Method, device, equipment and medium for evaluating space environment negative ions

Abstract

The application discloses a kind of space environment negative ion evaluation method, device, equipment and medium, the space environment negative ion evaluation method is by obtaining indoor environment parameter and equipment operating state parameter when air conditioner runs;Subsequently, the initial concentration of outlet is dynamically calculated based on the above parameters Negative ion decay rate;Further, the concentration distribution model is constructed in combination with spatial position relationship, the negative ion concentration distribution data of each position in target area is calculated;Finally, the data is sent to display terminal, and the space negative ion visualization view is generated and shown by preset mapping rule.The method effectively solves the problem that the influence of negative ion environment cannot be intuitively reflected, significantly improves the perception and acceptance of the user to air conditioning purification function.

Description

Technical Field

[0001] This invention relates to the field of smart home technology, and in particular to a method, apparatus, device and medium for assessing negative ions in a spatial environment. Background Technology

[0002] As air conditioning products become increasingly feature-rich, more and more air conditioning units are integrating negative ion generators to achieve air purification, sterilization, and improvement of indoor air quality by releasing negative ions. However, current technologies for detecting and displaying negative ion functions typically only provide a simple display of the negative ion generator's operating status, single-point ion concentration, or changes in air quality. They fail to adequately reflect the actual distribution of negative ions released by the air conditioning unit in different indoor locations and their dynamic impact on environmental factors such as distance, wind speed, humidity, and particulate matter.

[0003] Specifically, most existing negative ion detection methods employ fixed-location sampling or localized concentration measurement, often only providing ion concentration data for a specific moment and area. They cannot dynamically extrapolate the attenuation and diffusion processes of negative ions in the air by considering factors such as the operating status of the air conditioning unit, the airflow conditions at the vents, and indoor environmental parameters. Therefore, while existing technologies can reflect whether negative ions are released to some extent, they cannot visually represent the differences in negative ion concentration distribution within an indoor space, nor can they demonstrate the specific purification impact of air conditioning units on the target space.

[0004] Because the concentration of negative ions varies significantly across different spatial locations and is highly dependent on environmental conditions, and current technologies lack a visual representation of this spatial distribution pattern, users often only perceive whether the air conditioner's negative ion function is "on," but cannot directly observe the actual range of negative ions' effect in the room, their concentration strength, and their attenuation trend. This makes it difficult to develop a clear understanding and acceptance of the air conditioner's negative ion purification function. Especially in complex indoor environments with frequent changes in air conditioner airflow, relying solely on localized detection results makes it even more difficult to accurately reflect the impact of negative ions on the entire target space.

[0005] Therefore, existing negative ion detection and feedback methods cannot intuitively demonstrate the specific impact of negative ions generated by air conditioning equipment on the environment, making it difficult for users to establish an objective understanding of the actual effect of the air conditioner's negative ion purification function, and consequently failing to gain user recognition of the air conditioner's negative ion purification function. Summary of the Invention

[0006] The embodiments of the present invention provide a method, apparatus, device and medium for assessing negative ions in the spatial environment, aiming to solve the technical problem that the existing negative ion detection methods cannot intuitively reflect the specific impact of negative ions generated by air conditioning equipment in the environment, thus failing to gain user recognition of the negative ion purification function of air conditioning.

[0007] In a first aspect, embodiments of the present invention provide a method for assessing negative ions in a spatial environment. The method includes: acquiring indoor environmental parameters and operating status parameters of an air conditioning device during operation; dynamically calculating the attenuation rate of negative ions in the air and the initial negative ion concentration at the air outlet of the air conditioning device based on the indoor environmental parameters and the operating status parameters; constructing a spatial concentration distribution model based on the initial negative ion concentration, the attenuation rate, and a preset spatial positional relationship, and calculating negative ion concentration distribution data at each spatial location within a target spatial area; and sending the negative ion concentration distribution data to a display terminal, wherein the display terminal generates and displays a visual view of negative ions in the spatial environment of the target spatial area based on a preset concentration-visual mapping rule.

[0008] Secondly, embodiments of the present invention also provide a space environment negative ion assessment device for performing the space environment negative ion assessment method as described above.

[0009] Thirdly, embodiments of the present invention also provide a computer device, the computer device including a memory and a processor connected to the memory; the memory is used to store a computer program; the processor is used to run the computer program stored in the memory to perform the steps of the above-described space environment negative ion assessment method.

[0010] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, can implement the steps of the above-described method for evaluating negative ions in a spatial environment.

[0011] Compared with the prior art, the beneficial effects of the present invention are: In the technical solution of this invention, the spatial environment negative ion assessment method acquires indoor environmental parameters and equipment operating status parameters during air conditioner operation; then, based on the above parameters, dynamically calculates the negative ion attenuation rate and the initial concentration at the air outlet; further, it constructs a concentration distribution model by combining spatial location relationships to estimate the negative ion concentration distribution data at each location within the target area; finally, the data is sent to a display terminal, and a spatial negative ion visualization view is generated and displayed through preset mapping rules. This method effectively solves the problem that the impact of negative ions on the environment cannot be intuitively reflected, significantly improving users' perception and acceptance of the air conditioner's purification function. Attached Figure Description

[0012] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A flowchart of the spatial environment negative ion assessment method provided by the present invention; Figure 2 The first sub-flowchart of the spatial environment negative ion assessment method provided by the present invention; Figure 3 A sub-flowchart of the second sub-flowchart of the spatial environment negative ion assessment method provided by the present invention; Figure 4 The third sub-flowchart of the spatial environment negative ion assessment method provided by the present invention; Figure 5 The fourth sub-flowchart of the spatial environment negative ion assessment method provided by the present invention; Figure 6 The fifth sub-flowchart of the spatial environment negative ion assessment method provided by the present invention; Figure 7 The sixth sub-flowchart of the spatial environment negative ion assessment method provided by the present invention; Figure 8 A schematic block diagram of a unit of the spatial environment negative ion assessment device provided by the present invention; Figure 9 A schematic block diagram of a computer device provided in an embodiment of the present invention; Figure 10 A colorimetric mapping table for the spatial environment negative ion assessment method provided by this invention. Detailed Implementation

[0014] 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, not all, of the embodiments of the present invention. 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.

[0015] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0016] It should also be understood that the terminology used in this specification is for the purpose of describing embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0017] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0018] In order to solve the technical problem that existing negative ion detection methods cannot intuitively reflect the specific impact of negative ions generated by air conditioning equipment on the environment, thus failing to obtain user recognition of the negative ion purification function of air conditioning, this invention discloses a spatial environment negative ion assessment method.

