Paperboard folding storage box odor removal control system and method

Abstract

The invention discloses an odor removal control system and method for a paperboard folding storage box, and relates to the technical field of odor removal control, an occasion recognition module recognizes the category of a current application occasion through an environment recognition technology, corresponding reference values and boundary correction schemes are called according to different occasion categories, and a spread calculation module continuously collects various parameters in a cavity and calculates the odor of the paperboard folding storage box. The method comprises the following steps of: determining the situation of an occasion, calculating a breath spreading rate by fusing determined occasion attributes, marking a situation needing intervention if a certain parameter exceeds a corrected breath permissible limit corresponding to the occasion, and deducing an optimal odor removal action scheme under multiple limiting conditions by a scheme deduction module on the basis of the current marked situation situation and a multi-target planning function. The control module controls odor removal according to the optimal odor removal action scheme. According to the control system, closed-loop control and self-adaptive adjustment of multi-component linkage are achieved, peculiar smells can be restrained and eliminated on different occasions, and the storage quality of the paperboard folding storage box in a complex environment is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of odor control technology, specifically to an odor control system and method for cardboard folding storage boxes. Background Technology

[0002] In daily life and various storage scenarios, cardboard folding storage boxes are widely used because they are lightweight and highly malleable. However, their fibrous structure easily absorbs and retains odor molecules. Especially in enclosed storage environments or humid and moldy environments, the odor can spread quickly and cause secondary pollution, affecting the cleanliness and preservation quality of the stored items.

[0003] Traditional storage boxes lack the ability to perceive and dynamically regulate the odor state inside the cavity in real time. They rely mostly on passive ventilation or disposable adsorption materials, making it difficult to flexibly adjust the deodorization strategy according to the characteristics of different occasions and target needs. This results in unstable purification efficiency, poor energy consumption and noise control, and the regeneration of odors when the humidity is high.

[0004] Therefore, there is an urgent need for an intelligent control system that can comprehensively identify application scenarios, predict odor spread trends, and generate multi-objective optimized odor removal solutions to achieve precise, low-disturbance, and efficient odor removal management of cardboard folding storage boxes in complex environments. Summary of the Invention

[0005] The purpose of this invention is to provide a control system and method for removing odors from cardboard folding storage boxes, so as to solve the problems in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a cardboard folding storage box odor removal control system, comprising a registration module, an occasion identification module, a spread calculation module, a scheme deduction module, and a control module: Registration module: Enter the current values ​​of the storage cavity, and complete the initial registration by combining the adsorption saturation of the cardboard fiber with the background indicators of the environment. Set the tendency coefficient and permissible limit of the control target according to the usage requirements. Occasion Recognition Module: Identifies the current application occasion category through environmental recognition technology, calls up the corresponding reference values ​​and limit correction schemes for different occasion categories, and controls each functional component to be in a ready state; Spread Calculation Module: Continuously collects various parameters within the cavity and integrates the determined situation attributes to calculate the spread rate of the breath. If a parameter exceeds the corresponding corrected breath allowable limit for that situation, it is marked as a situation requiring intervention. Solution deduction module: Based on the current marked situation and multi-objective calculation function, the optimal odor removal action plan is deduced under multiple constraints; Control module: Controls odor removal according to the optimal odor removal action plan. During the removal process, it continuously tracks the rate of odor spread and concentration changes. If an abnormal spread is detected in a certain section, it increases the priority of treatment for that section and triggers the response of related components.

[0007] In a preferred embodiment, the propagation calculation module continuously acquires parameters such as the intensity of the air, the degree of humidity, the temperature level, and the gas flow rate within the cavity; The occasion category is converted into occasion feature identifier, and the occasion correction coefficient is appended to the normalized real-time parameters; Based on the preprocessed and fused multi-parameter parameter stream, the current rate of air spread within the cavity is calculated: The system calls upon the occasion identification module to provide the corrected permissible limits for the corresponding occasion, including limits for breath intensity, humidity, and heat level. The system then compares the real-time parameters with the corresponding limits one by one to analyze whether intervention is necessary.

[0008] In a preferred embodiment, the propagation estimation module estimates the current propagation rate of the air within the cavity based on a pre-processed and fused multi-parameter parameter stream containing contextual attributes, including the following steps: Calculate the spatial distribution gradient of each parameter, divide the cavity into several monitoring sub-regions, compare the numerical differences of adjacent sub-regions on the same parameter, and obtain the gradient direction and magnitude of concentration, humidity or temperature. By combining the direction and magnitude of gas flow velocity, assess the migration trend of air carried by the airflow; The gradient change amplitude and airflow velocity change within several sampling periods are taken to determine their growth momentum, and the increase weight is adjusted according to the occasion correction coefficient to obtain a comprehensive rate value that reflects the current air spread kinetic energy. If the intensity gradient of the air in a certain sub-region increases and the airflow direction is towards the center of that sub-region, and the environment is a closed environment, then it is marked as an accelerated spread trend.

[0009] In a preferred embodiment, the propagation estimation module calls the modified permissible air boundary corresponding to the occasion provided by the occasion identification module, and compares the real-time parameters with the corresponding boundaries one by one, including the following steps: For each parameter, determine whether its real-time value exceeds the limit range; If it exceeds the limit, check whether the spread rate of the parameter is accelerating to rule out misjudgment caused by occasional instantaneous fluctuations. When a parameter value exceeds the limit and the spread rate of the parameter indicates an increasing risk, the spatial segment or the overall cavity state where the parameter is located is marked as requiring intervention. The marking results include the type of parameter exceeding the limit, the extent of the exceedance, the location of the sub-regions involved, and the level of the spread trend.

[0010] In a preferred embodiment, the scheme deduction module maps the parameter status of each sub-region to a risk index, performs spatial clustering on the distribution of the same parameter in multiple sub-regions, and identifies areas of concentrated risk. Compare the difference in air intensity between adjacent sub-regions with the distance ratio, and select the sub-region with the largest gradient value and the risk index that meets the priority. Purification efficiency is quantified as the expected rate at which the air intensity in the target area is reduced to below the permissible limit within a specified time. The estimated score is obtained by simulating the parameter decay trend under different intervention measures. The sound and vibration control factor is quantified as the degree to which the noise and vibration levels generated by the adsorption unit and the ventilation guidance device are within acceptable limits during operation, and is mapped to a comfort score based on the component operating conditions and historical sound and vibration parameters. Based on the control tendency coefficient set in the registration module, the purification efficiency quantification and the estimated score of the sound and vibration control factor are combined into a comprehensive evaluation value according to their weights. When traversing the candidate combination of measures, the one with the best comprehensive evaluation value is selected as the preferred direction.

[0011] In a preferred embodiment, the scheme deduction module converts each constraint into a feasibility judgment rule, performs real-time verification when generating candidate schemes, and eliminates combinations that do not meet the conditions. Determine the coordinates or number of the area to be treated first, and adjust the operating intensity of the adsorption unit based on the risk characteristics of that area and the results of multi-objective calculations; plan the opening and closing method of the ventilation channel and the airflow direction.

