Control method of seven-in-one air quality detector and air quality detector

Abstract

The invention discloses a control method of a seven-in-one air quality detector and the air quality detector, and relates to the field of intelligent control, and the method comprises the steps: obtaining monitoring data collected by a sensor module at each sampling time point in real time; determining attention evaluation of various environmental parameters at various sampling time points based on the monitoring data, and determining a plurality of abnormal environmental parameters; aiming at any abnormal environment parameter, determining a ventilation adjustment factor of the abnormal environment parameter at each sampling time point based on the attention evaluation of the abnormal environment parameter at each sampling time point; determining an optimized ventilatory capacity of the air quality detector based on the ventilation adjustment factor; a control signal of the controller is determined based on the optimized throughput. The invention aims to solve the technical problem that the detection result is unreliable due to the conflict of airflow requirements of different sensors when the existing air quality detector is in a fixed ventilation mode.

Description

Technical Field

[0001] The present application relates to the field of intelligent control, and in particular to a control method and an air quality detector of a seven-in-one air quality detector. Background Art

[0002] The seven-in-one air quality detector is a device that integrates multiple air sensors and can perform real-time detection of seven sets of data in the air: CO2 (carbon dioxide), HCHO (formaldehyde), TVOC (volatile organic compounds), PM2.5, PM10, temperature, and humidity.

[0003] However, different sensors require conflicting airflow environments. For example, detecting gaseous pollutants requires a low, stable airflow to ensure accurate molecular adsorption, while measuring particulate matter requires turbulent flow to prevent particle settling. However, existing air quality monitoring equipment uses fixed ventilation control modes that cannot flexibly respond to changing environmental conditions. This can lead to anomalies in environmental parameter detection and unreliable air quality results for users. Summary of the Invention

[0004] The main purpose of this application is to provide a control method and air quality detector of a seven-in-one air quality detector, aiming to solve the technical problem that the detection results of existing air quality detectors are unreliable due to the conflict of airflow requirements of different sensors in a fixed ventilation mode.

[0005] To achieve the above-mentioned objectives, the present application provides a control method for a seven-in-one air quality detector, the air quality detector including a controller, a display, a sensor module, and a ventilation device, the method being executed by the controller, the method including: acquiring in real time monitoring data collected by the sensor module at each sampling time point, the monitoring data including monitoring data of seven environmental parameters in a target detection environment; determining an attention evaluation of various environmental parameters at each sampling time point based on the monitoring data, and determining several abnormal environmental parameters from the seven environmental parameters based on the attention evaluation; for any abnormal environmental parameter, determining a ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation of the abnormal environmental parameter at each sampling time point; determining an environmental adaptation degree of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point, and determining an optimized ventilation volume of the air quality detector based on the environmental adaptation degree and the current ventilation volume of the air quality detector; determining a control signal of the controller and a ventilation volume of the ventilation device based on the optimized ventilation volume, controlling the air quality detector to perform a preset detection operation based on the control signal, and sending the detection result to the display for display.

[0006] Optionally, before determining the attention evaluation of various environmental parameters at each sampling time point based on the monitoring data, the method also includes: obtaining the wind speed of the air quality detector at each sampling time point and determining the categories of various environmental parameters, the categories including the first category, the second category and the third category; determining the attention evaluation of various environmental parameters at each sampling time point based on the monitoring data includes: determining the attention evaluation of various environmental parameters at each sampling time point based on the monitoring data and the categories of various environmental parameters.

[0007] Optionally, the determining of several abnormal environmental parameters from seven environmental parameters based on the attention evaluation includes: constructing a current attention evaluation sequence based on the attention evaluation of all environmental parameters at the current sampling time point; and determining several abnormal environmental parameters from seven environmental parameters based on the current attention evaluation sequence.

