An ultraviolet intelligent disinfection control system and method based on environmental perception

Abstract

The application relates to the field of intelligent disinfection technology and discloses an ultraviolet intelligent disinfection control system and method based on environmental perception, which comprises an information extraction module, a radiation model construction module, a dose distribution module, a disinfection module, a data feedback module and a disinfection termination module, wherein: an initial model is constructed based on three-dimensional point cloud data and reflectivity characteristics, the initial model is subjected to reflectivity compensation, and an ultraviolet radiation field attenuation model is obtained; the ultraviolet radiation field attenuation model is coupled with an ultraviolet sterilization threshold database to obtain an ultraviolet dose space distribution graph; the objects to be disinfected are disinfected according to the ultraviolet dose space distribution graph; the ultraviolet radiation field attenuation model is dynamically corrected based on irradiance feedback data of the objects to be disinfected during disinfection to obtain an ultraviolet dose regulation and control instruction of the objects to be disinfected; and when the ultraviolet dose regulation and control instruction reaches a biological safety threshold, the disinfection process is terminated; and the application can improve the efficiency of intelligent disinfection.

Description

Technical Field

[0001] This invention relates to the field of intelligent disinfection technology, and in particular to an ultraviolet intelligent disinfection control system and method based on environmental perception. Background Technology

[0002] Existing technologies for ultraviolet (UV) disinfection lack sufficient environmental perception capabilities in the disinfection area, making it difficult to accurately obtain the three-dimensional spatial distribution and surface reflectivity characteristics of the objects to be disinfected. This results in significant discrepancies between the constructed UV radiation field model and the actual scene, failing to accurately reflect the attenuation patterns of UV radiation on different object surfaces and in space. Consequently, the distribution of disinfection dosage lacks specificity, easily leading to incomplete local disinfection or overdosing, severely impacting disinfection efficiency.

[0003] Meanwhile, existing technologies lack a dynamic correction mechanism, making it impossible to adjust the radiation field model based on real-time irradiance data during the disinfection process. When the position, surface condition, or environmental factors of the object to be disinfected change, the model cannot adapt to these changes in a timely manner, leading to a disconnect between subsequent disinfection dosage control instructions and actual needs. This further exacerbates the instability of the disinfection effect and makes it difficult to meet the requirements for efficient and precise intelligent disinfection. Summary of the Invention

[0004] This invention provides an environmentally sensitive ultraviolet intelligent disinfection control system and method to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides an environmentally sensitive ultraviolet intelligent disinfection control system, characterized in that the system includes an information extraction module, a radiation model construction module, a dose distribution module, a disinfection module, a data feedback module, and a disinfection termination module, wherein:

[0006] The information extraction module is used to acquire three-dimensional point cloud data of the disinfection area and reflectivity characteristics of the object to be disinfected.

[0007] The radiation model construction module is used to construct an initial model based on the three-dimensional point cloud data and the reflectivity features, and to perform reflectivity compensation on the initial model to obtain the ultraviolet radiation field attenuation model of the object to be disinfected.

[0008] The dose distribution module is used to couple the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain the ultraviolet dose spatial distribution map of the disinfection area.

[0009] The disinfection module is used to disinfect the object to be disinfected according to the ultraviolet dose spatial distribution map;

[0010] The data feedback module is used to dynamically correct the ultraviolet radiation field attenuation model based on the irradiance feedback data of the object to be disinfected during disinfection, so as to obtain the ultraviolet dose control command of the object to be disinfected.

[0011] The disinfection termination module is used to terminate the disinfection process when the ultraviolet dose control command reaches the biosafety threshold.

[0012] In a preferred embodiment, when the information extraction module acquires the three-dimensional point cloud data of the disinfection area and the reflectivity characteristics of the object to be disinfected, it is specifically used for:

[0013] Multi-angle depth scanning of the disinfection area is performed to obtain the original point cloud dataset of the disinfection area;

[0014] The original point cloud dataset after outlier filtering is reconstructed using a surface to form a three-dimensional point cloud model of the disinfected area.

[0015] Collect the surface spectral reflectance characteristics of the object to be disinfected;

[0016] The surface spectral reflectance characteristics are matched and mapped with the material optical database to obtain the reflectance parameters of the object to be disinfected.

[0017] In a preferred embodiment, when the radiation model construction module performs the initial model construction based on the three-dimensional point cloud data and the reflectivity features, it is specifically used for:

[0018] The surface curvature consistency filtering process is applied to the three-dimensional point cloud data.

[0019] A spatial-optical correlation dataset between the vertex coordinates of the point cloud and the reflectance acquisition location is established in the 3D point cloud data after surface curvature consistency filtering.

[0020] The spatial-optical correlation dataset is transformed into an initial radiative transfer model of the object to be disinfected.

[0021] In a preferred embodiment, when the radiation model construction module performs reflectivity compensation on the initial model to obtain the ultraviolet radiation field attenuation model of the object to be disinfected, it is specifically used for:

[0022] Identify the surface material type of the object to be disinfected;

[0023] Based on the reflectivity compensation coefficient set corresponding to the surface material type, the surface optical properties of the initial radiative transfer model are corrected to obtain the initial model of the object to be disinfected.

[0024] In a preferred embodiment, when the dose distribution module couples the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain the ultraviolet dose spatial distribution map of the disinfection area, it is specifically used for:

[0025] Extract the spatial distribution value of radiation intensity from the ultraviolet radiation field attenuation model;

[0026] Based on the disinfection target, the corresponding inactivation coefficient set is retrieved from the ultraviolet sterilization threshold database;

[0027] A spatial distribution map of ultraviolet dose is generated based on the inactivation coefficient set;

[0028] Perform a spatial continuity check on the ultraviolet dose spatial distribution map and output an ultraviolet dose spatial distribution map with a qualified spatial continuity check result.

[0029] In a preferred embodiment, when the dose distribution module generates an ultraviolet dose spatial distribution map based on the inactivation coefficient set, it is specifically used for:

[0030] The ultraviolet radiation dose in the disinfection area is generated using a dose mapping function, wherein the formula for calculating the ultraviolet radiation dose is as follows:

[0031] ;

[0032] In the formula, coordinates UV dose at the location, coordinates Disinfection time is Spatial distribution of radiation intensity at time The inactivation coefficients are the microbial inactivation coefficients in the inactivation coefficient set. For dose accumulation function, For differential operators, For disinfection duration;

[0033] A spatial distribution map of ultraviolet dose in the disinfection area is constructed based on the ultraviolet dose.

[0034] In a preferred embodiment, when the data feedback module performs dynamic correction on the ultraviolet radiation field attenuation model based on the irradiance feedback data of the object to be disinfected during disinfection, and obtains the ultraviolet dose control command for the object to be disinfected, it is specifically used for:

[0035] Obtain the measured irradiance dataset of the object to be disinfected;

[0036] Extract the predicted irradiance dataset for the corresponding location from the ultraviolet radiation field attenuation model;

[0037] The model parameter corrections for the ultraviolet radiation field attenuation model are generated based on the predicted irradiance dataset.

[0038] The model parameter correction is applied to the structural parameters of the ultraviolet radiation field attenuation model.

[0039] When the correction amount of the model parameters in three consecutive iterations is less than the convergence threshold, the ultraviolet dose control command for the object to be disinfected is obtained.