[0012] In a preferred embodiment, the occasion identification module selects dimensions related to occasion attributes in a preset feature space, and normalizes these dimensions to make them comparable within the same dimension range. A pattern matching logic based on historical samples is introduced to compare the current feature vector with the labeled occasion category sample library, and the category with the highest matching degree is selected as the final judgment result. Retrieve the occasion category index from the parameter library, load the preset basic atmospheric intensity tolerance limit, humidity tolerance limit, and heat level tolerance limit under that category, obtain the correction coefficient group for that occasion, and define the dynamic adjustment range of the limit values ​​under different environmental background conditions.

[0013] In a preferred embodiment, the occasion identification module parses the component operation strategy template corresponding to the occasion. The template specifies the initial power consumption mode of the deodorization adsorption unit, the default gear of the ventilation guidance device, and the initial opening and closing degree parameters of the barrier sheet. After the control command is executed, each component feeds back status information to the occasion identification module to confirm that it has entered the preparation state.

[0014] In a preferred embodiment, the registration module calls an odor detection element, a humidity detector, a heat sensor, and an airflow meter to obtain the odor intensity, humidity level, heat level, gas flow speed, and odor spread rate indicators in the receiving cavity, respectively. The adsorption saturation of the cardboard fibers was read, and background indicators of the surrounding environment were collected, including ambient temperature, ambient humidity, ambient air pressure and background odor. Parse the descriptions of purification timeliness, noise tolerance, energy consumption limit speed preference in user instructions or scenario configuration files, and locate the tendency coefficient vector of preference distribution in the preset multi-dimensional preference space; Based on the occasion category and the initial state assessment results, the permissible odor limit is derived, the pre-configured basic limit value corresponding to the occasion is called, and then dynamically corrected according to the environmental background indicators and fiber adsorption saturation.

[0015] This application also provides a method for controlling odors in cardboard folding storage boxes, the method comprising the following steps: S1: Enter the current values ​​of the storage cavity, and complete the initial registration by combining the adsorption saturation of the cardboard fiber with the background indicators of the environment. Set the tendency coefficient and permissible limit of the control target according to the usage requirements. S2: Identify the current application scenario category through environmental recognition technology, call the corresponding reference values ​​and limit correction schemes for different scenario categories, and control each functional component to be in the ready state; S3: Continuously collect various parameters within the cavity and integrate the determined situation attributes to calculate the rate of air spread. If a parameter exceeds the corresponding corrected air allowable limit for that situation, it is marked as a situation requiring intervention. S4: Based on the current situation and multi-objective calculation function, the optimal odor removal action plan is derived under multiple constraints. S5: Control and remove odors according to the optimal odor removal action plan; S6: During the removal process, continuously track the rate of odor spread and concentration changes. If an abnormal spread is detected in a certain section, increase the priority of treatment for that section and trigger the response of related components.

[0016] The technical effects and advantages provided by the present invention in the above technical solution are as follows: By using environmental identification technology, the system automatically identifies application scenarios such as enclosed storage environments and humid, mold-prone environments, and calls upon matching reference values ​​and limit correction schemes to enable the system to adapt to changing environments. At the same time, it presets each functional component to an appropriate standby state, ensuring both immediate response and reducing unnecessary energy consumption.

[0017] By continuously acquiring intracavity parameters through odor detection elements, humidity detectors, heat sensors, and airflow meters, and integrating ambient attributes to calculate the odor spread rate in real time, and promptly marking situations requiring intervention when parameters exceed limits, the system can achieve proactive early warning and precise location of odor risks.

[0018] Based on the marked situation and a multi-objective calculation function that takes into account both purification efficiency and acoustic vibration control, the optimal deodorization action plan is generated under multiple constraints. The priority treatment areas, adsorption unit strength and ventilation channel operation mode are clearly defined, so that the deodorization process is both highly efficient and low-disturbance.

[0019] Following the optimal solution, the ventilation guidance device, movable barrier plate and adsorption unit work together, and continuously track the spread rate and concentration changes of odor during the treatment process. Once an abnormal spread is detected in a certain section, its treatment priority is increased and related components are triggered to respond, such as prompting the user to temporarily remove the item, effectively preventing the spread of odor and secondary odor. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0021] Figure 1 This is a framework diagram of the control system of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] Example 1: This example provides an odor removal control system for cardboard folding storage boxes. Please refer to [link / reference]. Figure 1 As shown, it includes a registration module, an occasion identification module, a propagation calculation module, a scheme simulation module, and a control module: Registration Module: Input key values ​​such as the current odor intensity, humidity, temperature, gas flow rate, and odor spread rate of the storage cavity, and complete the initial registration by combining the adsorption saturation of the cardboard fiber and the background indicators of the surrounding environment. Set the tendency coefficient (such as rapid purification tendency) and odor tolerance limit of the control target according to the usage requirements. The tendency coefficient and odor tolerance limit are sent to the spread calculation module, and the environmental information is sent to the occasion recognition module.

[0024] Occasion Identification Module: This module uses environmental recognition technology to identify the current application scenario category, such as a confined storage environment or a humid, mold-prone environment. For each scenario category, it calls upon corresponding reference values ​​and boundary correction schemes. During this stage, all functional components are placed in a standby state: the odor removal and adsorption unit remains on standby with low power consumption, the ventilation guidance device is on standby at a gentle setting, and the barrier is set to partially closed or moderately open according to scenario conventions. Simultaneously, past odor fluctuation records are loaded for trend prediction reference, and the identified scenario type is sent to the spread calculation module.

[0025] Spread estimation module: Using odor detection elements, humidity detectors, heat sensors and airflow meters, it continuously collects various parameters in the cavity and integrates the determined environment attributes to estimate the odor spread rate; once a parameter exceeds the allowable limit corresponding to the environment, it is marked as a situation that requires intervention, and the marking result is sent to the scheme estimation module.

[0026] Solution deduction module: Based on the current marked situation and multi-objective calculation function (combining air purification efficiency and sound vibration control factor), the optimal deodorization action plan is deduced under multiple constraints. The deodorization action plan includes identifying the parts that should be treated first (usually the area with the steepest air concentration gradient), adjusting the operating intensity of the adsorption unit, planning the opening and closing mode and flow direction of the ventilation channel, and sending the deodorization action plan to the control module.

[0027] Control Module: Based on the optimal deodorization action plan calculated in the previous steps, the module drives the ventilation guidance device to operate at a predetermined wind speed and path, controls the movable barrier to close or open specific sections to cut off the odor spread path, allows the adsorption unit to enter the calculated intensity, and, when necessary, coordinates with the environmental humidity control unit to reduce humidity in advance to prevent secondary odor generation. During the removal process, the module continuously tracks the odor spread rate and concentration changes. If an abnormal spread is detected in a certain section, the priority of treatment for that section is increased and related components are triggered (such as prompting the user to temporarily remove items from the area), forming a multi-component collaborative operation mode. Once all key parameters return to the stable range corresponding to the situation and the odor concentration is stably below the limit, the module switches to a gradual recovery mode: gradually reducing the intensity of the adsorption unit and the ventilation rate, reducing the frequency of auxiliary mode use, and maintaining only minimal monitoring to prevent recurrence.