[0019] Reference Figures 1 to 7 The method includes the following steps: S110. Obtain the indoor environmental parameters and the operating status parameters of the air conditioning equipment during operation; S120. Based on the indoor environmental parameters and the operating status parameters, dynamically calculate the attenuation rate of negative ions in the air and the initial negative ion concentration at the air outlet of the air conditioning unit. S130. Based on the initial negative ion concentration, the decay rate, and the preset spatial position relationship, construct a spatial concentration distribution model and calculate the negative ion concentration distribution data of each spatial position within the target spatial region. S140. The negative ion concentration distribution data is sent to the display terminal, which generates and displays a spatial environment negative ion visualization view of the target spatial area based on a preset concentration and visual mapping rule.

[0020] The air conditioning unit used in this method integrates temperature and humidity sensors and particulate matter sensors inside its air inlet. These environmental sensors continuously collect raw environmental data within the target space area at a fixed sampling frequency. The main control unit of the air conditioning unit performs exponential moving average filtering on the collected raw environmental data to eliminate instantaneous noise caused by airflow pulsation and electrical interference. It also performs physical boundary verification on the filtered data, discarding abnormal sampling values ​​that exceed reasonable physical ranges and retaining valid environmental parameters. Simultaneously, the main control unit reads the current fan speed control command in real time, stamps the valid environmental parameters and fan speed control command with a unified system clock, and aligns them in time to generate indoor environmental parameters and air conditioning unit operating status parameters for subsequent calculations.

[0021] After acquiring the aligned parameters, the main control unit of the air conditioning unit dynamically calculates the attenuation rate of negative ions in the air and the initial negative ion concentration at the air outlet of the air conditioning unit based on indoor environmental parameters and the operating status parameters of the air conditioning unit. Specifically, the main control unit calls the baseline attenuation rate under preset benchmark operating conditions, combines the humidity, particulate matter concentration, and temperature parameters in the indoor environmental parameters, calculates the environmental correction coefficient through a preset empirical attenuation model, and couples the baseline attenuation rate and the environmental correction coefficient to obtain the theoretical attenuation rate. The environmental correction coefficient is the normalized proportion of the attenuation rate increment corresponding to the environmental deviation from the benchmark operating conditions. To prevent calculation overflow caused by extreme environmental parameters, the main control unit performs numerical range clamping protection on the theoretical attenuation rate and introduces an aging attenuation factor corresponding to the cumulative running time of the negative ion generator for compensation, finally outputting an accurate attenuation rate. When calculating the initial negative ion concentration, the main control unit queries the preset ion release mapping table according to the fan control command to obtain the current ion release and air supply speed. It then calculates the basic concentration value by combining the effective cross-sectional area of ​​the air outlet of the air conditioning equipment. Subsequently, the basic concentration value is converted to units and dimensions, and temperature volume correction coefficient and turbulent mixing efficiency coefficient are introduced for compensation calculation to obtain the initial negative ion concentration at the air outlet of the air conditioning equipment.

[0022] Based on the calculated initial negative ion concentration, attenuation rate, and preset spatial positional relationships, the main control unit of the air conditioning equipment constructs a spatial concentration distribution model and calculates the negative ion concentration distribution data at each spatial location within the target spatial area. The main control unit establishes a three-dimensional spatial coordinate system, including the air outlet vector angle, with the air outlet of the air conditioning equipment as the spatial origin. It divides the target spatial area into multiple grid cells of preset sizes and calculates the axial travel distance and lateral vertical distance of each grid cell relative to the spatial origin. The main control unit calculates the axial attenuation concentration of each grid cell based on the axial travel distance and attenuation rate. Then, based on the lateral vertical distance, it introduces a lateral diffusion correction term and combines it with a global attenuation term corresponding to the room air exchange rate to perform spatial diffusion correction on the axial attenuation concentration, thereby obtaining the negative ion concentration distribution data for each grid cell. During the preset transition period after the air conditioning equipment starts up or switches operating states, the spatial concentration distribution model updates the negative ion concentration distribution data in a transient accumulation manner. When the rate of change of the negative ion concentration distribution data within a continuous time window is lower than a preset convergence threshold, the main control unit automatically switches to a steady-state output mode and performs linear interpolation for smooth transition at the moment of mode switching, ensuring the continuity and stability of the concentration data output.

[0023] The main control unit of the air conditioning unit sends the calculated negative ion concentration distribution data to the display terminal via its built-in wireless communication module. Upon receiving the negative ion concentration distribution data, the display terminal generates and displays a visual view of the negative ion environment in the target space area based on preset concentration-visual mapping rules. The display terminal first obtains room outline information through camera scanning or manual user input, generating a two-dimensional grid matrix covering the target space area. It then performs bilinear interpolation on the negative ion concentration distribution data of adjacent grid cells in the two-dimensional grid matrix to generate a smoothly transitioning concentration isosurface. Subsequently, the display terminal dynamically matches a preset color gradient mapping table based on the numerical range of the concentration isosurface, rendering the concentration isosurface as a color gradient view and displaying it on the display terminal's interactive interface. To improve the user experience in weak network environments, an adaptive data push strategy is adopted between the display terminal and the air conditioning unit. The update frequency of the negative ion concentration distribution data is dynamically adjusted based on the display terminal's interaction status and network communication quality. When network communication is interrupted, the display terminal automatically switches to a local cache reading mode, using historical negative ion concentration distribution data pre-cached by the air conditioning unit's main control unit to maintain continuous rendering of the visual view.

[0024] Based on the specific implementation methods described above, this method can be further extended to intelligent safety control and multi-source data fusion scenarios. For example, when the display terminal detects that the negative ion concentration distribution data of grid cells outside a specific safety distance within the target space area continuously exceeds a preset warning threshold, the display terminal can push a high-concentration warning to the user and, after receiving the user's confirmed optimization command, issue a closed-loop control strategy to the air conditioning equipment. After receiving the control strategy, the main control unit of the air conditioning equipment smoothly adjusts the fan speed through a proportional-integral-differential algorithm and drives the sweeping mechanism to adjust to a preset elevation angle position, utilizing the natural diffusion characteristics of airflow to quickly dilute the negative ion concentration in the human activity area. In addition, the spatial concentration distribution model can further integrate the detection data from carbon dioxide concentration sensors or volatile organic compound sensors to construct a multi-pollutant synergistic decay assessment model, enabling the spatial environmental negative ion visualization view generated by the display terminal to simultaneously reflect the comprehensive air quality index, thereby providing users with a more comprehensive environmental health assessment and interactive experience.

[0025] The method in this embodiment transforms the abstract and invisible negative ion concentration into a quantifiable, perceptible, and interactive digital visual image through physical attenuation modeling and multidimensional spatial mapping algorithms. This allows users to observe the physical law of "high concentration at close range and low concentration at a distance," completely breaking the "invisible and intangible" black box of negative ion function experience. This significantly enhances users' recognition of the negative ion purification function of air conditioners and the market competitiveness of the product.

