A hazardous chemical storage environment adaptive regulation method and system

Abstract

The application relates to a dangerous chemical storage environment adaptive regulation method and system, and relates to the field of dangerous chemical storage safety. The method is applied to a storage safety control system and comprises the following steps: collecting multiple environment parameters corresponding to multiple monitoring points of a target storage; performing clustering analysis on the multiple monitoring points based on the multiple environment parameters corresponding to the multiple monitoring points, to generate multiple regulation areas; calculating area danger coefficients corresponding to the multiple regulation areas; determining multiple risk regulation areas from the multiple regulation areas according to a preset dynamic danger coefficient threshold; calculating area dispersion coefficients of the multiple risk regulation areas according to the center coordinates of the multiple risk regulation areas; formulating a regulation strategy of the target storage according to the area dispersion coefficients; and controlling multiple adjusting devices to adjust the environment of the target storage according to the regulation strategy, so as to solve the problem of local safety risks caused by the fact that a traditional dangerous chemical storage environment regulation mode cannot adapt to the dynamic distribution characteristics of dangerous chemicals.

Description

Technical Field

[0001] This application relates to the technical field of hazardous chemical storage safety, specifically to an adaptive control method and system for hazardous chemical storage environment. Background Technology

[0002] Because of their unstable chemical properties, hazardous chemicals are prone to explosion. Therefore, the stability of the storage environment is crucial for the storage of hazardous chemicals.

[0003] The current hazardous chemical storage environment control system mainly predicts the future trend of the storage environment based on real-time collected environmental parameters. If the environmental parameters are at risk of exceeding the preset safety threshold in the future trend, the control and regulation equipment will adjust the environmental parameters in advance to stabilize the storage environment within a safe range.

[0004] However, due to factors such as stacking methods, volatility characteristics, and airflow in the storage space, the volatilized hazardous chemicals in the warehouse exhibit a non-uniform spatial distribution. The aforementioned control methods are mostly based on the overall environmental parameters of the warehouse and adopt fixed control logic, which cannot adapt to the dynamic distribution characteristics of hazardous chemicals, thus easily causing local safety risks. Summary of the Invention

[0005] To address the localized safety risks arising from the inability of traditional hazardous chemical storage environment control methods to adapt to the dynamic distribution characteristics of hazardous chemicals, this application provides an adaptive control method and system for hazardous chemical storage environments.

[0006] In a first aspect, this application provides an adaptive control method for the hazardous chemical storage environment, applied in a storage safety control system, the method comprising:

[0007] Multiple environmental parameters are collected at multiple monitoring points in the target warehouse. The multiple environmental parameters at each monitoring point include temperature, humidity, concentration of harmful gases, and light intensity.

[0008] Based on the multiple environmental parameters corresponding to each of the multiple monitoring points, cluster analysis is performed on the multiple monitoring points to generate multiple control areas, wherein one monitoring point corresponds to one monitoring area.

[0009] Calculate the regional risk coefficient corresponding to each of the multiple control zones;

[0010] Based on a preset dynamic risk coefficient threshold, multiple risk control zones are determined from the multiple control zones;

[0011] Calculate the regional dispersion coefficient of the multiple risk control areas based on the center coordinates of the multiple risk control areas;

[0012] Based on the regional dispersion coefficient, formulate the control strategy for the target warehouse;

[0013] Multiple regulating devices are controlled to regulate the environment of the target warehouse according to the aforementioned regulation strategy.

[0014] Optionally, the step of performing cluster analysis on the multiple monitoring points based on the multiple environmental parameters corresponding to each of the multiple monitoring points to generate multiple control areas specifically involves:

[0015] Based on the concentration of harmful gases at multiple monitoring points, the gradient vector of harmful gas concentration in multiple monitoring areas is calculated.

[0016] Calculate the similarity of environmental parameters and the similarity of harmful gas concentration gradient vectors between the first monitoring area and the second monitoring area, wherein the first monitoring area and the second monitoring area are any two adjacent monitoring areas among the plurality of monitoring areas;

[0017] If the similarity of the environmental parameters is greater than or equal to a preset first similarity threshold, and the similarity of the harmful gas concentration gradient vector is greater than or equal to a preset second similarity threshold, then the first monitoring area and the second monitoring area are merged into a control area.