[0028] Example 2: This example provides a method for controlling odors in cardboard folding storage boxes. The method includes the following steps: The system is given basic operating conditions. Key values ​​such as current odor intensity, humidity, temperature, gas flow rate, and odor diffusion speed within the storage chamber are entered, and initial registration is completed by combining the adsorption saturation of the cardboard fibers with background indicators of the surrounding environment. Subsequently, based on usage requirements, the tendency coefficient of the control target (e.g., rapid purification tendency) and the permissible odor limits are set. Environmental identification technology is used to determine the current application scenario, such as a sealed storage environment or a humid, mold-prone environment, and corresponding reference values ​​and limit correction schemes are applied for different scenario categories. All functional components are placed in a ready state at this stage. The odor removal and adsorption unit remains on standby with low power consumption, the ventilation guidance device is on standby at a gentle setting, and the barrier is set to partially closed or moderately open according to the occasion, while loading past odor fluctuation records for reference in trend prediction.

[0029] Using odor detection elements, humidity detectors, heat sensors, and airflow meters, various parameters within the cavity are continuously collected, and the odor diffusion rate is calculated by integrating the determined environment attributes. Once a parameter exceeds the permissible limit corresponding to that environment, it is marked as a situation requiring intervention. Based on the current marked situation and a multi-objective calculation function (considering both odor purification efficiency and acoustic vibration control factors), the optimal odor removal action plan is derived under multiple constraints. Identify the areas that should be addressed first (usually the region with the steepest gas concentration gradient), adjust the operating intensity of the adsorption unit, and plan the opening and closing methods and flow direction of the ventilation channels. This application innovatively incorporates comprehensive analysis across different scenarios and flexibly adjusts the permissible gas limits and operating parameters of each component according to real-time trends, enabling the strategy to have self-adaptive capabilities across different scenarios.

[0030] Based on the optimal odor removal plan calculated previously, the ventilation and guidance device operates at a predetermined wind speed and path. Movable baffles are controlled to close or open specific sections to cut off the odor spread path, allowing the adsorption unit to reach its calculated intensity. When necessary, it coordinates with the environmental humidity control unit to reduce humidity and prevent secondary odor generation. During the removal process, the odor spread rate and concentration changes are continuously monitored. If abnormal spread is detected in a certain section, the priority for treatment in that area is increased, triggering responses from related components (such as prompting the user to temporarily remove items from the area), forming a multi-component collaborative operation. Once all key parameters return to the stable range corresponding to the situation and the odor concentration is consistently below the limit, a gradual recovery mode is entered. Gradually reduce the intensity of the adsorption unit and the ventilation rate, reduce the frequency of auxiliary methods, and maintain only the minimum monitoring to prevent recurrence.

[0031] Example 3: This example details the specific functional steps of each module in this application: Furthermore, the registration module utilizes sensing components such as odor detection elements, humidity detectors, heat sensors, and airflow meters to acquire key indicators within the receiving cavity, including odor intensity, humidity level, heat level, gas flow velocity, and odor diffusion speed. Odor intensity is obtained by detecting the cumulative concentration of characteristic odor molecules in the air, typically expressed as a graded quantification value, such as mapping concentration ranges to several levels to accommodate subsequent comparison calculations. Humidity level is derived from relative humidity sensor readings after smoothing and filtering to reflect the moisture content of the fiber surface and the air within the cavity. Heat level is taken from the real-time average value of a temperature sensor and can be combined with short-term fluctuation amplitudes to assess thermal field stability. Gas flow velocity is measured by a flow meter to obtain the volumetric flow rate and converted into the average flow velocity within the cavity. The odor diffusion speed is inferred through time window statistical analysis of historical concentration gradient change rates, such as observing the ratio of the distance traveled by the concentration isopleths to the time over the past few minutes, thus characterizing the diffusion kinetic energy.

[0032] Furthermore, after obtaining the aforementioned real-time values, the adsorption saturation status of the cardboard fibers is read. This parameter can be derived from an indirect estimation of the degree of adsorption capacity decay of the fiber material, for example, by comparing the cumulative adsorption time, the total amount of treated odor, and the material's calibrated saturation threshold to output a saturation ratio index. Simultaneously, background indicators of the surrounding environment are collected, including ambient temperature, humidity, air pressure, and background odor. These indicators can be provided by external environmental monitoring nodes or built-in auxiliary sensors. The real-time cavity values ​​are correlated and mapped with the fiber adsorption state and environmental background parameters to form a unified initial state vector, which is used to characterize the current starting point of odor control. This process employs a step-by-step normalization and weighted synthesis processing logic, that is, first converting various values ​​into relative scores under a unified dimension, and then linearly superimposing them according to their preset weights on odor control to obtain the overall initial state assessment result, avoiding the dominance of a single indicator bias in the judgment.

[0033] Furthermore, based on usage requirements, it supports setting bias coefficients for control targets, such as a high response coefficient biased towards rapid purification or a robust coefficient biased towards low noise and energy saving. (Borrow coefficient setting) First, the descriptions of preferences such as purification timeliness, noise tolerance, and energy consumption limits in user instructions or scenario configuration files are parsed and converted into calculable preference scores. Then, the tendency coefficient vector that is closest to the preference distribution is located in the preset multi-dimensional preference space, and each dimension of the vector corresponds to the weight ratio of different control objectives.

[0034] Suppose a user specifies in the scenario configuration file that they need to reduce odor concentration in the shortest possible time, allowing for a slight increase in noise and energy consumption. When parsing this instruction, the system first maps the reduction of odor concentration in the shortest possible time to a high purification timeliness preference score, maps the allowance for a slight increase in noise to a medium-to-high noise tolerance score, and maps the allowance for a slight increase in energy consumption to a low energy consumption limit score. Then, in a multi-dimensional preference space, within a three-dimensional space composed of the three axes of purification timeliness, noise tolerance, and energy consumption limit, the system finds the tendency coefficient vector with the closest Euclidean distance to the distribution points formed by this set of preference scores. For example, if the vector has a purification timeliness weight of 60%, a noise control weight of 25%, and an energy consumption control weight of 15%, this vector is the high response coefficient scheme, meaning that subsequent scheme deduction and resource scheduling will prioritize ensuring rapid purification effect, even if it results in a certain increase in noise or energy consumption, which is acceptable.

[0035] Furthermore, based on the occasion category and the initial state assessment results, the permissible air quality limits are derived as follows: The system calls the pre-configured baseline limit value for the specific situation and then dynamically adjusts it based on environmental background indicators and fiber adsorption saturation. For example, it tightens the humidity limit in a high humidity environment or lowers the odor intensity limit when adsorption is close to saturation, to ensure that the set allowable range matches the actual risk.

[0036] Taking a damp, mold-prone environment as an example, the system calls upon the preset basic humidity limit of 70% relative humidity for that setting. If the environmental background indicators show that the current ambient humidity has reached 80% and the trend continues to rise, then according to the dynamic correction logic, the humidity limit is tightened to 65% to prevent the humidity inside the cavity from easily triggering mold growth. At the same time, if the initial state assessment results show that the adsorption saturation ratio of the cardboard fibers has reached 85%, the system further determines that the adsorption margin is limited. To avoid the accumulation of odor molecules on the fiber surface, the odor intensity limit is lowered from the basic concentration level of 50 to 40. This corrected allowable range is more in line with the actual risk, with stricter humidity control in high humidity environments and stricter control of odor concentration when adsorption is close to saturation. This ensures that the system will not miss cases when intervention is required due to excessively high limit settings, improving the timeliness and effectiveness of treatment.