[0008] Optionally, the determining of the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation of the abnormal environmental parameter at each sampling time point includes: calculating the attention evaluation mean and the attention evaluation standard deviation of the abnormal environmental parameter from the starting sampling time point to the current sampling time point; obtaining the number of environmental parameters that are greater than or equal to the preset maximum thresholds of the sensor module at the current sampling time point; and determining the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation mean, the attention evaluation standard deviation, the attention evaluation of the abnormal environmental parameter at each sampling time point, and the number of environmental parameters that are greater than or equal to the preset maximum thresholds of the sensor module at the current sampling time point.

[0009] Optionally, the determining of the environmental adaptability of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point includes: for any abnormal environmental parameter, determining the preferred node corresponding to the abnormal environmental parameter based on the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point, wherein the preferred node is used to characterize the distinguishing position of the abnormal environmental parameter between the abnormal ventilation state and the adapted ventilation state; determining the environmental adaptability of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point and the preferred node corresponding to each abnormal environmental parameter.

[0010] Optionally, for any abnormal environmental parameter, the preferred node corresponding to the abnormal environmental parameter is determined based on the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point, including: constructing a ventilation adjustment factor differential sequence and a symbol sequence based on the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point; setting multiple sliding nodes, and determining the preferred node corresponding to the abnormal environmental parameter from the multiple sliding nodes based on the ventilation adjustment factor differential sequence and the symbol sequence.

[0011] In addition, to achieve the above-mentioned purpose, the present application also provides a controller, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method in any possible implementation manner described above.

[0012] The present application also provides a computer-readable storage medium, comprising: a computer program stored therein, wherein when the computer program is executed by a processor, the method in any of the possible implementations described above is implemented.

[0013] The present application also provides an air quality detector, comprising a controller, a display, a sensor module and a ventilation device; wherein the controller is communicatively connected with the sensor module, the display and the ventilation device; the sensor module is used to collect monitoring data of 7 environmental parameters in the target detection environment; the controller is used to determine a control signal and the ventilation volume of the ventilation device based on the monitoring data; the ventilation device is used to adjust the current ventilation volume of the air quality detector based on the ventilation volume; the controller is also used to control the air quality detector to perform a preset detection operation based on the control signal; and the display is used to display the detection results.

[0014] The present application proposes a control method for a seven-in-one air quality detector and an air quality detector, which dynamically adjusts the ventilation volume to meet the requirements of different sensors for the airflow environment, thereby improving the accuracy of the detection results. Specifically, the present application first identifies abnormal environmental parameters by real-time monitoring of environmental parameters and calculating attention evaluation. Subsequently, the ventilation adjustment factor is calculated using a formula based on the mean and standard deviation of the attention evaluation and the number of environmental parameters that exceed the preset threshold. This factor reflects the ventilation volume that needs to be adjusted to obtain reliable detection results under the current environmental conditions. Finally, the optimized ventilation volume is determined based on the ventilation adjustment factor, and the ventilation device of the air quality detector is adjusted accordingly to achieve environmental adaptation. The present application not only ensures that each sensor operates in the optimal airflow environment, but also improves the overall performance of air quality detection and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flow chart of a control method for a seven-in-one air quality detector provided in one embodiment of the present application; Figure 2 A schematic diagram of the display interface of an air quality detector provided in one embodiment of the present application; Figure 3 A schematic diagram of the physical structure of a controller is shown as an example.

[0016] The realization of the objectives, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0017] It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application.

[0018] Existing air quality detectors simultaneously collect multiple environmental parameters within a single integrated air circuit. These sensors require conflicting airflow environments (for example, detecting gaseous pollutants requires a low, stable flow rate to ensure accurate molecular adsorption, while measuring particulate matter requires turbulent flow to prevent particle settling). However, the ventilation control in existing air quality monitoring equipment uses a fixed mode, making it inflexible to real-time changing environmental conditions. This can lead to anomalies in environmental parameter detection, resulting in less reliable air quality results for users.

[0019] In order to solve the above problems, the present application provides a control method of a seven-in-one air quality detector and an air quality detector. The present application scheme is introduced in detail below.

