Rhythmic intelligent lighting method and device based on nano fluorescent materials

Abstract

The present invention discloses a rhythmic intelligent lighting method and device based on nano fluorescent materials, and relates to the field of intelligent lighting technology. Firstly, a preset first spectrum composition parameter is obtained by preliminary matching the time zone information of the ceiling lamp with the rhythmic intelligent lighting reference table. At the same time, the spectrum adjustment parameters of the ceiling lamp's operating area are obtained by monitoring and analyzing the user behavior information and environmental information belonging to the ceiling lamp's operating area. Finally, the required spectrum adjustment parameters of the ceiling lamp are analyzed. The wavelength intensity and color temperature value in the spectrum component are effectively modulated by switching the circuits of the light-emitting lamp beads with different nano fluorescent materials in the lighting device on and off and the current size. The required spectrum adjustment parameters of the ceiling lamp are analyzed, so that the lighting process can be personalized to adapt to user needs, and energy-saving optimization is achieved to reduce energy consumption.

Description

Technical Field

[0001] The present invention relates to the field of intelligent lighting technology, and in particular to a rhythmic intelligent lighting method and device based on nano fluorescent materials. Background Art

[0002] In today's society, people pay more and more attention to the quality of life, and have higher requirements for the comfort and quality of the living environment. As an important part of human life, the light environment has an important impact on the physiological rhythm and emotional state of the human body. Therefore, designing a lighting system that can be adjusted intelligently has become a hot topic in current lighting research.

[0003] The prior art, such as the invention patent with publication number: CN113760206A, is a method, device, electronic device and storage medium for adjusting the brightness of a lighting device. The method includes: determining target hormone secretion parameters and the current brightness of the lighting device; determining the target lighting device brightness according to the target hormone secretion parameters; and adjusting the current lighting device brightness according to the target lighting device brightness.

[0004] Combining the above solutions, it is found that the current rhythmic intelligent lighting method lacks monitoring and processing of user behavior information and environmental information, resulting in the inability to automatically adjust the lighting process according to actual lighting conditions or specific environments, which may cause energy waste and user visual discomfort, reduce lighting comfort, and cause the modulated spectral components to be inaccurate, which may affect the human physiological rhythm and emotional state. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a rhythmic intelligent lighting method and device based on nano fluorescent materials, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a rhythmic intelligent lighting method based on nano-fluorescent materials, including obtaining a rhythmic intelligent lighting reference table in a cloud server, and obtaining the time zone information of the ceiling lamp, and preliminarily matching the preset first spectral composition parameters of the ceiling lamp.

[0007] User behavior information and environmental information of the subordinate operation area of ​​the ceiling lamp are monitored to obtain the spectrum adjustment parameters of the subordinate operation area of ​​the ceiling lamp.

[0008] According to the preset first spectrum composition parameter of the ceiling lamp and the spectrum adjustment parameter of the subordinate operation area of ​​the ceiling lamp, the required spectrum adjustment parameter of the ceiling lamp is analyzed and obtained, and the wavelength intensity and color temperature of the ceiling lamp are controlled and adjusted.

[0009] The wavelength intensity and color temperature of the ceiling lamp are adjusted and controlled based on the white spectrum of the blue-violet light beads of the nano fluorescent material.

[0010] Furthermore, the preliminary matching obtains the preset first spectrum composition parameter of the ceiling lamp, and the specific analysis process is: according to the time zone information of the ceiling lamp, wherein the time zone information includes the current time period of the region where the ceiling lamp belongs to and operates.

[0011] According to the rhythmic intelligent lighting benchmark table in the cloud server, the rhythmic intelligent lighting benchmark table includes spectrum composition parameters for each time period.

[0012] The current time period of the area where the ceiling lamp is operating is compared with the spectral composition parameters of each time period. If the time period comparison is consistent, the spectral composition parameters obtained by the comparison are used as the preset first spectral composition parameters of the ceiling lamp, wherein the preset first spectral composition parameters include preset wavelength intensity and preset color temperature value.