[0018] Optionally, the calculation of the regional risk coefficient corresponding to each of the multiple control zones specifically involves:

[0019] By integrating the parameters of multiple control regions, multiple environmental parameters corresponding to each of the multiple control regions are obtained;

[0020] Based on multiple environmental parameters in the first control region, the deviation coefficients of multiple environmental parameters in the first control region are calculated, wherein the first control region is any one of the multiple control regions;

[0021] Based on the preset static hazard weights of multiple environmental parameters, the deviation coefficients of multiple environmental parameters in the first control area are weighted and summed to obtain the regional hazard coefficient of the first control area.

[0022] Optionally, the step of weighted summing of the deviation coefficients of multiple environmental parameters in the first control area according to preset hazard weights of multiple environmental parameters to obtain the regional hazard coefficient of the first control area further includes:

[0023] The concentration of harmful gas in the first control region is subtracted from the concentration of harmful gas in the adjacent control regions to obtain multiple concentration gradients.

[0024] The dynamic risk weight of the first control region is determined based on the multiple concentration gradients.

[0025] Based on the dynamic risk weight of the first control area, the regional risk coefficient of the first control area is adjusted to obtain the target area risk coefficient.

[0026] Optionally, determining multiple risk control zones from multiple control zones based on a preset dynamic risk coefficient threshold further includes:

[0027] The real-time rate of change of harmful gas concentration and the baseline rate of change of harmful gas concentration within the second control region are obtained, wherein the second control region is any one of the multiple control regions;

[0028] The adjustment coefficient of the dynamic hazard coefficient threshold is determined based on the real-time rate of change of hazardous gas concentration and the baseline rate of change of hazardous gas concentration.

[0029] The preset dynamic hazard threshold is adjusted according to the adjustment coefficient of the dynamic hazard threshold to obtain the dynamic hazard threshold of the second control area.

[0030] Optionally, the step of formulating a control strategy for the target warehouse based on the regional dispersion coefficient specifically includes:

[0031] The region dispersion coefficient is compared with a preset region dispersion coefficient threshold.

[0032] If the regional dispersion coefficient is greater than or equal to a preset regional dispersion coefficient threshold, then the control priority of the multiple risk control areas is determined based on the regional hazard coefficients of the multiple risk control areas.

[0033] Based on the control priorities of the multiple risk control areas, a control strategy for the target warehouse is generated.

[0034] Optionally, after comparing the regional dispersion coefficient with a preset regional dispersion coefficient threshold, the method further includes:

[0035] If the regional dispersion coefficient is less than the preset regional dispersion coefficient threshold, then the maximum values ​​of multiple environmental parameters in multiple risk control regions are read to obtain multiple environmental parameters to be adjusted.

[0036] Based on the deviation coefficients of multiple environmental parameters to be adjusted, the priority of the regulations for the multiple environmental parameters to be adjusted is determined;

[0037] A control strategy for the target warehouse is generated based on the control priority of multiple environmental parameters to be adjusted.

[0038] Secondly, this application provides an adaptive control system for hazardous chemical storage environment, which is a storage safety control system. The system includes an acquisition module (1), a processing module (2), and a control module (3), wherein:

[0039] The acquisition module is used to collect multiple environmental parameters corresponding to multiple monitoring points of the target warehouse. The multiple environmental parameters of each monitoring point include temperature, humidity, concentration of harmful gases and light intensity.

[0040] The processing module is configured to perform cluster analysis on the multiple monitoring points based on multiple environmental parameters corresponding to each monitoring point, generating multiple control areas, wherein each monitoring point corresponds to one monitoring area; calculate the regional risk coefficient corresponding to each of the multiple control areas; determine multiple risk control areas from the multiple control areas according to a preset dynamic risk coefficient threshold; calculate the regional dispersion coefficient of the multiple risk control areas according to the center coordinates of the multiple risk control areas; and formulate the control strategy for the target warehouse based on the regional dispersion coefficient.

[0041] The control module is used to control multiple control devices to adjust the environment of the target warehouse according to the control strategy.

[0042] Thirdly, this application provides an electronic device including a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of the first aspects.

[0043] Fourthly, this application provides a computer-readable storage medium storing instructions that, when executed, perform the method described in any one of the first aspects.