[0020] Figure 1 This is a flowchart of a control method for a seven-in-one air quality detector provided in Example 1 of the present application. The method is applied to an air quality detector, which can specifically be a seven-in-one air quality detector. The air quality detector includes a controller, a display, a sensor module, and a ventilation device. The controller is communicatively connected with the sensor module, the display, and the ventilation device, and the method is executed by the controller.

[0021] Please refer to Figure 1 The control method of the seven-in-one air quality detector may include the following steps: S11. Acquire in real time the monitoring data collected by the sensor module at each sampling time point, where the monitoring data includes monitoring data of seven environmental parameters in the target detection environment.

[0022] Among them, the sensor module includes multiple sensors, and the seven environmental parameters can be CO2 (carbon dioxide), HCHO (formaldehyde), TVOC (volatile organic compound), PM2.5, PM10, temperature, and humidity.

[0023] In the specific implementation process, first, in the target detection environment, the monitoring data collected by the sensor module at each sampling time point is obtained in real time. In this embodiment, the sampling frequency is set to 10 Hz. The technical principle, concentration unit and volume conversion of the sensor module collecting various environmental parameters in this embodiment are shown in the following table: It should be noted that, in this embodiment, the controller sends the sampling time point to the sensor module to ensure that the monitoring data of each sensor is updated at the same time, that is, sampled at the same time.

[0024] S12. Determine attention evaluations of various environmental parameters at various sampling time points based on the monitoring data, and determine several abnormal environmental parameters from the seven environmental parameters based on the attention evaluations.

[0025] It should be noted that the attention evaluation is based on comparing the monitored environmental parameter data with a preset maximum threshold. If the monitored data exceeds the preset standard or threshold, the corresponding environmental parameter is considered abnormal. In this embodiment, the attention evaluation helps to quickly identify potentially problematic air quality indicators, i.e., environmental parameters, in the target detection environment.

[0026] In one embodiment, in step S12, before determining the attention evaluation of various environmental parameters at each sampling time point based on the monitoring data, the method may also include: obtaining the wind speed of the air quality detector at each sampling time point and determining the category of various environmental parameters, which includes a first category, a second category, and a third category.

[0027] In the specific implementation process, the category of each environmental parameter is first determined. This embodiment divides the environmental parameters into three categories, among which the first category can be gaseous pollutants, such as CO2 (carbon dioxide) and HCHO (formaldehyde); the second category can be particulate matter, such as PM2.5 and PM10; the third category can be other parameters, such as temperature and humidity. Then, based on the category of each environmental parameter, the attention evaluation of various environmental parameters at each sampling time point is determined.

[0028] Specifically, the Taking the environmental parameters as an example, this embodiment can use the following formula (1) to determine the The environmental parameters are Attention evaluation at sampling time points : Where, Indicates the The environmental parameters are Attention evaluation at sampling time points, Indicates the The environmental parameters are Monitoring data at sampling time points, Indicates the The preset maximum thresholds of various environmental parameters, Indicates that the air quality detector is Wind speed at the sampling time, Indicates the preset maximum wind speed of the air quality detector.

[0029] It should be noted that The item can represent the relationship between the current monitoring data and the preset maximum threshold. The larger it is, the more abnormal the current monitoring data is.

[0030] In addition, when detecting gaseous pollutants, a low flow rate and stable airflow is required to ensure the accuracy of molecular adsorption; when measuring particulate matter, turbulence is required to prevent particle sedimentation. Therefore, when the environmental parameter is the first category, i.e., gaseous pollutants, this embodiment sets Item and Multiply the terms, It can be understood as , that is, when the wind speed is greater, the reliability of the monitoring data of the gas pollutant is lower, and the reference value of the current monitoring data for attention evaluation is lower; and when the environmental parameter is the second category, that is, particulate matter, this embodiment sets Item and The multiplication of the terms can be understood as that when the wind speed is greater, the particles can be better carried to the sensor, thereby making the monitoring data of the particles more reliable and the reference of the current monitoring data for attention evaluation more reliable; when the environmental parameters are the third category, i.e. other parameters, since the measurement of temperature and humidity is not affected by wind speed, and when the wind speed is medium, the confidence of the monitoring data of temperature and humidity is higher, and thus this embodiment sets Item and Multiply them to adjust the attention evaluation according to the actual monitoring data.