[0040] In a preferred embodiment, the formula for calculating the model parameter correction is as follows:

[0041] ;

[0042] In the formula, This is the correction amount for the model parameters. For parameter optimization functions, This is the measured irradiance dataset. For the predicted irradiance dataset, This is the spatial weight matrix.

[0043] In a preferred embodiment, when the disinfection termination module terminates the disinfection process upon reaching the biosafety threshold using the ultraviolet dose adjustment command, it is specifically configured to:

[0044] Compare the ultraviolet dose control command with the preset biosafety threshold;

[0045] When the value of the ultraviolet dose control command is consistently not lower than the biosafety threshold, a disinfection termination signal is generated;

[0046] The disinfection process is terminated by cutting off the power supply circuit of the ultraviolet emitting component based on the disinfection termination signal of the disinfection area.

[0047] To address the above problems, the present invention also provides an intelligent ultraviolet disinfection control method based on environmental perception, the method comprising:

[0048] S1. Obtain the three-dimensional point cloud data of the disinfection area and the reflectivity characteristics of the object to be disinfected;

[0049] S2. Based on the three-dimensional point cloud data and the reflectivity features, an initial model is constructed, and reflectivity compensation is performed on the initial model to obtain the ultraviolet radiation field attenuation model of the object to be disinfected.

[0050] S3. Couple the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain the ultraviolet dose spatial distribution map of the disinfection area.

[0051] S4. Disinfect the object to be disinfected according to the ultraviolet dose spatial distribution map;

[0052] S5. Based on the irradiance feedback data of the object to be disinfected during disinfection, the ultraviolet radiation field attenuation model is dynamically corrected to obtain the ultraviolet dose control command of the object to be disinfected.

[0053] S6. When the ultraviolet dose control command reaches the biosafety threshold, the disinfection process is terminated.

[0054] Compared with the prior art, the present invention has the following beneficial effects:

[0055] 1. This invention acquires three-dimensional point cloud data of the disinfection area and reflectivity characteristics of the object to be disinfected through an information extraction module. Based on this, an initial model is constructed and reflectivity compensation is performed to obtain an accurate ultraviolet radiation field attenuation model. The ultraviolet dose spatial distribution map generated by coupling this model with an ultraviolet sterilization threshold database provides targeted dose guidance for disinfection, ensuring that each area of ​​the object to be disinfected receives an appropriate disinfection dose, effectively improving the accuracy and comprehensiveness of disinfection.

[0056] 2. This invention introduces a data feedback module to dynamically correct the ultraviolet radiation field attenuation model based on irradiance feedback data during disinfection. This allows the model to adapt to environmental changes during disinfection in real time, thereby generating precise ultraviolet dose control commands. When the command reaches the biosafety threshold, the disinfection termination module promptly terminates the process, avoiding unnecessary energy consumption while ensuring the disinfection effect meets standards, thus significantly improving the efficiency of intelligent disinfection. Attached Figure Description

[0057] Figure 1 A system architecture diagram of an environmentally sensitive ultraviolet intelligent disinfection control system provided in an embodiment of the present invention;

[0058] Figure 2 This is a schematic flowchart of an environmentally sensitive ultraviolet intelligent disinfection control method provided in an embodiment of the present invention.

[0059] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments belong to some, but not all, 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.

[0061] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “said” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0062] Depending on the context, the word "if" or "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0063] Furthermore, the timing of the steps in the following method embodiments is merely an example and not a strict limitation.

[0064] In practice, the server-side equipment deployed in an environment-aware ultraviolet (UV) intelligent disinfection control system may consist of one or more devices. This environment-aware UV intelligent disinfection control system can be implemented as a business instance, a virtual machine, or hardware devices. For example, it can be implemented as a business instance deployed on one or more devices in a cloud node. Simply put, it can be understood as software deployed on a cloud node, providing environment-aware UV intelligent disinfection control to various user terminals. Alternatively, it can be implemented as a virtual machine deployed on one or more devices in a cloud node, with application software installed to manage various user terminals. Or, it can also be implemented as a server composed of numerous identical or different types of hardware devices, with one or more devices configured to provide environment-aware UV intelligent disinfection control to various user terminals.

[0065] In terms of implementation, the environmentally aware ultraviolet intelligent disinfection control system and the user terminal are mutually compatible. That is, if the environmentally aware ultraviolet intelligent disinfection control system is implemented as an application installed on a cloud service platform, then the user terminal is a client that establishes a communication connection with the application; or if the environmentally aware ultraviolet intelligent disinfection control system is implemented as a website, then the user terminal is implemented as a webpage; or if the environmentally aware ultraviolet intelligent disinfection control system is implemented as a cloud service platform, then the user terminal is implemented as a mini-program in an instant messaging application.

[0066] like Figure 1 The figure shown is a system architecture diagram of an ultraviolet intelligent disinfection control system based on environmental perception provided in an embodiment of the present invention.

[0067] The environmentally-aware ultraviolet intelligent disinfection control system 100 of this invention can be installed on a cloud server. In terms of implementation, it can function as one or more service devices, or as an application installed on the cloud (e.g., a mobile service operator's server, server cluster, etc.), or it can be developed into a website. Depending on the functions implemented, the environmentally-aware ultraviolet intelligent disinfection control system 100 may include an information extraction module 101, a radiation model construction module 102, a dose distribution module 103, a disinfection module 104, a data feedback module 105, and a disinfection termination module 106. The module described in this invention can also be called a unit, referring to a series of computer program segments that can be executed by an electronic device's processor and perform a fixed function, stored in the electronic device's memory.

[0068] In this embodiment of the invention, in the environmentally aware ultraviolet intelligent disinfection control system, each of the above-mentioned modules can be implemented independently and can call other modules. Here, "calling" can be understood as one module connecting to multiple modules of another type and providing corresponding services to those connected modules. In the environmentally aware ultraviolet intelligent disinfection control system provided by this embodiment of the invention, the applicable scope of the environmentally aware ultraviolet intelligent disinfection control system architecture can be adjusted by adding modules and directly calling them without modifying the program code, achieving cluster-based horizontal expansion to quickly and flexibly expand the environmentally aware ultraviolet intelligent disinfection control system. In practical applications, the above modules can be set in the same device or different devices, or they can be set in a virtual device, such as a service instance in a cloud server.

[0069] The following describes the components and specific workflow of the environmentally sensitive ultraviolet intelligent disinfection control system using specific embodiments:

[0070] The information extraction module 101 is used to acquire three-dimensional point cloud data of the disinfection area and reflectivity characteristics of the object to be disinfected.

[0071] In this embodiment of the invention, when the information extraction module acquires the three-dimensional point cloud data of the disinfection area and the reflectivity characteristics of the object to be disinfected, it is specifically used for:

[0072] Multi-angle depth scanning of the disinfection area is performed to obtain the original point cloud dataset of the disinfection area;

[0073] The original point cloud dataset after outlier filtering is reconstructed using a surface to form a three-dimensional point cloud model of the disinfected area.

[0074] Collect the surface spectral reflectance characteristics of the object to be disinfected;

[0075] The surface spectral reflectance characteristics are matched and mapped with the material optical database to obtain the reflectance parameters of the object to be disinfected.

