultimately achieving highly efficient acoustic fire extinguishing.

Description

Technical Field

[0001] This invention relates to the field of acoustic fire extinguishing technology, and in particular to a multi-objective optimized adaptive waveform switching acoustic fire extinguishing method and system. Background Technology

[0002] Acoustic fire suppression technology has attracted attention due to its clean and pollution-free characteristics and its ability to be used repeatedly. At the same time, acoustic fire suppression technology also has problems such as rapid sound energy dissipation, difficulty in automatically adapting to different fire conditions, and serious noise pollution at high power.

[0003] Current research primarily reveals the correlation between sound wave frequency and flame extinguishing, indicating the existence of an "optimal extinguishing frequency" range within which sound waves can most effectively couple with flames, inducing flame instability. Based on this research, the main fire extinguishing solutions currently include setting up isolation barriers and throwing-type sound wave extinguishing devices. Setting up isolation barriers enhances the reflection of emitted longitudinal waves in the direction of their travel, forming a stable superimposed sound field in the space between the electroacoustic transducer and the isolation barrier. This method improves fire extinguishing efficiency, but it cannot guarantee effective fire extinguishing enhancement for flames at different locations within the sound field. Throw-type sound wave extinguishing devices involve throwing a specific sound wave extinguishing device near the fire point, which automatically carries out fire extinguishing operations. However, since sound propagation requires a medium, if the sound-emitting device is located inside the throwable device and not in contact with the outside air, the acoustic impedance of solid materials is significantly greater than that of gases. This method leads to a rapid dissipation of sound wave energy inside the device, making it difficult to extinguish the fire.

[0004] To address the problems existing in current main fire extinguishing solutions, researchers are working on automatically adjusting the output power based on the size of the flames detected by sensors, directly increasing the power to extinguish the flames. This method still uses traditional sine waves and only adjusts the power of the sine wave to achieve fire extinguishing. However, in real fire scenes, different environments and different fire conditions need to be considered. Moreover, sound waves are not only a tool for fire extinguishing, but also a form of environmental pollution. At present, relying solely on the power regulation of sine waves is confined to the single perspective of "sine waves." It is difficult to make intelligent trade-offs and adaptive selections between different waveforms based on dynamically changing fire conditions (such as distance from the fire source, flame size, and fire extinguishing efficiency) and complex and ever-changing environmental constraints (such as day / night noise restrictions). In other words, it is impossible to deeply couple the switching of sound wave waveforms with noise control and fire extinguishing efficiency, thus making it difficult to achieve high-efficiency sound wave fire extinguishing. Summary of the Invention

[0005] This invention provides a multi-objective optimized adaptive waveform switching acoustic fire extinguishing method and system, which can solve the problems existing in the prior art.

[0006] This invention provides a multi-objective optimized adaptive waveform switching acoustic fire extinguishing method, comprising the following steps: Collect flame information of the target flame and real-time environmental noise values ​​in the current environment, and obtain the distance between the sound source and the target flame; Based on the flame information of the target flame, obtain the critical acoustic particle velocity required to achieve effective fire extinguishing; based on the current acoustic environment standards and real-time noise values, set the total weighted sound pressure level of the environment; Set a composite waveform containing sine wave, square wave and sawtooth wave, and set the waveform performance sensitivity of the composite waveform based on the rate of change of the sound power of each waveform in the composite waveform with the fire extinguishing efficiency; obtain the sound pressure at the flame when the composite waveform reaches the target flame according to the distance between the sound source and the target flame. Based on the sound pressure at the flame when the composite waveform reaches the target flame, the waveform performance sensitivity of the composite waveform, and the set environmental total weighted sound pressure level, a waveform switching objective function is constructed; wherein, the sound pressure at the flame when the composite waveform reaches the target flame is used to characterize the fire extinguishing performance of each waveform combination, the waveform performance sensitivity is used to guide the selection of waveform combinations of composite waveforms, and the environmental total weighted sound pressure level is used to limit the sound pressure level of the composite waveform in the current environment. With the goal of maximizing fire extinguishing efficiency and minimizing noise pollution, and with the critical acoustic particle velocity and the upper limit of the acoustic environment standard as constraints, and with each waveform parameter in the composite waveform as the optimization variable, the objective function of waveform switching is solved to obtain the optimal combination of acoustic parameters for extinguishing the target flame in the current environment. The sound source is then driven to extinguish the fire based on the optimal combination of acoustic parameters.

[0007] Preferably, the step of collecting flame information of the target flame and real-time ambient noise values ​​in the current environment, and obtaining the distance between the sound source and the target flame, includes: Infrared thermal imagers, lidar, and environmental noise monitoring units are deployed in the current environment. The infrared thermal imager is used to identify target flames in real time and collect flame temperature data. T Flame height h The lidar collects point cloud data from the current environment and combines it with flame temperature data. T Flame height h By using image recognition and coordinate registration algorithms, the distance between the sound wave source and the target flame is calculated. d ; The environmental noise monitoring unit includes a microphone array set in the current environment, which is used to collect real-time noise values ​​in the current environment.

[0008] Preferably, the composite waveform is represented as: ; in: Represents a sine wave; Represents a square wave; Indicates a sawtooth wave; Indicates the amplitude weight of a sine wave, square wave, or sawtooth wave; Indicates the phase shift of a sine wave, square wave, or sawtooth wave; This involves adjusting the amplitude weights of sine waves, square waves, or sawtooth waves. or phase shift To generate composite waveforms with different waveform combinations.

