Odor removal methods, devices, low-temperature refrigeration equipment and storage media

Abstract

This application relates to the field of smart home appliance technology, and provides an odor treatment method, device, low-temperature refrigeration equipment, and storage medium. Multiple gas sensors are deployed in each storage compartment of the low-temperature storage equipment. Simultaneously, the detection values ​​of each gas sensor are acquired at set time intervals, and the measured concentration and odor type of each storage compartment are generated based on the detection values. Then, combined with a pre-stored airflow transfer model corresponding to the current fan operating conditions, the probability of each storage compartment being an odor source is calculated. Based on the measured concentration and probability of each storage compartment being an odor source, the odor source compartment is located. Finally, targeted purification matching the odor type is performed on the odor source compartment, thereby enabling targeted odor removal at the source, improving purification efficiency, and reducing energy consumption.

Description

Technical Field

[0001] This application relates to the field of smart home appliance technology, and more specifically, to an odor treatment method, apparatus, low-temperature refrigeration equipment, and storage medium. Background Technology

[0002] With the increasing demand for food preservation, medical refrigeration, and cold chain transportation, the deodorization function of low-temperature storage equipment (such as refrigerators, medical refrigerators, and vehicle-mounted freezers) is receiving more and more attention.

[0003] Existing odor removal technologies mainly employ methods such as negative ions, photocatalysis, or activated carbon adsorption, which can reduce the concentration of odors inside the equipment to a certain extent. However, this method typically performs global odor removal on the entire storage cavity, requiring the odor removal module to operate frequently or for extended periods, resulting in high energy consumption. Furthermore, because it cannot focus on the source of the odor, the overall purification efficiency is relatively low. Summary of the Invention

[0004] The purpose of this application is to provide an odor treatment method, apparatus, low-temperature refrigeration equipment and storage medium, which can locate the odor source and perform targeted purification of the odor source.

[0005] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows: In a first aspect, embodiments of this application provide an odor treatment method applied to a controller of a low-temperature storage device. Each storage compartment of the low-temperature storage device is equipped with multiple gas sensors, which are used to detect various gases. The controller pre-stores an airflow transfer model corresponding to each fan operating condition. The airflow transfer model characterizes the relative concentration percentage of the odor in each storage compartment when one storage compartment is an odor source under the corresponding fan operating condition. The method includes: According to the set time interval, the detection values ​​of each gas sensor corresponding to each storage zone are obtained; Based on the detection values ​​of each gas sensor corresponding to each storage zone, the measured concentration and odor type of each storage zone are generated; Based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating condition, the probability that each storage zone is an odor source is calculated. Based on the measured concentration of each of the storage zones and the probability that each of the storage zones is an odor source, odor source zones are determined from all the storage zones; Based on the odor type of the odor source zone, the odor source zone is targeted for purification.

[0006] Optionally, generating the measured concentration and odor type for each storage zone based on the detection values ​​of each gas sensor corresponding to each storage zone includes: Obtain the sensor reference value, which is the average detection value of all gas sensors under clean air conditions within a set time period each day; For each storage zone, the detection values ​​of each gas sensor corresponding to the storage zone are normalized using the sensor reference value to obtain the odor feature vector of the storage zone. The odor feature vector is mathematically transformed to obtain the measured concentration of the storage zone; The odor type of the storage zone is determined based on the sensor reference value and the detection values ​​of each gas sensor corresponding to the storage zone.

[0007] Optionally, the plurality of gas sensors includes a first gas sensor, a second gas sensor, and a third gas sensor; The step of normalizing the detection values ​​of each gas sensor corresponding to the storage zone using the sensor reference value to obtain the odor feature vector of the storage zone includes: The odor feature vector is obtained by calculating the ratio of the detection values ​​of the first gas sensor, the second gas sensor, and the third gas sensor to the sensor reference value, respectively. The step of determining the odor type of the storage zone based on the sensor reference value and the detection values ​​of each gas sensor corresponding to the storage zone includes: If the ratio of the detection value of the first gas sensor to the detection value of the third gas sensor is greater than a first threshold and the ratio of the detection value of the sensor to the reference value is greater than a second threshold, then the odor type is determined to be protein putrefaction. If the ratio of the detection value of the third gas sensor to the detection value of the first gas sensor is greater than a third threshold and the ratio of the detection value of the sensor to the reference value is greater than a fourth threshold, then the odor type is determined to be carbohydrate fermentation. If neither of the above two conditions is met, and the detection value of the second gas sensor is continuously greater than the fifth threshold within the first set time period, then the odor type is determined to be an unknown odor.

[0008] Optionally, the airflow transfer model includes a predicted concentration matrix for each of the storage zones, the predicted concentration matrix including the relative concentration percentage of odor in each storage zone when the corresponding storage zone is an odor source, and the sum of all relative concentration percentages is 1; The method for calculating the probability that each storage zone is an odor source based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating conditions includes: For any target storage zone, the predicted concentration matrix of the target storage zone is obtained from the target airflow transfer model; Based on the predicted concentration matrix and the measured concentration of each of the storage zones, the scaling factor of the target storage zone is calculated; The predicted concentration matrix is ​​scaled according to the scaling factor to obtain the scaled predicted concentration matrix; The matching score of the target storage partition is calculated based on the scaled predicted concentration matrix and the measured concentration of each storage partition. Traverse each of the storage partitions to obtain the matching score for each of the storage partitions; Based on the matching score of each storage compartment, the probability that each storage compartment is a source of odor is calculated.

[0009] Optionally, the scaling factor satisfies the following formula:

[0010] in, This represents the scaling factor of the j-th storage partition. N represents the total number of storage zones. This represents the measured concentration in the j-th storage zone; Let represent the predicted concentration matrix for the j-th storage zone, and s represent the target airflow transfer model; express The L2 norm; The scaled predicted concentration matrix satisfies the following formula:

[0011] in, Represents the scaled predicted concentration matrix for the j-th storage partition; The matching score satisfies the following formula:

[0012] in, This represents the matching score of the j-th storage partition; The probability that the storage area is a source of odor satisfies the following formula:

[0013] in, This represents the matching score of the k-th storage partition.

[0014] Optionally, determining the odor source zone from all the storage zones based on the measured concentration of each of the storage zones and the probability that each of the storage zones is an odor source includes: The storage area where the probability is greater than the first preset threshold and the measured concentration is continuously greater than the second preset threshold within a second set time period is determined as the odor source area.