[0037] Furthermore, after calculating the tendency coefficient and the permissible odor limit, these are packaged into a control strategy initialization parameter package and sent to the spread estimation module as the threshold basis for subsequent spread rate determination and intervention decisions. Simultaneously, environmental information (including background temperature and humidity, air pressure, background odor, etc.) is separately packaged and sent to the occasion identification module for occasion category identification and corresponding reference value retrieval. The entire registration process emphasizes the timeliness and consistency of parameters. All data collection actions are completed synchronously within a short time window, and abnormal jump values ​​are eliminated through a verification mechanism to ensure the accuracy and repeatability of the initial registration, thereby laying a solid parameter and strategy foundation for subsequent odor spread estimation and scheme simulation.

[0038] Furthermore, the occasion recognition module receives environmental information parameter packages from the registration module, including external environmental parameters such as temperature, relative humidity, air pressure, background odor, and possible auxiliary sensing parameters such as light and vibration. Simultaneously, the occasion recognition module can call upon its own configured auxiliary sensors (such as independent environmental temperature and humidity probes and odor background samplers) for synchronous measurement to eliminate transmission delays or single-point errors, forming a multi-dimensional set of environmental parameters. All parameters undergo time-series alignment and anomaly removal processing before being input into the classification stage. For example, values ​​from different sampling times are rearranged according to a unified timestamp, and readings that suddenly deviate from the normal range are verified for reasonableness, with the average of nearby time periods used as a substitute if necessary.

[0039] Furthermore, the occasion recognition module performs feature extraction based on the acquired set of environmental parameters, and the processing is as follows: First, dimensions highly correlated with the occasion's attributes are selected from the pre-defined feature space. For example, the degree of airtightness can be indirectly reflected by the ratio of gas exchange rate to ambient wind speed, while the tendency to be damp is assessed by the dew point margin, which is jointly determined by ambient relative humidity and temperature. These dimensions are then normalized to ensure comparability within the same dimensional range. Classification is achieved using a hybrid approach of rule-based and empirical models: initially, threshold rules accumulated through industry or experiments are used for preliminary classification. For instance, when the ambient relative humidity consistently exceeds a certain limit and the temperature is within a mold-prone range, it is initially classified as a damp and mold-prone environment; when the environment is highly airtight and ventilation is limited, it is initially classified as a closed storage environment. To further reduce misjudgments, pattern matching logic based on historical samples is introduced. The current feature vector is compared with a library of labeled occasion categories for similarity, and the category with the highest matching degree is selected as the final judgment result. Simultaneously, a judgment confidence score is output for subsequent decision-making reference. For example, if the current relative humidity is 85%, the temperature is 26 degrees Celsius, and the background airflow is extremely low, the rule indicates a humid and moldy environment. If the pattern matching result has a similarity of more than 90% with this type of sample, the classification can be confirmed.

[0040] Furthermore, based on the determined occasion category, the occasion recognition module retrieves the corresponding set of reference values ​​and boundary correction schemes from its built-in occasion parameter library. Specifically: The system retrieves the occasion category index from the parameter library, loads the preset allowable limits for basic odor intensity, humidity, and heat levels under that category, and obtains a set of correction coefficients specific to that occasion. These coefficients define the dynamic adjustment range of the limit values ​​under different environmental background conditions. For example, for humid and mold-prone environments, the humidity limit will be further tightened when the ambient humidity is high to reduce the risk of mold growth; for enclosed storage environments, the odor intensity limit may be appropriately reduced to account for the cumulative effect of low ventilation rates. The calling process ensures that the parameter version is synchronized with the occasion classification version to avoid using outdated or incompatible standards. For example, if the occasion identification module determines that the current environment is humid and prone to mold, it will retrieve the humid and prone to mold environment category index from the built-in occasion parameter library, load the preset basic odor intensity tolerance limit of this category as concentration level 45, basic humidity tolerance limit as relative humidity 70%, and basic temperature tolerance limit as 32℃; at the same time, it will obtain the correction coefficient group specific to this occasion, where the humidity correction coefficient stipulates that when the ambient humidity is higher than 75%, the limit value is tightened by 5 percentage points, and the odor intensity correction coefficient stipulates that when the ambient humidity is higher than 75% and the temperature is higher than 28℃, the limit value is further reduced by 3 concentration levels. Assuming the current environmental background indicators show an ambient humidity of 82% and a temperature of 29°C, the system will tighten the allowable humidity limit from 70% to 65% and the allowable odor intensity limit from 45 to 42 based on the correction factor, in order to more strictly control humidity and odor concentration and reduce the risk of mold and odor accumulation. If the occasion classification version is updated to V2.1, the parameter library will also load the corresponding parameters of version V2.1 to ensure that the standards used are consistent with the latest occasion classification and avoid the possibility of overly broad limits or strategy mismatch caused by old parameters.

[0041] Furthermore, the occasion identification module issues preliminary control commands to each functional component based on the occasion category and correction scheme: The system analyzes the corresponding component operation strategy template for this scenario. The template specifies parameters such as the initial power consumption mode of the odor-absorbing unit, the default setting of the ventilation guiding device, and the initial opening / closing degree of the barrier plate. For the odor-absorbing unit, in a sealed storage environment, it can be set to a medium standby adsorption capacity to ensure it is always available; in a humid and mold-prone environment, it is set to low power consumption standby while maintaining a high response to moisture sensitivity. The ventilation guiding device is set to a gentle setting in a sealed environment to avoid abrupt airflow disturbing items; in a humid environment, the preparatory airflow speed can be appropriately increased to facilitate moisture removal. The barrier plate is set to partially closed according to scenario conventions to maintain necessary isolation or to allow for appropriate communication when slow ventilation is needed. After the control command is executed, each component feeds back status information to the scenario identification module to confirm that it has entered the standby state.

[0042] Furthermore, the occasion identification module retrieves historical odor monitoring records from long-term storage that are similar to the occasion category and the current environmental background: Record sets are filtered by occasion tags and time proximity, and the variation curves of odor intensity, humidity, heat level, and spread rate are extracted. Trend features are then abstracted, such as extracting periodic fluctuation cycles, common peak occurrence periods, and amplitude ranges. These historical trend features will be combined with real-time parameters to enhance the spread prediction module's ability to predict potential abnormal trends.

[0043] Furthermore, the propagation estimation module continuously acquires raw parameters such as odor intensity, humidity, temperature, and gas flow velocity within the cavity at a fixed sampling period (e.g., once per second) using an odor detection element, a humidity detector, a heat sensor, and a gas flow meter. The collected parameters undergo preprocessing before entering the estimation stage. First, time synchronization is performed, arranging all sensor readings according to a unified timestamp. Then, noise filtering is executed, using methods such as sliding window mean or median filtering to smooth short-term fluctuations and reduce the impact of random interference on trend judgment. Next, missing values ​​are filled; if a parameter is missing due to a brief communication interruption, it is reasonably estimated and filled based on the linear trend of adjacent periods. Furthermore, to eliminate the impact of differences in physical dimensions on subsequent fusion analysis, each parameter needs to be normalized, mapping it to the same relative scoring range; for example, the odor intensity is converted into a score from 0 to 100 based on concentration levels.