[0009] Preferably, the waveform performance sensitivity of the composite waveform is expressed as: ; ; in: Indicates the first element within the composite waveform Waveform performance sensitivity of each waveform; This indicates the feedback quantity of fire extinguishing effectiveness; It represents a tiny change in sound wave power; This indicates that the "efficiency-power" rate of change is used as a reference with a baseline waveform. Indicates the first The rate of change of "efficiency-power" for each waveform; Among them, waveform effectiveness sensitivity characterizes the rate of change in fire extinguishing effectiveness caused by a unit power change. A waveform with high waveform effectiveness sensitivity indicates that a small power increase will cause a significant improvement in fire extinguishing efficiency.

[0010] Preferably, the waveform switching objective function is expressed as: ; ; ; in: Indicates a composite waveform; Represents the flame height function; Indicates the height of the flame; Indicates the weighting coefficient; Represents different waveforms from the sound source to the distance The waveform of the sound pressure loss at the flame - the propagation loss function. ; Indicates the total weighted sound pressure level in the environment; The waveform-noise function representing the A-weighted sound pressure level at the sound source for different waveforms under different sound pressure levels. ; The waveform-conversion efficiency function represents the relationship between the input signal Vpp of different waveform signal generators and the sound pressure level of the sound source. ; Indicates the first i Waveform parameters of each waveform; This indicates the ambient ambient noise level measured by the loudspeaker array used for environmental noise monitoring. This represents the critical acoustic particle velocity required to achieve effective fire extinguishing. in, The indicator is that when the fire situation changes, leading to... When it increases, As the weight increases, the system automatically tends to use a high WES waveform to increase the fire extinguishing efficiency within the limited sound power.

[0011] Preferably, obtaining the optimal combination of acoustic parameters includes: The constraints for solving the waveform switching objective function include: Noise at the source ; As a hard constraint on reliability, it means that the generated acoustic particle velocity is greater than 1.2 times the critical particle velocity; As an environmental constraint, the perceived noise generated should be less than the upper limit of noise required by the environment. The optimization variables in solving the waveform switching objective function include composite waveforms. Sound wave frequency Distance from the sound source sound pressure at the flame Total weighted sound pressure level with environment ; A multi-objective optimization algorithm is employed to optimize the objective function within the feasible solution space defined by constraints, thereby obtaining the globally optimal composite waveform in the current environment. Sound wave frequency Sound pressure at the sound source .

[0012] Preferably, the step of obtaining the globally optimal composite waveform in the current environment is... Sound wave frequency Sound pressure at the sound source And based on composite waveforms Sound wave frequency Sound pressure at the sound source After completing the firefighting operation, record the fire parameters for that operation. The waveform parameters used Ultimate fire extinguishing efficiency The features are merged into a single feature vector, and this feature vector is recorded in the waveform-fire matching library. When a new fire occurs, the system determines the similarity between the current fire characteristics and the waveform-fire matching database features, and prioritizes recommending the waveform parameter combination that has historically performed best under similar fire conditions as the initial value for optimization.

[0013] This invention also provides a multi-objective optimized adaptive waveform switching acoustic fire extinguishing system, including a perception layer, a decision layer, and an execution layer; The perception layer includes a fire identification module, a distance detection module, and an environmental noise monitoring module. The fire identification module is used to collect flame information of the target flame in the current environment. The distance detection module is used to collect the distance between the sound source and the target flame in the current environment. The environmental noise monitoring module is used to collect the real-time noise value in the current environment. The decision layer is connected to the perception layer. The decision layer is used to implement the steps of the multi-objective optimized adaptive waveform switching acoustic fire extinguishing method as described above based on the data collected by the perception layer, and transmits the optimal combination of output acoustic parameters to the execution layer. The execution layer includes a programmable waveform generator and a sound wave emitting unit. The programmable waveform generator generates waveform electrical signals corresponding to the optimal combination of sound wave parameters. The sound wave emitting unit converts the waveform electrical signals into high-intensity sound waves to act on the target flame to extinguish the fire.

[0014] This invention also provides an electronic device, including a memory and a processor; The memory is used to store computer programs; When the processor executes the computer program stored in the memory, it implements the steps of the multi-objective optimized adaptive waveform switching acoustic fire extinguishing method described above.

[0015] This invention also provides a computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the steps of a multi-objective optimized adaptive waveform switching acoustic fire extinguishing method as described above.