[0076] Specifically, a 3D laser scanner is used to perform multi-angle depth scanning of the disinfection area. First, the boundary of the disinfection area is determined. Eight to ten scanning stations are evenly selected around the perimeter of the area, maintaining a distance of 3 to 5 meters between each station, ensuring that the scanning range of adjacent stations overlaps by more than 30%. The scanner is fixed on a tripod, and the tripod height is adjusted to 1.5 meters, ensuring the scanner lens is level with the center of the area. After turning on the scanner, the scanning resolution is set to 1000 points per square meter. Automatic scanning mode is activated, and the scanner rotates 360 degrees to emit a laser beam. The laser beam reflects immediately upon contact with walls, floors, and object surfaces within the area. The scanner's built-in timer records the round-trip time of the laser beam. Combined with the scanner's spatial coordinates, the X, Y, and Z 3D coordinates of each reflection point are calculated. After scanning one station, the tripod is moved to the next station, and the above operation is repeated until all stations have been scanned. The 3D coordinate data acquired from each station is imported into a computer and merged to form a 3D coordinate set containing millions of points, i.e., the original point cloud dataset of the disinfection area.

[0077] Furthermore, outlier filtering is performed on the original point cloud dataset using a radius filtering method. First, 100 evenly distributed points are randomly selected from the dataset. The average number of points within a 10cm radius of each point is counted, and 60% of this average is taken as a preset minimum value. Simultaneously, the sphere radius is set to 10cm. A computer program extracts each point from the original point cloud dataset, generating a virtual sphere with a 10cm radius centered on that point. The number of other points contained within the sphere is counted; if the number is lower than the preset minimum value, the program automatically deletes that point from the dataset. After checking all points, the outlier-filtered point cloud dataset is obtained. Next, surface reconstruction is performed using the Poisson reconstruction method. The processed point cloud data is input into the computer, and the program calculates a normal vector pointing outwards for each point. A 3D mesh is then constructed based on the coordinates and normal vectors of all points. A continuous implicit function is generated through mesh interpolation, ensuring all points fall on the zero-value surface of this function. Finally, a coherent surface is generated based on the contour of the zero-value surface, forming a 3D point cloud model of the disinfected area.

[0078] Further, a portable spectrometer was used to collect the surface spectral reflectance characteristics of the object to be disinfected. First, the spectrometer was connected to the computer, and the accompanying software was opened for a 30-minute warm-up. A standard white board was placed next to the object to be disinfected, and the spectrometer's probe was aligned with the center of the white board at a distance of 10 cm and perpendicular to the surface. The "Calibrate" button in the software was clicked to complete the baseline calibration of the spectrometer. After calibration, the white board was removed, and the probe was aligned with the surface of the object to be disinfected, maintaining the same distance and angle, ensuring that the probe lens completely covered a 2 square centimeter area on the object's surface without any shadows. The software controlled the spectrometer to emit a continuous light beam with wavelengths from 400 nm to 1000 nm. After the beam irradiated the object's surface, some light was absorbed and some was reflected. The spectrometer's sensor received the reflected light, converted the light signal into an electrical signal, and the software recorded the electrical signal intensity corresponding to each wavelength, generating a continuous curve with wavelength as the horizontal axis and reflected light intensity as the vertical axis, which represents the surface spectral reflectance characteristics of the object to be disinfected.

[0079] Furthermore, the surface spectral reflectance characteristics of the object to be disinfected are matched and mapped with a material optics database. This database contains information on over 500 materials, including metals, plastics, wood, and fabrics. The surface spectral reflectance characteristics of each material are collected using the same spectrometer under identical conditions and archived as standard curves. Each standard curve is associated with the reflectance parameters of that material at different wavelengths. During matching, the spectral reflectance characteristic curve of the object to be disinfected is imported into the database matching system. The system automatically compares this curve with the standard curves in the database. Starting from a wavelength of 400 nanometers, every 5 nanometers is considered an interval. The difference in the ordinate of the curve of the object to be disinfected and each standard curve is calculated for each interval. The sum of the differences across all intervals is accumulated, and the standard curve with the smallest sum of differences is the curve with the highest matching degree. The system extracts the reflectance parameter corresponding to this curve as the reflectance parameter of the object to be disinfected.

[0080] In summary, acquiring 3D point cloud data of the disinfection area and reflectivity characteristics of the objects to be disinfected provides fundamental data support for subsequently constructing an accurate ultraviolet radiation field attenuation model. 3D point cloud data accurately presents the spatial structure of the disinfection area and the 3D distribution of the objects to be disinfected, while reflectivity characteristics reflect the surface reflection of ultraviolet light. The combination of these two features makes the initial model more closely resemble the actual scene, laying the foundation for the accuracy of subsequent reflectivity compensation and radiation field models.

[0081] In summary, the acquisition of this data allows the system to analyze the optical properties of different objects in a targeted manner, ensuring that the influence of the surface reflectivity of objects on ultraviolet radiation can be fully considered when constructing the spatial distribution map of ultraviolet dose. This makes the dose distribution more in line with the actual needs of the objects to be disinfected, providing data support for precise disinfection and helping to improve the effectiveness and rationality of disinfection.

[0082] The radiation model construction module 102 is used to construct an initial model based on the three-dimensional point cloud data and the reflectivity features, perform reflectivity compensation on the initial model, and obtain the ultraviolet radiation field attenuation model of the object to be disinfected.

[0083] In this embodiment of the invention, when the radiation model construction module performs the initial model construction based on the three-dimensional point cloud data and the reflectivity features, it is specifically used for:

[0084] The surface curvature consistency filtering process is applied to the three-dimensional point cloud data.

[0085] A spatial-optical correlation dataset between the vertex coordinates of the point cloud and the reflectance acquisition location is established in the 3D point cloud data after surface curvature consistency filtering.

[0086] The spatial-optical correlation dataset is transformed into an initial radiative transfer model of the object to be disinfected.

[0087] When the radiation model construction module performs reflectivity compensation on the initial model to obtain the ultraviolet radiation field attenuation model of the object to be disinfected, it is specifically used for:

[0088] Identify the surface material type of the object to be disinfected;

[0089] Based on the reflectivity compensation coefficient set corresponding to the surface material type, the surface optical properties of the initial radiative transfer model are corrected to obtain the initial model of the object to be disinfected.

[0090] Specifically, surface curvature consistency filtering is performed on the 3D point cloud data. First, a neighborhood range is determined for each point in the dataset. The 50 nearest points around each point are selected to form its neighborhood. The curvature value is obtained by calculating the curvature of the surface formed by all points in the neighborhood at that point. Specifically, the points in the neighborhood are fitted to a plane, and the ratio of the distance from the point to the plane to the radius of the neighborhood is measured. The larger the ratio, the greater the curvature. Then, the curvature values ​​of each point are compared with those of all points in its neighborhood. The difference between the curvature values ​​of the neighborhood points and the curvature value of the point is calculated. If more than 80% of the curvature differences between the point and the neighboring points are within a preset range, the point is retained; otherwise, it is identified as a noise point and removed. After processing, the 3D point cloud data with surface curvature consistency filtering is obtained.

[0091] Furthermore, the 3D coordinates of all point cloud vertices are extracted and recorded from the 3D point cloud data after surface curvature consistency filtering. Simultaneously, the 3D coordinates of the reflectance acquisition locations recorded when collecting spectral reflectance characteristics of the object to be disinfected are retrieved. These coordinates are obtained by placing positioning markers at the acquisition points and then scanning the markers with a 3D laser scanner. The point cloud vertex coordinates and reflectance acquisition location coordinates are imported into the same coordinate system. The spatial distance between each reflectance acquisition location coordinate and all point cloud vertex coordinates is calculated. The nearest point cloud vertex is found, and its coordinates are bound to the corresponding reflectance data. The set formed by summing all binding relationships is the spatial-optical correlation dataset of point cloud vertex coordinates and reflectance acquisition locations.