[0031] In one embodiment, in step S12, determining several abnormal environmental parameters from the seven environmental parameters based on the attention evaluation may specifically include: S121, constructing a current attention evaluation sequence based on the attention evaluation of all environmental parameters at the current sampling time point; S122. Determine several abnormal environmental parameters from the seven environmental parameters based on the current attention evaluation sequence.

[0032] In the specific implementation process, the attention evaluation of all environmental parameters at the current sampling time point is first obtained, and they are sorted in ascending order to construct the current attention evaluation sequence.

[0033] Furthermore, a first-order difference is performed on the attention evaluation sequence to obtain a current attention evaluation difference sequence and obtain the maximum value in the current attention evaluation difference sequence, and then several abnormal attention evaluations are determined based on the maximum value, thereby determining several abnormal environmental parameters based on the several abnormal attention evaluations.

[0034] Specifically, since the first The data is the first in the current attention evaluation sequence Data and The difference between the data, if the maximum value in the current attention evaluation difference sequence is the data, then the first The data from the first bit to the last bit of the sequence are used as several abnormal attention evaluations, and then the environmental parameters corresponding to the abnormal attention evaluations are used as abnormal environmental parameters.

[0035] S13. For any abnormal environmental parameter, determine the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation of the abnormal environmental parameter at each sampling time point.

[0036] It should be noted that due to differences in wind speed acquisition and corresponding testing methods among integrated sensors, poor airflow after testing can cause airborne matter to settle on the testing surface, further interfering with test results due to dust and other impurities carried in the air. Therefore, dynamic monitoring of airflow changes is necessary to remove any abnormal matter deposited between sensors through airflow, enabling the air quality detector's self-cleaning function and ensuring the credibility of test results.

[0037] Based on this, this embodiment completes the cumulative abnormality analysis of the ventilation process by analyzing the ventilation results accumulated by each abnormal environmental parameter during the ventilation process, that is, the changes in the attention evaluation, thereby achieving the goal of self-cleaning the air quality detector.

[0038] In one embodiment, in step S13, determining the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation of the abnormal environmental parameter at each sampling time point may specifically include: S131, calculating the mean value and standard deviation of the attention evaluation of the abnormal environmental parameter from the starting sampling point to the current sampling point, and obtaining the number of environmental parameters greater than or equal to each preset maximum threshold at the current sampling time point; S132. Determine the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation mean, the attention evaluation standard deviation, the attention evaluation of the abnormal environmental parameter at each sampling time point, and the number of environmental parameters greater than or equal to each preset maximum threshold.

[0039] In the specific implementation process, any abnormal environmental parameter is used as the target environmental parameter. This embodiment takes the target environmental parameter as an example to illustrate. First, the attention evaluation mean and attention evaluation standard deviation of the target environmental parameter from the starting sampling point to the current sampling point are obtained, and then the number of environmental parameters greater than or equal to each preset maximum threshold at the current sampling time point is obtained.

[0040] Furthermore, the ventilation adjustment factor of the target environmental parameter at each sampling time point is determined based on the attention evaluation mean, the attention evaluation standard deviation, the attention evaluation of the target environmental parameter at each sampling time point, and the number of environmental parameters greater than or equal to each preset maximum threshold.

[0041] Specifically, the target environmental parameter is Taking the abnormal environmental parameters as an example, this embodiment can use the following formula (2) to determine the Abnormal environmental parameters in the Ventilation adjustment factor at sampling time : Where, Indicates the Abnormal environmental parameters in the Ventilation adjustment factor at the sampling time point, Indicates the Abnormal environmental parameters in the Monitoring data at sampling time points, represents the mean value of attention evaluation, represents the standard deviation of attention evaluation, Indicates in The number of environmental parameters greater than or equal to each preset maximum threshold at the sampling time point, represents the number of environmental parameters, Indicates the preset adjustment coefficient, is a positive odd number greater than or equal to 3, Indicates the current sampling time point.