[0015] Optionally, the odor type includes one of protein putrefaction, carbohydrate fermentation, and unknown odor; each of the storage compartments is provided with an electric damper in the return air duct between the storage compartments and other storage compartments, and each of the storage compartments is equipped with a purification device, which integrates an ultraviolet LED array and a plasma generator; The step of targeting and purifying the odor source area according to the odor type includes: Close the electric damper in the return air passage between the odor source zone and other storage zones, and adjust the guide plate of the low-temperature storage equipment so that the airflow of the other storage zones bypasses the odor source zone. If the odor type is protein putrefaction, then start the ultraviolet LED array corresponding to the odor source partition to run for a preset time; If the odor type is carbohydrate fermentation, then the plasma generator corresponding to the odor source zone is activated; If the odor type is an unknown odor, then control the ultraviolet LED array and plasma generator corresponding to the odor source zone to alternately start and stop operation.

[0016] Secondly, embodiments of this application provide an odor treatment device applied to a controller of a low-temperature storage equipment. Each storage compartment of the low-temperature storage equipment is equipped with multiple gas sensors for detecting various gases. The controller pre-stores an airflow transfer model corresponding to each fan operating condition. This airflow transfer model characterizes the relative concentration percentage of the odor in each storage compartment when an odor source is identified under the corresponding fan operating condition. The device includes: The acquisition module is used to acquire the detection values ​​of each gas sensor corresponding to each of the storage zones at set time intervals; An odor source location module is used to generate the measured concentration and odor type of each storage zone based on the detection values ​​of each gas sensor corresponding to each storage zone; calculate the probability that each storage zone is an odor source based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating condition; and determine the odor source zone from all the storage zones according to the measured concentration of each storage zone and the probability that each storage zone is an odor source. The odor purification module is used to perform targeted purification of the odor source zone according to the odor type of the odor source zone.

[0017] Thirdly, embodiments of this application provide a low-temperature storage device, including a controller and a memory, wherein the memory is used to store a program, and the controller is used to implement the odor treatment method in the first aspect above when executing the program.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a controller, implements the odor treatment method described in the first aspect above.

[0019] Compared to existing technologies, the odor treatment method, apparatus, low-temperature refrigeration equipment, and storage medium provided in this application embodiment deploy multiple gas sensors in each storage compartment of the low-temperature storage equipment. Simultaneously, the detection values ​​of each gas sensor are acquired at set time intervals, and the measured concentration and odor type of each storage compartment are generated based on the detection values. Then, combined with a pre-stored airflow transfer model corresponding to the current fan operating conditions, the probability of each storage compartment being an odor source is calculated. Based on the measured concentration and probability of each storage compartment being an odor source, the odor source compartment is located. Finally, targeted purification matching the odor type is performed on the odor source compartment, thereby enabling targeted odor removal at the source, improving purification efficiency, and reducing energy consumption. Attached Figure Description

[0020] Figure 1 A block diagram of a cryogenic storage device provided in an embodiment of this application is shown.

[0021] Figure 2 This application provides a schematic flowchart of an odor treatment method according to an embodiment. Figure 1 .

[0022] Figure 3 This application provides a schematic flowchart of an odor treatment method according to an embodiment. Figure 2 .

[0023] Figure 4 A block diagram of an odor treatment device provided in an embodiment of this application is shown.

[0024] Icons: 10-Low-temperature storage equipment; 11-Controller; 12-Memory; 13-Gas sensor; 14-Electric damper; 15-Purification device; 151-Ultraviolet LED array; 152-Plasma generator; 16-Bus; 100-Odor treatment device; 101-Acquisition module; 102-Odor source location module; 103-Odor purification module. Detailed Implementation

[0025] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0026] The odor treatment method provided in this application embodiment is applied to the low-temperature storage device 10 as shown in Figure 1. The low-temperature storage device 10 includes a controller 11, a memory 12, a gas sensor 13, an electric damper 14, a purification device 15, and a bus 16. The controller 11 is connected to the memory 12, the gas sensor 13, the electric damper 14, and the purification device 15 via the bus 16.

[0027] The memory 12 stores a program, and the controller 11 executes the program after receiving an execution instruction to implement the odor treatment method disclosed in the following embodiments. The memory 12 may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0028] The low-temperature storage device 10 includes multiple storage compartments, each equipped with multiple gas sensors 13. These gas sensors 13 are used to detect various gases; that is, each gas sensor 13 has differentiated response characteristics to different types of gases. Optionally, the multiple gas sensors 13 may include at least a sensor sensitive to ammonia (for identifying protein spoilage), a sensor sensitive to volatile organic compounds (for indicating carbohydrate fermentation), and a sensor sensitive to ethanol / acetone (for capturing the volatile characteristics of fruits, vegetables, or alcoholic beverages).

[0029] Taking a storage zone as an example, the multiple gas sensors 13 installed in the storage zone can be deployed as a whole as a sensor array, or each sensor can be deployed individually, without any restrictions.

[0030] Optionally, the low-temperature storage device 10 can be, but is not limited to, a refrigerator, a medical refrigerator, or a vehicle freezer. Taking a refrigerator as an example, multiple storage compartments can include an upper refrigerator compartment, a middle refrigerator compartment, a lower refrigerator compartment, a variable temperature compartment, and a freezer compartment. For each storage compartment, multiple gas sensors are installed, and the installation positions can be flexibly adjusted by the user as needed. For example, the upper refrigerator compartment can be installed in the center of the top panel, the middle refrigerator compartment in the middle of the back wall of the drawer, the lower refrigerator compartment in the side wall of the fruit and vegetable drawer, the variable temperature compartment in the upper part of the shelf, and the freezer compartment in the rear of the inner liner.

[0031] It should be noted that the installation locations of the above-mentioned storage compartments are only examples and are not limited to the above locations in actual applications. For example, the upper refrigeration compartment is not limited to the center of the top panel, but can also be installed at the edge of the top panel without any restrictions.

[0032] Each storage compartment is equipped with an electric damper 14 in the return air duct between other storage compartments. The electric damper 14 can be installed at the entrance of each return air duct. The electric damper 14 can be driven by a stepper motor and needs to have the characteristics of fast response, low noise and high sealing performance. It can be independently closed or opened under the control of the controller 11 to achieve physical isolation of airflow between the odor source compartment and other storage compartments.