[0026] In one embodiment, step S110 includes: S111. The environmental sensor integrated at the air inlet of the air conditioning equipment collects raw environmental data at a preset sampling frequency. The raw environmental data includes the temperature, humidity and particulate matter concentration in the target space area. S112. Filter and physically verify the original environmental data to remove abnormal data and retain valid environmental parameters. S113. Obtain the current fan speed control command of the air conditioning equipment, and align the effective environmental parameters with the fan speed control command using timestamps to generate the indoor environmental parameters and the operating status parameters.

[0027] After the air conditioner is started, the temperature and humidity detection module and the particulate matter concentration detection module continuously sample the air in the target space area at a preset sampling frequency. The environmental sensors convert the collected physical quantities into raw environmental data, which explicitly includes the real-time temperature, humidity, and particulate matter concentration values ​​in the target space area. The environmental sensors transmit the raw environmental data to the main control unit of the air conditioning equipment in real time via an internal communication bus, ensuring the continuity and real-time nature of the data acquisition process.

[0028] After acquiring the raw environmental data, the system filters and performs physical boundary checks, eliminating outliers and retaining valid environmental parameters. Specifically, to eliminate sampling jitter caused by sensor transient noise, electrical interference, and airflow pulsations, the system uses exponential moving average filtering or median filtering algorithms to filter the raw environmental data. Simultaneously, the system performs strict physical boundary checks, ensuring that temperature, humidity, and particulate matter concentration remain within the valid acquisition range. If the acquired raw environmental data exceeds these physical boundaries, the system classifies it as outlier and discards it. If multiple consecutive sampling data exceed the physical boundaries or packet loss occurs, the system automatically identifies a transient anomaly in the environmental sensor, marks an internal fault flag, and uses the data from the previous valid time window as valid environmental parameters, thereby preventing dirty data from being injected into subsequent calculation models and ensuring system robustness.

[0029] In one embodiment, step S120 includes: S121. Obtain the reference attenuation rate under the preset reference operating conditions; S122. Calculate the environmental correction coefficient based on the humidity parameter, particulate matter concentration parameter and temperature parameter in the indoor environmental parameters; S123. Couple the reference attenuation rate with the environmental correction coefficient to obtain the theoretical attenuation rate; S124. The theoretical attenuation rate is clamped within a numerical range and the attenuation rate is calculated by combining the aging attenuation factor corresponding to the cumulative operating time of the negative ion generator in the air conditioning equipment.

[0030] The system first obtains the baseline attenuation rate under preset baseline conditions. These preset baseline conditions are typically set as a typical indoor standard environment, such as a relative humidity of 50%, a temperature of 25 degrees Celsius, and a particulate matter concentration of 30 micrograms per cubic meter. Under these preset baseline conditions, the baseline attenuation rate, calibrated through experimental testing, is set to 85%, meaning an 85% reduction in negative ions per second. Subsequently, based on the humidity, particulate matter concentration, and temperature parameters within the indoor environment, the system calculates an environmental correction factor and couples the baseline attenuation rate with the environmental correction factor to obtain the theoretical attenuation rate. The specific coupling calculation formula is as follows:

[0031] In this formula, k represents the theoretical decay rate. RH represents the baseline decay rate, PM represents the particulate matter concentration, and T represents the temperature.

[0032] The environmental correction coefficient is calculated using a preset empirical attenuation model. This model uses a preset baseline condition as a reference point and characterizes the relative changes in the intensity of negative ion recombination and adsorption dissipation when indoor environmental conditions deviate from the preset baseline condition. Specifically, the humidity deviation between the humidity parameter and the baseline humidity, the particulate matter concentration deviation between the particulate matter parameter and the baseline particulate matter concentration, and the temperature deviation between the baseline temperature and the temperature parameter are calculated. These three deviations are multiplied by their corresponding environmental sensitivity coefficients and summed to obtain the environmental deviation index. The environmental deviation index is then negatively exponentially and normalized to obtain the environmental correction coefficient, expressed as follows:

[0033] Wherein, F represents the environmental correction coefficient, ranging from 0 to 1; RH represents the humidity parameter; PM represents the particulate matter concentration parameter; and T represents the temperature parameter. In the formula, 0.03 represents the relative humidity sensitivity coefficient, measured per percentage of relative humidity, used to characterize the degree to which the increased water molecule content in the air leads to enhanced negative ion hydration and ion recombination when relative humidity increases; 0.01 represents the particulate matter concentration sensitivity coefficient, measured per microgram per cubic meter, used to characterize the degree to which aerosol particles enhance the adsorption and capture of negative ions when particulate matter concentration increases; and 0.01 represents the temperature sensitivity coefficient, measured per degree Celsius, used to characterize the degree to which the decreased thermal motion activity of air molecules and the decreased mobility of negative ions lead to an increased recombination probability when temperature decreases. The above environmental sensitivity coefficients are obtained through experimental testing and calibration. Specifically, near a preset baseline condition, with all other environmental parameters fixed and only one environmental parameter changed, the actual attenuation rate of negative ions under different parameter values ​​is measured. The test data is then fitted using the above expression for the environmental correction coefficient to determine the value of each environmental sensitivity coefficient.

[0034] After obtaining the environmental correction factor, the system couples the reference attenuation rate with the environmental correction factor to obtain the theoretical attenuation rate, which is expressed as follows:

[0035] As can be seen from this expression, it is the coupling operation formula mentioned above. When the indoor environmental conditions are equal to the preset benchmark conditions, the environmental deviation index is zero, the environmental correction coefficient is zero, and the theoretical attenuation rate is equal to the benchmark attenuation rate. When the relative humidity increases, the particulate matter concentration increases, or the temperature decreases, the environmental deviation index increases, the environmental correction coefficient increases accordingly, and the theoretical attenuation rate increases accordingly. Furthermore, since the environmental correction coefficient is always less than 1 and the theoretical attenuation rate is always less than 1, there will be no non-physical result where the attenuation ratio is greater than the total number of negative ions.

[0036] Using the above formula, the system can quantify the exacerbating effect of increased humidity, increased particulate matter, or decreased temperature on the collision and recombination intensity of negative ions with water molecules, positive ions, and charged aerosols in the air. For example, the theoretical attenuation rate calculated under typical conditions is 85.00%, while under conditions of high humidity, high particulate matter, and low temperature, such as a relative humidity of 70%, a particulate matter concentration of 100 micrograms per cubic meter, and a temperature of 15 degrees Celsius, the calculated theoretical attenuation rate will rise to 96.30%.