[0044] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0045] This application generates multiple control zones by collecting environmental parameters from multiple monitoring points and performing cluster analysis to accurately adapt to the non-uniform distribution of hazardous chemicals in the storage space. Then, it calculates the regional hazard coefficients corresponding to each control zone, and determines multiple risk control zones based on preset dynamic hazard coefficient thresholds. The dispersion coefficients of these risk control zones are then calculated to determine their distribution within the target storage area. If the multiple risk control zones are relatively dispersed and cannot influence each other, the control priority of each risk control zone is determined based on its regional hazard coefficient. When formulating control strategies, priority is given to controlling the risk control zones with higher regional hazard coefficients to reduce the probability of accidents. If the multiple risk control zones are relatively concentrated and have strong mutual influence, priority should be given to adjusting environmental parameters with larger deviations. During the adjustment process, the strong mutual influence is used to simultaneously adjust other deviation coefficients to improve the overall control effect. For example, when the ambient temperature is lowered, the volatilization efficiency of the release source decreases, and the rate of increase in the concentration of harmful gases slows down, resulting in better control of the concentration of harmful gases. The entire plan focuses on the spatial distribution of hazardous chemicals and formulates different control strategies based on different distribution patterns in order to reduce the probability of local risks occurring within the warehouse. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating an adaptive control method for the storage environment of hazardous chemicals provided in an embodiment of this application.

[0047] Figure 2 This is a schematic diagram of the structure of an adaptive control system for hazardous chemical storage environment provided in an embodiment of this application.

[0048] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0049] Explanation of reference numerals in the attached drawings: 1. Acquisition module; 2. Processing module; 3. Control module; 300. Electronic device; 301. Processor; 302. Communication bus; 303. User interface; 304. Network interface; 305. Memory. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0051] Currently, the storage environment control logic for hazardous chemical storage is mostly based on the overall environmental parameters of the storage. However, due to factors such as stacking method, volatility characteristics, and airflow in the storage space, hazardous chemicals in the storage often exhibit a non-uniform spatial distribution. This means that such a fixed control logic cannot adapt to the dynamic distribution characteristics of hazardous chemicals. For example, when the concentration of hazardous chemicals in a local area is close to the upper limit of the safety threshold, while the overall storage concentration is still within the safe range, the fixed control strategy cannot be used to initiate targeted local control, thereby causing local safety risks.

[0052] Therefore, to address this problem, this application provides an adaptive control method for the hazardous chemical storage environment, which is applied to a storage safety control system, such as... Figure 1 As shown, the method includes steps S101 to S107, which are as follows:

[0053] S101. Collect multiple environmental parameters corresponding to multiple monitoring points of the target warehouse. The multiple environmental parameters of each monitoring point include temperature, humidity, concentration of harmful gases and light intensity.

[0054] In the above steps, multiple monitoring points are set up in the target warehouse. Each monitoring point is equipped with a temperature sensor, a humidity sensor, a gas detector array, and a photosensitive sensor to construct a three-dimensional monitoring network for the target warehouse. During actual operation, the three-dimensional monitoring network uploads multiple environmental parameters collected in real time to the warehouse safety control system. The warehouse safety control system performs preprocessing operations such as data cleaning, standardization, and smoothing on the collected data to obtain clean, uniform, and effective data.

[0055] S102. Based on the multiple environmental parameters corresponding to each of the multiple monitoring points, perform cluster analysis on the multiple monitoring points to generate multiple control areas, wherein each monitoring point corresponds to one monitoring area.

[0056] In the above steps, each monitoring point is responsible for monitoring a local area within the target warehouse. The local areas monitored by multiple monitoring points together constitute the complete area of ​​the target warehouse. To clarify the distribution of hazardous chemicals within the target warehouse, the gradient vector of hazardous gas concentrations in multiple monitoring areas is first calculated. The gradient vector represents, on the one hand, the degree of clustering of hazardous gas concentration changes within the monitoring area, and on the other hand, it clarifies the movement trend of hazardous gases within the monitoring area. Specifically, the finite difference method can be used to calculate the concentration change rate in the X, Y, and Z directions based on the spatial coordinates of adjacent monitoring points and the hazardous gas concentration. The vector constructed by the concentration change rates in the three directions is then the gradient vector. Then, cluster analysis is used to generate multiple control areas, specifically:

[0057] Calculate the similarity of environmental parameters and the similarity of harmful gas concentration gradient vectors between the first monitoring area and the second monitoring area, where the first monitoring area and the second monitoring area are any two adjacent monitoring areas among multiple monitoring areas;

[0058] If the similarity of environmental parameters is greater than or equal to the preset first similarity threshold, and the similarity of the concentration gradient vector of harmful gases is greater than or equal to the preset second similarity threshold, it indicates that the first monitoring area and the second monitoring area are not only highly similar in terms of environmental parameters, but also that the harmful gases have the same direction of movement. At this time, the first monitoring area and the second monitoring area can be merged into a control area.