[0016] This invention provides a multi-objective optimized adaptive waveform switching acoustic fire extinguishing method and system, which has the following advantages compared with the prior art: This invention establishes a waveform switching objective function. On one hand, the objective function incorporates the sound pressure level at the flame when the composite waveform reaches the target flame into the optimization scope. This optimization term characterizes the fire extinguishing efficiency of each waveform combination. Therefore, when the fire source distance is close, it tends to select waveform combinations with high near-field suppression efficiency; as the fire source distance increases, it selects waveform combinations with smaller sound attenuation coefficients and stronger far-field energy retention capabilities. This decouples "efficiency" and "distance," two originally mutually exclusive indicators within a "sine wave." On the other hand, it incorporates the waveform efficiency sensitivity of the composite waveform into the optimization scope. This optimization term guides the selection of waveform combinations for the composite waveform. Thus, when the fire intensifies, it guides the system to select a more "sensitive" and efficient waveform combination that responds to power changes. The sensitive waveform combination enables the maximum fire extinguishing efficiency with the minimum power increment. Furthermore, the total weighted sound pressure level of the environment is included in the optimization scope. This optimization term limits the sound pressure level of the composite waveform in the current environment. This signifies that the system no longer solely pursues the maximization of fire extinguishing efficiency, but seeks Pareto optimality between the conflicting goals of "efficiency" and "noise and environmental protection". That is, through waveform combination design, efficiency and noise are actively harmonized. Thus, in the overall optimization, this invention can adaptively optimize the selection of waveform combinations by taking into account the dynamically changing fire situation and complex and ever-changing environmental constraints, and make deep coupling decisions between waveform combination, noise control, and fire extinguishing efficiency, ultimately achieving highly efficient acoustic fire extinguishing. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the overall process of multi-objective optimization switching provided in an embodiment of the present invention; Figure 2 A schematic diagram of the overall process for adaptive optimization of composite waveform performance sensitivity (WES) provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the architecture of an adaptive optimization fire extinguishing system provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0019] Acoustic fire suppression technology has attracted attention due to its clean, pollution-free, and reusable characteristics. However, it also suffers from problems such as rapid sound energy dissipation, difficulty in automatically adapting to different fire conditions, and severe noise pollution at high power levels. Existing academic research and technological applications largely focus on the impact of sound frequency and sound pressure level on fire suppression effectiveness, primarily improving efficiency by optimizing sound frequency or increasing sound pressure level, while generally neglecting the crucial parameter of "waveform." This invention reveals that different waveforms (such as sine waves, square waves, and sawtooth waves) exhibit significant inherent differences in sound energy propagation efficiency, fire suppression effect, and noise level. Specifically, when Vpp (peak-to-peak value of the signal emitted by the signal generator) is the same, the square wave has the fastest fire suppression speed, significantly outperforming the sine wave and sawtooth wave. When the sound pressure level at the fire source is the same, the sine wave has a faster fire suppression speed than the other two, such as at 75Hz. Under 6.00Vpp conditions, three waveforms were applied to a laminar diffusion flame with a height of 1.00cm, a bottom diameter of 1.50cm, and methane fuel, at a distance of 5.00cm between the sound source and the fire source. Using the square wave reduced the extinguishing time by more than 50% compared to the sine wave. At the same time, the sound attenuation trends of the three waveforms were also different. The sound pressure of the sine wave attenuated the fastest with distance, the sawtooth wave attenuated more slowly at close distances, and the square wave attenuated more slowly at greater distances. Under 100Hz and 60dB conditions, at a distance of 30cm from the sound source, the residual sound pressure of the sine wave in the direction of sound emission was only about 35% of that of the square wave and about 50% of that of the sawtooth wave. This means that in practical applications, the difference in sound energy attenuation of different waveforms will become a key factor that cannot be ignored in affecting their extinguishing efficiency.

[0020] Furthermore, the three types of acoustic fire suppression systems differ significantly in perceived noise. Sine waves exhibit the least perceived noise, followed by sawtooth waves, while square waves have the most. Using a single waveform cannot simultaneously address energy retention for long-range fire suppression, peak efficiency at close range, and control of environmental noise. Currently, most research on acoustic fire suppression technologies remains focused on a single sine wave perspective, failing to effectively combine the unique advantages of different waveforms. Moreover, existing technologies generally lack comprehensive consideration of sound wave propagation loss, waveform conversion efficiency, and noise pollution to address the technical challenges of improving acoustic fire suppression efficiency and expanding its applicability. This results in a significant disconnect from practical applications, hindering the achievement of truly adaptive and intelligent fire suppression.

[0021] Currently, the main methods to improve firefighting efficiency include: (1) Set up a partition to reflect and enhance the emitted longitudinal wave in the direction of the low-frequency longitudinal wave, and form a stable superimposed sound field in the space between the electroacoustic transducer and the partition. Improve the fire extinguishing efficiency by superimposing the sound field (such as patent CN112774058A). Although the concept of "superimposed sound field" proposed by this scheme is a relatively novel technical idea, due to the fixed sound-emitting device, it cannot be guaranteed that it will have an effective fire extinguishing effect on flames at different positions in the sound field. In fact, for flames at the sound pressure node, the fire extinguishing effect may be worse than that of ordinary traveling waves without a partition due to the cancellation of sound wave energy. Moreover, this fire extinguishing method requires the addition or intentional setting of "partition", resulting in limited applicability and significantly increased cost. Although it is proposed that the existing curved wall of the balcony or bay window can be used, since the wall is in the external space, the sound wave will be subject to severe airflow interference, resulting in rapid energy dissipation. Therefore, its feasibility is difficult to guarantee in terms of both mechanism and engineering, and it cannot be used on a large scale in real life.

[0022] (2) The output power is automatically adjusted according to the size of the flame identified by the sensor, and the power is directly increased to extinguish the flame (such as patent CN111202934A). This method can indeed enhance the extinguishing efficiency of sound wave fire extinguishing, but it still uses the traditional sine wave. When the upper limit of Vpp emitted by the signal generator is reached, it cannot effectively deal with larger flames. However, since the present invention uses waveform switching, it can increase the sound pressure of the effective extinguishing frequency band emitted by the signal generator under the same Vpp by more than 120% by using a square wave with stronger sound energy under the same Vpp or by modulating a specific waveform. This significantly improves the extinguishing efficiency and applicability of the sound wave fire extinguishing device under the same Vpp. At the same time, directly increasing the power will lead to serious noise pollution and even strong mechanical resonance, which will limit the use in some scenarios. However, the present invention can minimize this noise pollution while achieving efficient fire extinguishing by modulating a special fire extinguishing waveform and using a global optimization function.