[0044] Furthermore, the propagation estimation module receives the determined occasion categories and their corresponding reference values ​​and boundary correction schemes from the occasion identification module, and incorporates these occasion attributes as background constraints for estimation into the parameter processing flow: The process transforms the environment categories into a set of environment characteristic identifiers (e.g., low ventilation rate for enclosed storage environments, high humidity sensitivity for damp and moldy environments), and applies environment-specific correction coefficients to the normalized real-time parameters to reflect the amplification or inhibition effect of the environment on odor parameters. For example, in damp and moldy environments, the weight of the humidity parameter is increased because its impact on odor growth and spread is more significant; in enclosed storage environments, the cumulative effect of odor intensity is additionally taken into account. This process ensures that subsequent spread rate calculations reflect the dynamic characteristics brought about by environment differences.

[0045] Furthermore, the propagation estimation module, based on a pre-processed and fused multi-parameter parameter stream with contextual attributes, estimates the current propagation rate of the air within the cavity: First, calculate the spatial distribution gradient of each parameter. For example, divide the cavity into several monitoring sub-regions and compare the numerical differences of adjacent sub-regions on the same parameter to obtain the gradient direction and magnitude of concentration, humidity, or temperature. Then, combine the direction and magnitude of gas flow velocity to assess the migration trend of the gas carried by the airflow. The calculation of the spread rate comprehensively considers three factors: the parameter gradient change rate, the airflow delivery capacity, and the environment characteristics correction. Specifically, a time-series-based trend extrapolation logic can be used: take the gradient change amplitude and airflow velocity change in the most recent sampling periods, determine its growth momentum, and adjust the increase weight according to the environment correction coefficient to obtain a comprehensive rate value reflecting the current gas spread momentum. This rate value can be presented using relative levels or trend descriptions (such as slow spread, accelerated spread, stable spread) for easy subsequent rapid judgment. For example, if the gas intensity gradient in a certain sub-region increases significantly in a short period of time and the airflow direction points towards the center of the region, and the environment is a closed environment causing slow dissipation, the calculated spread rate will be high and marked as an accelerated spread trend. The cavity was divided into 25 monitoring sub-zones (5×5). The propagation calculation module sampled the gas intensity of sub-zone A and its eastern and southern adjacent sub-zones. The current period's gas intensity for sub-zone A was 78 (normalized concentration level), while the eastern sub-zone was 62 and the southern sub-zone was 58. The difference in gas intensity gradient was 16 in the east and 20 in the south, indicating a gradient primarily pointing southeast with a significant amplitude. Combined with the airflow velocity measured by the airflow meter at 0.18 m / s, pointing from northwest to southeast, covering the center of sub-zone A, this suggests that the airflow would transport gas from high-concentration areas to this sub-zone. The module took the gradient change amplitude over the most recent four sampling periods (1 second per period), finding that the eastward gradient increased from 12 to 16 and the southward gradient from 15 to 20, showing a continuous increase; the airflow velocity also increased from 0.14 to 0.18 m / s, indicating an enhanced transport capacity. The environment identification module determines that the current environment is a closed storage environment. Its environment correction coefficient stipulates that the weights of the gradient and airflow velocity increases are both multiplied by 1.3 under closed conditions to reflect the slow dissipation effect caused by low ventilation rates. Therefore, the parameter gradient change rate is increased by 30% after weight adjustment, and the airflow transport capacity increase is also increased by 30%. The combined calculation shows that the overall gas diffusion rate of this sub-region is at a high level, described as accelerating diffusion. Thus, this sub-region is marked as requiring intervention, and the subsequent scheme deduction module can prioritize the allocation of adsorption and ventilation resources accordingly.

[0046] Furthermore, the propagation estimation module calls the occasion identification module to provide the corrected permissible air limits (including air intensity limits, humidity limits, heat level limits, etc.) corresponding to the occasion, and compares the real-time parameters with the corresponding limits one by one: For each key parameter, its real-time value is checked to see if it exceeds the limit range. If it does, the spread rate of the parameter is further examined to see if it shows an upward or accelerating trend, in order to rule out misjudgments caused by occasional instantaneous fluctuations. Only when the parameter value exceeds the limit and the spread rate of the parameter indicates an increasing risk is the spatial segment or overall cavity state where the parameter is located marked as requiring intervention. The marking results may include the type of parameter exceeding the limit, the extent of the exceedance, the location of the sub-region involved, and the level of spread trend. This information will constitute the triggering basis for intervention decisions. For example, if the humidity level exceeds the limit in a certain sub-region and the humidity spread rate in that region shows an increasing trend, then that sub-region is marked as a priority intervention target. Assuming the current environment is humid and prone to mold, the following permissible limits for odors are provided after correction: odor intensity limit is concentration level 42, humidity limit is relative humidity 65%, and temperature limit is 31℃. In a certain sampling period, the spread estimation module detected a real-time humidity level of 68% in sub-region B, exceeding the limit by 3 percentage points; the real-time odor intensity was 40, below the intensity limit; and the temperature level was 29℃, below the temperature limit. Upon comparison, the system detected the humidity exceeding the limits and further retrieved humidity spread rate data for the sub-region over the past four periods (1 second per period): the humidity gradient increase was 0.5% / s in period 1, 0.7% / s in period 2, 1.0% / s in period 3, and 1.4% / s in period 4. The increase is continuously rising, and the current rate is significantly higher than the initial value. After adjusting for the environment using a correction coefficient (the weight of the humidity spread rate increase in a humid environment is multiplied by 1.2), it is determined that the humidity spread rate in this area is increasing. Because this sub-area not only exceeded the humidity limit but also showed an increasing risk of spread, it was marked as requiring intervention. The marking results included the following parameters: humidity level (type of exceeding the limit), magnitude of exceeding the limit (+3% relative humidity), location of sub-area B involved, and increasing spread trend level. This information will serve as the trigger for the solution simulation module, causing it to prioritize sub-area B when generating the odor removal action plan and specifically strengthen dehumidification and adsorption measures in this area, thereby effectively suppressing further increases in humidity and the potential risk of mold growth.