[0013] Furthermore, the user behavior information and environmental information of the subordinate operation area of ​​the ceiling lamp are monitored, and the specific process is: the time period between the current moment and the end time of the current time period in the area where the ceiling lamp is operated is calibrated as the designated time period, and divided to obtain each monitoring time point, the user's position in the subordinate operation area of ​​the ceiling lamp is identified at each monitoring time point, and the acceleration data of the user at each monitoring time point is collected, the acceleration data includes acceleration values ​​in each direction, and the acceleration data is processed by Fourier transform to obtain the spectral energy of the user at each monitoring time point, thereby fitting the acceleration data and spectral energy of the user at each monitoring time point into a four-dimensional feature vector, and counting the four-dimensional feature vector of the user at each monitoring time point.

[0014] The four-dimensional feature vector of the user at each monitoring time point is imported into the machine learning model to obtain the predicted behavior type of the user at each monitoring time point.

[0015] The spectral demand adjustment factors corresponding to each behavior type stored in the database are extracted, and the spectral demand adjustment factors corresponding to the predicted behavior types of the users at each monitoring time point are screened. The wavelength intensity and color temperature values ​​of the ceiling lamps at each monitoring time point are extracted, and compared with the spectral factors corresponding to each wavelength intensity interval and the spectral factors corresponding to each color temperature value interval stored in the database, respectively, to obtain the spectral factors corresponding to the wavelength intensity and color temperature values ​​of the ceiling lamps at each monitoring time point, and then accumulated to obtain the spectral factors of the ceiling lamps at each monitoring time point.

[0016] According to the spectral factor of the ceiling lamp at each monitoring time point and the spectral demand adjustment factor corresponding to the predicted behavior type of the user at each monitoring time point, the spectral demand adjustment measurement value at each monitoring time point is obtained through processing.

[0017] The spectral demand adjustment metering threshold in the database is extracted and compared with the spectral demand adjustment metering value at each monitoring time point. If the spectral demand adjustment metering value at a certain time point is higher than the spectral demand adjustment metering threshold, the time point is recorded as the adjustment time point.

[0018] At each adjustment time point, environmental information of the operating area to which the ceiling lamp belongs is collected, wherein the environmental information includes light intensity, temperature and humidity.

[0019] Furthermore, the spectral demand adjustment measurement value at each monitoring time point represents a quantitative result obtained by monitoring the user behavior in the subordinate operating area of ​​the ceiling lamp, which is used to analyze the degree of adjustment of the spectral demand of the ceiling lamp due to user behavior, and serves as a basis for analyzing the spectral adjustment parameters of the subordinate operating area of ​​the ceiling lamp.

[0020] Furthermore, the spectral adjustment parameters of the subordinate operating area of ​​the ceiling lamp are obtained, and the specific process is: counting the light intensity of the subordinate operating area of ​​the ceiling lamp at each adjustment time point, and matching it with the adapted wavelength intensity corresponding to each light intensity interval in the database, to obtain the adapted wavelength intensity of the ceiling lamp at each adjustment time point.

[0021] The color temperature value of the ceiling lamp at each adjustment time point is extracted, and compared with the regional adaptation temperature and regional adaptation humidity corresponding to each color temperature interval stored in the database to obtain the regional adaptation temperature and regional adaptation humidity of the ceiling lamp at each adjustment time point.

[0022] The temperature of the operating area of ​​the ceiling lamp at each adjustment time point is counted, and the difference is processed with the regional adaptation temperature corresponding to each color temperature interval to obtain the regional temperature deviation value at each adjustment time point, and the first color temperature adjustment value of the ceiling lamp at each adjustment time point is obtained by processing.

[0023] The humidity of the operating area of ​​the ceiling lamp at each adjustment time point is counted, and the difference is processed with the regional adaptation humidity corresponding to each color temperature interval to obtain the regional humidity deviation value at each adjustment time point, and the second color temperature adjustment value of the ceiling lamp at each adjustment time point is obtained by processing.

[0024] The first color temperature adjustment value of the ceiling lamp at each adjustment time point and the second color temperature adjustment value of the ceiling lamp at each adjustment time point are accumulated and averaged to obtain the target color temperature adjustment value of the ceiling lamp at each adjustment time point.

[0025] The adapted wavelength intensity of the ceiling lamp at each adjustment time point and the target color temperature adjustment value of the ceiling lamp at each adjustment time point are combined as the spectrum adjustment parameters of the subordinate operation area of ​​the ceiling lamp.