[0023] (3) Throwable sonic fire extinguishing devices: Users throw a specific sonic fire extinguishing device near the fire point, and it automatically starts fire extinguishing (e.g., patent CN216366406U). This method aims to keep people at a safe distance while the sonic fire extinguisher is as close to the fire source as possible to shorten the sound propagation loss distance and achieve efficient fire extinguishing. However, since sound propagation requires a medium, if the sound-generating device is located inside the throwable device and does not come into contact with the outside air, the sound impedance of solid materials is significantly greater than that of gases, which will lead to a rapid dissipation of sound energy inside the device. If the sound-generating device can come into direct contact with the outside air, the relevant electronic components are difficult to... The fact that the device operates normally in the high-temperature environment near a fire raises questions about its feasibility for use in extinguishing fires. However, this invention modulates a specific waveform, such as a square wave, which attenuates significantly slower than a sine wave over long distances. This reduces the sound energy loss from the sound source to the fire source, thus maximizing the reduction of sound energy loss even when the device is located in a safe working area. Furthermore, because the device is located in a safe area, it has excellent continuous use capability. When powered on, it can continuously maintain sound emission to suppress the flames and can be used in subsequent fires after the fire is extinguished.

[0024] Based on the problems existing in current technology, this invention aims to solve the technical problem that existing acoustic fire extinguishing technologies cannot adaptively select the optimal acoustic waveform according to dynamic fire conditions and complex environmental constraints, and achieve optimal overall fire extinguishing performance. On the one hand, it provides an intelligent decision-making method and system that deeply couples waveform switching with noise control and fire extinguishing reliability through a multi-objective optimization function. Furthermore, in the multi-objective optimization decision unit, the optimization variables are not limited to the selection of a single waveform. On the other hand, as a further optimization of this invention, it can also be configured to support the generation and optimization of composite waveforms. By intelligently combining the characteristics of different waveforms (such as the high fundamental energy of square waves, the pure spectrum of sine waves, and low perceived noise), customized acoustic waves with superior overall performance under specific fire conditions can be generated, achieving fire extinguishing effects that surpass any single waveform. This represents an advanced form of acoustic fire extinguishing waveform optimization.

[0025] This invention provides an adaptive waveform switching acoustic fire extinguishing method and system based on multi-objective optimization. Its core lies in constructing an intelligent central control unit that, based on real-time fire conditions and environmental constraints, adaptively selects optimal acoustic parameters (especially waveforms) by solving a multi-objective optimization problem to achieve the best balance between fire extinguishing efficiency, effective range, and noise control. The system includes a perception layer and a decision layer, such as... Figure 3 shown; specifically: (1) Perception layer (integrating the following modules): Fire detection module: Can use an infrared thermal imager to identify flames and collect flame temperature data in real time. Flame height Wait for flame information.

[0026] Distance detection module: A combination of LiDAR and infrared thermal imager can be used to obtain the distance between the sound source and the fire source. .

[0027] Environmental noise monitoring module: It can use a microphone array to monitor the basic noise level of the current environment and continuously monitor the environmental noise value during the operation of the sound wave generating device, so as to provide a basis for noise control.

[0028] (2) Decision layer (central control unit): This is the core module, which embeds a multi-objective optimization decision function. It also integrates a waveform-conversion efficiency function that shows the relationship between the input signal Vpp of different waveform signal generators (such as sine waves) and the sound pressure at the sound source. Different waveforms, such as sine waves, vary in distance from the sound source. Waveform of sound pressure - propagation loss function ; sine waves and other waveforms at different sound pressure levels at the sound source A Waveform-noise function of weighted sound pressure level ,in Indicates the first Waveform parameters of each waveform.

[0029] The two solutions of this invention specifically include: I. Multi-target optimized switching of system preset waveforms, such as Figure 1 As shown.

[0030] Step S101: The system starts up; the system is powered on, and the infrared thermal imager monitors the infrared thermal image of the target area in real time to determine whether a fire has occurred; if no fire has occurred, the monitoring status is maintained; if a fire is detected, step S102 and the following steps are executed.

[0031] Step S102: Multi-source information sensing; the infrared thermal imager identifies the flame in real time and collects the flame temperature. Flame height Flame information; the central control unit fuses point cloud data from lidar and infrared thermal imaging data, and accurately calculates the distance between the fire source and the sound source through image recognition and coordinate registration algorithms. An environmental noise monitoring microphone array detects the basic ambient noise level.

[0032] Step S103: Based on the flame temperature provided by the infrared thermal imager Flame height Based on the acoustic extinguishing criticality criterion model and flame information, the critical acoustic particle velocity required for extinguishing the fire is calculated. As a hard constraint of the optimization problem; if the critical acoustic particle velocity required for fire extinguishing is found... If the fire exceeds the system's independent firefighting capacity, proceed to step S103-A "Execute Emergency Response"; if the fire scale does not exceed the limit, continue with the normal optimized firefighting procedure step S204.

[0033] Step S103-A: Execute emergency response. When the fire exceeds the limit, the system immediately enters the highest priority emergency mode: (1) Activate emergency response plan: The system ignores noise limits. The sound wave generator is controlled to emit optimized, high-impact sound waves at the maximum safe power allowed by the equipment (e.g., square waves are preferred, and frequencies that produce the maximum sonic particle velocity are used) to suppress the spread of fire as much as possible and buy time for professional firefighting forces.

[0034] (2) Report the fire and raise the alarm: Immediately upload the fire location, scale, video information, etc. to the central monitoring center via the network, and trigger the sound and light alarm to request manual intervention.

[0035] (3) After the emergency response is completed, the process continues to step S106 to execute the suppression plan.

[0036] (4) If the fire scale does not exceed the limit, continue to execute the normal optimized fire extinguishing process step S204.

[0037] Step S104: Define the multi-objective optimization problem; the central control unit constructs the following optimization model: (1) Define optimization variables: selected waveform Sound wave frequency Acoustic particle velocity at the flame (The objective function is represented by the distance from the sound source) sound pressure at the flame ), , For acoustic impedance, environmental total A Weighted sound pressure level , , This indicates the ambient ambient noise level measured by the loudspeaker array used for environmental noise monitoring.