[0047] Furthermore, the scheme simulation module receives the marked results from the spread calculation module, analyzes the information contained therein, such as the type of boundary crossing parameter, the magnitude of the boundary crossing, the location of the involved sub-regions, and the level of spread trend, and combines it with real-time collected snapshot parameters such as cavity air intensity, humidity, heat level, and gas flow velocity to construct a current problem situation model: The parameter states of each sub-region are mapped to risk indices. For example, sub-regions with excessive fumes and high spread rates are assigned higher risk values. Spatial clustering is performed on the distribution of the same parameter across multiple sub-regions to identify areas of concentrated risk. Based on this, the region with the steepest fumes concentration gradient is extracted as a candidate for priority treatment. The decision logic is: compare the difference in fumes intensity between adjacent sub-regions with the distance ratio, and select the sub-region with the largest gradient value and a risk index that meets the priority criteria. For example, if the difference in fumes intensity between the upper right corner sub-region and its neighboring sub-regions is significantly higher than in other regions, and this region has been marked as having excessive humidity and showing an accelerating spread trend, then this region is identified as a priority treatment site. The scenario simulation module received the labeled results from the spread prediction module, indicating that sub-region E (located in the upper right corner of the cavity) had an air intensity exceeding the limit by +6 (real-time value 48, correction limit 42), a humidity exceeding the limit by +4% (real-time 68%, limit 64%), and a spread trend level of accelerated spread. Simultaneously, the module acquired real-time snapshot parameters for sub-region E: air intensity 48, humidity 68%, temperature 30℃, and gas flow velocity 0.22m / s. The module first mapped the parameter states of each sub-region to a risk index. An air intensity exceeding the limit and an accelerated spread trend were assigned a risk value of 80; a humidity exceeding the limit and an accelerated spread trend were assigned a risk value of 75; and temperatures and airflow not exceeding the limits were assigned a base value of 20. The total risk index for sub-region E was 80 + 75 + 20 = 175, classifying it as a high-risk sub-region. Subsequently, spatial clustering of the air intensity parameters across all sub-regions was performed. It was found that the intensity values ​​in the upper right corner region (including sub-region E and its north and east neighboring regions) were generally higher than other regions, forming a high-intensity cluster, which was identified as a concentrated risk area. Based on this, the region with the steepest atmospheric concentration gradient was extracted: The difference between sub-region E and its eastern neighbor F (atmosphere intensity 36) and northern neighbor G (atmosphere intensity 34) was compared. The eastward gradient = (48-36) / 1 grid = 12, and the northward gradient = (48-34) / 1 grid = 14, with a distance of 1 grid for both. The calculated gradient values ​​were 12 and 14 respectively. Sub-region G, while not crossing the boundary, had the largest northward gradient and was located on the edge of the same high-value cluster. Sub-region E, on the other hand, not only had a large gradient but also the highest risk index and exhibited dual boundary-crossing attributes. Therefore, the decision logic selected sub-region E as the region with the steepest atmospheric concentration gradient and the highest risk priority, i.e., the candidate for initial treatment. This result will be clearly defined as the target intervention area in subsequent plans, prioritizing the allocation of high-intensity adsorption units and directional ventilation resources to quickly curb the accelerated spread of atmospheric and humidity in this area.

[0048] Furthermore, based on the current marked situation, the scheme deduction module introduces a multi-objective calculation function to evaluate and weigh the schemes. This function takes into account both the air purification efficiency and the acoustic vibration control factor. Purification efficiency is quantified as the rate at which the air intensity in the target area is reduced to below the allowable limit within a specified time. An estimated score can be obtained by simulating the parameter decay trend under different intervention measures. The sound and vibration control factor is quantified as the degree to which the noise and vibration levels generated by the adsorption unit and ventilation guidance device are within acceptable limits. It can be mapped to a comfort score based on component operating conditions and historical sound and vibration parameters. The application of the function does not directly seek the extreme value, but rather constructs a target weight space: based on the control tendency coefficients set by the registration module (e.g., rapid purification tendency increases the weight of purification efficiency, and low-noise and energy-saving tendency increases the weight of sound and vibration control), the estimated scores of the two targets are combined into a comprehensive evaluation value according to their weights. When traversing candidate combinations of measures, the one with the best comprehensive evaluation value is selected as the preferred direction. For example, when the tendency coefficient is rapid purification, even if a certain scheme has slightly higher sound and vibration, as long as it can significantly reduce the air intensity in a shorter time, a higher comprehensive evaluation value can be obtained. Assuming the received status indicator shows an odor intensity of 48 in sub-area C, exceeding the corrected allowable limit of 42 for humid and moldy environments, and with an accelerating spread trend, it needs to be addressed within 5 minutes. The module first simulates the parameter decay trends of three candidate intervention measures: Option 1 uses a high-intensity adsorption unit (power level 9) in sub-area C, with a ventilation guide device directly discharging at a wind speed of 2.5 m / s. The odor intensity is expected to drop to 39 within 5 minutes, a high probability and fast achievement, with a predicted purification efficiency score of 92. However, under this condition, the noise from the adsorption unit and the fan is superimposed, and historical acoustic and vibration data show a comfort level of 62. Option 2 uses a medium-intensity adsorption unit (power level 6) with a wind speed of 1.8 m / s. The odor intensity is expected to drop to 43 within 5 minutes, still slightly exceeding the limit, with a predicted purification efficiency score of 76 and improved acoustic and vibration comfort to 88. Option 3 uses low-intensity adsorption (power level 4) with a wind speed of 1.2 m / s. The odor intensity is expected to drop to 46 within 5 minutes, with a predicted purification efficiency score of only 58, but an acoustic and vibration comfort level as high as 95. At this point, the control tendency coefficient set in the registration module is rapid purification (purification efficiency weight 70%, sound and vibration control weight 30%). The module constructs a target weight space and synthesizes the two scores of each scheme into a comprehensive evaluation value according to their weights: Scheme 1 comprehensive evaluation value = 92 × 0.7 + 62 × 0.3 = 82.4, Scheme 2 = 76 × 0.7 + 88 × 0.3 = 79.6, Scheme 3 = 58 × 0.7 + 95 × 0.3 = 69.1. The traversal results show that Scheme 1 has the highest comprehensive evaluation value, so it is selected as the preferred direction. Even though its sound and vibration are slightly higher, under the rapid purification tendency, its higher purification efficiency can bring the intensity of C odor in sub-region back below the allowable limit in a short period of time, thereby achieving the goal of rapid risk suppression.

[0049] Furthermore, the scheme simulation module incorporates multiple operational constraints to limit the feasible solution space. These constraints include: physical capacity limitations of components (such as the maximum and minimum action intensity of the adsorption unit, and the upper and lower limits of the wind speed of the ventilation guiding device), cavity structure constraints (such as the inability to change the position of the baffle plate in certain sections due to the placement of items), energy consumption limits (especially in battery-powered mode), and safety regulations (such as avoiding forced high-speed airflow that could cause dust or disturbance in high-humidity environments). Each constraint is transformed into a Boolean or quantifiable feasibility judgment rule, which is then validated in real time during candidate solution generation, eliminating combinations that do not meet the conditions. For example, if a candidate solution requires the adsorption unit to operate at full load for a long period in a closed environment, and this mode would exceed the energy consumption limit, then the solution is directly excluded. When generating candidate odor removal schemes for sub-region D, multiple operational constraints need to be verified: the adsorption unit's operating intensity range is power level 3 to 10, and the allowable wind speed range for the ventilation guiding device is 0.8. m / s to 3.0 m / s, the cavity structure constraints indicate that the position of the barrier plate on the right side of sub-area D cannot be changed due to the placement of fragile containers. The current system is in battery-powered mode and the energy consumption limit is set to a total power consumption of no more than 120 units for 10 consecutive minutes. Safety regulations require that the ventilation velocity not exceed 2.0 m / s in high humidity environments (relative humidity > 75%). To prevent dust from flying, candidate scheme four proposes that the adsorption unit in sub-region D adopt a power level of 10 (full load) and the ventilation guiding device wind speed be set to 2.8 m / s. m / s, and adjust the opening of the baffle plate on the right side of sub-region D to enhance exhaust ventilation. Feasibility assessments were performed on each module: ① If the adsorption unit power is within the allowable range of 3 to 10, it is considered qualified by Boolean. ② Wind speed 2.8 The speed exceeds the safety limit of 2.0 m / s for high humidity environments. m / s, is deemed unqualified; ③ The alteration of the position of the right-side baffle violates the constraints of the cavity structure and is therefore deemed unqualified; ④ Regarding energy consumption, the unit power consumption of power level 10 for 10 minutes is 130, which exceeds the battery mode energy consumption limit of 120, and is therefore deemed unqualified.