[0059] S103. Calculate the regional risk coefficients corresponding to each of the multiple control zones.

[0060] In the above steps, since the control area consists of one or more monitoring areas, it is necessary to integrate multiple environmental parameters of each control area before calculating the regional hazard coefficients corresponding to each control area. Specifically, if the control area consists of two monitoring areas, the multiple environmental parameters of the control area are replaced by the average values ​​of the corresponding environmental parameters of the multiple monitoring areas. For example, the temperature of the control area is the average temperature of the two monitoring areas, and other environmental parameters of the control area are obtained similarly. Then, the degree of deviation of multiple environmental parameters in each control area is determined, which can be represented by a deviation coefficient, calculated as follows:

[0061]

[0062] in, To determine the deviation coefficient of the i-th environmental parameter within the control area, To regulate the i-th environmental parameter within the region, To regulate the safety threshold of the i-th environmental parameter within the region, > .

[0063] In the above formula, the larger the deviation coefficient, the higher the risk of the accident. Less than or equal to The condition indicates that the i-th environmental parameter is within the safe threshold, and its deviation coefficient is set to 0 at this time.

[0064] Then, based on the static risk weights of multiple environmental parameters, the deviation coefficients of multiple environmental parameters within the control area are weighted and summed to obtain the regional risk coefficient.

[0065] In one possible implementation, multiple environmental parameters of the controlled area can only characterize the static risk level within that area. In real-world scenarios, harmful gases exhibit diffusion effects, with higher concentration gradients leading to stronger diffusion. Therefore, to more accurately assess the risk level of the controlled area, the risk amplification caused by dynamic changes in harmful gases must also be considered. Specifically:

[0066] The concentration of harmful gases in the controlled area is subtracted from the concentrations of harmful gases in multiple adjacent controlled areas to obtain multiple concentration gradients. These gradients are then averaged to obtain the average concentration gradient. Finally, the dynamic risk weight is calculated based on the average concentration gradient, as follows:

[0067]

[0068] in, For dynamic risk weights, Based on dynamic risk weights, The concentration of harmful gases This represents the average concentration gradient.

[0069] In the above formula, It describes the concentration difference between the harmful gas concentration in the current control area and the harmful gas concentration in multiple adjacent control areas. According to the principle that gas diffuses from high concentration to low concentration, if the concentration difference is negative, the harmful gas in the multiple adjacent control areas diffuses into the current control area; if the concentration difference is positive, the harmful gas in the current control area diffuses into the multiple adjacent control areas. In addition, an exponential form is used to characterize the phenomenon that the greater the concentration difference, the faster the diffusion rate.

[0070] Finally, the regional risk coefficient of the controlled area is multiplied by its corresponding dynamic risk weight to obtain the target area risk coefficient.

[0071] S104. Based on the preset dynamic risk coefficient threshold, multiple risk control areas are determined from multiple control areas.

[0072] In the above steps, the regional risk coefficients of multiple control areas are compared with the dynamic risk coefficient threshold. If the regional risk coefficient of a control area is greater than or equal to the dynamic risk coefficient threshold, the risk of an accident in the control area is determined to be high, and the control area is marked as a risk control area.

[0073] In one possible implementation, when a hazardous chemical leaks, the rate of evaporation of the hazardous chemical changes with the storage environment. When the evaporation rate is high, a fixed hazard threshold, while capable of determining whether a risk has occurred in the controlled area, requires time for the control equipment, easily leading to untimely control. Therefore, this application adjusts the preset hazard threshold in each controlled area based on the rate of change of hazardous gas concentration to obtain a dynamic hazard threshold. Specifically:

[0074] The system obtains the real-time rate of change of hazardous gas concentration and the baseline rate of change of hazardous gas concentration within the control area. The baseline rate of change of hazardous gas concentration is the maximum safe rate of change of hazardous gas concentration allowed under normal storage conditions of hazardous chemicals, as specified in the storage safety regulations. Then, the ratio of the real-time rate of change of hazardous gas concentration to the baseline rate of change of hazardous gas concentration is calculated to obtain the adjustment coefficient. Finally, the adjustment coefficient is multiplied by a preset hazard coefficient threshold to obtain the dynamic hazard coefficient threshold of the control area.