[0038] (2) Define constraints: ① (A hard reliability constraint requires that the generated acoustic particle velocity be greater than 1.2 times the critical particle velocity to ensure successful fire extinguishing.)

[0039] ② Noise at the source (Environmental constraints: the perceived noise level should be less than the total noise limit required by the environment.) ).

[0040] All parameters are within the allowable range of the equipment.

[0041] (3) Define the objective function: Construct a maximization objective function : .

[0042] .

[0043] This multi-objective optimization function takes into account the effectiveness of acoustic fire extinguishing (as manifested in...). Noise pollution during sound wave fire extinguishing (manifested as) ) and sound wave energy consumption (manifested as By selecting the optimal waveform to ensure effective fire extinguishing while minimizing noise pollution and unnecessary power consumption during the sound generation process; among other things, This is the weighting coefficient, which can be customized according to the specific usage environment.

[0044] Step S105: Solving the optimization problem and achieving optimal execution; the system uses an optimization algorithm (such as the weighted sum method) to solve the problem based on the flame information provided by each sensor and the pre-calibrated functions, obtaining the current globally optimal waveform. Sound wave frequency and sound pressure at the sound source Subsequently, the drive waveform generator produces... Waveform, loudspeaker array at sound wave frequency and sound pressure at the sound source The parameters emit sound waves; if the ambient noise monitoring speaker array detects that the total noise in the space exceeds the upper limit set by the system, it returns to step S104 to readjust the output signal by adjusting the weights; if it is found that the total noise of the ambient noise and the fire extinguishing noise is less than the maximum value set by the system, it returns to step S104 to readjust the output signal by adjusting the weights; Under the conditions that cannot be satisfied If the fire is detected, the location, scale, and video information of the fire will be immediately uploaded to the central monitoring center via the network, and an audible and visual alarm will be triggered to request manual judgment. If the manual judgment result is "execute emergency response", then step S103-A will be implemented. If the manual judgment result is "do not execute emergency response", then jump to S105-A "execute maximum suppression". If no manual intervention is received 15 seconds after the alarm is issued, then the default is "execute emergency response" and step S103-A will be implemented (or it can be preset to execute S105-A).

[0045] Step S105-A: Perform maximum suppression; when Effective fire extinguishing conditions and noise at the source When a conflict occurs and the system is manually determined to "not execute an emergency response," the system executes a maximum suppression scheme: (1) Activate the maximum suppression scheme: The system ignores the effective fire suppression limit. Control the sound wave generator to meet the noise level at the sound source. Under the premise of maximizing the ability to suppress fire with minimal noise pollution, the optimized sound waves are emitted at the maximum safe power allowed by the equipment (e.g., sine waves are preferred and frequencies that produce the maximum sonic particle velocity are used) to suppress the spread of fire as much as possible and buy time for professional firefighting forces.

[0046] Step S106: Effectiveness Evaluation and Closed-Loop Feedback. During the fire extinguishing process, the infrared thermal imager and LiDAR continuously monitor and update the flame data. The system determines whether the flame has been extinguished:

[0047] (1) If the fire has been extinguished, perform a short-term continuous acoustic interference to prevent reignition, and then resume the inspection.

[0048] (2) If the fire is not extinguished, it indicates that the fire situation has changed (such as the fire source has moved). The process will immediately return to step S102 and restart the entire global optimization process with the latest sensing data to achieve dynamic tracking of the fire source and continuous and efficient fire extinguishing.

[0049] II. Composite waveform adaptive optimization modulation based on fusion waveform performance sensitivity (WES).

[0050] To further improve performance, this invention also provides a more advanced composite waveform optimization scheme, such as... Figure 2 As shown, this scheme is not limited to selecting a single waveform, but uses the generation of composite waveforms as an optimization variable, aiming to integrate the advantages of different waveforms. The specific composition of the composite waveform is determined by global optimization of the actual fire situation and the parameter settings of the objective function, so as to achieve true adaptive fire extinguishing and targeted acoustic waveform modulation.

[0051] Step S201: The system starts up; the system is powered on, and the infrared thermal imager monitors the infrared thermal image of the target area in real time to determine whether a fire has occurred; if no fire has occurred, the monitoring status is maintained; if a fire is detected, step S202 and the following steps are executed.

[0052] Step S202: Multi-source information sensing; the infrared thermal imager identifies the flame in real time and collects the flame temperature. Flame height Flame information; the central control unit fuses point cloud data from lidar and infrared thermal imaging data, and accurately calculates the distance between the fire source and the sound source through image recognition and coordinate registration algorithms. An environmental noise monitoring microphone array detects the basic ambient noise level.

[0053] Step S203: Based on the flame temperature provided by the infrared thermal imager Flame height Based on the acoustic extinguishing criticality criterion model and flame information, the critical acoustic particle velocity required for extinguishing the fire is calculated. As a hard constraint of the optimization problem; if the critical acoustic particle velocity required for fire extinguishing is found... If the fire has exceeded the system's independent firefighting capacity, proceed to step S203-A to execute the emergency response; if the fire scale has not exceeded the limit, continue to execute the normal optimized firefighting procedure step S204.

[0054] Step S203-A: Execute emergency response; when the fire exceeds the limit, the system immediately enters the highest priority emergency mode: (1) Activate emergency response plan: The system ignores noise limits. The sound wave generator is controlled to emit optimized composite sound waves with the strongest impact at the maximum safe power allowed by the equipment (for example, for close-range fire suppression, square waves and sawtooth waves can be superimposed and the frequency that produces the maximum sonic particle velocity can be selected), aiming to suppress the spread of fire as much as possible and buy time for professional fire fighting forces.