[0033] Each storage compartment is equipped with a purification device 15, for example, the purification devices 15 are deployed one-to-one within each storage compartment. Each purification device 15 integrates an ultraviolet LED array 151 and a plasma generator 152. The ultraviolet LED array emits 265 nm wavelength ultraviolet light, efficiently catalyzing the decomposition of ammonia and nitrogen-containing organic compounds. The plasma generator 152 generates non-equilibrium plasma rich in active oxygen clusters at room temperature and pressure, oxidizing aldehydes, ketones, and alcohols (VOCs). Optionally, the ultraviolet LED array 151 and the plasma generator 152 can be co-encapsulated in a low-temperature resistant, condensation-resistant sealed cavity, supporting independent power supply, independent enable, and alternating / combined operating modes.

[0034] The controller 11 may be an integrated circuit chip with signal processing capabilities. In implementation, the steps of the following methods can be completed through integrated logic circuits in the hardware of the controller 11 or through software instructions. The controller 11 described above can be a general-purpose processor, including a central processing unit (CPU), a microcontroller unit (MCU), a complex programmable logic device (CPLD), a field programmable gate array (FPGA), an embedded ARM chip, etc.

[0035] Meanwhile, the controller 11 pre-stores the airflow transfer model corresponding to each fan operating condition. The airflow transfer model represents the relative concentration of odor in each storage zone when a storage zone is an odor source under the corresponding fan operating condition.

[0036] In one possible implementation, taking a refrigerator as an example of a low-temperature storage device 10, the process of constructing the airflow transfer model corresponding to each fan operating condition may include the following steps: The first step involves using the professional computational fluid dynamics (CFD) simulation software ANSYS Fluent to create a precise three-dimensional geometric model of the entire refrigerator cavity, including all structural features such as the inner liner, partitions, drawers, air ducts, air outlets, and return air inlets. Simultaneously, ANSYS Fluent software and a steady-state k-ε turbulence model are used to simulate the turbulent flow of air inside the refrigerator, thereby obtaining the airflow field and odor concentration field within the cavity.

[0037] The second step is to divide the cavity into logical partitions that correspond perfectly to the locations of the gas sensors. For example, assuming the gas sensors are located in the upper, middle, and lower layers of the refrigerator, the variable temperature compartment, and the freezer compartment, the cavity is divided into K=5 logical partitions P1~P5 (i.e., the upper, middle, and lower layers of the refrigerator, the variable temperature compartment, and the freezer compartment) to ensure that the logical partitions correspond one-to-one with the locations of the sensors.

[0038] The third step involves conducting independent simulations for different wind turbine operating conditions s (e.g., low wind speed, high wind speed, defrosting mode), generating a unique airflow transfer model M for each wind turbine operating condition s. （s） M （s） It can be a 5×5 dimensional matrix.

[0039] The fourth step is to process each logical partition. P j A unit intensity odor source is set within (j∈{1,2,3,4,5}). Simultaneously, the odor concentration field is solved under any fan operating condition s (e.g., low wind speed), and the data for each logical partition is recorded when a steady state is reached (i.e., the concentration no longer changes with time). P i The steady-state concentration values ​​of (i∈{1,2,3,4,5}).

[0040] Fifth, after completing the previous step, you will obtain 5 steady-state concentration values, corresponding to 5 logical partitions. These 5 concentration values ​​will then be normalized, i.e.: M ij （s） =( Pi Partition in P j (Steady-state concentration value when the zone is the odor source) / (Sum of steady-state concentration values ​​of all zones), and ∑ i M ij （s） = 1.

[0041] in, M ij （s） Characterizing the situation under current wind turbine operating conditions s (e.g., low wind speed) when the odor source is located P j When partitioning, odors are present P i The relative concentration percentage within a zone, or in other words, when the odor source is located in... P j When partitioning, odors exist. P i The probability of odor in a partition (i.e., the probability of odor) M ij （s） The probability exists P i (In the partition).

[0042] Step 6, take the result from the previous step M ij （s） As M （s） The j-th column of the matrix is ​​filled with M. （s） In the matrix, this column is... P j The predicted concentration matrix for each storage zone includes the relative concentration percentage of the odor in each storage zone when the corresponding storage zone is the odor source, and the sum of all relative concentration percentages is 1.

[0043] Repeat steps four and five above to iterate through all logical partitions P and fill M. （s） The matrix provides the airflow transfer model corresponding to the current wind turbine operating condition s (e.g., low wind speed), which includes the predicted concentration matrix for each storage zone.

[0044] Next, repeat the above six steps, traversing each wind turbine operating condition s, and finally obtain a matrix set, including the airflow transfer model corresponding to each wind turbine operating condition s (e.g., low wind speed, high wind speed, defrosting mode).

[0045] Finally, the matrix set obtained above is stored as offline data in the refrigerator's controller (e.g., MCU). During actual operation, the controller directly looks up the corresponding M based on the current fan operating condition. （s） The matrix is ​​used for subsequent odor source location calculations.

[0046] The odor treatment method provided in the embodiments of this application will be described in detail below.

[0047] Please refer to Figure 2 , Figure 2 This invention illustrates a flowchart of an odor treatment method provided by the present invention, which is applied to... Figure 1 The controller 11 in the middle may include the following steps: S101, according to the set time interval, acquire the detection values ​​of each gas sensor corresponding to each storage zone; S102, Based on the detection values ​​of each gas sensor corresponding to each storage zone, generate the measured concentration and odor type of each storage zone; S103, based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating condition, calculate the probability that each storage zone is an odor source; S104, Based on the measured concentration of each storage zone and the probability that each storage zone is an odor source, determine the odor source zone from all storage zones; S105 performs targeted purification of odor source zones based on the type of odor.

[0048] In step S101, the set time interval refers to the time period during which the controller periodically executes the data acquisition task, for example, once every 10 seconds or every 30 seconds. The specific value can be flexibly set according to the device power consumption constraints and real-time response requirements, and is not limited here.

[0049] Each gas sensor corresponding to a storage compartment refers to a variety of gas sensors installed in the same storage compartment, including but not limited to the MQ-135 sensor sensitive to ammonia (NH3) (used to indicate protein spoilage), the TGS2600 sensor sensitive to methane (CH4), hydrogen (H2) and broad-spectrum volatile organic compounds (VOCs) (used to indicate basic organic volatilization), and the TGS2620 sensor highly sensitive to small molecule polar organic compounds such as ethanol and acetone (used to indicate fruit and vegetable fermentation or alcoholic beverage volatilization), etc.