[0075] S105. Calculate the regional dispersion coefficient of multiple risk control areas based on the center coordinates of multiple risk control areas.

[0076] In the above steps, firstly, a three-dimensional spatial coordinate system of the target warehouse is constructed based on the structural information of the target warehouse, and the coordinates and monitoring ranges of multiple monitoring points are marked in the three-dimensional spatial coordinate system. Then, based on the coordinates and monitoring ranges of the multiple monitoring points, a geometric algorithm is used to calculate the center coordinates of each of the multiple risk control areas. Then, the Euclidean distance between the center coordinates of each of the multiple risk control areas is calculated. Finally, the standard deviation of the Euclidean distance between the multiple center coordinates is calculated to obtain the regional dispersion coefficient of the multiple risk control areas.

[0077] S106. Based on the regional dispersion coefficient, formulate control strategies for target warehousing.

[0078] In the above steps, the regional dispersion coefficient is compared with a preset regional dispersion coefficient threshold. If the regional dispersion coefficient is greater than or equal to the preset regional dispersion coefficient threshold, it indicates that multiple risk control areas are widely dispersed in the target warehouse. This is understandable because the risk sources differ in different locations within the target warehouse, such as high density of hazardous chemicals, poor ventilation, and strong sunlight. Therefore, for this situation where multiple risk control areas are widely dispersed in the target warehouse, since the physical distance between them is relatively large and they do not affect each other, this application prioritizes the multiple risk control areas according to their regional hazard coefficients, from largest to smallest, to obtain multiple... The control priority of risk control areas is determined, and then control plans for multiple risk control areas are generated independently. These control plans are then sorted according to their control priority, and control strategies are generated. Specifically, during the control process, if the control priority of the first risk control area is greater than that of the second risk control area, the regional risk coefficient of the first risk control area is first controlled to be lower than its corresponding dynamic risk threshold before the second risk control area is controlled. When controlling the first and second risk control areas, the environmental parameter with the largest deviation coefficient is adjusted first, thereby prioritizing the control of core risks and reducing the probability of accidents in the target warehouse. The first and second risk control areas can be any two of the multiple risk control areas.

[0079] If the regional dispersion coefficient is less than the preset regional dispersion coefficient threshold, it indicates that multiple risk control areas are highly concentrated in the target warehouse. In this case, the risk sources of multiple risk control areas are basically the same. Therefore, for this situation where multiple risk control areas are highly concentrated in the target warehouse, due to the strong regional correlation and mutual influence among the multiple risk control areas, this application reads the maximum value of the deviation coefficients of multiple environmental parameters in multiple risk control areas to obtain multiple environmental parameters to be adjusted. Then, according to the magnitude relationship of the deviation coefficients of multiple environmental parameters to be adjusted, the multiple environmental parameters to be adjusted are prioritized in descending order to obtain the control priority of multiple environmental parameters to be adjusted. The control priority of the environmental parameters to be adjusted is then used to generate a control strategy, thereby prioritizing the correction of the environmental parameter with the most severe deviation while simultaneously affecting the changes of other environmental parameters, thereby improving the overall control effect. For example, when the ambient temperature is reduced, the volatilization efficiency of the release source will be weakened, and the growth rate of harmful gas concentration will slow down, resulting in a better control effect on the concentration of harmful gases.

[0080] S107. Control multiple regulating devices to regulate the environment of the target warehouse according to the regulation strategy.

[0081] In the above steps, the warehouse safety control system configures the target power values ​​and adjustment times of multiple adjustment devices according to the adjustment strategy, so that the multiple adjustment devices can adjust the target warehouse environment according to the set program. In addition, during the adjustment process of multiple adjustment devices, the changes in environmental parameters are monitored in real time. When the rate of change of environmental parameters is too fast, the power value of the adjustment device is appropriately reduced to avoid the emergence of new risks; when the rate of change of environmental parameters is too fast, the power value of the adjustment device is appropriately increased to ensure that the environmental parameters can be effectively adjusted.