[0042] It should be noted that Indicates the The fluctuation deviation degree of attention evaluation of abnormal environmental parameters in time series. The greater the deviation from the mean value of an abnormal environmental parameter, the more significant the numerical change in the environmental perception feature corresponding to the abnormal environmental parameter. In other words, the more significant the temporal change in the value of the abnormal environmental parameter, the more attention it needs to pay to determine whether there is an abnormal event in the current environment. In addition, since the values of various environmental parameters in the actual environment remain within a certain range, representing the physical limit of the change in environmental indicators, processing the fraction through odd powers amplifies small numerical differences while retaining the direction of the numerical change of the abnormal environmental parameter represented by the symbol information, that is, the direction of data fluctuation, thereby more intelligently reflecting the abnormal situation of the actual environmental feature represented by the abnormal environmental parameter.

[0043] It should be further explained that Indicates the proportion of abnormal environmental parameters at the current sampling time point. The larger the value is, the more abnormal environmental parameters there are at the current sampling time point, and the more necessary it is to adjust the air flow at the current sampling time point to achieve self-cleaning of the sensor.

[0044] S14. Determining an environmental adaptation degree of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point, and determining an optimized ventilation volume of the air quality detector based on the environmental adaptation degree and a current ventilation volume of the air quality detector; S15. Determine a control signal of the controller and a ventilation volume of the ventilation device based on the optimized ventilation volume, control the air quality detector to perform a preset detection operation based on the control signal, and send the detection result to the display for display.

[0045] The degree of environmental adaptation is used to characterize the degree of adaptation between the current ventilation volume of the air quality detector and the monitoring environment of various environmental parameters.

[0046] In one embodiment, in step S14, determining the environmental adaptability of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point may specifically include: S141. For any abnormal environmental parameter, determine a preferred node corresponding to the abnormal environmental parameter based on the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point, wherein the preferred node is used to represent the position of the abnormal environmental parameter that distinguishes between an abnormal ventilation state and an adapted ventilation state; S142: Determine the environmental adaptability of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point and the preferred node corresponding to each abnormal environmental parameter.

[0047] It should be noted that in the embodiments of the present application, taking any abnormal environmental parameter as an example, a ventilation adjustment factor differential sequence and a symbol sequence are first constructed based on the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point. The symbol changes in the symbol sequence can reflect the changing trend of the ventilation state of the abnormal environmental parameter. Multiple sliding nodes are then set, and based on the ventilation adjustment factor differential sequence and the symbol sequence, the preferred node corresponding to the abnormal environmental parameter is determined from the multiple sliding nodes. This can represent the key position where the abnormal environmental parameter transitions from an abnormal ventilation state to an adaptive ventilation state.

[0048] In a specific implementation process, the ventilation adjustment factors of the target environmental parameters from the initial sampling time point to the current sampling time point are firstly used to form a ventilation adjustment factor sequence, and then the ventilation adjustment factor sequence is first-order differencing performed on the ventilation adjustment factor sequence to obtain a ventilation adjustment factor difference sequence.

[0049] Furthermore, a number of data with opposite signs to the previous data in the ventilation adjustment factor differential sequence are extracted to form a difference sequence, that is, if a certain data is a positive number and the previous data is a negative number, the data is extracted; the numerical sign of each data in the difference sequence is obtained to obtain a sign sequence.

[0050] Furthermore, a sliding node is set, which divides the symbol sequence into two parts and calculates the degree of fluctuation of each part of the sequence.

[0051] Specifically, the following formula (3) can be used to calculate the degree of volatility of each part of the series: : Where, Represents this part of the sequence Middle The ventilation adjustment factor difference value corresponding to each element in the ventilation adjustment factor difference sequence, Represents this part of the sequence The standard deviation of all elements in the difference series of ventilation adjustment factors, Represents this part of the sequence The number of elements in .