[0050] Due to multiple failures in Boolean-type criteria, this scheme was directly eliminated during real-time verification and was not included in the subsequent comprehensive evaluation value calculation. Conversely, candidate scheme five sets the adsorption unit power to 8 and the wind speed to 1.9. The solution operates at m / s without altering the position of the right-side barrier. Verification has shown that it fully meets the physical capabilities, cavity structure, energy consumption, and safety specifications of the components. Therefore, it is retained as a feasible solution to continue participating in multi-objective calculations and optimization, ensuring that the generated deodorization action plan can achieve the purification goal while remaining safe and reliable within the system's operating boundaries.

[0051] Furthermore, based on the evaluation of the objective function and the filtering of constraints, the solution derivation module generates action plans: First, determine the specific coordinates or number of the area to be treated first; second, based on the risk characteristics and multi-objective calculation results of this area, adjust the operating intensity of the adsorption unit (e.g., use high-intensity adsorption in high-risk, high-humidity areas to rapidly reduce humidity and odor molecule concentration); third, plan the opening and closing methods of the ventilation channels (e.g., close the channels leading to low-risk areas to prevent odor diffusion, and open low-disturbance air paths from high-risk areas to guide exhaust) and airflow direction (prioritize airflow from high-risk areas to low-concentration areas or exhaust outlets). After generation, one or more rounds of local optimization can be performed, specifically: While keeping the primary treatment area unchanged, fine-tune the adsorption intensity distribution or airflow layout, and observe whether the overall evaluation value further improves. If so, adopt the optimized result. For example, if the airflow direction in the initial plan can remove odors but causes the acoustic vibration of another sub-zone to exceed the standard, adjusting the opening of the airflow branches or changing the flow path can reduce the acoustic vibration score while maintaining purification efficiency, thereby optimizing the overall plan.

[0052] Furthermore, the control module receives the structured action plan from the scheme deduction module and analyzes key information such as priority treatment location identifiers, target effect intensity of adsorption units in each sub-region, ventilation channel opening and closing status table and airflow direction vector, and expected execution sequence suggestions: The process involves mapping component identifiers to actual control coordinates or channel numbers; converting adsorption unit intensity values ​​into power or speed command levels recognizable by the equipment; synthesizing channel opening / closing states and flow direction vectors into damper control codes and fan rotation parameters; and simultaneously decomposing timing suggestions into phased execution queues to ensure that each component operates in a predetermined order and rhythm. This process requires command validity verification, such as checking whether the target intensity is within the hardware limits of the adsorption unit and whether duct switching will cause structural interference. If any irregularities are found, an internal alarm is triggered, and the solution simulation module is requested to regenerate a feasible solution.

[0053] Furthermore, according to the execution queue obtained from the analysis, the control module sequentially drives each functional component to enter the working state: the ventilation guiding device operates according to the predetermined wind speed and path, sets the fan speed level and guide vane angle according to the airflow direction vector, so that the airflow flows from the high-risk area to the emission port or low-concentration area along the designed path, and adopts a gradual acceleration during the start-up phase to avoid dust or noise impact caused by sudden airflow changes; the movable baffle closes or opens specific sections according to the channel opening and closing status table, positions the movable baffle driving mechanism of the corresponding section, executes the closing action to cut off the air spread path, or guides the airflow when necessary. The system communicates appropriately according to the set opening degree, while ensuring no gaps or leaks occur during operation. The adsorption unit enters the calculated intensity level, adjusting the motor speed or heating power (if it is heat-assisted adsorption) according to the target intensity level. In the case of multiple sub-zones, it implements zoned intensity allocation to concentrate resources on priority treatment areas. When the scheme requires dehumidification to prevent secondary odor generation, the environmental humidity control unit and the adsorption unit start in conjunction. The humidity control unit runs the dehumidification program first to reduce the relative humidity in the cavity to a safe threshold before the adsorption unit focuses on removing odor molecules, thereby avoiding the adsorption material from becoming saturated too quickly or mold growth under high humidity conditions. While executing commands, each component sends status feedback (such as actual wind speed, baffle position, adsorption power, and humidity reading) back to the control module for subsequent process tracking.

[0054] Furthermore, during the odor removal process, the control module continuously receives updated odor spread rate and concentration change parameters from the spread estimation module and compares them with the target trajectory set in the plan. For each sub-zone, the deviation of the current spread rate from the initial estimated value is calculated in real time. If the spread rate in a certain section accelerates abnormally (e.g., the gradient increase exceeds the preset warning ratio in a short period) or the concentration rebounds to near the limit, it is determined that an abnormal spread has occurred in that area. At this time, the module increases the priority of handling that area, increases the corresponding adsorption intensity weight and ventilation volume ratio in the internal scheduling table, and triggers the response strategies of related components. For example, it instructs the adsorption unit in that area to temporarily switch to the highest intensity, increases the opening and wind speed of the corresponding air duct in that area, and simultaneously informs the user to temporarily remove items from the area via the human-machine interface or through prompts to reduce the adsorption of odors on the surface of items or obstruction of airflow. This process forms a multi-component collaborative operation: the ventilation guidance device, barrier plate, adsorption unit, and humidity control unit adjust their operating conditions in conjunction with the abnormal area information, thereby curbing the spread and preventing the diffusion of secondary pollution.

[0055] Specifically, the module continuously monitors all key parameters (smell intensity, humidity, heat level, and gas flow rate) to ensure they return to the stable range corresponding to the given situation, and confirms that the smell concentration is consistently below the corrected tolerance limit. A sliding window statistical method is used to calculate the mean and fluctuation range of each parameter. If the mean parameter remains within the stable range and the fluctuation is less than the set tolerance for multiple consecutive sampling periods, and the smell concentration shows no signs of rebounding, the task is considered accomplished. Afterward, a gradual recovery mode is implemented: the adsorption unit's intensity and ventilation rate are gradually reduced, and the power or wind speed setpoints are decreased in stages, maintaining each stage for a certain period to observe parameter stability and avoid concentration rebound due to sudden drops; the frequency of auxiliary methods (such as the humidity control unit) is reduced, only briefly activated when the humidity monitoring value approaches the upper limit; finally, only minimal monitoring is maintained (such as reducing the sampling frequency and turning off the power to unnecessary components) to prevent recurrence, while maintaining immediate response capability to abnormal signals. For example, if a slight increase in humidity and a tendency for the spread rate to increase are detected in a sub-area during the recovery phase, the adsorption unit in that area will be restored to medium intensity operation immediately and the user will be prompted to check the status of the items.

[0056] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0057] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A cardboard folding storage box odor removal control system, characterized in that: It includes a registration module, an occasion identification module, a propagation calculation module, a scheme simulation module, and a control module: Registration module: Enter the current values ​​of the storage cavity, and complete the initial registration by combining the adsorption saturation of the cardboard fiber with the background indicators of the environment. Set the tendency coefficient and permissible limit of the control target according to the usage requirements. Occasion Recognition Module: Identifies the current application occasion category through environmental recognition technology, calls up the corresponding reference values ​​and limit correction schemes for different occasion categories, and controls each functional component to be in a ready state; Spread Calculation Module: Continuously collects various parameters within the cavity and integrates the determined situation attributes to calculate the spread rate of the breath. If a parameter exceeds the corresponding corrected breath allowable limit for that situation, it is marked as a situation requiring intervention. Solution deduction module: Based on the current marked situation and multi-objective calculation function, the optimal odor removal action plan is deduced under multiple constraints; Control module: Controls odor removal according to the optimal odor removal action plan. During the removal process, it continuously tracks the rate of odor spread and concentration changes. If an abnormal spread is detected in a certain section, it increases the priority of treatment for that section and triggers the response of related components.