[0026] Furthermore, the first color temperature adjustment value of the ceiling lamp at each adjustment time point and the second color temperature adjustment value of the ceiling lamp at each adjustment time point, the specific processing process includes: extracting the regional temperature deviation value at each adjustment time point, if the regional temperature deviation value at a certain adjustment time point is equal to 0, then defining the color temperature value of the ceiling lamp at the adjustment time point as the first color temperature adjustment value, if the regional temperature deviation value at a certain adjustment time point is greater than 0 or the regional temperature deviation value is less than 0, then extracting the set color temperature reduction value and color temperature supplement value of the unit temperature difference, processing to obtain the first color temperature adjustment value of the ceiling lamp at the adjustment time point, and traversing and counting the first color temperature adjustment values ​​of the ceiling lamp at each adjustment time point in turn.

[0027] The regional humidity deviation value at each adjustment time point is extracted. If the regional humidity deviation value at a certain adjustment time point is equal to 0, the color temperature value of the ceiling lamp at the adjustment time point is defined as the second color temperature adjustment value. If the regional humidity deviation value at a certain adjustment time point is greater than 0 or the regional humidity deviation value is less than 0, the color temperature loss value and color temperature supplement value of the set unit humidity difference are extracted, and the second color temperature adjustment value of the ceiling lamp at the adjustment time point is obtained by processing. The second color temperature adjustment value of the ceiling lamp at each adjustment time point is traversed and counted in turn.

[0028] Furthermore, the analysis obtains the required spectrum adjustment parameters of the ceiling lamp, and controls the wavelength intensity and color temperature of the ceiling lamp. The specific analysis process is: according to the preset first spectrum composition parameters of the ceiling lamp and the spectrum adjustment parameters of the subordinate operating area of ​​the ceiling lamp, wherein the preset first spectrum composition parameters include preset wavelength intensity and preset color temperature value, and the spectrum adjustment parameters include the adapted wavelength intensity and target color temperature adjustment value of the ceiling lamp at each adjustment time point.

[0029] The execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point and the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point are obtained in sequence through numerical processing.

[0030] According to the execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point, the specified wavelength intensity corresponding to each execution wavelength intensity adjustment coefficient interval stored in the database is compared to obtain the specified wavelength intensity of the ceiling lamp at each adjustment time point.

[0031] According to the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point, the specified color temperature value of the ceiling lamp at each adjustment time point is obtained by comparing it with the specified color temperature value corresponding to each execution color temperature adjustment coefficient interval stored in the database.

[0032] According to the specified wavelength intensity of the ceiling lamp at each adjustment time point and the specified color temperature value of the ceiling lamp at each adjustment time point, the required spectrum adjustment parameters of the ceiling lamp are obtained, thereby adjusting the wavelength intensity and color temperature value of the ceiling lamp at each adjustment time point.

[0033] Furthermore, the spectrum demand adjustment measurement value at each monitoring time point is specifically analyzed under the following conditions:

[0034]

[0035] In the formula, ω j represents the spectral demand adjustment measurement value at the jth monitoring time point, F j represents the spectral factor of the ceiling lamp at the jth monitoring time point, represents the spectrum demand adjustment factor corresponding to the predicted behavior type of the user at the jth monitoring time point, j represents the number of each monitoring time point, j=1,2,3,...,m, and m represents the total number of monitoring time points.

[0036] Furthermore, the specific processing process of the execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point and the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point is: according to the following numerical processing conditions:

[0037]

[0038] Wherein, Y1i represents the execution wavelength intensity adjustment coefficient of the ceiling lamp at the i-th adjustment time point, E1 represents the preset wavelength intensity of the ceiling lamp, Ei2 represents the adaptation wavelength intensity of the ceiling lamp at the i-th adjustment time point, σ1 represents the weight factor corresponding to the preset wavelength intensity, σ2 represents the weight factor corresponding to the set adaptation wavelength intensity, i represents the number of each adjustment time point, i=1,2,3,...,n, n represents the total number of adjustment time points, according to the following numerical processing conditions:

[0039]

[0040] Wherein, Y2i represents the execution color temperature adjustment coefficient of the ceiling lamp at the i-th adjustment time point, E3 represents the preset color temperature value of the ceiling lamp, Ei4 represents the target color temperature adjustment value of the ceiling lamp at the i-th adjustment time point, σ3 represents the weight factor corresponding to the set preset color temperature value, and σ4 represents the weight factor corresponding to the set target color temperature adjustment value.