[0037] After obtaining the theoretical decay rate, the system performs numerical range clamping protection on the theoretical decay rate and calculates the final decay rate by combining it with the aging decay factor corresponding to the cumulative operating time of the negative ion generator in the air conditioning unit. Specifically, to prevent floating-point overflow or negative value anomalies in the embedded microcontroller caused by substituting extreme environmental parameters into the exponential function, the system performs numerical range clamping protection on the theoretical decay rate, forcibly limiting the value of the theoretical decay rate to a safe range of 0.5 to 0.99. The lower limit of the safe range is used to avoid extreme combinations of environmental sensitivity coefficient values ​​that would lead to an excessively low decay rate, causing the subsequent concentration distribution model to lose its discriminative power. The upper limit is used to avoid a decay rate value of 1 that would result in a calculated negative ion concentration that is always zero. At the same time, considering that the corona discharge needle of the negative ion generator in the air conditioning unit will undergo physical wear and tear with the increase of usage time, the system introduces an aging decay factor that decays exponentially with the cumulative operating time. The specific formula for calculating the aging decay factor is as follows:

[0038] in, Here, t represents the factory-calibrated aging factor, and t represents the cumulative operating time. The system multiplies the theoretical decay rate after numerical interval clamping protection by the aging decay factor to calculate the final actual decay rate used in the spatial concentration distribution model.

[0039] When the system recognizes that it is currently in an extreme operating condition with superimposed ultra-high humidity and extremely high particulate matter concentration, in order to ensure the real-time performance and stability of the embedded microcontroller, the system will automatically pause the calculation of the above empirical formula and downgrade to a bilinear interpolation lookup table mode, directly obtaining the current decay rate by querying the extreme operating condition decay rate mapping table pre-stored in local memory.

[0040] This embodiment ensures the physical authenticity and scientific validity of the attenuation rate calculation results in complex and variable indoor environments, and also eliminates the risk of algorithm crashes caused by extreme parameters and evaluation errors caused by equipment aging. In one embodiment, step S120 further includes: S125. According to the windshield control command, query the preset ion release mapping table to obtain the current ion release and air supply speed. S126. Calculate the basic concentration value based on the current ion release amount, the air supply velocity, and the effective cross-sectional area of ​​the air outlet of the air conditioning equipment; S127. The basic concentration value is converted to a unit dimension, and a temperature-volume correction coefficient and a turbulent mixing efficiency coefficient are introduced for compensation calculation to obtain the initial negative ion concentration.

[0041] The system queries a preset ion release mapping table based on the fan speed control command to obtain the current ion release rate and airflow velocity. After reading the current fan speed control command, the main control unit of the air conditioning unit accesses the preset ion release mapping table stored in local non-volatile memory. This table records the release capacity of the negative ion generator and the airflow capacity of the air conditioning unit's fan under different fan speed settings. For example, when the fan speed control command is low, the current ion release rate is 5.0 × 10^7 ions / s, and the airflow velocity is 1 m / s; when the fan speed control command is medium, the current ion release rate is 7.5 × 10^7 ions / s, and the airflow velocity is 1.5 m / s; when the fan speed control command is high, the current ion release rate is 1.0 × 10^8 ions / s, and the airflow velocity is 2 m / s.

[0042] After obtaining the current ion release rate and supply air velocity, the system calculates the baseline concentration value based on these parameters and the effective cross-sectional area of ​​the air outlet. Specifically, the system calls a preset concentration calculation formula, dividing the current ion release rate by the product of the supply air velocity and the effective cross-sectional area of ​​the air outlet to obtain the baseline concentration value. The formula for calculating the baseline concentration value is as follows:

[0043] in, Q represents the baseline concentration value, A represents the current ion release amount, and v represents the effective cross-sectional area of ​​the air outlet.

[0044] The effective cross-sectional area of ​​the air outlet is a fixed physical parameter specified by the manufacturer when the air conditioning equipment leaves the factory, and its value typically ranges from 0.03 to 0.05 square meters. For example, when the effective cross-sectional area of ​​the air outlet is set to 0.04 square meters, and the air conditioning equipment is set to a low fan speed (i.e., the current ion release is 5.0 × 10^7 ions / s, and the air supply velocity is 1 m / s), the calculated baseline concentration value is... It is 1.25 × 10^9 ions / m 3 .

[0045] After calculating the baseline concentration value, the system performs a unit dimension conversion on the baseline concentration value and introduces a temperature-volume correction coefficient and a turbulent mixing efficiency coefficient for compensation calculation to obtain the initial negative ion concentration. Since the physical dimension of the baseline concentration value is ions per cubic meter (ions / m³), the initial negative ion concentration is calculated accordingly. 3 Subsequent spatial concentration distribution models and visualizations typically use the number of ions per cubic centimeter (ions / cm³). 3 As the standard unit of measurement, the system first performs a unit conversion on the basic concentration value, that is, divides the basic concentration value by 10^6.

[0046] Subsequently, in order to eliminate the concentration calculation deviation caused by the expansion or contraction of air volume due to changes in indoor temperature, the system introduces a temperature-volume correction coefficient. The specific formula for calculating the temperature-volume correction coefficient is as follows:

[0047] Where T represents the real-time temperature in Celsius within the indoor environment, and 273.15 refers to the conversion constant between Celsius and thermodynamic temperature. Furthermore, considering that the airflow at the air outlet of the air conditioning unit is not an ideal uniform piston flow but rather involves complex eddies and mixing phenomena, the system further incorporates a turbulent mixing efficiency coefficient calibrated through computational fluid dynamics (CFD) simulation, typically ranging from 0.7 to 0.9, for compensation calculations.

[0048] Finally, the complete formula for calculating the initial negative ion concentration is:

[0049] in, This represents the initial negative ion concentration. This represents the turbulent mixing efficiency coefficient. Through the above multi-dimensional compensation calculations, the system can obtain an initial negative ion concentration that closely matches the real physical environment.

[0050] The solution in this embodiment not only solves the problems of inconsistent dimensions and deviations in idealized assumptions in the practical application of basic physical formulas, but also fully considers the combined effects of thermodynamic temperature volume effect and fluid dynamics turbulent mixing effect on the initial concentration, ensuring a high degree of consistency between the calculated initial negative ion concentration and the three dimensions of thermodynamics, fluid dynamics and engineering practice.