[0055] (2) Report the fire and raise the alarm: Immediately upload the fire location, scale, video information, etc. to the central monitoring center via the network, and trigger the sound and light alarm to request manual intervention.

[0056] (3) After the emergency response is completed, the process continues to step S206 to execute the suppression plan.

[0057] (4) If the fire scale does not exceed the limit, continue to execute the normal optimized fire extinguishing process step S204.

[0058] Step S204: Combine waveform performance sensitivity (WES) and define a multi-objective optimization problem; the central control unit constructs the following optimization model: (1) Define the optimization variable: composite waveform Sound wave frequency Acoustic particle velocity at the flame (The objective function is represented by the distance from the sound source) sound pressure at the flame ), total environment A Weighted sound pressure level , , This indicates the ambient ambient noise level measured by the loudspeaker array used for environmental noise monitoring.

[0059] (2) Define constraints: ① (A hard reliability constraint requires that the generated acoustic particle velocity be greater than 1.2 times the critical particle velocity to ensure successful fire extinguishing.)

[0060] ② Noise at the source (Environmental constraints mean that the perceived noise level should be less than the upper limit of environmental noise requirements).

[0061] All parameters are within the allowable range of the equipment.

[0062] (3) Define the objective function: Construct a maximization objective function : .

[0063] .

[0064] Composite waveform ,in Represents a sine wave, Indicates square wave, These three waveforms, representing sawtooth waves, are the basic waveforms for composite waveform modulation. Their amplitude weights can be adjusted. and phase shift Generate different composite waveforms; It is a function of flame height, positively correlated with flame height, and is used to characterize flame size or the severity of a fire (selective). The reason why, rather than other flame parameters, and The molecules are adopted The reasons are the same; at the same time, this solution adds a waveform performance sensitivity-based ( WES ) and real-time fire situation An adaptive waveform optimization modulation mechanism.

[0065] While the "multi-objective optimization" model in step S104 above is powerful, its core is "one-time solution based on a physical model," which assumes that the fire environment is static. Once the optimal solution is calculated ( The existing technology, however, is dynamic: flames may flicker, spread, and fluctuate in intensity, all of which alter the optimal standing wave field parameters. This is a common problem with existing solutions, which rely on a binary signal such as "whether the flame is extinguished." Therefore, this invention creatively introduces the concept of "Waveform Performance Sensitivity (WES)" as a more innovative and groundbreaking preferred solution. Its calculation formula is as follows: .

[0066] in: This is the feedback quantity of fire extinguishing effectiveness. For initial flames less than 10cm in height, which are mainly targeted by acoustic fire extinguishing, it follows the above-mentioned thermodynamic model of acoustic fire extinguishing critical criteria, and its flame height term index... Furthermore, the critical acoustic particle velocity for acoustic extinguishing is... Since the exponent is 2 / 3, it can be considered that the two are approximately proportional. The model can easily adjust the acoustic parameters according to the flame height, so it is preferable to use... Defined as follows: .

[0067] It represents a tiny change in sound wave power; This indicates that the "efficiency-power" change rate is used as a reference with a baseline waveform (such as a sine wave); Then it is the first The "efficiency-power" change rate of a waveform; WES quantifies the rate of change in fire extinguishing efficiency caused by a unit power change. It measures the "sensitivity" of different waveforms to power changes. A waveform with a high WES (such as a square wave with a high amplitude weight) means that a slight increase in power will greatly improve the fire extinguishing efficiency, making it suitable for quickly suppressing fires.

[0068] This complex objective function is introduced by... This significantly improves the system's adaptability and intelligence, enabling it to adapt to changes in the fire situation. When it increases, As the weight increases, the system automatically tends to use a high WES waveform to increase the fire extinguishing efficiency within the limited sound power. By modulating the composite waveform in this way, the best fire extinguishing waveform can be obtained, ensuring the fire extinguishing effect while minimizing noise pollution and unnecessary power consumption during the sound generation process. This is the weighting coefficient, which can be customized according to the specific usage environment.

[0069] Step S205: Solving the optimization problem and achieving optimal execution; Based on the flame information provided by each sensor and the pre-calibrated functions, the system uses an optimization algorithm (such as the weighted sum method) to solve the problem and obtain the current globally optimal composite waveform. Sound wave frequency and sound pressure at the sound source Subsequently, the drive waveform generator modulates and generates a composite waveform. The loudspeaker array uses sound wave frequencies and sound pressure at the sound source The parameters emit sound waves; if the ambient noise monitoring speaker array detects that the total noise in the space exceeds the upper limit set by the system, it returns to step S204 to readjust the output signal by adjusting the weights; if it is found that the total noise of the ambient noise and the fire extinguishing noise is less than the maximum value set by the system, it returns to step S204 to readjust the output signal by adjusting the weights; Under the conditions that cannot be met If the fire is detected, the location, scale, and video information of the fire will be immediately uploaded to the central monitoring center via the network, and an audible and visual alarm will be triggered, requesting manual judgment. If the manual judgment result is "execute emergency response", then step S203-A will be implemented; if the manual judgment result is "do not execute emergency response", then proceed to S205-A "execute maximum suppression"; if no manual intervention is received 15 seconds after the alarm is issued, then the default is "execute emergency response", and step S203-A will be implemented (or it can be preset to execute S205-A).

[0070] Step S205-A: Perform maximum suppression; when Effective fire extinguishing conditions and noise at the source When a conflict occurs and the system is manually determined to "not execute an emergency response," the system executes a maximum suppression scheme: (1) Activate the maximum suppression scheme: The system ignores the effective fire suppression limit. Control the sound wave generator to meet the noise level at the sound source. Under the premise of maximizing the ability to suppress fire with minimal noise pollution, the optimized sound waves are emitted at the maximum safe power allowed by the equipment (e.g., prioritizing the superposition of sine and square waves and using frequencies that produce the maximum sonic particle velocity) to suppress the spread of fire as much as possible and buy time for professional firefighting forces.