[0092] Furthermore, the spatial-optical correlation dataset is transformed into an initial radiative transfer model of the object to be disinfected. First, a 3D mesh model of the object is constructed based on the vertex coordinates of the point cloud in the spatial-optical correlation dataset, with each vertex of the mesh corresponding to a reflectivity value. Next, the light propagation rules in the model are set, i.e., when light shines on a vertex of the mesh, the direction and intensity of the reflected light are determined based on the reflectivity value of that vertex. The reflection direction is calculated based on the normal direction of the surface where the vertex is located, and the reflection intensity is proportional to the reflectivity value. Then, a light source position and intensity are preset in the model to simulate the process of light emanating from the light source and undergoing reflection and absorption at each vertex of the surface of the object to be disinfected. Finally, the transmission path and energy change of the light on the surface of the object are output. The model constructed in this way is the initial radiative transfer model of the object to be disinfected.

[0093] Specifically, to identify the surface material type of the object to be disinfected, first obtain the surface spectral reflectance characteristic curve of the object, which contains reflected light intensity data in the wavelength range from 400 nm to 1000 nm. Prepare a pre-established material spectral feature library, which includes standard spectral reflectance characteristic curves of 50 common materials. The standard curve for each material is generated by averaging the spectral data of a standard sample of that material under the same environmental conditions after 10 spectral acquisitions. Each standard curve is clearly labeled with the corresponding material name, such as stainless steel, polyethylene, ceramic, pine, etc. Compare the spectral reflectance characteristic curve of the object to be disinfected with the standard curves in the material spectral feature library one by one. The comparison starts from the 400 nm wavelength, with each interval being 10 nm. Calculate the difference in reflected light intensity between the curve of the object to be disinfected and the standard curve in each interval. If the difference is less than 0.05, the interval is considered to overlap. Count the proportion of all overlapping intervals to the total number of intervals, and select the material name corresponding to the standard curve with the highest proportion, which is the surface material type of the object to be disinfected.

[0094] Furthermore, based on the reflectivity compensation coefficient set corresponding to the surface material type of the object to be disinfected, the initial radiative transfer model is corrected for its surface optical properties. The reflectivity compensation coefficient set corresponding to the surface material type is extracted from the material parameter database. This coefficient set includes compensation coefficients for every 20 nanometers within the wavelength range of 400 nm to 1000 nm at incident angles of 0°, 15°, 30°, 45°, 60°, 75°, and 90°. These coefficients are calculated by performing 100 reflectivity measurements on the material sample at different incident angles and wavelengths in the laboratory, and then comparing these measurements with theoretical values. The parameter editing interface of the initial radiative transfer model is opened. Each grid vertex in this interface contains corresponding input boxes for the incident angle and wavelength. Based on the incident ray angle and wavelength of each grid vertex in the model, the corresponding compensation coefficient is selected from the reflectivity compensation coefficient set and input into the compensation parameter field of that vertex. The model automatically multiplies the original reflectivity value by the input compensation coefficient to obtain the corrected reflectivity value, and recalculates the propagation direction and energy attenuation of the reflected light accordingly. After correction, three different mesh vertices in the model are selected, and the reflected light intensity at each location is measured and compared with the reflected light intensity output by the model. If the deviation is less than 5% for all three locations, the correction is considered effective, and the model at this point becomes the initial model of the object to be disinfected.

[0095] In summary, an initial model is constructed based on 3D point cloud data and reflectivity features, and reflectivity compensation is applied to obtain an ultraviolet radiation field attenuation model. This model can accurately characterize the spatial structure of the disinfection area and the surface optical properties of the objects to be disinfected. The 3D point cloud data provides the model with information on the 3D spatial distribution of the objects, while the reflectivity features incorporate the reflection patterns of ultraviolet light on the object's surface. The combination of these two features ensures that the initial model closely matches the actual scene in terms of both spatial morphology and optical interaction.

[0096] In summary, the reflectivity compensation performed on this basis further corrects for the differences in the impact of different surface materials on ultraviolet radiation, enabling the final ultraviolet radiation field attenuation model to accurately reflect the transmission and attenuation patterns of ultraviolet radiation in complex environments. This provides a reliable model foundation for the subsequent generation of accurate spatial distribution maps of ultraviolet dose, ensuring that the calculation and allocation of ultraviolet dose during disinfection are more in line with actual needs, thereby improving the accuracy and effectiveness of disinfection.

[0097] The dose distribution module 103 is used to couple the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain the ultraviolet dose spatial distribution map of the disinfection area.

[0098] In this embodiment of the invention, when the dose distribution module couples the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain the ultraviolet dose spatial distribution map of the disinfection area, it is specifically used for:

[0099] Extract the spatial distribution value of radiation intensity from the ultraviolet radiation field attenuation model;

[0100] Based on the disinfection target, the corresponding inactivation coefficient set is retrieved from the ultraviolet sterilization threshold database;

[0101] A spatial distribution map of ultraviolet dose is generated based on the inactivation coefficient set;

[0102] Perform a spatial continuity check on the ultraviolet dose spatial distribution map and output an ultraviolet dose spatial distribution map with a qualified spatial continuity check result.

[0103] When the dose distribution module generates an ultraviolet dose spatial distribution map based on the inactivation coefficient set, it is specifically used for:

[0104] The ultraviolet radiation dose in the disinfection area is generated using a dose mapping function, wherein the formula for calculating the ultraviolet radiation dose is as follows:

[0105] ;

[0106] In the formula, coordinates UV dose at the location, coordinates Disinfection time is Spatial distribution of radiation intensity at time The inactivation coefficients are the microbial inactivation coefficients in the inactivation coefficient set. For dose accumulation function, For differential operators, For disinfection duration;

[0107] A spatial distribution map of ultraviolet dose in the disinfection area is constructed based on the ultraviolet dose.

[0108] Specifically, the spatial distribution values ​​of radiation intensity are extracted from the ultraviolet radiation field attenuation model. First, the three-dimensional coordinate system of the model is defined, with the bottom left corner of the disinfection area as the origin, the horizontal axis as the X-axis, the vertical axis as the Y-axis, and the vertical axis as the Z-axis, all in centimeters. A grid is created at 5-centimeter intervals along the X-axis, Y-axis, and Z-axis, forming uniformly distributed spatial sampling points throughout the disinfection area, ensuring that each corner contains at least one sampling point. The data recording file of the ultraviolet radiation field attenuation model is opened. This file stores the radiation intensity data for each location in coordinate order, with the data format "X coordinate, Y coordinate, Z coordinate, radiation intensity (µW / cm²)". The coordinates of each sampling point are located one by one, and the corresponding radiation intensity value is found in the file. The correspondence between coordinates and values ​​is checked during recording to avoid misalignment. The coordinates and corresponding intensities of all sampling points are compiled into a table. The first column of the table is the X-coordinate, the second column is the Y-coordinate, the third column is the Z-coordinate, and the fourth column is the radiation intensity. This table represents the spatial distribution values ​​of radiation intensity.