[0051] In one embodiment, step S130 includes: S131. Establish a three-dimensional spatial coordinate system including the air outlet vector angle, with the air outlet of the air conditioning equipment as the spatial origin; S132. Divide the target space region into multiple grid cells of preset size, and calculate the axial travel distance and lateral vertical distance of each grid cell relative to the origin of the space. S133. Based on the axial travel distance and the attenuation rate, calculate the axial attenuation concentration of each of the grid cells; S134. Based on the horizontal and vertical distance, a horizontal diffusion correction term is introduced, and combined with the global attenuation term corresponding to the room air exchange rate, the axial attenuation concentration is spatially diffused to correct for spatial diffusion, thereby obtaining the negative ion concentration distribution data of each grid unit. S135. During the preset transition period after the air conditioning equipment starts up or switches its operating state, update the negative ion concentration distribution data in a transient accumulation manner. S136. When the rate of change of the negative ion concentration distribution data within the continuous time window is lower than the preset convergence threshold, switch to steady-state output mode and perform linear interpolation for smooth transition at the moment of mode switching.

[0052] The system establishes a three-dimensional spatial coordinate system, including the air outlet vector angle, with the air outlet of the air conditioner as the spatial origin. The spatial origin is precisely anchored at the geometric center of the air outlet, and the air outlet vector angle is determined in real time based on the current position of the air guide plate and the sweeping state of the air conditioner, thus accurately defining the initial emission direction of the negative ion jet in three-dimensional space. Subsequently, the system divides the target space area into multiple grid cells of preset sizes and calculates the axial travel distance and lateral vertical distance of each grid cell relative to the spatial origin. Taking a practical application scenario as an example, if the user inputs the room dimensions of the target space area as 4 meters long and 5 meters wide through the display terminal, the system automatically divides the two-dimensional planar projection of the target space area into 500 grid cells of 20×25 according to the preset size of 0.2 meters × 0.2 meters. For any grid cell, the system uses a three-dimensional spatial analytical geometry algorithm to calculate the projection distance of the center point of the grid cell along the jet axis as the axial travel distance, and simultaneously calculates the shortest vertical distance from the center point of the grid cell to the jet axis as the lateral vertical distance.

[0053] After obtaining the precise spatial distance parameters, the system calculates the axial attenuation concentration of each grid cell based on the axial travel distance and attenuation rate. The specific formula for calculating the axial attenuation concentration is as follows:

[0054] In the above formula, Represents the axial attenuation concentration. The initial negative ion concentration is represented by , k by the decay rate, d by the axial travel distance, and v by the air supply velocity. This step quantifies the natural dissipation process of negative ions as they propel through the airflow and over time in a one-dimensional axial dimension. Taking typical indoor environmental conditions—50% relative humidity, 30 micrograms per cubic meter particulate matter concentration, and 25 degrees Celsius—as an example, the calculated decay rate k is 85%, i.e., k = 0.85, the air supply velocity v is 1 m / s, and the initial negative ion concentration at the air outlet is... 1,250,000 ions / cm 3 Substituting into the formula, the axial attenuation concentration at a distance of 1 meter along the axial path is approximately 530,500 ions / cm³. 3 At 2 meters, the concentration is approximately 224,300 ions / cm². 3 At 3 meters, the concentration is approximately 95,100 ions / cm. 3 At 4 meters, the concentration is approximately 40,300 ions / cm. 3At 5 meters, it is approximately 17,100 ions / cm. 3 This calculation result intuitively and accurately reflects the physical law that the concentration of negative ions decreases exponentially with increasing distance.

[0055] To ensure the spatial concentration distribution model closely matches the three-dimensional airflow organization of a real air conditioner, the system introduces a lateral diffusion correction term based on the horizontal and vertical distances. This, combined with a global attenuation term corresponding to the room's air exchange rate, corrects the axial attenuation concentration for spatial diffusion, resulting in negative ion concentration distribution data for each grid cell. Specifically, the system introduces a lateral diffusion coefficient proportional to the square root of the axial travel distance. The specific formula for calculating the lateral diffusion coefficient is as follows:

[0056] In this formula, The lateral diffusion coefficient represents the distance traveled dd along the axial direction, which is used to characterize the degree of diffusion of the negative ion jet on the cross section (i.e., the standard deviation of the Gaussian distribution); d represents the axial distance traveled by the grid cell relative to the origin of space; 0.15 is a preset empirical diffusion constant, which reflects the intensity of lateral turbulent diffusion under the air outlet structure of the air conditioning equipment and the indoor airflow environment. This constant is usually obtained by computational fluid dynamics (CFD) simulation or actual wind tunnel test calibration. The larger the value, the faster the jet diffuses in the lateral direction and the wider the coverage area.

[0057] A Gaussian distribution function is constructed based on the lateral diffusion coefficient as a lateral diffusion correction term, so that the negative ion concentration exhibits a natural diffusion attenuation characteristic with a high center and low edge on the cross section perpendicular to the jet axis. At the same time, the system obtains the room air change rate (ACH) of the target space area and constructs an exponential decay function as a global attenuation term to simulate the dilution effect of air exchange caused by infiltration through room door and window gaps and mechanical ventilation on the overall concentration.

[0058] Finally, the negative ion concentration distribution data of the grid cells is obtained by multiplying the axial attenuation concentration, the lateral diffusion correction term, and the global attenuation term. The complete spatial diffusion correction formula is as follows:

[0059] Where r represents the horizontal and vertical distance. represents the lateral diffusion coefficient, and t represents the running time.

[0060] During the dynamic evolution of the equipment operation, considering that the accumulation and diffusion of negative ions in space requires a certain amount of time, the system updates the negative ion concentration distribution data in a transient accumulation manner during the preset transition period after the air conditioning equipment starts up or switches operating states. In the transient accumulation mode, the system simulates the physical process of negative ion concentration gradually increasing from zero or the previous state and filling the space through time integration or discrete time step accumulation algorithms, avoiding abrupt changes in the initial instantaneous concentration data that violate physical common sense. When the rate of change of negative ion concentration distribution data within a continuous time window is lower than the preset convergence threshold, the system determines that the generation and decay of negative ions in the space have reached a dynamic equilibrium, and then switches to the steady-state output mode. At the moment of mode switching, the system performs linear interpolation for smooth transition, linearly fusing the final concentration value output by the transient accumulation mode with the initial concentration value of the steady-state output mode. This smooth transition mechanism ensures that the concentration data is continuous and without abrupt changes throughout the entire process from dynamic optimization to stable output, completely eliminating screen flickering or color level jumps that may occur when the display terminal renders the visualization view.

[0061] In one embodiment, step S140 includes: S141. Receive the concentration viewing request initiated by the display terminal, and forward the concentration viewing request to the main control unit of the air conditioning equipment through a wireless communication link; S142. The main control unit extracts the latest aligned negative ion concentration distribution data from the local cache, packages it into a structured data message, and sends it to the display terminal. S143. Based on the interaction status of the display terminal and the network communication quality, adaptively adjust the push frequency of the negative ion concentration distribution data.