[0041] The second aspect of the present invention provides a rhythmic intelligent lighting device based on nano-fluorescent materials, which also includes: a processor, and a memory and a network interface connected to the processor; the network interface is connected to a non-volatile memory in a server; when the processor is running, it retrieves a computer program from the non-volatile memory through the network interface, and runs the computer program through the memory to execute the above-mentioned rhythmic intelligent lighting method based on nano-fluorescent materials.

[0042] The present invention has the following beneficial effects:

[0043] (1) The present invention provides a rhythmic intelligent lighting method and device based on nano-fluorescent materials. First, a preset first spectral composition parameter is obtained by preliminary matching according to the time zone information of the ceiling lamp. At the same time, the spectral adjustment parameters of the area are obtained by monitoring the user behavior information and environmental information of the operating area of ​​the ceiling lamp, so as to effectively modulate the wavelength intensity and color temperature value in the spectral component, so that the lighting process can be personalized to adapt to user needs, achieve energy-saving optimization, and reduce energy consumption.

[0044] (2) By obtaining the preset first spectral composition parameters of the ceiling lamp, the present invention can determine the preset spectral composition parameters according to different geographical locations, so that the lighting process is more adapted to the lighting environment and climate characteristics of the area, and helps to more accurately adjust the wavelength intensity and color temperature value of the lighting system, thereby achieving the purpose of energy saving optimization and reducing energy waste.

[0045] (3) The present invention monitors the user behavior information and environmental information of the ceiling lamp's subordinate operating area to obtain the spectral adjustment parameters of the ceiling lamp's subordinate operating area, and can realize personalized lighting adjustment according to the user's behavioral needs and environmental conditions, which helps to provide a lighting experience that is more suitable for user needs, realizes intelligent control of the lighting process, improves the intelligence and adaptability of the system, and thus helps to improve the user's usage experience and comfort.

[0046] (4) The present invention obtains the required spectrum adjustment parameters of the ceiling lamp and controls the wavelength intensity and color temperature of the ceiling lamp, thereby achieving effective control of the spectrum composition parameters, thereby improving energy efficiency, reducing energy consumption, and helping to improve the comfort of the lighting environment, so that users can get a more comfortable lighting environment.

[0047] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] See also Figure 1As shown, an embodiment of the present invention provides a rhythmic intelligent lighting method and device technical solution based on nano-fluorescent materials: a rhythmic intelligent lighting method based on nano-fluorescent materials, comprising obtaining a rhythmic intelligent lighting reference table in a cloud server, and obtaining the time zone information of the ceiling lamp, and preliminarily matching the preset first spectral composition parameters of the ceiling lamp.

[0051] User behavior information and environmental information of the subordinate operation area of ​​the ceiling lamp are monitored to obtain the spectrum adjustment parameters of the subordinate operation area of ​​the ceiling lamp.

[0052] According to the preset first spectrum composition parameter of the ceiling lamp and the spectrum adjustment parameter of the subordinate operation area of ​​the ceiling lamp, the required spectrum adjustment parameter of the ceiling lamp is analyzed and obtained, and the wavelength intensity and color temperature of the ceiling lamp are controlled and adjusted.

[0053] The wavelength intensity and color temperature of the ceiling lamp are adjusted and controlled based on the white spectrum of the blue-violet light beads of the nano fluorescent material.

[0054] It should be noted that the regulation of wavelength intensity and color temperature in this embodiment is based on the white spectrum of LED cold white light beads, or based on the white spectrum of blue-violet light beads encapsulating yellow-green fluorescent materials. This is because when the white spectrum of blue-violet light beads encapsulating yellow-green fluorescent materials is used as the basis, it is easier to modulate the intelligent rhythmic spectrum.

[0055] It should be noted that, in this embodiment, based on white light, a narrow-band excitation spectrum based on nano fluorescent materials is used in combination with an intelligent algorithm to perform precise spectrum modulation. For example, a narrow-band cyan fluorescent material absorbs blue-violet light and emits light with a peak wavelength of 470nm to 495nm. A deep red fluorescent material absorbs blue-violet light and emits light with a peak wavelength of 630nm to 680nm.