[0109] Further, based on the disinfection target, the corresponding inactivation coefficient set is retrieved from the ultraviolet sterilization threshold database. First, the main pollutant microbial species in the environment to be disinfected are determined through laboratory testing. For example, if Bacillus subtilis is identified through colony observation in a petri dish, this species becomes the disinfection target. The ultraviolet sterilization threshold database is opened. This database uses a hierarchical directory structure. The first-level directory lists microbial categories (e.g., bacteria, viruses, fungi), and the second-level directory lists specific microbial names. Each second-level directory contains an Excel file containing the inactivation coefficient set for that microorganism. The coefficient set is divided into three columns: radiation intensity range (µW / cm²), corresponding inactivation rate (percentage), and required contact time (minutes). The corresponding category directory in the database is opened sequentially, and the Excel file matching the disinfection target is found. The file is opened by double-clicking, and the data is checked for completeness. After confirming there are no missing rows or incorrect values, the file is saved as a CSV file in the current working folder. This CSV file is the retrieved inactivation coefficient set.

[0110] Further, an ultraviolet dose spatial distribution map is generated based on the inactivation coefficient set. First, the radiation intensity spatial distribution value table and the inactivation coefficient set CSV file are imported into the same data processing table. The correspondence between the two is matched by the radiation intensity values; that is, for each value in the radiation intensity spatial distribution values, the corresponding exposure time for the same intensity range in the inactivation coefficient set is found. For each sampling point, its radiation intensity value is multiplied by the matched exposure time to calculate the ultraviolet dose value at that point (in microwatts per minute per square centimeter), which is recorded in the fifth column of the data processing table. The data containing three-dimensional coordinates and dose values ​​is imported into a three-dimensional drawing tool. The tool automatically constructs a spatial coordinate system with X, Y, and Z axes, setting dose values ​​of 0-500 microwatts per minute per square centimeter to blue, 501-1000 to green, 1001-1500 to yellow, and above 1501 to red. The tool fills the corresponding color according to the dose value of each point and connects discrete points into a continuous surface using an interpolation algorithm, generating a graph containing coordinate scales, color legends, and dose range labels. This graph is the ultraviolet dose spatial distribution map.

[0111] Furthermore, the spatial continuity of the ultraviolet dose spatial distribution map is verified. First, based on experimental data of ultraviolet radiation attenuation on surfaces of the same material, the maximum allowable difference in dose values ​​between adjacent 5 cm sampling points is determined to be 100 microwatts per minute per square centimeter. A table of sampling point coordinates and dose values ​​for the ultraviolet dose spatial distribution map is printed out. Each sampling point is selected sequentially in ascending order along the X-axis, Y-axis, and Z-axis, and its dose value is recorded. Then, adjacent sampling points in the X+5 cm, X-5 cm, Y+5 cm, Y-5 cm, Z+5 cm, and Z-5 cm directions are found, and their dose values ​​are recorded as well. The dose difference in each direction is calculated. If all differences are ≤100 microwatts per minute per square centimeter, it is marked as "qualified" in the table; if any difference is >100, it is marked as "unqualified," and the specific coordinates are recorded. After all checks are completed, if the number of points marked "unqualified" is 0, the ultraviolet dose spatial distribution map is directly output; if there are unqualified points, the matching calculation process between the radiation intensity value of the point and the inactivation coefficient set is rechecked, the error is corrected, the dose value and distribution map are regenerated, and the same method is used to check again until the difference between all adjacent points meets the requirements, and the qualified ultraviolet dose spatial distribution map is output.

[0112] Specifically, The parameters are derived from the coordinates within the disinfection area. The location is determined by a three-dimensional coordinate system and corresponds to the coordinates of the sampling point in the spatial distribution of radiation intensity. The parameters are derived from the ultraviolet radiation field attenuation model. The spatial distribution values ​​of radiation intensity extracted from this model include coordinates. Different disinfection times The corresponding radiation intensity value at that time. The parameters are sourced from an ultraviolet sterilization threshold database. Based on the inactivation coefficient set retrieved according to the disinfection target, the biological inactivation coefficient corresponding to that microorganism is... . The parameters are derived from a functional relationship established based on the correspondence between the spatial distribution values ​​of radiation intensity and the set of inactivation coefficients. The specific form of the function is determined by matching the radiation intensity values ​​with the exposure time. The parameters are derived from the duration set for the disinfection operation, and are determined based on the action time parameters of the disinfection target and the inactivation coefficient.

[0113] Furthermore, the formula is used to calculate the coordinates within the disinfection area. The ultraviolet dose at the location is determined by the coordinates during the disinfection duration. At different times Spatial distribution of radiation intensity With biological inactivation coefficient After dose accumulation function The results after treatment are integrated to obtain the total ultraviolet radiation dose received at that location during the entire disinfection process. This dose reflects the inactivation effect of ultraviolet light on microorganisms at that location.

[0114] Furthermore, the trend of the formula is that as the disinfection duration... As the value increases, the interval of integration expands. If, within the increased time, the spatial distribution value of radiation intensity... Remaining constant or with minimal change, after dose accumulation function After processing, the integration result It will increase with the increase of t. When the spatial distribution value of radiation intensity... When the dose increases, the result processed by the dose accumulation function f(*) increases within the same time period, and the integral is obtained as follows: It will also increase accordingly. When the bioinactivation coefficient k_m increases, it will increase through the dose accumulation function. This processing will increase the accumulated amount at each time point, thus leading to a decrease in the final integral. Increase.

[0115] In summary, coupling the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain a spatial distribution map of ultraviolet dose in the disinfection area enables precise matching between ultraviolet radiation characteristics and sterilization requirements. The ultraviolet radiation field attenuation model provides the spatial distribution law of ultraviolet radiation intensity within the disinfection area, while the ultraviolet sterilization threshold database contains the inactivation standards required for different disinfection targets. The coupling of the two can transform radiation field data into dose distribution information with clear sterilization significance.

[0116] In summary, the ultraviolet dose spatial distribution map generated by this coupling can clearly show the required ultraviolet dose at each location within the disinfection area, providing a precise operational basis for the disinfection module. This ensures that each area of ​​the object to be disinfected receives an ultraviolet dose that meets the sterilization requirements, avoiding incomplete disinfection due to insufficient dose and reducing resource waste caused by excessive dose, thereby improving the scientific nature and efficiency of the disinfection process.

[0117] The disinfection module 104 is used to disinfect the object to be disinfected according to the ultraviolet dose spatial distribution map;

[0118] In this embodiment of the invention, the required ultraviolet irradiation time for each location on the surface of the object to be disinfected is determined based on the ultraviolet dose spatial distribution map. First, the three-dimensional coordinate region corresponding to the object to be disinfected is located in the distribution map, and the ultraviolet dose value and corresponding radiation intensity of each sampling point within this region are read. Combining this with the action time parameter used when generating the dose value, the irradiation duration corresponding to each dose value is determined, that is, the continuous irradiation time required to reach the dose value when the radiation intensity remains stable. These times are then organized into a table according to their coordinate positions, and the table contains the coordinates of each sampling point on the surface of the object to be disinfected and the corresponding required irradiation time.