[0052] It should be noted that, in this embodiment, by traversing the partial sequence The ventilation adjustment factor difference value of all elements in the ventilator can be used to obtain the ventilation factor fluctuations that appear when the current ventilation environment is abnormal, which is more reflected in the small vibration situation, that is, the fluctuation of each position (the value of each position) ) is closer to the fluctuation (standard deviation) of the current partial sequence, which means that the ventilation state of the current period represented by the current partial sequence is closer to the required ventilation state of the attribute, that is, the current sliding node can be used as a position to distinguish between abnormal ventilation state and adaptive ventilation state.

[0053] Furthermore, starting from the first element of the symbol sequence, the sliding nodes are continuously adjusted, and the fluctuation degree on both sides of each sliding node is calculated, and the absolute value of the difference between the fluctuation degrees on both sides is calculated, and the sliding node corresponding to the largest absolute value of the difference is taken as the preferred node.

[0054] It should be noted that, in this embodiment, the sliding node is first set between the first element and the second element of the symbol sequence, and then the sliding node is adjusted to set between the second element and the third element of the symbol sequence, and so on, until the sliding node is set between the second to last element and the last element of the symbol sequence.

[0055] It can be understood that the symbol sequences of all abnormal environment parameters are divided according to the preferred nodes.

[0056] Furthermore, the number of abnormal environmental parameters with a larger fluctuation degree at the current sampling time point is obtained, and the environmental adaptation degree of the air quality detector is calculated.

[0057] Specifically, the environmental adaptation degree of the air quality detector can be calculated using the following formula (4): : Where, Indicates the number of abnormal environmental parameters with greater fluctuation at the current sampling time point. represents the number of environmental parameters, Indicates summation, After the symbol sequence representing the abnormal environmental parameters is divided according to the preferred nodes, the absolute value of the difference in the fluctuation degree on both sides is It represents the sum of the absolute values of the differences in the fluctuation levels of all abnormal environmental parameters on both sides after being divided according to the preferred nodes when they are on the side with a larger fluctuation level at the current moment. It represents the sum of the absolute values of the differences in the fluctuation levels of all abnormal environmental parameters on both sides after being divided according to the preferred nodes when the parameters are on the side with smaller fluctuation level at the current moment. Indicates the number of abnormal environmental parameters that are on the side with a larger fluctuation degree at the current moment. Indicates the number of abnormal environmental parameters that are on the side with smaller fluctuation at the current moment.

[0058] It should be noted that This indicates that the current fluctuation range is more stable, that is, the wind speed of the current air quality detector is more suitable for data detection of more environmental parameters.

[0059] Furthermore, the environmental adaptation degree is multiplied by the current ventilation volume of the air quality detector to obtain the optimized ventilation volume of the air quality detector. After obtaining the optimized ventilation volume, the current ventilation volume and the optimized ventilation volume are simultaneously input into the controller to obtain a control signal of the controller.

[0060] Furthermore, the air quality detector is controlled to perform a preset detection operation based on the control signal, and the detection result is sent to the display for display.

[0061] The embodiment of the present application proposes a control method for a seven-in-one air quality detector, which dynamically adjusts the ventilation volume to meet the requirements of different sensors for the airflow environment, thereby improving the accuracy of the detection results. Specifically, the embodiment of the present application first identifies abnormal environmental parameters by real-time monitoring of environmental parameters and calculating attention evaluation. Subsequently, the ventilation adjustment factor is calculated using a formula based on the mean and standard deviation of the attention evaluation and the number of environmental parameters exceeding the preset threshold. This factor reflects the ventilation volume that needs to be adjusted in order to obtain reliable detection results under the current environmental conditions. Finally, the optimized ventilation volume is determined based on the ventilation adjustment factor, and the ventilation device of the air quality detector is adjusted accordingly to achieve environmental adaptation. The embodiment of the present application not only ensures that each sensor operates in the optimal airflow environment, but also improves the overall performance of air quality detection and user experience.