[0056] It should be noted that in this embodiment, quantum dot fluorescent materials or quantum rod fluorescent materials are used to emit light with a half-peak width of less than 40nm and various peak wavelengths. The different sizes of quantum dot fluorescent materials or quantum rod fluorescent materials are used to facilitate accurate modulation of the spectrum. The peak wavelength of the emitted light of the quantum dot fluorescent material or quantum rod fluorescent material is directly related to its size. Specifically, the smaller the size, the shorter the emission wavelength (that is, the color of the emitted light is closer to blue light); the larger the size, the longer the emission wavelength (that is, the color of the emitted light is closer to red light). This characteristic originates from the quantum confinement effect. The basic principle is that when the size of the quantum dot is close to or less than its exciton Bohr radius, the energy state of the electron and the hole will change significantly, thereby affecting its optical properties. For example, oil-soluble ZnCds / ZnS quantum dots are usually coated with a layer of ZnS shell to enhance their optical stability and luminous efficiency. By changing the composition and size of the ZnCdS core, the peak wavelength of its emitted light can be adjusted. Such quantum dots are widely used in light-emitting diodes (LEDs) and display backlights because they have a narrow half-width (typically less than 40nm) and can provide pure color output.

[0057] It should be noted that quantum dot fluorescent materials or quantum rod fluorescent materials have excellent and flexible selectivity, and can accurately emit the required narrow-band spectrum by changing the size of the material, thereby facilitating precise modulation of the spectrum.

[0058] It should be noted that the regulation of wavelength intensity and color temperature in this embodiment is achieved by opening and closing the circuits of the light-emitting lamp beads with different nano-fluorescent materials in the lighting device and regulating the current size. For the light-emitting lamp beads with different nano-fluorescent materials, a dual-channel current output control system or a multi-channel current output control system can be used in parallel to facilitate independent regulation. That is, the current output control system is electrically connected to the light-emitting lamp beads with different nano-fluorescent materials, and they are in a parallel relationship, and the circuits of the light-emitting lamp beads with different nano-fluorescent materials can be opened and closed and the current size can be adjusted through a separate sliding resistor and / or a separate switch.

[0059] Specifically, the preset first spectrum composition parameter of the ceiling lamp is initially matched, and the specific analysis process is: according to the time zone information of the ceiling lamp, wherein the time zone information includes the current time period of the region where the ceiling lamp is operated.

[0060] According to the rhythmic intelligent lighting benchmark table in the cloud server, the rhythmic intelligent lighting benchmark table includes spectrum composition parameters for each time period.

[0061] In this embodiment, based on the characteristics of the narrow-band excitation spectrum of the nano fluorescent material, the spectral components can be effectively modulated.

[0062] It should be noted that light is a key factor affecting human productivity, mental alertness, sleep quality and health. Studies show that unhealthy lighting can disrupt our circadian rhythm cycle, which in turn interferes with sleep and wakefulness, and has adverse effects on physical and mental health. For example, lack of sleep can damage the insulin and blood sugar systems, making people more susceptible to diabetes. Lack of sleep can also increase the body's inflammatory response, affecting the function of anti-cancer cells and the production of anti-infection antibodies. Therefore, a human-centered lighting spectrum that conforms to the physiological rhythm is particularly important for people's life, study, and work.

[0063] It should also be noted that the photosensitive structure of the human eye includes: retina, ganglion cells, rods and cones. Rods are responsible for dark vision and perception of objects in low light, cones are responsible for bright vision and color perception, and retinal ganglion cells are also called photosensitive retinal ganglion cells (i pRGCs), which are scattered in the retina, above the rods and cones. i pRGCs form the main neural pathway from the eye to the hypothalamus region of the brain. The hypothalamus is the location of the human body's biological clock and controls the body's internal cycle mechanism - that is, our circadian rhythm. When light enters the eye, it emits a light-sensitive protein called melanopsin in each i pRGC. In this multi-step process, melanopsin suppresses melatonin (a hormone that induces sleep) during the day, and as the light gradually disappears at night, the production of melatonin gradually increases. Melanopsin responds most to the main colors of daylight - blue and cyan, and is most sensitive around 485nm to be precise. M / Prat i (Melanopic / Photopic) is usually used to quantify the effect of light on circadian rhythm: the degree of stimulation of the human circadian system by the light source. The higher the M / P ratio, the stronger the circadian effect of the light source, and the more it can promote alertness and wakefulness; while a low M / P ratio, with less blue light / cyan light, is most suitable for relaxing at night and preparing for sleep. Therefore, the spectrum of healthy lighting needs to be consistent with the human circadian physiological rhythm, and needs to take into account melanopsin, that is, to regulate melatonin, so that people can stay energetic and awake when studying and working, and can naturally fall asleep when resting at night, and maintain physical and mental health.