2. The odor removal control system for cardboard folding storage boxes according to claim 1, characterized in that: The propagation calculation module continuously acquires parameters such as air intensity, humidity, heat level, and gas flow rate within the cavity; The occasion category is converted into occasion feature identifier, and the occasion correction coefficient is appended to the normalized real-time parameters; Based on the preprocessed and fused multi-parameter parameter stream, the current rate of air spread within the cavity is calculated: The system calls upon the occasion identification module to provide the corrected permissible limits for the corresponding occasion, including limits for breath intensity, humidity, and heat level. The system then compares the real-time parameters with the corresponding limits one by one to analyze whether intervention is necessary.

3. The odor removal control system for cardboard folding storage boxes according to claim 2, characterized in that: The propagation estimation module calculates the current propagation rate of the air within the cavity based on a pre-processed and fused multi-parameter parameter stream containing contextual attributes, including the following steps: Calculate the spatial distribution gradient of each parameter, divide the cavity into several monitoring sub-regions, compare the numerical differences of adjacent sub-regions on the same parameter, and obtain the gradient direction and magnitude of concentration, humidity or temperature. By combining the direction and magnitude of gas flow velocity, assess the migration trend of air carried by the airflow; The gradient change amplitude and airflow velocity change within several sampling periods are taken to determine their growth momentum, and the increase weight is adjusted according to the occasion correction coefficient to obtain a comprehensive rate value that reflects the current air spread kinetic energy. If the intensity gradient of the air in a certain sub-region increases and the airflow direction is towards the center of that sub-region, and the environment is a closed environment, then it is marked as an accelerated spread trend.

4. The odor removal control system for cardboard folding storage boxes according to claim 3, characterized in that: The propagation estimation module calls the occasion identification module to provide the corrected permissible air limits corresponding to the occasion, and compares the real-time parameters with the corresponding limits one by one, including the following steps: For each parameter, determine whether its real-time value exceeds the limit range; If it exceeds the limit, check whether the spread rate of the parameter is accelerating to rule out misjudgment caused by occasional instantaneous fluctuations. When a parameter value exceeds the limit and the spread rate of the parameter indicates an increasing risk, the spatial segment or the overall cavity state where the parameter is located is marked as requiring intervention. The marking results include the type of parameter exceeding the limit, the extent of the exceedance, the location of the sub-regions involved, and the level of the spread trend.

5. The odor removal control system for cardboard folding storage boxes according to claim 1, characterized in that: The scheme deduction module maps the parameter status of each sub-region to a risk index, performs spatial clustering on the distribution of the same parameter in multiple sub-regions, and identifies areas of concentrated risk. Compare the difference in air intensity between adjacent sub-regions with the distance ratio, and select the sub-region with the largest gradient value and the risk index that meets the priority. Purification efficiency is quantified as the expected rate at which the air intensity in the target area is reduced to below the permissible limit within a specified time. The estimated score is obtained by simulating the parameter decay trend under different intervention measures. The sound and vibration control factor is quantified as the degree to which the noise and vibration levels generated by the adsorption unit and the ventilation guidance device are within acceptable limits during operation, and is mapped to a comfort score based on the component operating conditions and historical sound and vibration parameters. Based on the control tendency coefficient set in the registration module, the purification efficiency quantification and the estimated score of the sound and vibration control factor are combined into a comprehensive evaluation value according to their weights. When traversing the candidate combination of measures, the one with the best comprehensive evaluation value is selected as the preferred direction.

6. The odor removal control system for cardboard folding storage boxes according to claim 5, characterized in that: The scheme deduction module transforms each constraint into a feasibility judgment rule, performs real-time verification when generating candidate schemes, and eliminates combinations that do not meet the conditions. Determine the coordinates or number of the area to be treated first, and adjust the operating intensity of the adsorption unit based on the risk characteristics of that area and the results of multi-objective calculations; plan the opening and closing method of the ventilation channel and the airflow direction.

7. The odor removal control system for cardboard folding storage boxes according to claim 1, characterized in that: The occasion recognition module selects dimensions related to occasion attributes in a preset feature space, and normalizes these dimensions to make them comparable within the same dimension range. A pattern matching logic based on historical samples is introduced to compare the current feature vector with the labeled occasion category sample library, and the category with the highest matching degree is selected as the final judgment result. Retrieve the occasion category index from the parameter library, load the preset basic atmospheric intensity tolerance limit, humidity tolerance limit, and heat level tolerance limit under that category, obtain the correction coefficient group for that occasion, and define the dynamic adjustment range of the limit values ​​under different environmental background conditions.

8. The odor removal control system for cardboard folding storage boxes according to claim 7, characterized in that: The occasion identification module parses the component operation strategy template corresponding to the occasion. The template specifies the initial power consumption mode of the deodorization adsorption unit, the default gear of the ventilation guidance device, and the initial opening and closing degree parameters of the barrier sheet. After the control command is executed, each component feeds back status information to the occasion identification module to confirm that it has entered the preparation state.

9. The odor removal control system for cardboard folding storage boxes according to claim 1, characterized in that: The registration module calls the odor detection element, humidity detector, heat sensor and airflow meter to obtain the odor intensity, humidity, heat level, gas flow speed and odor spread rate in the storage cavity, respectively. The adsorption saturation of the cardboard fibers was read, and background indicators of the surrounding environment were collected, including ambient temperature, ambient humidity, ambient air pressure and background odor. Parse the descriptions of purification timeliness, noise tolerance, energy consumption limit speed preference in user instructions or scenario configuration files, and locate the tendency coefficient vector of preference distribution in the preset multi-dimensional preference space; Based on the occasion category and the initial state assessment results, the permissible odor limit is derived, the pre-configured basic limit value corresponding to the occasion is called, and then dynamically corrected according to the environmental background indicators and fiber adsorption saturation.

10. A method for controlling odor removal in cardboard folding storage boxes, implemented by the control system described in any one of claims 1-9, characterized in that: The control method includes the following steps: S1: Enter the current values ​​of the storage cavity, and complete the initial registration by combining the adsorption saturation of the cardboard fiber with the background indicators of the environment. Set the tendency coefficient and permissible limit of the control target according to the usage requirements. S2: Identify the current application scenario category through environmental recognition technology, call the corresponding reference values ​​and limit correction schemes for different scenario categories, and control each functional component to be in the ready state; S3: Continuously collect various parameters within the cavity and integrate the determined situation attributes to calculate the rate of air spread. If a parameter exceeds the corresponding corrected air allowable limit for that situation, it is marked as a situation requiring intervention. S4: Based on the current situation and multi-objective calculation function, the optimal odor removal action plan is derived under multiple constraints. S5: Control and remove odors according to the optimal odor removal action plan; S6: During the removal process, continuously track the rate of odor spread and concentration changes. If an abnormal spread is detected in a certain section, increase the priority of treatment for that section and trigger the response of related components.

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