[0062] Based on the above embodiment, the embodiment of the present application further proposes an air quality detector, which includes a controller, a display, a sensor module and a ventilation device. The controller is communicatively connected with the sensor module, the display and the ventilation device, wherein: The sensor module is used to collect monitoring data of seven environmental parameters in the target detection environment; The controller is used to determine a control signal and a ventilation volume of the ventilation device based on the monitoring data; The ventilation device is used to adjust the current ventilation volume of the air quality detector based on the ventilation volume; The controller is further configured to control the air quality detector to perform a preset detection operation based on the control signal; The display is used to show the test results, see Figure 2 , Figure 2 The figure is a schematic diagram of the display interface of an air quality detector provided according to one embodiment of the present application.

[0063] Based on the above embodiments, Figure 3 FIG. 1 is a schematic diagram of a controller according to an embodiment of the present application, as shown in FIG. Figure 3 As shown, the controller may include: a processor (processor) 310, a communication interface (CommunicationsInterface) 320, a memory (memory) 330 and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other through the communication bus 340. The processor 310 can call the logic instructions in the memory 330 to execute a control method for a seven-in-one air quality detector, the method including: acquiring in real time the monitoring data collected by the sensor module at each sampling time point, the monitoring data including monitoring data of seven environmental parameters in the target detection environment; determining the attention evaluation of various environmental parameters at each sampling time point based on the monitoring data, and determining several abnormal environmental parameters from the seven environmental parameters based on the attention evaluation; for any abnormal environmental parameter, determining the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation of the abnormal environmental parameter at each sampling time point; determining the environmental adaptation degree of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point, and determining the optimized ventilation volume of the air quality detector based on the environmental adaptation degree and the current ventilation volume of the air quality detector; determining the control signal of the controller and the ventilation volume of the ventilation device based on the optimized ventilation volume, and controlling the air quality detector to perform a preset detection operation based on the control signal, and sending the detection result to the display for display.

[0064] Furthermore, the logic instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product, stored in a storage medium, includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0065] On the basis of the above embodiments, on the other hand, the present invention further provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute a control method for a seven-in-one air quality detector provided by the above methods, the method comprising: acquiring in real time the monitoring data collected by the sensor module at each sampling time point, the monitoring data including monitoring data of seven environmental parameters in the target detection environment; determining the attention evaluation of various environmental parameters at each sampling time point based on the monitoring data, and determining several abnormal environments from the seven environmental parameters based on the attention evaluation. environmental parameters; for any abnormal environmental parameter, determining the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation of the abnormal environmental parameter at each sampling time point; determining the environmental adaptation degree of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point, and determining the optimized ventilation volume of the air quality detector based on the environmental adaptation degree and the current ventilation volume of the air quality detector; determining the control signal of the controller and the ventilation volume of the ventilation device based on the optimized ventilation volume, and controlling the air quality detector to perform a preset detection operation based on the control signal, and sending the detection result to the display for display.

[0066] On the basis of the above embodiments, on another aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute a control method for a seven-in-one air quality detector provided by the above methods, the method comprising: acquiring in real time the monitoring data collected by the sensor module at each sampling time point, the monitoring data comprising monitoring data of seven environmental parameters in the target detection environment; determining an attention evaluation of various environmental parameters at each sampling time point based on the monitoring data, and determining a number of abnormal environmental parameters from the seven environmental parameters based on the attention evaluation; and determining a number of abnormal environmental parameters for any abnormal environmental parameter. number, determine the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation of the abnormal environmental parameter at each sampling time point; determine the environmental adaptation degree of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point, and determine the optimized ventilation volume of the air quality detector based on the environmental adaptation degree and the current ventilation volume of the air quality detector; determine the control signal of the controller and the ventilation volume of the ventilation device based on the optimized ventilation volume, and control the air quality detector to perform a preset detection operation based on the control signal, and send the detection result to the display for display.