[0050] In step S102, the measured concentration is a dimensionless relative concentration value obtained by correcting and normalizing the detection values ​​of each gas sensor after baseline drift correction. It is used to characterize the current odor intensity of the storage zone. Odor types can include three categories: protein spoilage, carbohydrate fermentation, and unknown odors. These correspond to nitrogenous compounds produced by the spoilage of meat and dairy products, alcohols and ketones produced by the fermentation of fruits, vegetables, and alcohols, as well as mixed odors that are complex and difficult to classify, respectively.

[0051] In step S103, the airflow transfer model is a set of matrices constructed in advance using CFD simulation. This is done on a three-dimensional structural model of the target device (e.g., a refrigerator) under different fan operating conditions (e.g., low fan speed, high fan speed, defrosting mode) to simulate the release of odor sources from a single zone, recording the average concentration distribution of each zone under steady-state conditions, and then normalizing the results. The j-th column of any matrix represents the relative concentration distribution of the odor across all storage zones when the actual odor source is located in the j-th storage zone. The target airflow transfer model refers to the model automatically selected and called by the controller from multiple pre-stored airflow transfer models based on the current actual fan operating conditions.

[0052] In step S104, the odor source zone refers to the unique storage zone that is identified as the actual location of the odor after probability calculation and threshold determination.

[0053] In step S105, targeted purification refers to the combination of physical isolation of the odor source zone and activation of a dedicated purification device, without affecting the operation of other normal zones.

[0054] In existing technologies, refrigerators and other low-temperature storage equipment generally adopt a global odor removal solution. This means that regardless of the location or composition of the odor, the negative ion generator, photocatalytic module, or activated carbon filter throughout the entire machine is activated for uniform treatment. This cannot distinguish the location and type of odor, resulting in high energy consumption and low efficiency. Even if some products deploy multiple gas sensors, they are only used to trigger a buzzer alarm or simply adjust the fan speed, and cannot achieve spatial positioning of the odor source. Due to the lack of accurate judgment of the odor generation area, the equipment cannot perform differentiated treatment based on the location of the odor, further exacerbating the energy consumption and efficiency problems caused by global odor removal.

[0055] To overcome the above problems, this embodiment provides an odor treatment method. The controller continuously collects the detection values ​​of multiple gas sensors configured in each storage zone at set time intervals. These detection values ​​reflect the local gas composition changes in the corresponding storage zone. Then, based on the detection values ​​of each storage zone, the measured concentration and odor type of each storage zone are generated. This not only tells us whether there is an odor, but also determines what kind of odor it is. Based on this, the probability of each storage zone being an odor source is calculated based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating conditions. Combining the measured concentration of each storage zone and the probability of each storage zone being an odor source, a unique odor source zone is determined from all storage zones. Finally, targeted purification matching its odor type is performed on the odor source zone, thereby enabling targeted odor removal at the source, improving purification efficiency, and reducing energy consumption.

[0056] In one possible implementation, Figure 2Based on this, please refer to Figure 3 Step S102, which generates the measured concentration and odor type for each storage zone based on the detection values ​​of each gas sensor corresponding to each storage zone, may include: S1021, Obtain the sensor reference value. The sensor reference value is the average detection value of all gas sensors under clean air conditions within a set time period each day. S1022, for each storage zone, the detection values ​​of each gas sensor corresponding to the storage zone are normalized using the sensor reference value to obtain the odor feature vector of the storage zone; the odor feature vector is mathematically transformed to obtain the measured concentration of the storage zone; the odor type of the storage zone is determined based on the sensor reference value and the detection values ​​of each gas sensor corresponding to the storage zone.

[0057] In sub-step S1021, the sensor reference value can be the detection value of all gas sensors automatically recorded by the controller during a set period each day (e.g., from 2:00 AM to 4:00 AM) when there is no odor in the equipment, the door is closed, and the fan is running stably. The controller then calculates the arithmetic mean of all the detection values ​​and uses the mean as the sensor reference value. The purpose of this is to eliminate systematic deviations caused by temperature and humidity drift, component aging, etc.

[0058] The daily set time period can be a period of low user usage, such as 2:00 AM to 4:00 AM every day. The sensor average value is updated during the daily set time period in order to prevent long-term drift.

[0059] Clean air condition can be defined as a stable operating condition in which there are no obvious odor sources inside the low-temperature storage equipment, the items stored in each storage zone are in a normal preservation state, and the ambient temperature and humidity are within the nominal operating range.

[0060] In sub-step S1022, the odor feature vector can be an ordered array composed of the ratios of the detection values ​​of multiple gas sensors in the same storage zone to the sensor reference values, which enables the response amplitudes of different sensors to be comparable.

[0061] The measured concentration can be a single scalar value obtained by performing specific mathematical transformations on the odor feature vector (e.g., weighted summation, norm calculation, nonlinear mapping, etc.), which is used to quantify the current odor intensity of the corresponding storage zone.

[0062] Odor types can include protein putrefaction, carbohydrate fermentation, and unknown odors. The determination of odor type depends on the detection values ​​of each gas sensor and the sensor reference value, without introducing any external input or human intervention.

[0063] In this embodiment, the multiple gas sensors include a first gas sensor, a second gas sensor, and a third gas sensor. For example, the first gas sensor may be an MQ-135 sensor that is sensitive to ammonia (NH3), and its response intensity increases with the degree of spoilage of protein-based foods. The second gas sensor may be a TGS2600 sensor that is sensitive to methane (CH4), hydrogen (H2), and VOCs, and its response intensity increases with the intensification of the fermentation process of fruits, vegetables, and dairy products. The third gas sensor may be a TGS2620 sensor that is highly sensitive to small molecule polar organic compounds such as ethanol and acetone, and its response is basic and generalized, making it suitable for initial screening of mixed odors.

[0064] Based on this, the process of normalizing the detection values ​​of each gas sensor corresponding to the storage zone using the sensor reference value in sub-step S1022 may include: calculating the ratio of the detection values ​​of the first gas sensor, the second gas sensor, and the third gas sensor to the sensor reference value to obtain the odor feature vector.

[0065] For example, with P i Taking a partitioned approach as an example, suppose the detection values ​​of the first gas sensor, the second gas sensor, and the third gas sensor are respectively... , , The sensor reference value is ,but P i The odor feature vector of a partition can be represented as:

[0066] Meanwhile, the process of determining the odor type of the storage zone based on the sensor reference value and the detection values ​​of each gas sensor corresponding to the storage zone in sub-step S1022 may include: if the ratio of the detection value of the first gas sensor to the detection value of the third gas sensor is greater than a first threshold and the ratio to the sensor reference value is greater than a second threshold, then the odor type is determined to be protein putrefaction; if the ratio of the detection value of the third gas sensor to the detection value of the first gas sensor is greater than a third threshold and the ratio to the sensor reference value is greater than a fourth threshold, then the odor type is determined to be carbohydrate fermentation; if neither of the above two conditions is met and the detection value of the second gas sensor is continuously greater than a fifth threshold within a first set time period, then the odor type is determined to be an unknown odor.