[0119] Furthermore, based on the required irradiation time for each location on the prepared surface of the object to be disinfected, the operating parameters of the ultraviolet disinfection equipment are set. The disinfection equipment is placed in a preset fixed position within the disinfection area, ensuring that the ultraviolet emission direction of the equipment can cover all surfaces of the object to be disinfected. The total operating time of the equipment is set according to the longest required irradiation time for each location on the surface of the object to be disinfected. Simultaneously, the power output of the equipment is checked to ensure that its radiation intensity is consistent with the radiation intensity recorded in the ultraviolet dose spatial distribution map, avoiding insufficient or excessive actual doses due to intensity deviations.

[0120] Next, start the ultraviolet disinfection equipment and begin irradiating the objects to be disinfected within the set total running time. During the irradiation process, keep the disinfection area closed to prevent personnel from entering or external light from interfering with the equipment's operation. Observe the equipment's operating status every 10 minutes to confirm that the equipment is emitting ultraviolet light normally and has not experienced any abnormal shutdowns. At the same time, record the irradiation time to ensure that the actual irradiation time is consistent with the set total running time.

[0121] Furthermore, after the irradiation time reaches the set total running time, the ultraviolet disinfection equipment is turned off and allowed to cool down for 30 minutes. Then, the ventilation device in the disinfection area is turned on and ventilated for 15 minutes to reduce the ozone concentration in the area. Afterward, the person enters the disinfection area and uses an ultraviolet dosimeter to detect multiple sampling points on the surface of the object to be disinfected, reading the actual received ultraviolet dose values. These values ​​are compared with the dose values ​​at the corresponding locations on the ultraviolet dose spatial distribution map. If the actual dose values ​​at all detection points reach or exceed the dose values ​​on the distribution map, the disinfection is deemed qualified, and the disinfection of the object to be disinfected is completed. If there are any detection points that do not meet the standards, the irradiation time at that location is readjusted according to the distribution map, and the equipment is restarted for supplementary irradiation until all detection points meet the standards.

[0122] In summary, disinfecting objects based on the spatial distribution map of ultraviolet (UV) dose allows for a highly targeted and precise disinfection process. This map clearly shows the required UV dose at each location within the disinfection area, and the disinfection module operates accordingly, ensuring that every area of ​​the object receives sufficient UV irradiation to meet sterilization requirements.

[0123] In summary, this disinfection method based on precise dosage distribution can ensure that all parts to be disinfected receive an effective disinfection dose, avoiding incomplete disinfection due to insufficient dosage, and can also prevent excessive dosage caused by blind irradiation. Thus, while ensuring the disinfection effect, it improves the efficiency and rationality of the disinfection process.

[0124] The data feedback module 105 is used to dynamically correct the ultraviolet radiation field attenuation model based on the irradiance feedback data of the object to be disinfected during disinfection, so as to obtain the ultraviolet dose control command of the object to be disinfected.

[0125] In this embodiment of the invention, when the data feedback module performs dynamic correction of the ultraviolet radiation field attenuation model based on the irradiance feedback data of the object to be disinfected during disinfection, and obtains the ultraviolet dose adjustment command for the object to be disinfected, it is specifically used for:

[0126] Obtain the measured irradiance dataset of the object to be disinfected;

[0127] Extract the predicted irradiance dataset for the corresponding location from the ultraviolet radiation field attenuation model;

[0128] The model parameter corrections for the ultraviolet radiation field attenuation model are generated based on the predicted irradiance dataset.

[0129] The model parameter correction is applied to the structural parameters of the ultraviolet radiation field attenuation model.

[0130] When the correction amount of the model parameters in three consecutive iterations is less than the convergence threshold, the ultraviolet dose control command for the object to be disinfected is obtained.

[0131] The formula for calculating the model parameter correction is as follows:

[0132] ;

[0133] In the formula, This is the correction amount for the model parameters. For parameter optimization functions, This is the measured irradiance dataset. For the predicted irradiance dataset, This is the spatial weight matrix.

[0134] Specifically, to obtain the measured irradiance dataset of the object to be disinfected, first select three-dimensional coordinate positions on the surface of the object that are the same as the sampling points in the spatial distribution of radiation intensity, ensuring that each position represents a different area of ​​the object's surface. Fix the probe of the portable radiometer at each selected coordinate position, keeping the probe perpendicular to the object's surface and 1 cm away to avoid interference from external light. Turn on the radiometer, and after the values ​​stabilize, read and record the irradiance value at each position in microwatts per square centimeter. Compile the three-dimensional coordinates of all positions and the corresponding measured irradiance values ​​into a table, with the columns of the table being X coordinate, Y coordinate, Z coordinate, and measured irradiance, respectively. This table is the measured irradiance dataset of the object to be disinfected.

[0135] Further, the predicted irradiance dataset for the corresponding location is extracted from the ultraviolet radiation field attenuation model. The data record file of the ultraviolet radiation field attenuation model is opened; this file stores the radiation intensity data for each location in coordinate order, i.e., the predicted irradiance data. Based on the three-dimensional coordinates in the measured irradiance dataset, the radiation intensity value corresponding to the same coordinates is searched one by one in the model data record file. When recording these values, it is ensured that the coordinates are completely matched and no measured location is missed. All the found predicted irradiance values ​​are organized into a table according to their corresponding coordinates. The columns of the table are X coordinate, Y coordinate, Z coordinate, and predicted irradiance, respectively. This table is the predicted irradiance dataset for the corresponding location.

[0136] Furthermore, based on the predicted irradiance dataset, model parameter correction amounts are generated for the ultraviolet radiation field attenuation model. The measured irradiance dataset and the predicted irradiance dataset are placed in the same table, and the measured values ​​and predicted values ​​at the same coordinate locations are compared. The difference between the measured value and the predicted value at each location is calculated. If the measured value is greater than the predicted value, it indicates that the model predicts the irradiance at that location too low, and the corresponding parameter needs to be increased; if the measured value is less than the predicted value, it indicates that the model predicts too high, and the corresponding parameter needs to be decreased. The direction and magnitude of the differences at all locations are statistically analyzed to determine the model parameters that need to be adjusted, such as the light source intensity coefficient and the distance attenuation coefficient. The specific adjustment value for each parameter is calculated based on the average degree of the difference. The set of these adjustment values ​​is the model parameter correction amount.

[0137] Furthermore, the model parameter corrections are applied to the structural parameters of the ultraviolet radiation field attenuation model. The parameter configuration file for the ultraviolet radiation field attenuation model is opened; this file contains various structural parameters of the model, such as the initial intensity of the light source, the reflectivity of different materials, and the air attenuation coefficient. Based on the adjustment value of each parameter in the model parameter corrections, the corresponding structural parameter is found in the configuration file, and the parameter value is increased or decreased according to the correction requirements. For example, if the correction for the light source intensity coefficient is an increase of 5%, then the initial intensity value of the light source in the configuration file is multiplied by 1.05. After modification, the configuration file is saved, and the ultraviolet radiation field attenuation model is rerun to make the corrected structural parameters take effect and generate new predicted irradiance data.

[0138] Furthermore, when the model parameter correction amount in three consecutive iterations is less than the convergence threshold, the ultraviolet dose control command for the object to be disinfected is obtained. The convergence threshold is set to 1% of the initial value of each parameter; that is, when the absolute value of the parameter correction amount is less than 1% of the initial value of the parameter, it is considered that the convergence condition has been met. After completing the first model parameter correction, a new measured irradiance dataset and a predicted irradiance dataset are obtained using the same method, and the second model parameter correction amount is calculated to determine whether it is less than the convergence threshold. If it is not satisfied, the third iteration calculation continues. If the model parameter correction amount in three consecutive iterations is less than the convergence threshold, it indicates that the model prediction value is sufficiently close to the measured value. At this time, based on the ultraviolet dose spatial distribution map generated by the final ultraviolet radiation field attenuation model, the required irradiation time and equipment operating power for each location of the object to be disinfected are determined. This information is organized into a clear operation command, including equipment turn-on time, turn-off time, power level, etc. This command is the ultraviolet dose control command for the object to be disinfected.