[0071] Step S206: Effectiveness evaluation and closed-loop feedback; During the fire extinguishing process, the infrared thermal imager and LiDAR continuously monitor and update the flame data; The system determines whether the flame has been extinguished: (1)If it has been extinguished, perform continuous short-term acoustic interference to prevent reignition, then resume inspection and proceed to step S207.

[0072] (2)If the fire is not extinguished, it indicates that the fire situation has changed (such as the fire source has moved). The process will immediately return to step S202 and restart the entire global optimization process with the latest sensing data to achieve dynamic tracking of the fire source and continuous and efficient fire extinguishing.

[0073] Step S207: Construct a "waveform-fire" matching library and an online learning strategy; after each successful fire extinguishing, the system records a feature vector: [fire parameters] The waveform parameters used, etc. Ultimate fire extinguishing efficiency The matching library has a network sharing function, which makes it easy for the same model of equipment in different regions to obtain the latest cases. When a new fire occurs, the system can calculate the similarity between the current fire characteristics and the characteristics in the historical database, and give priority to recommending the waveform parameter combination that performed best under similar fire conditions in the past as the initial value for optimization. This can greatly speed up the convergence speed, enable the system to have the ability of "experience learning", and make it more intelligent.

[0074] This invention can automatically find the optimal balance between fire extinguishing efficiency and noise control while ensuring successful fire extinguishing, achieving optimal comprehensive performance in engineering applications. It can dynamically select the most suitable waveform or automatically modulate a composite waveform according to the fire situation (distance, scale) and environmental requirements (noise limits) to meet specific requirements such as low noise, high fire extinguishing speed, and low system power consumption, making it applicable to a wide range of scenarios. By modulating specific fire extinguishing waveforms and utilizing the unique physical characteristics of different sound waves, it can increase the sound pressure of the effective fire extinguishing frequency band emitted by the signal generator under the same Vpp by more than 120%, thereby doubling the fire extinguishing efficiency with limited sound wave power.

[0075] This invention incorporates the sound pressure at the flame when the composite waveform reaches the target flame into the optimization scope, explicitly including the "sound source-fire source distance d" as a key variable influencing decision-making. This distance-based adaptive waveform switching and modulation capability allows the system to consistently "customize" the most efficient sound wave pattern for the fire source location across a wide spatial range from near to far field. This fundamentally decouples and simultaneously optimizes the previously mutually exclusive indicators of "efficiency" and "distance," achieving true "precise targeting, suitable for both near and far distances." Furthermore, this invention incorporates the environmental total weighted sound pressure level into the optimization scope, allowing the system to flexibly adapt to the needs of different scenarios: in unattended operation... In warehouses, efficiency can be given higher weight, while in hospitals or libraries operating at night, noise control can be given higher weight. This ability to actively reconcile the contradiction between "efficiency and noise" through waveform design enables acoustic fire extinguishing technology to leap from "extensive energy delivery" to "refined green fire protection". The waveform efficiency sensitivity of this invention is included in the optimization scope, realizing a deep understanding and intelligent utilization of the nonlinear relationship between "power and efficiency" of the system. The system can adjust the WES value of the composite waveform to make it work in a "stable zone" where efficiency changes relatively smoothly with power, avoiding drastic fluctuations in efficiency due to environmental disturbances, and improving the robustness and controllability of the system.

[0076] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A multi-objective optimized adaptive waveform switching acoustic fire extinguishing method, characterized in that, Includes the following steps: Collect flame information of the target flame and real-time environmental noise values ​​in the current environment, and obtain the distance between the sound source and the target flame; Based on the flame information of the target flame, obtain the critical acoustic particle velocity required to achieve effective fire extinguishing; based on the current acoustic environment standards and real-time noise values, set the total weighted sound pressure level of the environment; Set a composite waveform containing sine wave, square wave and sawtooth wave, and set the waveform performance sensitivity of the composite waveform based on the rate of change of the sound power of each waveform in the composite waveform with the fire extinguishing efficiency; obtain the sound pressure at the flame when the composite waveform reaches the target flame according to the distance between the sound source and the target flame. Based on the sound pressure at the flame when the composite waveform reaches the target flame, the waveform performance sensitivity of the composite waveform, and the set environmental total weighted sound pressure level, a waveform switching objective function is constructed; wherein, the sound pressure at the flame when the composite waveform reaches the target flame is used to characterize the fire extinguishing performance of each waveform combination, the waveform performance sensitivity is used to guide the selection of waveform combinations of composite waveforms, and the environmental total weighted sound pressure level is used to limit the sound pressure level of the composite waveform in the current environment. With the goal of maximizing fire extinguishing efficiency and minimizing noise pollution, and with the critical acoustic particle velocity and the upper limit of the acoustic environment standard as constraints, and with each waveform parameter in the composite waveform as the optimization variable, the objective function of waveform switching is solved to obtain the optimal combination of acoustic parameters for extinguishing the target flame in the current environment. The sound source is then driven to extinguish the fire based on the optimal combination of acoustic parameters.

2. The multi-objective optimized adaptive waveform switching acoustic fire extinguishing method according to claim 1, characterized in that, The process of collecting flame information of the target flame and real-time environmental noise values ​​in the current environment, and obtaining the distance between the sound source and the target flame, includes: Infrared thermal imagers, lidar, and environmental noise monitoring units are deployed in the current environment. The infrared thermal imager is used to identify target flames in real time and collect flame temperature data. T Flame height h The lidar collects point cloud data from the current environment and combines it with flame temperature data. T Flame height h By using image recognition and coordinate registration algorithms, the distance between the sound wave source and the target flame is calculated. d ; The environmental noise monitoring unit includes a microphone array set in the current environment, which is used to collect real-time noise values ​​in the current environment.