[0067] Optionally, the first threshold, the second threshold, the third threshold, the fourth threshold, the fifth threshold, and the first set duration are all fixed values ​​that are pre-calibrated and stored in the controller. For example, the first threshold is 2.0, the second threshold is 1.5, the third threshold is 1.8, the fourth threshold is 1.4, the fifth threshold is 1.6, and the first set duration is 10 seconds, etc.

[0068] The off-odor type is one of protein putrefaction, carbohydrate fermentation, and unknown off-odor. Protein putrefaction can be represented as NH3-type, which represents the putrefaction process of nitrogen-containing substances such as meat and dairy products; carbohydrate fermentation can be represented as VOC-type, which represents the fermentation process of sugar-containing substances such as fruits, vegetables, bread, and alcoholic beverages; unknown off-odor can be represented as Mixed-type, which represents a situation where multiple putrefaction processes coexist or the composition is complex and difficult to classify.

[0069] That is, if >2.0 and If the value is >1.5, the odor type is determined to be protein putrefaction NH3-type; if >1.8 and If the value is greater than 1.4, the odor type is determined to be carbohydrate fermentation VOC-type; if neither of the above two conditions is met, and If the odor is greater than 1.6 and lasts for ≥10 seconds, then the odor type is determined to be an unknown odor mixed-type.

[0070] It should be noted that the values ​​of the first threshold, second threshold, third threshold, fourth threshold, fifth threshold and first set duration mentioned above are only examples. In practice, the values ​​may be different for different low-temperature storage equipment. The specific values ​​can be flexibly set according to the actual situation of the equipment, and no restrictions are imposed here.

[0071] In one possible implementation, please refer again. Figure 3 Step S103, which calculates the probability that each storage zone is an odor source based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating condition, may include: S1031, for any target storage zone, obtain the predicted concentration matrix of the target storage zone from the target airflow transfer model; calculate the scaling factor of the target storage zone based on the predicted concentration matrix and the measured concentration of each storage zone; scale the predicted concentration matrix according to the scaling factor to obtain the scaled predicted concentration matrix; calculate the matching score of the target storage zone based on the scaled predicted concentration matrix and the measured concentration of each storage zone. S1032, Traverse each storage partition and obtain the matching score for each storage partition; S1033, Calculate the probability that each storage compartment is a source of odor based on the matching score of each storage compartment.

[0072] In this embodiment, as can be seen from the aforementioned construction process of the airflow transfer model, the airflow transfer model includes a predicted concentration matrix for each storage zone. The predicted concentration matrix includes the relative concentration percentage of the odor in each storage zone when the corresponding storage zone is the odor source, and the sum of all relative concentration percentages is 1.

[0073] Therefore, after obtaining the target airflow transfer model corresponding to the current wind turbine operating condition, for any target storage zone, the predicted concentration matrix corresponding to the target storage zone as a potential odor source can be obtained from the target airflow transfer model. This matrix represents the relative concentration distribution that the odor would form in all storage zones if it were actually generated in the target storage zone under ideal airflow conditions. Subsequently, based on the above predicted concentration matrix and the measured concentration of each storage zone, the scaling factor of the target storage zone is calculated so that the theoretical distribution, after scaling, is closest to the measured results in overall shape. Then, based on the scaled predicted concentration matrix and the measured concentration of each storage zone, the matching score of the target storage zone is calculated to quantify the consistency between the assumption that the target storage zone is an odor source and the observed data. At the same time, following the above process, each storage zone is traversed to obtain the matching score of each storage zone. Finally, the matching scores of all candidate zones are subjected to Softmax normalization to obtain the probability that each storage zone is a real odor source.

[0074] Optionally, for storage partition P j For the j-th storage partition, the scaling factor satisfies the following formula:

[0075] in, This represents the scaling factor of the j-th storage partition. N represents the total number of storage zones. This represents the measured concentration in the j-th storage zone; Let represent the predicted concentration matrix for the j-th storage zone, and s represent the target gas flow transfer model; express The L2 norm.

[0076] The scaled predicted concentration matrix satisfies the following formula:

[0077] in, This represents the scaled predicted concentration matrix for the j-th storage partition.

[0078] The matching score satisfies the following formula:

[0079] in, This represents the matching score of the j-th storage partition.

[0080] Storage Zone P j The probability of being a source of odor satisfies the following formula:

[0081] in, This represents the matching score of the k-th storage partition, where k=1,…,N, and N represents the total number of storage partitions.

[0082] In one possible implementation, please refer again. Figure 3 Step S104, which involves determining the odor source zone from all storage zones based on the measured concentration of each storage zone and the probability that each storage zone is an odor source, may include: S1041, the storage area with a probability greater than the first preset threshold and a measured concentration that is continuously greater than the second preset threshold within a second set time period is identified as the odor source area.

[0083] In this embodiment, after obtaining the probability that each storage compartment is an odor source, the highest probability term is not directly used as the final determination result. Instead, a time-duration constraint on the measured concentration is further introduced. That is, a storage compartment is officially confirmed as an odor source only when the probability of it being an odor source exceeds a first preset threshold and its corresponding measured concentration remains higher than a second preset threshold for a second set time period. This conditional design avoids accidental high-probability misjudgments caused by transient airflow disturbances, sensor noise, or model fitting fluctuations, and also eliminates false triggers caused by low-concentration background drift or weak interference.

[0084] Optionally, the first preset threshold is a threshold value used to determine the reliability of the probability, and its value can be set to 0.7, meaning that only when the probability of a certain storage area being inferred as a source of odor is not less than 70%, that is, Only then will the next confirmation process begin.

[0085] The second preset threshold is a concentration threshold used to determine the intensity of the odor. Its value can be set to 1.6 to exclude environmental fluctuations and minor interferences. The second preset duration can be 10 seconds to ensure that the confirmed odor event has sufficient persistence and physical authenticity.

[0086] That is, if storage partition P j satisfy And C j If the odor source is >1.6 and lasts for ≥10 seconds, then the odor source zone is confirmed as P. j .

[0087] In one possible implementation, as described above Figure 1As described, each storage compartment is equipped with an electric damper in the return air duct between other storage compartments, and each storage compartment is equipped with a purification device that integrates an ultraviolet LED array and a plasma generator.