[0067] The above are only preferred embodiments of the present application and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A control method for a seven-in-one air quality detector, characterized in that: The air quality detector includes a controller, a display, a sensor module, and a ventilation device. The method is executed by the controller, and the method includes: Acquire in real time the monitoring data collected by the sensor module at each sampling time point, wherein the monitoring data includes monitoring data of seven environmental parameters in the target detection environment; determining attention evaluations of various environmental parameters at various sampling time points based on the monitoring data, and determining several abnormal environmental parameters from the seven environmental parameters based on the attention evaluations; For any abnormal environmental parameter, determining a ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on an attention evaluation of the abnormal environmental parameter at each sampling time point; determining an environmental adaptation degree of the air quality detector based on a ventilation adjustment factor of each abnormal environmental parameter at each sampling time point, and determining an optimized ventilation volume of the air quality detector based on the environmental adaptation degree and a current ventilation volume of the air quality detector; The control signal of the controller and the ventilation volume of the ventilation device are determined based on the optimized ventilation volume, and the air quality detector is controlled to perform a preset detection operation based on the control signal, and the detection result is sent to the display for display.

2. The method according to claim 1, characterized in that Before determining the attention evaluation of various environmental parameters at each sampling time point based on the monitoring data, the method further includes: Obtaining the wind speed of the air quality detector at each sampling time point and determining categories of various environmental parameters, wherein the categories include a first category, a second category, and a third category; The step of determining the attention evaluation of various environmental parameters at each sampling time point based on the monitoring data includes: The attention evaluation of various environmental parameters at each sampling time point is determined based on the monitoring data and the categories of various environmental parameters.

3. The method according to claim 2, characterized in that The method of determining several abnormal environmental parameters from seven environmental parameters based on the attention evaluation includes: Construct a current attention evaluation sequence based on the attention evaluation of all environmental parameters at the current sampling time point; Based on the current attention evaluation sequence, several abnormal environmental parameters are determined from the seven environmental parameters.

4. The method according to claim 1, wherein The determining of the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point based on the attention evaluation of the abnormal environmental parameter at each sampling time point includes: Calculate the attention evaluation mean and attention evaluation standard deviation of the abnormal environment parameter from the starting sampling time point to the current sampling time point; Obtain the number of environmental parameters that are greater than or equal to the preset maximum thresholds of the sensor module at the current sampling time point; The ventilation adjustment factor of the abnormal environmental parameter at each sampling time point is determined based on the attention evaluation mean, the attention evaluation standard deviation, the attention evaluation of the abnormal environmental parameter at each sampling time point, and the number of environmental parameters greater than or equal to the preset maximum thresholds of the sensor module at the current sampling time point.

5. The method according to claim 1, wherein The determining of the environmental adaptability of the air quality detector based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point includes: For any abnormal environmental parameter, determining a preferred node corresponding to the abnormal environmental parameter based on the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point, wherein the preferred node is used to represent the position of the abnormal environmental parameter that distinguishes between an abnormal ventilation state and an adapted ventilation state; The environmental adaptability of the air quality detector is determined based on the ventilation adjustment factor of each abnormal environmental parameter at each sampling time point and the preferred node corresponding to each abnormal environmental parameter.

6. The method according to claim 5, characterized in that The determining, for any abnormal environmental parameter, a preferred node corresponding to the abnormal environmental parameter based on the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point includes: Constructing a ventilation adjustment factor difference sequence and a symbol sequence based on the ventilation adjustment factor of the abnormal environmental parameter at each sampling time point; A plurality of sliding nodes are set, and a preferred node corresponding to the abnormal environment parameter is determined from the plurality of sliding nodes based on the ventilation adjustment factor differential sequence and the symbol sequence.

7. A controller comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

9. An air quality detector comprising the controller according to claim 7, a display, a sensor module, and a ventilation device, wherein the controller is in communication with the sensor module, the display, and the ventilation device; The sensor module is used to collect monitoring data of seven environmental parameters in the target detection environment; The controller is used to determine a control signal and a ventilation volume of the ventilation device based on the monitoring data; The ventilation device is used to adjust the current ventilation volume of the air quality detector based on the ventilation volume; The controller is further configured to control the air quality detector to perform a preset detection operation based on the control signal; The display is used to display the detection results.

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