3. The multi-objective optimized adaptive waveform switching acoustic fire extinguishing method according to claim 1, characterized in that, The composite waveform is represented as follows: ； in: Represents a sine wave; Represents a square wave; Indicates a sawtooth wave; Indicates the amplitude weight of a sine wave, square wave, or sawtooth wave; Indicates the phase shift of a sine wave, square wave, or sawtooth wave; This involves adjusting the amplitude weights of sine waves, square waves, or sawtooth waves. or phase shift To generate composite waveforms with different waveform combinations.

4. The multi-objective optimized adaptive waveform switching acoustic fire extinguishing method according to claim 3, characterized in that, The waveform performance sensitivity of the composite waveform is expressed as: ； ； in: Indicates the first element within the composite waveform Waveform performance sensitivity of each waveform; This indicates the feedback quantity of fire extinguishing effectiveness; It represents a tiny change in sound wave power; This indicates that the "efficiency-power" change rate is used as a reference with a baseline waveform; Indicates the first The rate of change of "efficiency-power" for each waveform; Among them, waveform effectiveness sensitivity characterizes the rate of change in fire extinguishing effectiveness caused by a unit power change. A waveform with high waveform effectiveness sensitivity indicates that a small power increase will cause a significant improvement in fire extinguishing efficiency.

5. The multi-objective optimized adaptive waveform switching acoustic fire extinguishing method according to claim 4, characterized in that, The waveform switching objective function is expressed as follows: ； ； ； in: Indicates a composite waveform; A function representing the flame height; Indicates the height of the flame; Indicates the weighting coefficient; Represents different waveforms from the sound source to the distance The waveform of the sound pressure loss at the flame - the propagation loss function. ; Indicates the total weighted sound pressure level in the environment; The waveform-noise function representing the A-weighted sound pressure level at the sound source for different waveforms under different sound pressure levels. ; The waveform-conversion efficiency function represents the relationship between the input signal Vpp of different waveform signal generators and the sound pressure level of the sound source. ; Indicates the first i Waveform parameters of each waveform; This indicates the ambient ambient noise level measured by the loudspeaker array used for environmental noise monitoring. This represents the critical acoustic particle velocity required to achieve effective fire extinguishing. in, The indicator is that when the fire situation changes, leading to... When it increases, As the weight increases, the system automatically tends to use a high WES waveform to increase the fire extinguishing efficiency within the limited sound power.

6. The multi-objective optimized adaptive waveform switching acoustic fire extinguishing method according to claim 5, characterized in that, Obtaining the optimal combination of acoustic parameters includes: The constraints for solving the waveform switching objective function include: Noise at the source ; As a hard constraint on reliability, it means that the generated acoustic particle velocity is greater than 1.2 times the critical particle velocity; As an environmental constraint, the perceived noise generated should be less than the upper limit of noise required by the environment. The optimization variables in solving the waveform switching objective function include composite waveforms. Sound wave frequency Distance from the sound source sound pressure at the flame Total weighted sound pressure level with environment ; A multi-objective optimization algorithm is employed to optimize the objective function within the feasible solution space defined by constraints, thereby obtaining the globally optimal composite waveform in the current environment. Sound wave frequency Sound pressure at the sound source .

7. The multi-objective optimized adaptive waveform switching acoustic fire extinguishing method according to claim 6, characterized in that, The result is the globally optimal composite waveform in the current environment. Sound wave frequency Sound pressure at the sound source And based on composite waveforms Sound wave frequency Sound pressure at the sound source After completing the firefighting operation, record the fire parameters for that operation. The waveform parameters used Ultimate fire extinguishing efficiency The features are merged into a single feature vector, and this feature vector is recorded in the waveform-fire matching library. When a new fire occurs, the system determines the similarity between the current fire characteristics and the waveform-fire matching database features, and prioritizes recommending the waveform parameter combination that has historically performed best under similar fire conditions as the initial value for optimization.

8. A multi-objective optimized adaptive waveform switching acoustic fire extinguishing system, characterized in that, include: The layers are: perception layer, decision-making layer, and execution layer. The perception layer includes a fire identification module, a distance detection module, and an environmental noise monitoring module. The fire identification module is used to collect flame information of the target flame in the current environment. The distance detection module is used to collect the distance between the sound source and the target flame in the current environment. The environmental noise monitoring module is used to collect the real-time noise value in the current environment. The decision layer is connected to the perception layer. The decision layer is used to implement the steps of the multi-objective optimization adaptive waveform switching acoustic fire extinguishing method as described in any one of claims 1 to 7 based on the data collected by the perception layer, and transmits the optimal combination of output acoustic parameters to the execution layer. The execution layer includes a programmable waveform generator and a sound wave emitting unit. The programmable waveform generator generates waveform electrical signals corresponding to the optimal combination of sound wave parameters. The sound wave emitting unit converts the waveform electrical signals into high-intensity sound waves to act on the target flame to extinguish the fire.

9. An electronic device, characterized in that, include: Memory and processor; The memory is used to store computer programs; When the processor executes the computer program stored in the memory, it implements the steps of the multi-objective optimized adaptive waveform switching acoustic fire extinguishing method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, Used to store a computer program, which, when executed by a processor, implements the steps of a multi-objective optimized adaptive waveform switching acoustic fire extinguishing method as described in any one of claims 1 to 7.

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