[0088] Based on this, please refer again Figure 3 Step S105, which involves targeted purification of the odor source zone based on the odor type, may include: S1051, close the electric damper in the return air duct between the odor source zone and other storage zones, and adjust the deflector of the low-temperature storage equipment so that the airflow of the remaining storage zones bypasses the odor source zone. S1052, If the odor type is protein putrefaction, start the UV LED array corresponding to the odor source partition and run for the preset time. S1053, if the odor type is carbohydrate fermentation, then start the plasma generator corresponding to the odor source zone; S1054, if the odor type is an unknown odor, then control the ultraviolet LED array and plasma generator corresponding to the odor source zone to start and stop alternately.

[0089] In this embodiment, after identifying the odor source zone and its corresponding odor type, the electric dampers in the return air duct between the odor source zone and all other storage zones are first closed to physically block the odor from spreading outward with the internal circulating airflow. Secondly, the guide vanes inside the low-temperature storage equipment are adjusted to guide the airflow in the remaining clean areas to actively bypass the odor source zone, forming a local airflow avoidance zone to further suppress cross-contamination. Finally, based on the chemical properties of the odor type, the matching purification device is precisely activated. Specifically, an ultraviolet LED array is used for photolysis of ammonia (NH3-type) produced by protein putrefaction, a low-temperature plasma generator is used for oxidative decomposition of volatile organic compounds (VOC-type) produced by carbohydrate fermentation, and the two devices are controlled to alternately start and stop for mixed-type odors, ensuring purification efficiency while avoiding the accumulation of byproducts.

[0090] Among them, the electric damper refers to a mechanical valve installed in the return air channel of each storage zone, which can be electrically adjusted to open and close, and is used to dynamically cut off or connect the gas exchange path between the storage zone and the main air duct. The baffle plate refers to an adjustable angle baffle installed in the air duct or air outlet inside the low-temperature storage equipment; its position adjustment can change the airflow direction, allowing clean airflow to actively avoid the space where the odor source zone is located. The ultraviolet LED array refers to a deep ultraviolet light-emitting diode (UV-LED) module integrated inside each storage zone, whose emission wavelength is concentrated around 265nm, which can efficiently break down nitrogen-containing small molecules such as ammonia (NH3). The low-temperature plasma generator refers to a discharge device that generates non-equilibrium plasma under normal temperature and pressure conditions; it is rich in highly reactive oxygen free radicals, which can rapidly oxidize volatile organic compounds (VOCs) such as ethanol and acetone.

[0091] Optionally, the UV LED array can be set to operate for a preset duration, which can be 60 seconds. Alternating start-stop operation means that the UV LED array and the low-temperature plasma generator work alternately at a fixed cycle (e.g., switching every 10 seconds), taking into account the complementarity of the two types of purification equipment and the thermal management requirements of the equipment.

[0092] It should be noted that while targeting and purifying the odor source area, the odor source area can be retested after a set time (e.g., 30 minutes), and reset if the standard is met.

[0093] In existing technologies, various sensor signals, fan status, damper opening, and purification module start / stop are all managed independently by different control logics. There is no data exchange or action coordination between them, making it impossible to form a closed loop of "identification → isolation → purification → anti-diffusion". This not only causes a lot of ineffective energy consumption, but also allows odors to continue to mix and spread in the cavity, which can easily contaminate other foods in adjacent storage areas.

[0094] In this embodiment, after identifying the type of odor and confirming the odor source zone, the controller immediately closes the electric damper in the return air channel between the odor source zone and other storage zones to achieve physical airflow isolation. At the same time, it adjusts the guide plate of the low-temperature storage equipment to guide the airflow of the remaining clean areas to actively bypass the odor source zone, forming a local airflow avoidance zone to further suppress cross-contamination. Furthermore, based on the type of odor, it precisely activates the purification device of the odor source zone. That is, if it is protein putrefaction, the ultraviolet LED array is activated for 60 seconds; if it is carbohydrate fermentation, the plasma generator is activated; if it is an unknown odor, the ultraviolet LED array and the plasma generator are controlled to alternately start and stop, thereby achieving a closed-loop process of "identification → isolation → purification → prevention of diffusion".

[0095] Taking a refrigerator as an example, in practice, when a user opens the refrigerator door and stores fresh food, the gas sensor on the side wall of the lower crisper drawer detects an abnormally high concentration of ethanol and acetone. Based on this, the controller identifies the odor type as carbohydrate fermentation (VOC-type). Simultaneously, based on the detection values ​​collected by the gas sensors in each storage compartment, it generates the measured concentration for each storage compartment. Then, it calls the airflow transfer model corresponding to the current fan operating condition (e.g., high fan speed) and calculates that the probability of the lower crisper drawer being the odor source is as high as 92%, far exceeding the judgment threshold, and the concentration remains high. If the time exceeds 10 seconds, the lower refrigerated compartment is confirmed as the source of the odor. The controller then issues a control command to close the electric damper in the return air duct connecting to the lower refrigerated compartment to block the odor from escaping. It also activates the built-in low-temperature plasma generator in the lower refrigerated compartment for 60 seconds of directional oxidation. At the same time, it finely adjusts the angle of the guide vane to guide the clean airflow from the upper refrigerated compartment to bypass the lower refrigerated compartment. After the purification is completed, the monitoring is automatically restarted. The entire process requires no manual intervention and does not trigger any purification actions in other storage compartments, achieving a closed-loop process of "identification → isolation → purification → prevention of diffusion".

[0096] Compared with the prior art, the embodiments of this application have the following beneficial effects: First, multiple gas sensors are deployed in each storage zone of the low-temperature storage equipment. Simultaneously, the measured concentration and odor type of each storage zone are generated based on the detection values ​​of each gas sensor, achieving an odor type identification accuracy of over 88%. Combined with an airflow transfer model corresponding to the current fan operating conditions, the probability of each storage zone being an odor source is calculated. Then, based on the measured concentration and probability of each storage zone being an odor source, the odor source zone is located, achieving an odor source zone location accuracy of 92% and a response time of less than 15 seconds. Finally, targeted purification matching the odor type is performed on the odor source zone, thereby enabling targeted odor removal at the source, improving purification efficiency, and reducing energy consumption by 40-62% compared to global purification.