[0062] The system first receives a concentration viewing request from the display terminal and forwards it to the main control unit of the air conditioning unit via a wireless communication link. When a user triggers the operation to view ion concentration on the display terminal's interactive interface, the display terminal generates a concentration viewing request. The concentration viewing request first undergoes authentication by the cloud server, and then the cloud server routes and forwards it to the air conditioning unit's built-in WIFI module via a wireless communication link based on IoT standard message queues. After receiving the concentration viewing request, the WIFI module communicates with the main control unit of the air conditioning unit via a UART serial port, forwarding the concentration viewing request to the main control unit.

[0063] After receiving a concentration viewing request, the main control unit of the air conditioner retrieves the latest aligned negative ion concentration distribution data from its local cache, packages it into a structured data message, and sends it to the display terminal. Specifically, the main control unit has a built-in local cache for storing historical data from the most recent operating cycle. It retrieves the latest timestamp-aligned negative ion concentration distribution data and corresponding environmental parameters from this cache, packages them into a JSON-formatted structured data message, and adds a cyclic redundancy check (CRC) code to the structured data message to prevent transmission errors. Subsequently, the main control unit sends the structured data message to the cloud server via a Wi-Fi module. The cloud server then forwards the structured data message directly to the display terminal, which receives and parses it to obtain the negative ion concentration distribution data.

[0064] During data transmission, the system adaptively adjusts the push frequency of negative ion concentration distribution data based on the interaction status of the display terminal and the network communication quality. Specifically, the system monitors the interface interaction status and network communication quality of the display terminal in real time. For example, when a user is statically browsing a visual view on the display terminal, the system sets the push frequency of negative ion concentration distribution data to once every 5 seconds; when the user performs high-frequency interactive operations such as dragging or zooming on the display terminal interface, the system increases the push frequency to once every 1 second; when the display terminal is in a screen-off state or the application is running in the background, the system automatically pauses high-frequency uploads, thereby ensuring a real-time interactive experience while effectively reducing network bandwidth consumption and the power consumption of the air conditioning unit's main control unit.

[0065] To ensure service availability in weak network environments, the system introduces a weak network degradation and reconnection mechanism. When the home network is interrupted or the cloud server times out, the display terminal automatically degrades to Bluetooth Low Energy Direct mode, directly reads the negative ion concentration distribution data from the local cache of the air conditioner's main control unit, and uses an exponential backoff algorithm to perform reconnection, ensuring the continuity and availability of the visualization view in complex network environments.

[0066] In one embodiment, step S140 further includes: S144. Based on the room outline information obtained by the display terminal, generate a two-dimensional grid matrix covering the target space area; S145. Perform interpolation on the negative ion concentration distribution data of adjacent grid cells in the two-dimensional grid matrix to generate a smoothly transitioning concentration isosurface. S146. Based on the numerical range of the concentration isosurface, dynamically match a preset color gradient mapping table, render the concentration isosurface as a color gradient view, and display it on the interactive interface of the display terminal.

[0067] The system first generates a two-dimensional grid matrix covering the target space area based on the room outline information acquired by the display terminal. After activating the visualization function on the display terminal, the user can scan the room outline using the terminal's camera or manually input the room's length and width dimensions to establish a spatial base. Once the display terminal acquires the room outline information, it generates a two-dimensional grid matrix covering the target space area. As a technological extension, the origin of the coordinate system of the two-dimensional grid matrix is ​​bound by default to the wall mounting location of the air conditioning unit, and users can perform millimeter-level calibration via touch dragging to accurately match the actual apartment layout and ensure accurate spatial mapping.

[0068] After generating a two-dimensional grid matrix, the system interpolates the negative ion concentration distribution data of adjacent grid cells to generate a smoothly transitioning concentration isosurface. Specifically, since the negative ion concentration distribution data calculated in the preceding steps is discretely distributed at the center of each grid cell, to eliminate the visual discontinuity caused by grid boundaries, the system uses a bilinear interpolation algorithm to interpolate the negative ion concentration distribution data of adjacent grid cells, thereby generating a smoothly transitioning concentration isosurface. As a technical extension, to balance rendering frame rate and visual accuracy under the limited computing power of the display terminal, the display terminal's rendering engine prioritizes the use of the graphics hardware acceleration interface and implements a level-of-detail strategy: areas farther from the user's viewpoint are rendered using a coarse-grained grid, while nearby interactive areas automatically have a finer grid density. In addition, the rendering engine is compatible with professional color difference optimization algorithms and has a built-in colorblind-friendly color matching mode to ensure an accessible experience for users with different visual conditions.

[0069] See Figure 10 The table is a preset color gradient mapping table described in the steps of this embodiment of the invention. After generating the concentration isosurface, the system dynamically matches the preset color gradient mapping table according to the numerical range of the concentration isosurface, renders the concentration isosurface as a color gradient view, and displays it on the interactive interface of the display terminal. In specific implementation, the preset color gradient mapping table defines seven levels of heatmap rules corresponding to the extremely low to extremely high concentration ranges.

[0070] The system dynamically matches the actual values ​​of the concentration isosurface. Figure 10 The system uses a color gradient mapping table to render concentration isosurfaces as a color gradient view and display them. As a technological extension, to address the issue of the heat map displaying no color or pale blue in low-concentration environments, leading to users misinterpreting that the negative ion function is not enabled, the system introduces a dynamic threshold scaling mechanism. When the global maximum concentration falls below a specific threshold, the system automatically and linearly compresses the color gradient range proportionally, ensuring that concentration gradient differences remain clearly visible. Simultaneously, the legend panel dynamically redraws based on real-time extreme values ​​and provides an automatic and manual color gradient switching switch, greatly enhancing the intuitiveness of the visualization and the user experience.

[0071] The spatial environment negative ion assessment method of the present invention can be widely applied to smart home scenarios with high requirements for air quality visualization, health purification effect perception and intelligent environmental control. The following uses two typical home spaces, the bedroom and the living room, as examples for illustration.

[0072] In a bedroom setting, this method can be used for air quality monitoring and seamless purification control during nighttime sleep. After the user activates the air conditioner's negative ion purification function, the system simultaneously collects room temperature, humidity, and particulate matter concentration, dynamically calculates the attenuation and distribution of negative ions in key activity areas such as the bed, and generates a spatial concentration heatmap on the mobile device. When the system detects excessively high negative ion concentrations in the bedside area, potentially causing static electricity discomfort or the accumulation of trace byproducts, the app proactively pushes optimization suggestions. If the user chooses optimization or the system is in automatic sleep mode, the air conditioner's main controller smoothly reduces the fan speed and adjusts the sweeping mechanism to its highest tilt angle, using airflow diffusion to dilute the localized high concentration. Because the evaluation process possesses dynamic convergence and steady-state smooth transition capabilities, the system can also adjust the concentration distribution model in real time according to changes in ambient temperature and humidity at night, maintaining the ion concentration within a healthy and comfortable range throughout sleep, thus improving the health and tranquility of nighttime sleep.