[0082] Reference Figure 2 This application also provides an adaptive control system for hazardous chemical storage environment. The system is a storage safety control system, which includes an acquisition module 1, a processing module 2, and a control module (3), wherein:

[0083] The acquisition module 1 is used to collect multiple environmental parameters corresponding to multiple monitoring points of the target warehouse. The multiple environmental parameters of each monitoring point include temperature, humidity, concentration of harmful gases and light intensity.

[0084] Processing module 2 is used to perform cluster analysis on multiple monitoring points based on multiple environmental parameters corresponding to each monitoring point, generating multiple control areas, where one monitoring point corresponds to one monitoring area; calculate the regional risk coefficient corresponding to each of the multiple control areas; determine multiple risk control areas from the multiple control areas according to a preset dynamic risk coefficient threshold; calculate the regional dispersion coefficient of the multiple risk control areas according to the center coordinates of the multiple risk control areas; and formulate control strategies for the target warehouse based on the regional dispersion coefficients.

[0085] Control module 3 is used to control multiple control devices to adjust the environment of the target warehouse according to the control strategy.

[0086] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0087] This application also discloses an electronic device. (See reference...) Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 300 may include: at least one processor 301, at least one network interface 304, a user interface 303, a memory 305, and at least one communication bus 302.

[0088] The communication bus 302 is used to enable communication between these components.

[0089] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0090] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0091] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 305, and by calling data stored in memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0092] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. (Refer to...) Figure 2 The memory 305, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for an adaptive control method for hazardous chemical storage environments.

[0093] exist Figure 3 In the illustrated electronic device 300, the user interface 303 is mainly used to provide an input interface for the user and acquire user input data; while the processor 301 can be used to call an application program stored in the memory 305 for an adaptive control method for hazardous chemical storage environment. When executed by one or more processors 301, the electronic device 300 performs one or more of the methods described in the above embodiments. It should be noted that, for the foregoing method embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, because according to this application, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0094] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0095] In the various embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between apparatuses or units may be electrical or other forms.

[0096] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0097] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0098] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0099] The above description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and the disclosure of practical truths.

[0100] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for adaptive control of the hazardous chemical storage environment, characterized in that, The method, applied in a warehouse safety control system, includes: Multiple environmental parameters are collected at multiple monitoring points in the target warehouse. The multiple environmental parameters at each monitoring point include temperature, humidity, concentration of harmful gases, and light intensity. Based on multiple environmental parameters corresponding to each of the multiple monitoring points, cluster analysis is performed on the multiple monitoring points to generate multiple control areas. Specifically, each monitoring point corresponds to one monitoring area. Based on the concentration of harmful gases at multiple monitoring points, the gradient vector of harmful gas concentration in multiple monitoring areas is calculated. Calculate the similarity of environmental parameters such as temperature, humidity, and light intensity, and the similarity of the gradient vector of harmful gas concentration between the first monitoring area and the second monitoring area, wherein the first monitoring area and the second monitoring area are any two adjacent monitoring areas among the multiple monitoring areas; If the similarity of temperature, humidity, and light intensity in the environmental parameters is greater than or equal to a preset first similarity threshold, and the similarity of the gradient vector of harmful gas concentration is greater than or equal to a preset second similarity threshold, then the first monitoring area and the second monitoring area are merged into a control area. Calculate the regional risk coefficient corresponding to each of the multiple control zones; Based on a preset dynamic hazard coefficient threshold, multiple risk control zones are determined from the multiple control zones, which specifically includes: The real-time rate of change of hazardous gas concentration and the baseline rate of change of hazardous gas concentration are obtained within the second control area. The second control area is any one of the multiple control areas. The baseline rate of change of hazardous gas concentration is the maximum safe rate of change of hazardous gas concentration allowed under normal storage conditions of hazardous chemicals in the storage safety specifications. The adjustment coefficient of the dynamic hazard coefficient threshold is determined based on the real-time rate of change of hazardous gas concentration and the baseline rate of change of hazardous gas concentration. The preset dynamic hazard threshold is adjusted according to the adjustment coefficient of the dynamic hazard threshold to obtain the dynamic hazard threshold of the second control area. Calculate the regional dispersion coefficient of the multiple risk control areas based on the center coordinates of the multiple risk control areas; Based on the regional dispersion coefficient, a control strategy for the target warehouse is formulated, specifically as follows: The region dispersion coefficient is compared with a preset region dispersion coefficient threshold. If the regional dispersion coefficient is greater than or equal to a preset regional dispersion coefficient threshold, then the control priority of the multiple risk control regions is determined based on the regional hazard coefficients of the multiple risk control regions. Based on the control priorities of the multiple risk control zones, a control strategy for the target warehouse is generated, specifically as follows: If the control priority of the first risk control area is greater than that of the second risk control area, then the regional risk coefficient of the first risk control area is first controlled to be less than its corresponding dynamic risk threshold before the second risk control area is controlled. The first risk control area and the second risk control area are any two of the multiple risk control areas. After comparing the regional dispersion coefficient with a preset regional dispersion coefficient threshold, the method further includes: If the regional dispersion coefficient is less than the preset regional dispersion coefficient threshold, then the maximum values ​​of multiple environmental parameters in multiple risk control regions are read to obtain multiple environmental parameters to be adjusted. Based on the deviation coefficients of multiple environmental parameters to be adjusted, the control priority of the multiple environmental parameters to be adjusted is determined. Specifically, the multiple environmental parameters to be adjusted are sorted in order from largest to smallest to obtain the control priority of the multiple environmental parameters to be adjusted. Based on the control priority of multiple environmental parameters to be adjusted, a control strategy for the target warehouse is generated, wherein the control strategy prioritizes correcting the environmental parameter with the most severe deviation. Multiple regulating devices are controlled to regulate the environment of the target warehouse according to the aforementioned regulation strategy.