[0139] Specifically, The parameters are obtained through the parameter optimization function. The calculation, based on the relative difference between the measured irradiance dataset and the predicted irradiance dataset, as well as the spatial weight matrix, ultimately yields specific adjustment values ​​for correcting the structural parameters of the ultraviolet radiation field attenuation model. The parameters are derived from the measured irradiance at each sampling point on the surface of the object to be disinfected. The measured irradiance dataset is formed by fixing the irradiance meter probe at the corresponding three-dimensional coordinate position, reading the stable values, and organizing them. The parameters are derived from the ultraviolet radiation field attenuation model, which is the predicted irradiance corresponding to the same coordinates as the measured location, and the resulting predicted irradiance dataset is formed after processing. The parameters are derived from the importance of disinfection at each location within the disinfection area. For example, the location on the surface of the object to be disinfected has a higher weight than an open area, and the location near a place where microorganisms are prone to grow has a higher weight. A matrix is ​​constructed by assigning different weight values ​​to different locations to reflect the degree of influence of spatial location on the correction.

[0140] Furthermore, the significance of this formula lies in calculating the relative difference between the measured irradiance dataset and the predicted irradiance dataset, combined with the spatial weight matrix. via parameter optimization function Processing yields the model parameter correction values. This allows for the quantification of the extent to which structural parameters in the ultraviolet radiation field attenuation model need adjustment, making the model's prediction results closer to actual measurements and improving the model's accuracy in predicting irradiance.

[0141] Furthermore, the trend of this formula is: when As the value of increases, meaning the relative difference between the measured irradiance and the predicted irradiance becomes greater, the parameter optimization function... It will output a larger amount The amount of model parameter correction increases accordingly, because a larger adjustment is needed to narrow the gap between the measured and predicted values; when When the value decreases, The magnitude will decrease accordingly, and the correction will be smaller. When the spatial weight matrix... When the weight value at a certain position increases, if the weight value at that position... Differences exist, which will affect The higher the weight of a position, the greater its difference contributes to the correction amount, making the correction focus more on the accuracy of that position.

[0142] In summary, dynamically correcting the ultraviolet radiation field attenuation model based on irradiance feedback data of the object to be disinfected during disinfection enables the model to adapt to environmental changes in real time during the disinfection process. Measured irradiance data directly reflects the radiation state of ultraviolet radiation in actual scenarios. By comparing this data with model predictions and adjusting model parameters, the deviation between the model and reality can be continuously reduced, ensuring that the ultraviolet radiation field attenuation model always accurately depicts the current disinfection environment and improving the model's dynamic adaptability.

[0143] In summary, the resulting ultraviolet dose control instructions better match the real-time needs of the objects to be disinfected. The dynamically calibrated model provides an accurate calculation basis for the control instructions, ensuring that the instructions can be flexibly adjusted according to real-time factors such as the surface condition and position changes of the objects. This ensures that the disinfection dose always meets the sterilization requirements, while avoiding dose imbalance caused by model fixation, thereby enhancing the precise control capability of the disinfection process and further guaranteeing the stability and efficiency of the disinfection effect.

[0144] The disinfection termination module 106 is used to terminate the disinfection process when the ultraviolet dose control command reaches the biosafety threshold.

[0145] In this embodiment of the invention, when the disinfection termination module terminates the disinfection process upon reaching the biosafety threshold using the ultraviolet dose adjustment command, it is specifically used for:

[0146] Compare the ultraviolet dose control command with the preset biosafety threshold;

[0147] When the value of the ultraviolet dose control command is consistently not lower than the biosafety threshold, a disinfection termination signal is generated;

[0148] The disinfection process is terminated by cutting off the power supply circuit of the ultraviolet emitting component based on the disinfection termination signal of the disinfection area.

[0149] Specifically, the ultraviolet (UV) dose values ​​for each location on the object to be disinfected, contained in the UV dose control instructions, are obtained. These values ​​are the core content of the control instructions and reflect the dose that should be achieved at each location during the actual disinfection process. Simultaneously, preset biosafety thresholds are retrieved from biosafety standard documents. These thresholds represent the minimum effective inactivation dose set for the target microorganism; for example, the biosafety threshold for E. coli is a specific value. The dose value for each location in the control instructions is compared one by one with the corresponding biosafety threshold. The dose value, threshold, and comparison result for each location are recorded in a table, with the comparison result marked as "not lower than" or "lower than".

[0150] Furthermore, the continuous detection time interval is set to 5 minutes. After the first comparison shows that the value of the ultraviolet dose regulation command is not lower than the biosafety threshold, the timer starts, and the comparison operation is repeated every 5 minutes for three consecutive comparisons. If the results of the three comparisons all show that the value of the regulation command is not lower than the biosafety threshold, that is, the condition of "continuously not lower than" is met, the control module outputs a high-level electrical signal. This signal carries the disinfection termination indicator information. The time of signal generation and the corresponding comparison result are recorded. This signal is the disinfection termination signal.

[0151] Furthermore, an electromagnetic relay is connected in series in the power supply circuit of the ultraviolet emitting component. The control terminal of this relay is connected to the control module that generates the disinfection termination signal. When the circuit is normally powered, the relay is in a normally closed state, and the contacts are closed to allow current to flow. When the disinfection termination signal is received by the relay control terminal, the control terminal generates a magnetic force after receiving the signal, causing the normally closed contacts of the relay to open, resulting in an interruption of the power supply circuit. The ultraviolet emitting component stops working due to the power failure. At the same time, the indicator light connected in series in the circuit changes from lit to off, indicating that the power supply has been cut off. The time of the power supply circuit cutoff is recorded, and the disinfection process is terminated.

[0152] In summary, terminating the disinfection process when the ultraviolet (UV) dose control command reaches the biosafety threshold ensures precise compliance with disinfection standards. The biosafety threshold is a key indicator for assessing whether disinfection meets safety standards. Using it as the basis for termination ensures that the objects to be disinfected fully meet biosafety requirements after disinfection, fundamentally avoiding safety hazards caused by incomplete disinfection.

[0153] In summary, this termination mechanism effectively avoids excessive ultraviolet radiation. Stopping the disinfection process once the dose reaches the threshold reduces unnecessary energy consumption and lowers equipment operating costs. It also prevents potential damage to certain object surfaces caused by prolonged ultraviolet radiation, thus improving the economy and safety of the disinfection process while ensuring disinfection effectiveness.

[0154] Reference Figure 2 The diagram shown is a flowchart illustrating an environmentally perceptive-based intelligent ultraviolet disinfection control method according to an embodiment of the present invention. In this embodiment, the environmentally perceptive-based intelligent ultraviolet disinfection control method includes:

[0155] S1. Obtain the three-dimensional point cloud data of the disinfection area and the reflectivity characteristics of the object to be disinfected;

[0156] S2. Based on the three-dimensional point cloud data and the reflectivity features, an initial model is constructed, and reflectivity compensation is performed on the initial model to obtain the ultraviolet radiation field attenuation model of the object to be disinfected.