[0073] In living room scenarios, this method can be used to visualize and precisely intervene in purification effects in large spaces with multiple dead corners and complex airflow organization. For example, living rooms are typically large and have different activity areas such as sofa areas, passageways, and corners. Traditional air conditioners often release negative ions with extremely high concentrations near the air outlet, while distant areas have almost no purification effect, making it difficult for users to perceive the overall purification situation. With the method of this invention, the system can generate a high-precision two-dimensional grid matrix based on the room outline, and combine it with a three-dimensional Gaussian diffusion and room ventilation rate model to accurately calculate the actual negative ion concentration in each corner of the living room. The spatial distribution pattern can then be intuitively displayed through heat maps or AR augmented reality. At the same time, when the system detects that the concentration in the distant core activity area is low, it can automatically raise the fan speed or adjust the angle of the air guide plate to enhance the jet penetration. For complex usage scenarios such as family gatherings, pet activities, or smoggy days, this method can continuously perform dynamic mapping and visualization updates of spatial concentration, making the overall air purification effect in the living room clearly visible and improving the user's perception of the purification function.

[0074] As can be seen from the above applications, the method of the present invention can realize dynamic modeling, spatial mapping and visual interaction of the negative ion purification process in different home spaces, taking into account health and comfort, functional perception and intelligent control. It is especially suitable for smart home air conditioning environments with air purification functions, and has good practical value and promotion prospects.

[0075] Figure 8This is a schematic block diagram of a space environment negative ion assessment device 600 provided in an embodiment of the present invention. Figure 8 As shown, corresponding to the above-described method for assessing negative ions in a spatial environment, the present invention also provides a spatial environment negative ion assessment device 600. This spatial environment negative ion assessment device 600 includes a unit for performing the above-described spatial environment negative ion assessment method, and the device can be configured in an air conditioner controller, a smart home central control unit, or a mobile terminal.

[0076] Specifically, please refer to Figure 8 The space environment negative ion assessment device 600 includes: The parameter acquisition unit 610 is used to acquire indoor environmental parameters and operating status parameters of the air conditioning equipment during operation. The dynamic calculation unit 620 is used to dynamically calculate the attenuation rate of negative ions in the air and the initial negative ion concentration at the air outlet of the air conditioning equipment based on the indoor environmental parameters and the operating status parameters. The distribution calculation unit 630 is used to construct a spatial concentration distribution model based on the initial negative ion concentration, the decay rate and the preset spatial position relationship, and to calculate the negative ion concentration distribution data of each spatial position in the target spatial area. The view generation unit 640 is used to send the negative ion concentration distribution data to the display terminal, which generates and displays a spatial environment negative ion visualization view of the target spatial area based on a preset concentration and visual mapping rule.

[0077] In one embodiment, the parameter acquisition unit 610 includes: The data acquisition unit is used to collect raw environmental data at a preset sampling frequency through an environmental sensor integrated at the air inlet of the air conditioning equipment. The raw environmental data includes the temperature, humidity and particulate matter concentration in the target space area. The data processing unit is used to filter and verify the physical boundaries of the raw environmental data, remove abnormal data and retain valid environmental parameters; The status synchronization unit is used to obtain the current fan speed control command of the air conditioning equipment, and to align the valid environmental parameters with the fan speed control command by timestamp to generate the indoor environmental parameters and the operating status parameters.

[0078] In one embodiment, the dynamic computing unit 620 includes: The reference acquisition unit is used to acquire the reference attenuation rate under a preset reference operating condition. The coefficient calculation unit is used to calculate the environmental correction coefficient based on the humidity parameter, particulate matter concentration parameter and temperature parameter in the indoor environmental parameters; A rate coupling unit is used to couple the reference attenuation rate with the environmental correction coefficient to obtain the theoretical attenuation rate. The attenuation calculation unit is used to perform numerical range clamping protection on the theoretical attenuation rate, and calculate the attenuation rate by combining it with the aging attenuation factor corresponding to the cumulative running time of the negative ion generator in the air conditioning equipment.

[0079] In one embodiment, the dynamic computing unit 620 further includes: The parameter query unit is used to query a preset ion release mapping table according to the windshield control command to obtain the current ion release amount and the air supply speed. The basic calculation unit is used to calculate the basic concentration value based on the current ion release amount, the air supply velocity, and the effective cross-sectional area of ​​the air outlet of the air conditioning equipment. The concentration compensation unit is used to perform unit dimension conversion on the basic concentration value and introduce temperature volume correction coefficient and turbulent mixing efficiency coefficient for compensation calculation to obtain the initial negative ion concentration.

[0080] In one embodiment, the distributed computing unit 630 includes: The coordinate system establishment unit is used to establish a three-dimensional spatial coordinate system including the air outlet vector angle, with the air outlet of the air conditioning equipment as the spatial origin; The distance calculation unit is used to divide the target space region into multiple grid cells of preset size, and to calculate the axial travel distance and lateral vertical distance of each grid cell relative to the spatial origin. An axial calculation unit is used to calculate the axial attenuation concentration of each of the grid cells based on the axial travel distance and the attenuation rate. A diffusion correction unit is used to introduce a lateral diffusion correction term based on the lateral and vertical distances, and combine it with a global attenuation term corresponding to the room air exchange rate to perform spatial diffusion correction on the axial attenuation concentration, thereby obtaining negative ion concentration distribution data for each of the grid cells. The transient update unit is used to update the negative ion concentration distribution data in a transient accumulation manner during a preset transition period after the air conditioning equipment starts up or switches its operating state. The steady-state switching unit is used to switch to steady-state output mode when the rate of change of the negative ion concentration distribution data within a continuous time window is lower than a preset convergence threshold, and to perform linear interpolation for smooth transition at the moment of mode switching.

[0081] In one embodiment, the view generation unit 640 includes: The request receiving unit is used to receive the concentration viewing request initiated by the display terminal and forward the concentration viewing request to the main control unit of the air conditioning equipment through a wireless communication link. The message sending unit is used by the main control unit to extract the latest aligned negative ion concentration distribution data from the local cache, package it into a structured data message, and send it to the display terminal. The frequency adjustment unit is used to adaptively adjust the push frequency of the negative ion concentration distribution data according to the interaction status of the display terminal and the network communication quality.