[0064] It should also be noted that the M / P ratio is an indicator used to measure the degree of stimulation of the human circadian system by a light source. It measures the relative effect of a light source in stimulating the visual system (photopic, light-sensitive vision) and stimulating the biological clock system (melanopic, melanopsin-sensitive vision). Melanopic vision refers to the effect of light on the pigments on the retina of the human eye, while photopic vision refers to the effect of light on the cones on the retina of the human eye (mainly responsible for daytime vision). The specific process of calculating the M / P ratio is to extract the spectral data of light source A and light source B, which are usually given in the form of wavelength (nanometers) and corresponding radiation or luminous flux intensity (watts / nanometer or lumens / nanometer). Then, the Melanopic effect function and the Photopic effect function are used to weight the spectral data to obtain the Melanopic effect spectrum and the Photopic effect spectrum. For example, suppose that the integral value of the Melanopic effect spectrum of light source A is 1000 units and the integral value of the Photopic effect spectrum is 2000 units after calculation. The integral value of the Melanopic effect spectrum of light source B is 1500 units, and the integral value of the Photopic effect spectrum is 2500 units. Then the BM / P ratio of light source A is M / P = 1000 / 2000 = 0.5; the BM / P ratio of light source B is M / P = 1500 / 2500 = 0.6. Therefore, the M / P ratio of light source A is 0.5, and the M / P ratio of light source B is 0.6. This means that light source B has a stronger stimulating effect on the biological clock system than light source A.

[0065] It should also be noted that another important spectral component in health and human-centered lighting is the red light spectrum. Natural sunlight has a very rich spectrum and is also the healthiest light source. Each type of spectrum has its own unique health effects, such as red light on liver construction, green light on human balance, blue light on human calmness, cyan light on human wakefulness, yellow light on muscle stimulation, purple light on pain suppression, ultraviolet light on bone growth, infrared light on heat supply, etc. However, in today's artificial light sources, people have noticed the adverse effects of blue light and the sterilization and disinfection of ultraviolet light, but have ignored the health effects of red light. Studies have shown that red light components not only help stimulate melatonin and help people fall asleep, but also promote blood circulation, enhance immunity and metabolism. In addition, it has effects on slowing down skin aging, improving human fertility, liver health, stabilizing emotions and preventing depression. However, in daily lighting, red light components are seriously lacking, especially in artificial light, which is mostly LED light sources. White light LEDs usually produce white light spectra by adding blue light-emitting chips to yellow and red phosphors, and red phosphors are usually broadband spectra with a FWHM bandwidth greater than 100nm. If the peak wavelength of red phosphor excitation is above 630nm, there will be many spectral components above 660nm, which rarely contribute to human vision (illuminance). Therefore, in the existing LED artificial light source spectrum, the peak wavelength of red light is mostly within 610nm to achieve high light efficiency lamps. Therefore, it is very important to improve the red light spectrum components in healthy and human-centered lighting, especially the red light spectrum containing a peak wavelength above 630nm.

[0066] In this embodiment, the rhythmic intelligent lighting reference table refers to a reference table containing the spectrum composition parameters that the lighting system should adopt in different time periods, as shown in Table 1, which is an example data of the rhythmic intelligent lighting reference table, including the composition parameters of the preset spectrum in different time periods. The various time periods of the rhythmic intelligent lighting reference table include sunrise, early morning, morning, noon, afternoon, evening meal, sunset, night and late night. These time periods are divided according to the changes in natural light in a day to adapt to people's activities and physiological rhythm needs in different time periods. The spectral wavelength ranges of different time periods cover 400nm-780nm. The second column in Table 1 is the wavelength range for spectral correction, where the plus sign indicates that the spectrum of the wavelength range is emitted by exciting the corresponding fluorescent material; the minus sign indicates that the spectrum of the wavelength range is absorbed by exciting the corresponding fluorescent material. The wavelength range values ​​are all peak wavelengths, and the half-peak width range is 20nm-30nm. Spectral bands that are targeted and adjusted in the form of peak wavelength and half-peak width. For example, blue light is absorbed at night, cyan light faults are compensated, and purple light is compensated to form a warm white spectrum. In addition, the wavelength range of harmful blue light is 435-450nm (the spectrum within this range is suitable for absorption and reduction by fluorescent materials).