[0097] Secondly, after identifying the type of odor and confirming the odor source zone, the controller immediately closes the electric damper in the return air duct between the odor source zone and other storage zones to achieve physical airflow isolation. At the same time, it adjusts the guide plate of the low-temperature storage equipment to guide the airflow of the remaining clean areas to actively bypass the odor source zone, forming a local airflow avoidance zone, further suppressing cross-contamination. The probability of odor spreading to other storage zones is reduced by ≥85%. Furthermore, based on the type of odor, the controller accurately activates the purification device of the odor source zone, with a false activation rate of less than 2%, thereby achieving a closed-loop treatment of "identification → isolation → purification → prevention of diffusion".

[0098] In order to perform the corresponding steps in the above method embodiments and various possible implementations, an implementation of an odor treatment device is given below.

[0099] Please refer to Figure 4 , Figure 4 A block diagram of an odor treatment device 100 provided in an embodiment of this application is shown. The odor treatment device 100 is applied to... Figure 1 The controller 11 includes: an acquisition module 101, an odor source location module 102, and an odor purification module 103.

[0100] The acquisition module 101 is used to acquire the detection values ​​of each gas sensor corresponding to each storage zone according to a set time interval.

[0101] The odor source location module 102 is used to generate the measured concentration and odor type of each storage zone based on the detection values ​​of each gas sensor corresponding to each storage zone; calculate the probability that each storage zone is an odor source based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating condition; and determine the odor source zone from all storage zones based on the measured concentration of each storage zone and the probability that each storage zone is an odor source.

[0102] Odor purification module 103 is used to perform targeted purification of odor source zones according to the odor type of the odor source zone.

[0103] Optionally, the odor source location module 102 performs a method to generate the measured concentration and odor type of each storage zone based on the detection values ​​of each gas sensor corresponding to each storage zone, including: obtaining sensor reference values, which are the average detection values ​​of all gas sensors under clean air conditions within a set time period each day; for each storage zone, using the sensor reference values, normalizing the detection values ​​of each gas sensor corresponding to the storage zone to obtain the odor feature vector of the storage zone; performing mathematical transformation on the odor feature vector to obtain the measured concentration of the storage zone; and determining the odor type of the storage zone based on the sensor reference values ​​and the detection values ​​of each gas sensor corresponding to the storage zone.

[0104] Optionally, the multiple gas sensors include a first gas sensor, a second gas sensor, and a third gas sensor; the odor source localization module 102 performs a method of normalizing the detection values ​​of each gas sensor corresponding to the storage zone using the sensor reference value to obtain the odor feature vector of the storage zone, including: calculating the ratio of the detection values ​​of the first gas sensor, the second gas sensor, and the third gas sensor to the sensor reference value respectively to obtain the odor feature vector; The odor source location module 102 executes a method to determine the odor type of the storage zone based on the sensor reference value and the detection values ​​of each gas sensor corresponding to the storage zone, including: if the ratio of the detection value of the first gas sensor to the detection value of the third gas sensor is greater than a first threshold and the ratio to the sensor reference value is greater than a second threshold, then the odor type is determined to be protein putrefaction; if the ratio of the detection value of the third gas sensor to the detection value of the first gas sensor is greater than a third threshold and the ratio to the sensor reference value is greater than a fourth threshold, then the odor type is determined to be carbohydrate fermentation; if neither of the above two conditions is met and the detection value of the second gas sensor is continuously greater than a fifth threshold within a first set time period, then the odor type is determined to be an unknown odor.

[0105] Optionally, the airflow transfer model includes a predicted concentration matrix for each storage zone. The predicted concentration matrix includes the relative concentration percentage of the odor in each storage zone when the corresponding storage zone is an odor source, and the sum of all relative concentration percentages is 1. The odor source location module 102 executes a method to calculate the probability that each storage zone is an odor source based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating condition. This method includes: for any target storage zone, obtaining the predicted concentration matrix of the target storage zone from the target airflow transfer model; calculating the scaling factor of the target storage zone based on the predicted concentration matrix and the measured concentration of each storage zone; scaling the predicted concentration matrix based on the scaling factor to obtain a scaled predicted concentration matrix; calculating the matching score of the target storage zone based on the scaled predicted concentration matrix and the measured concentration of each storage zone; traversing each storage zone to obtain the matching score of each storage zone; and calculating the probability that each storage zone is an odor source based on the matching score of each storage zone.

[0106] Optionally, the odor source location module 102 performs a method of determining the odor source zone from all storage zones based on the measured concentration of each storage zone and the probability that each storage zone is an odor source, including: determining the storage zone with a probability greater than a first preset threshold and a measured concentration that is continuously greater than a second preset threshold within a second set time period as the odor source zone.

[0107] Optionally, the odor type includes one of protein putrefaction, carbohydrate fermentation, and unknown odor; each storage zone is equipped with an electric damper in the return air duct between other storage zones, and each storage zone is equipped with a purification device that integrates an ultraviolet LED array and a plasma generator; the odor purification module 103 is specifically used to: close the electric damper in the return air duct between the odor source zone and other storage zones, and adjust the guide vane of the low-temperature storage equipment to make the airflow of the other storage zones bypass the odor source zone; if the odor type is protein putrefaction, start the ultraviolet LED array corresponding to the odor source zone to run for a preset time; if the odor type is carbohydrate fermentation, start the plasma generator corresponding to the odor source zone; if the odor type is unknown odor, control the ultraviolet LED array and plasma generator corresponding to the odor source zone to alternately start and stop.

[0108] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the odor treatment device 100 described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0109] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by the controller 11, implements the odor treatment method disclosed in the following embodiments.

[0110] In summary, the odor treatment method, apparatus, low-temperature refrigeration equipment, and storage medium provided in this application deploy multiple gas sensors in each storage compartment of the low-temperature storage equipment. Simultaneously, the detection values ​​of each gas sensor are acquired at set time intervals, and the measured concentration and odor type of each storage compartment are generated based on the detection values. Then, combined with a pre-stored airflow transfer model corresponding to the current fan operating conditions, the probability of each storage compartment being an odor source is calculated. Next, the odor source compartment is located based on the measured concentration and probability of being an odor source in each storage compartment. Finally, targeted purification matching the odor type is performed on the odor source compartment, thereby enabling targeted odor removal at the source, improving purification efficiency, and reducing energy consumption.