[0082] In one embodiment, the view generation unit 640 further includes: A matrix generation unit is used to generate a two-dimensional grid matrix covering the target space area based on the room outline information obtained by the display terminal. An interpolation unit is used to perform interpolation operations on the negative ion concentration distribution data of adjacent grid cells in the two-dimensional grid matrix to generate a smoothly transitioning concentration isosurface. The view rendering unit is used to dynamically match a preset color gradient mapping table according to the numerical range of the concentration isosurface, render the concentration isosurface as a color gradient view and display it on the interactive interface of the display terminal.

[0083] The aforementioned space environment negative ion assessment device 600 can be implemented as a computer program, which can, for example... Figure 9 It runs on the computer device shown.

[0084] Please see Figure 9 , Figure 9 This is a schematic block diagram of a computer device 500 provided in an embodiment of this application. The computer device 500 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as an air conditioner controller, a smart home control unit, or a mobile terminal. The server can be a standalone server or a server cluster composed of multiple servers.

[0085] See Figure 9 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0086] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a method for evaluating negative ions in a space environment.

[0087] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0088] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can perform a method for evaluating negative ions in the space environment.

[0089] This network interface 505 is used for network communication with other devices. Those skilled in the art will understand that... Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0090] The processor 502 is used to run a computer program 5032 stored in a memory to implement the steps of the above method.

[0091] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0092] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0093] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the steps of the above-described method.

[0094] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0095] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0096] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0097] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0098] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0099] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for evaluating negative ions in a spatial environment, characterized in that, The method includes: Obtain indoor environmental parameters and operating status parameters of the air conditioning equipment during operation; Based on the indoor environmental parameters and the operating status parameters, the attenuation rate of negative ions in the air and the initial negative ion concentration at the air outlet of the air conditioning unit are dynamically calculated. Based on the initial negative ion concentration, the decay rate, and the preset spatial position relationship, a spatial concentration distribution model is constructed, and the negative ion concentration distribution data of each spatial position within the target spatial region is calculated. The negative ion concentration distribution data is sent to a display terminal, which generates and displays a spatial environment negative ion visualization view of the target spatial area based on a preset concentration and visual mapping rule.

2. The method for evaluating negative ions in the space environment according to claim 1, characterized in that, The steps of obtaining the indoor environmental parameters and the operating status parameters of the air conditioning equipment during operation include: The environmental sensor integrated at the air inlet of the air conditioning equipment collects raw environmental data at a preset sampling frequency. The raw environmental data includes the temperature, humidity and particulate matter concentration in the target space area. The original environmental data is filtered and physical boundary verified to remove abnormal data and retain valid environmental parameters. Obtain the current fan speed control command of the air conditioning equipment, and align the valid environmental parameters with the fan speed control command using timestamps to generate the indoor environmental parameters and the operating status parameters.

3. The method for evaluating negative ions in the space environment according to claim 1, characterized in that, The step of dynamically calculating the attenuation rate of negative ions in the air includes: Obtain the baseline attenuation rate under preset baseline operating conditions; Based on the humidity, particulate matter concentration and temperature parameters in the indoor environmental parameters, calculate the environmental correction factor; The theoretical attenuation rate is obtained by coupling the reference attenuation rate with the environmental correction coefficient. The theoretical attenuation rate is clamped within a numerical range and, combined with the aging attenuation factor corresponding to the cumulative operating time of the negative ion generator in the air conditioning equipment, the attenuation rate is calculated.

4. The method for evaluating negative ions in the space environment according to claim 2, characterized in that, The step of dynamically calculating the initial negative ion concentration at the air outlet of the air conditioning unit includes: According to the windshield control command, query the preset ion release mapping table to obtain the current ion release and air supply speed; The baseline concentration value is calculated based on the current ion release amount, the air supply velocity, and the effective cross-sectional area of ​​the air outlet of the air conditioning equipment. The base concentration value is converted to a unit dimension, and a temperature-volume correction coefficient and a turbulent mixing efficiency coefficient are introduced for compensation calculation to obtain the initial negative ion concentration.

5. The method for evaluating negative ions in the space environment according to claim 1, characterized in that, The step of constructing a spatial concentration distribution model based on the initial negative ion concentration, the attenuation rate, and the preset spatial positional relationship, and calculating the negative ion concentration distribution data at each spatial position within the target spatial region includes: A three-dimensional spatial coordinate system including the air outlet vector angle is established with the air outlet of the air conditioning equipment as the spatial origin; The target space region is divided into multiple grid cells of preset size, and the axial travel distance and lateral vertical distance of each grid cell relative to the origin of space are calculated. Based on the axial travel distance and the attenuation rate, the axial attenuation concentration of each grid cell is calculated; Based on the horizontal and vertical distances, a horizontal diffusion correction term is introduced, and combined with the global attenuation term corresponding to the room ventilation rate, the axial attenuation concentration is spatially diffused to correct for the negative ion concentration distribution data of each grid cell. During the preset transition period after the air conditioning equipment starts up or switches to the operating state, the negative ion concentration distribution data is updated in a transient accumulation manner. When the rate of change of the negative ion concentration distribution data within a continuous time window is lower than the preset convergence threshold, the system switches to steady-state output mode and performs linear interpolation for smooth transition at the moment of mode switching.

6. The method for evaluating negative ions in the space environment according to claim 1, characterized in that, The step of sending the negative ion concentration distribution data to the display terminal includes: The system receives a concentration viewing request initiated by the display terminal and forwards the concentration viewing request to the main control unit of the air conditioning equipment via a wireless communication link. The main control unit extracts the latest aligned negative ion concentration distribution data from the local cache, packages it into a structured data message, and sends it to the display terminal. The frequency of pushing the negative ion concentration distribution data is adaptively adjusted based on the interaction status of the display terminal and the network communication quality.

7. The method for evaluating negative ions in the space environment according to claim 1, characterized in that, The steps of generating and displaying a spatial environment negative ion visualization view of the target spatial region include: Based on the room outline information obtained by the display terminal, a two-dimensional grid matrix covering the target space area is generated; Interpolation is performed on the negative ion concentration distribution data of adjacent grid cells in the two-dimensional grid matrix to generate a smoothly transitioning concentration isosurface. Based on the numerical range of the concentration isosurface, a preset color gradient mapping table is dynamically matched, and the concentration isosurface is rendered as a color gradient view and displayed on the interactive interface of the display terminal.

8. A space environment negative ion assessment device, characterized in that, Used to perform the space environment negative ion assessment method as described in any one of claims 1 to 7.

9. A computer device, characterized in that, The computer device includes a memory and a processor connected to the memory; the memory is used to store a computer program; the processor is used to run the computer program stored in the memory to perform the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which includes program instructions that, when executed by a processor, can implement the steps of the method as described in any one of claims 1 to 7.

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