[0067] It should be noted that the white spectrum of conventional fluorescent lamps has a cyan fault due to the limitation of the spectrum synthesis method. The wavelength range of cyan light is 450-492nm (the spectrum within this range is suitable for compensation by using fluorescent materials to excite the corresponding spectrum).

[0068] In this embodiment, Table 1 also includes spectrum composition parameters such as wavelength distribution, color temperature value and light intensity, which determine the properties of the light emitted by the lamp at a specific time, such as color, brightness and temperature. By comparing the current time period of the region where the ceiling lamp is operated with the spectrum composition parameters of each time period in the table, the spectrum composition parameters suitable for the current time period can be determined as the preset first spectrum composition parameters of the ceiling lamp, so that the spectrum of the ceiling lamp can be specifically in line with the circadian rhythm of the human body, promote alertness and wakefulness, or be suitable for relaxation and preparation for sleep at night, thereby helping the user to maintain physical and mental health.

[0069] Table 1 Example data of rhythmic intelligent lighting benchmark table

[0070]

[0071]

[0072] It should also be noted that the spectrum of each color band has its unique health effect, such as red light on the construction of the liver, green light on the balance of the human body, blue light is conducive to human calmness, light with a low M / P ratio is conducive to wakefulness and learning, yellow light stimulates muscles, purple light inhibits pain, ultraviolet light promotes bone growth, and near-infrared light may improve sub-health problems such as body pain, inflammation, and poor microcirculation.

[0073] The current time period of the area where the ceiling lamp is operating is compared with the spectral composition parameters of each time period. If the time period comparison is consistent, the spectral composition parameters obtained by the comparison are used as the preset first spectral composition parameters of the ceiling lamp, wherein the preset first spectral composition parameters include preset wavelength intensity and preset color temperature value.

[0074] Specifically, the user behavior information and environmental information of the subordinate operation area of ​​the ceiling lamp are monitored, and the specific process is: the time period between the current moment and the end time of the current time period in the area where the ceiling lamp is operated is calibrated as the designated time period, and each monitoring time point is obtained by dividing it, and the user's position in the subordinate operation area of ​​the ceiling lamp is identified at each monitoring time point, and the acceleration data of the user at each monitoring time point is collected, and the acceleration data includes acceleration values ​​in each direction, and the acceleration data is processed by Fourier transform to obtain the spectral energy of the user at each monitoring time point, thereby fitting the acceleration data and spectral energy of the user at each monitoring time point into a four-dimensional feature vector, and counting the four-dimensional feature vector of the user at each monitoring time point.

[0075] In this embodiment, the infrared sensor can be used to detect the presence and position of the human body. By installing the infrared sensor, the user's position can be detected to help adjust the lighting settings.

[0076] In this embodiment, velocity data refers to the acceleration information of an object in space collected by an acceleration sensor or an accelerometer. Acceleration sensors are usually able to detect the acceleration of an object on three directional axes, i.e., the x-axis, the y-axis, and the z-axis, as shown in Table 2, which is the example data of the four-dimensional feature vectors at each monitoring time point, wherein the acceleration value can be obtained directly by the acceleration sensor, and the acceleration value is usually raw data, i.e., the acceleration change of the object on each axial direction. Acceleration sensor is a commonly used sensor, and these acceleration values ​​are usually expressed in standard units (such as meters per second 2), and common acceleration sensors include MEMS (Micro-Electro-Mechanical Systems) acceleration sensors.