[0157] S3. Couple the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain the ultraviolet dose spatial distribution map of the disinfection area.

[0158] S4. Disinfect the object to be disinfected according to the ultraviolet dose spatial distribution map;

[0159] S5. Based on the irradiance feedback data of the object to be disinfected during disinfection, the ultraviolet radiation field attenuation model is dynamically corrected to obtain the ultraviolet dose control command of the object to be disinfected.

[0160] S6. When the ultraviolet dose control command reaches the biosafety threshold, the disinfection process is terminated.

[0161] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0162] The embodiments of this application can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0163] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A UV intelligent disinfection control system based on environmental perception, characterized in that, The system includes an information extraction module, a radiation model construction module, a dose distribution module, a disinfection module, a data feedback module, and a disinfection termination module, wherein: The information extraction module is used to acquire three-dimensional point cloud data of the disinfection area and reflectivity characteristics of the object to be disinfected. The radiation model construction module is used to construct an initial model based on the three-dimensional point cloud data and the reflectivity features, and to perform reflectivity compensation on the initial model to obtain the ultraviolet radiation field attenuation model of the object to be disinfected. The dose distribution module is used to couple the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain the ultraviolet dose spatial distribution map of the disinfection area. The disinfection module is used to disinfect the object to be disinfected according to the ultraviolet dose spatial distribution map; The data feedback module is used to dynamically correct the ultraviolet radiation field attenuation model based on the irradiance feedback data of the object to be disinfected during disinfection, so as to obtain the ultraviolet dose control command of the object to be disinfected. The disinfection termination module is used to terminate the disinfection process when the ultraviolet dose control command reaches the biosafety threshold.

2. The ultraviolet intelligent disinfection control system based on environmental perception as described in claim 1, characterized in that, When the information extraction module acquires the three-dimensional point cloud data of the disinfection area and the reflectivity characteristics of the object to be disinfected, it is specifically used for: Multi-angle depth scanning of the disinfection area is performed to obtain the original point cloud dataset of the disinfection area; The original point cloud dataset after outlier filtering is reconstructed using a surface to form a three-dimensional point cloud model of the disinfected area. Collect the surface spectral reflectance characteristics of the object to be disinfected; The surface spectral reflectance characteristics are matched and mapped with the material optical database to obtain the reflectance parameters of the object to be disinfected.

3. The ultraviolet intelligent disinfection control system based on environmental perception as described in claim 1, characterized in that, When the radiation model construction module executes the initial model construction based on the 3D point cloud data and the reflectivity features, it is specifically used for: The surface curvature consistency filtering process is applied to the three-dimensional point cloud data. A spatial-optical correlation dataset between the vertex coordinates of the point cloud and the reflectance acquisition location is established in the 3D point cloud data after surface curvature consistency filtering. The spatial-optical correlation dataset is transformed into an initial radiative transfer model of the object to be disinfected.

4. The ultraviolet intelligent disinfection control system based on environmental perception as described in claim 3, characterized in that, When the radiation model construction module performs reflectivity compensation on the initial model to obtain the ultraviolet radiation field attenuation model of the object to be disinfected, it is specifically used for: Identify the surface material type of the object to be disinfected; Based on the reflectivity compensation coefficient set corresponding to the surface material type, the surface optical properties of the initial radiative transfer model are corrected to obtain the initial model of the object to be disinfected.

5. The ultraviolet intelligent disinfection control system based on environmental perception as described in claim 1, characterized in that, When the dose distribution module couples the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain the ultraviolet dose spatial distribution map of the disinfection area, it is specifically used for: Extract the spatial distribution value of radiation intensity from the ultraviolet radiation field attenuation model; Based on the disinfection target, the corresponding inactivation coefficient set is retrieved from the ultraviolet sterilization threshold database; A spatial distribution map of ultraviolet dose is generated based on the inactivation coefficient set; Perform a spatial continuity check on the ultraviolet dose spatial distribution map and output an ultraviolet dose spatial distribution map with a qualified spatial continuity check result.

6. The ultraviolet intelligent disinfection control system based on environmental perception as described in claim 5, characterized in that, When the dose distribution module generates an ultraviolet dose spatial distribution map based on the inactivation coefficient set, it is specifically used for: The ultraviolet radiation dose in the disinfection area is generated using a dose mapping function, wherein the formula for calculating the ultraviolet radiation dose is as follows: ； In the formula, coordinates UV dose at the location, coordinates Disinfection time is Spatial distribution of radiation intensity at time The inactivation coefficients are the microbial inactivation coefficients in the inactivation coefficient set. For dose accumulation function, For differential operators, For disinfection duration; A spatial distribution map of ultraviolet dose in the disinfection area is constructed based on the ultraviolet dose.

7. The ultraviolet intelligent disinfection control system based on environmental perception as described in claim 1, characterized in that, When the data feedback module performs dynamic correction on the ultraviolet radiation field attenuation model based on the irradiance feedback data of the object to be disinfected during disinfection, and obtains the ultraviolet dose control command for the object to be disinfected, it is specifically used for: Obtain the measured irradiance dataset of the object to be disinfected; Extract the predicted irradiance dataset for the corresponding location from the ultraviolet radiation field attenuation model; The model parameter corrections for the ultraviolet radiation field attenuation model are generated based on the predicted irradiance dataset. The model parameter correction is applied to the structural parameters of the ultraviolet radiation field attenuation model. When the correction amount of the model parameters in three consecutive iterations is less than the convergence threshold, the ultraviolet dose control command for the object to be disinfected is obtained.

8. The ultraviolet intelligent disinfection control system based on environmental perception as described in claim 7, characterized in that, The formula for calculating the model parameter correction is as follows: ； In the formula, This is the correction amount for the model parameters. For parameter optimization functions, This is the measured irradiance dataset. For the predicted irradiance dataset, This is the spatial weight matrix.

9. The ultraviolet intelligent disinfection control system based on environmental perception as described in claim 1, characterized in that, When the disinfection termination module terminates the disinfection process upon receiving the ultraviolet dose adjustment command reaching the biosafety threshold, it is specifically used for: Compare the ultraviolet dose control command with the preset biosafety threshold; When the value of the ultraviolet dose control command is consistently not lower than the biosafety threshold, a disinfection termination signal is generated; The disinfection process is terminated by cutting off the power supply circuit of the ultraviolet emitting component based on the disinfection termination signal of the disinfection area.

10. A method for intelligent ultraviolet disinfection control based on environmental perception, characterized in that, The method includes: S1. Obtain the three-dimensional point cloud data of the disinfection area and the reflectivity characteristics of the object to be disinfected; S2. Based on the three-dimensional point cloud data and the reflectivity features, an initial model is constructed, and reflectivity compensation is performed on the initial model to obtain the ultraviolet radiation field attenuation model of the object to be disinfected. S3. Couple the ultraviolet radiation field attenuation model with the ultraviolet sterilization threshold database to obtain the ultraviolet dose spatial distribution map of the disinfection area. S4. Disinfect the object to be disinfected according to the ultraviolet dose spatial distribution map; S5. Based on the irradiance feedback data of the object to be disinfected during disinfection, the ultraviolet radiation field attenuation model is dynamically corrected to obtain the ultraviolet dose control command of the object to be disinfected. S6. When the ultraviolet dose control command reaches the biosafety threshold, the disinfection process is terminated.

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