2. The method according to claim 1, characterized in that, The calculation of the regional risk coefficient corresponding to each of the multiple control zones is specifically as follows: By integrating the parameters of multiple control regions, multiple environmental parameters corresponding to each of the multiple control regions are obtained; Based on multiple environmental parameters in the first control region, the deviation coefficients of multiple environmental parameters in the first control region are calculated, wherein the first control region is any one of the multiple control regions; Based on the preset static hazard weights of multiple environmental parameters, the deviation coefficients of multiple environmental parameters in the first control area are weighted and summed to obtain the regional hazard coefficient of the first control area.

3. The method according to claim 2, characterized in that, The step of weighted summing of the deviation coefficients of multiple environmental parameters in the first control region based on preset hazard weights of multiple environmental parameters to obtain the regional hazard coefficient of the first control region further includes: The concentration of harmful gas in the first control region is subtracted from the concentration of harmful gas in the adjacent control regions to obtain multiple concentration gradients. The dynamic risk weight of the first control region is determined based on the multiple concentration gradients. Based on the dynamic risk weight of the first control area, the regional risk coefficient of the first control area is adjusted to obtain the target area risk coefficient.

4. An adaptive control system for hazardous chemical storage environment, characterized in that, The system is used to implement an adaptive control method for a hazardous chemical storage environment as described in any one of claims 1-3. The system is a storage safety control system, comprising an acquisition module (1), a processing module (2), and a control module (3), wherein: The acquisition module (1) is used to collect multiple environmental parameters corresponding to multiple monitoring points of the target warehouse. The multiple environmental parameters of each monitoring point include temperature, humidity, concentration of harmful gases and light intensity. The processing module (2) is used to perform cluster analysis on the multiple monitoring points based on the multiple environmental parameters corresponding to each of the multiple monitoring points, and generate multiple control areas, wherein one monitoring point corresponds to one monitoring area; calculate the regional risk coefficient corresponding to each of the multiple control areas; determine multiple risk control areas from the multiple control areas according to a preset dynamic risk coefficient threshold; calculate the regional dispersion coefficient of the multiple risk control areas according to the center coordinates of the multiple risk control areas; and formulate the control strategy for the target warehouse according to the regional dispersion coefficient. The control module (3) is used to control multiple control devices to adjust the environment of the target warehouse according to the control strategy.

5. An electronic device, characterized in that, The device includes a processor (301), a memory (305), a user interface (303), and a network interface (304). The memory (305) is used to store instructions. The user interface (303) and the network interface (304) are used to communicate with other devices. The processor (301) is used to execute the instructions stored in the memory (305) to cause the electronic device (300) to perform the method as described in any one of claims 1 to 3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the method as described in any one of claims 1 to 3.

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