[0111] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for treating odors, characterized in that, A controller for a cryogenic storage device, wherein each storage compartment of the cryogenic storage device is equipped with multiple gas sensors for detecting various gases; the controller pre-stores an airflow transfer model corresponding to each fan operating condition, the airflow transfer model representing the relative concentration percentage of an odor in each storage compartment when an odor source is identified under the corresponding fan operating condition; the method includes: According to the set time interval, the detection values ​​of each gas sensor corresponding to each storage zone are obtained; Based on the detection values ​​of each gas sensor corresponding to each storage zone, the measured concentration and odor type of each storage zone are generated; Based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating condition, the probability that each storage zone is an odor source is calculated. Based on the measured concentration of each of the storage zones and the probability that each of the storage zones is an odor source, odor source zones are determined from all the storage zones; Based on the odor type of the odor source zone, the odor source zone is targeted for purification.

2. The odor treatment method as described in claim 1, characterized in that, The step of generating the measured concentration and odor type for each storage zone based on the detection values ​​of each gas sensor corresponding to each storage zone includes: Obtain the sensor reference value, which is the average detection value of all gas sensors under clean air conditions within a set time period each day; For each storage zone, the detection values ​​of each gas sensor corresponding to the storage zone are normalized using the sensor reference value to obtain the odor feature vector of the storage zone. The odor feature vector is mathematically transformed to obtain the measured concentration of the storage zone; The odor type of the storage zone is determined based on the sensor reference value and the detection values ​​of each gas sensor corresponding to the storage zone.

3. The odor treatment method as described in claim 2, characterized in that, The plurality of gas sensors includes a first gas sensor, a second gas sensor, and a third gas sensor; The step of normalizing the detection values ​​of each gas sensor corresponding to the storage zone using the sensor reference value to obtain the odor feature vector of the storage zone includes: The odor feature vector is obtained by calculating the ratio of the detection values ​​of the first gas sensor, the second gas sensor, and the third gas sensor to the sensor reference value, respectively. The step of determining the odor type of the storage zone based on the sensor reference value and the detection values ​​of each gas sensor corresponding to the storage zone includes: If the ratio of the detection value of the first gas sensor to the detection value of the third gas sensor is greater than a first threshold and the ratio of the detection value of the sensor to the reference value is greater than a second threshold, then the odor type is determined to be protein putrefaction. If the ratio of the detection value of the third gas sensor to the detection value of the first gas sensor is greater than a third threshold and the ratio of the detection value of the sensor to the reference value is greater than a fourth threshold, then the odor type is determined to be carbohydrate fermentation. If neither of the above two conditions is met, and the detection value of the second gas sensor is continuously greater than the fifth threshold within the first set time period, then the odor type is determined to be an unknown odor.

4. The odor treatment method as described in claim 1, characterized in that, The airflow transfer model includes a predicted concentration matrix for each of the storage zones. The predicted concentration matrix includes the relative concentration percentage of the odor in each storage zone when the corresponding storage zone is an odor source, and the sum of all relative concentration percentages is 1. The method for calculating the probability that each storage zone is an odor source based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating conditions includes: For any target storage zone, the predicted concentration matrix of the target storage zone is obtained from the target airflow transfer model; Based on the predicted concentration matrix and the measured concentration of each of the storage zones, the scaling factor of the target storage zone is calculated; The predicted concentration matrix is ​​scaled according to the scaling factor to obtain the scaled predicted concentration matrix; The matching score of the target storage partition is calculated based on the scaled predicted concentration matrix and the measured concentration of each storage partition. Traverse each of the storage partitions to obtain the matching score for each of the storage partitions; Based on the matching score of each storage compartment, the probability that each storage compartment is a source of odor is calculated.

5. The odor treatment method as described in claim 4, characterized in that, The scaling factor satisfies the following formula: in, This represents the scaling factor of the j-th storage partition. N represents the total number of storage zones. This represents the measured concentration in the j-th storage zone; Let represent the predicted concentration matrix for the j-th storage zone, and s represent the target airflow transfer model; express The L2 norm; The scaled predicted concentration matrix satisfies the following formula: in, Represents the scaled predicted concentration matrix for the j-th storage partition; The matching score satisfies the following formula: in, This represents the matching score of the j-th storage partition; The probability that the storage area is a source of odor satisfies the following formula: in, This represents the matching score of the k-th storage partition.

6. The odor treatment method as described in claim 1, characterized in that, The step of determining the odor source zone from all the storage zones based on the measured concentration of each of the storage zones and the probability that each of the storage zones is an odor source includes: The storage area where the probability is greater than the first preset threshold and the measured concentration is continuously greater than the second preset threshold within a second set time period is determined as the odor source area.

7. The odor treatment method as described in claim 1, characterized in that, The odor type includes one of protein putrefaction, carbohydrate fermentation and unknown odor; each of the storage compartments is equipped with an electric damper in the return air channel between the storage compartments and other storage compartments, and each of the storage compartments is equipped with a purification device, which integrates an ultraviolet LED array and a plasma generator; The step of targeting and purifying the odor source area according to the odor type includes: Close the electric damper in the return air passage between the odor source zone and other storage zones, and adjust the guide plate of the low-temperature storage equipment so that the airflow of the other storage zones bypasses the odor source zone. If the odor type is protein putrefaction, then start the ultraviolet LED array corresponding to the odor source partition to run for a preset time; If the odor type is carbohydrate fermentation, then the plasma generator corresponding to the odor source zone is activated; If the odor type is an unknown odor, then control the ultraviolet LED array and plasma generator corresponding to the odor source zone to alternately start and stop operation.

8. An odor treatment device, characterized in that, A controller for a cryogenic storage device, wherein each storage compartment of the cryogenic storage device is equipped with multiple gas sensors for detecting various gases; the controller pre-stores an airflow transfer model corresponding to each fan operating condition, the airflow transfer model representing the relative concentration percentage of an odor in each storage compartment when an odor source is identified under the corresponding fan operating condition; the device includes: The acquisition module is used to acquire the detection values ​​of each gas sensor corresponding to each of the storage zones at set time intervals; An odor source location module is used to generate the measured concentration and odor type of each storage zone based on the detection values ​​of each gas sensor corresponding to each storage zone; calculate the probability that each storage zone is an odor source based on the measured concentration of each storage zone and the target airflow transfer model corresponding to the current fan operating condition; and determine the odor source zone from all the storage zones according to the measured concentration of each storage zone and the probability that each storage zone is an odor source. The odor purification module is used to perform targeted purification of the odor source zone according to the odor type of the odor source zone.

9. A low-temperature storage device, characterized in that, It includes a controller and a memory, the memory being used to store a program, and the controller being used to implement the odor treatment method according to any one of claims 1-7 when executing the program.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by the controller, implements the odor treatment method as described in any one of claims 1-7.

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