[0077] Table 2 Example data of four-dimensional feature vectors at each monitoring time point

[0078]

[0079] In this embodiment,

[0080] The three columns of acceleration X, acceleration Y, and acceleration Z represent the acceleration of the object in the X-axis, Y-axis, and Z-axis directions, respectively. These acceleration values ​​may change over time as the object moves or vibrates. In the sample data, the acceleration values ​​of the object in three directions are recorded at each time point. Table 2 shows the user's motion state at different time points, as well as its corresponding spectrum characteristics, which can be used to analyze the user's motion patterns.

[0081] In this embodiment, Fourier transform is a mathematical tool for converting a time domain signal into a frequency domain representation, so as to analyze the spectral characteristics of the signal at different frequencies. In the embodiment, Fourier transform is used to convert the acceleration data changing with time into a frequency domain representation. The specific Fourier transform process involves the following steps: preprocessing the acceleration data, expressing the preprocessed acceleration data as a function in the time domain, applying Fourier transform to the time domain acceleration data, and finally obtaining the acceleration data in the frequency domain. The frequency domain acceleration data generally includes information such as spectral energy and frequency components, and finally calculating the spectral energy of the frequency domain acceleration data.

[0082] The four-dimensional feature vector of the user at each monitoring time point is imported into the machine learning model to obtain the predicted behavior type of the user at each monitoring time point.

[0083] In this implementation scheme, the four-dimensional feature vector of the user at each monitoring time point is imported into the machine learning model. The specific process of obtaining the predicted behavior type of the user at each monitoring time point is to standardize or normalize the four-dimensional feature vector, and then select a suitable machine learning model for training and prediction, such as decision tree, random forest, support vector machine (SVM) and neural network models. The four-dimensional feature vector of the user at each monitoring time point is input into the trained machine learning model. The model will predict the corresponding behavior type based on the input feature vector to obtain the predicted behavior type of the user at each monitoring time point.

[0084] In an embodiment, the spectrum energy can be used to describe the energy distribution of the object vibration signal in different frequency ranges. By analyzing the spectrum energy of the acceleration signal, it is possible to help identify the frequency characteristics of the user motion analysis.

[0085] In a specific embodiment, as shown in Table 3, Table 3 is example data of spectral demand adjustment factors corresponding to each behavior type, which lists the spectral demand adjustment factors corresponding to different user behavior types. The spectral demand adjustment factor corresponding to the user's behavior type refers to the parameters for adjusting the lighting spectrum set in advance according to the user's behavior characteristics and duration. These parameters can be preset and optimized according to the user's behavior type to adapt to the lighting needs in different behavior scenarios. For example, when the user is in a sitting position, a more comfortable and soft lighting environment may be required to help maintain physical and mental relaxation and comfort. Therefore, a higher spectral demand adjustment factor may be set to reduce the wavelength intensity and color temperature value of the light to provide a soft and comfortable lighting effect.

[0086] Table 3 Example data of spectral demand adjustment factors corresponding to each behavior type

[0087] User behavior type Spectral Requirement Adjustment Factor sit 1.2 lie 0.8 Standing 1.1 walk 1.3

[0088] It should be noted that the user behavior type lists different user behavior types, such as sitting, lying, standing and walking. Each behavior type represents the state or posture of the user in a specific situation or scene. The spectrum demand adjustment factor lists the spectrum demand adjustment factor corresponding to each user behavior type, which is used to adjust the lighting spectrum according to the user's behavior characteristics and duration to meet the lighting needs in different behavior scenarios. It can help optimize the lighting so that the lighting environment can better adapt to different user behavior scenarios and provide a more comfortable and suitable lighting environment.

[0089] The spectral demand adjustment factors corresponding to each behavior type stored in the database are extracted, and the spectral demand adjustment factors corresponding to the predicted behavior types of the users at each monitoring time point are screened. The wavelength intensity and color temperature values ​​of the ceiling lamps at each monitoring time point are extracted, and compared with the spectral factors corresponding to each wavelength intensity interval and the spectral factors corresponding to each color temperature value interval stored in the database, respectively, to obtain the spectral factors corresponding to the wavelength intensity and color temperature values ​​of the ceiling lamps at each monitoring time point, and then accumulated to obtain the spectral factors of the ceiling lamps at each monitoring time point.

[0090] According to the spectral factor of the ceiling lamp at each monitoring time point and the spectral demand adjustment factor corresponding to the predicted behavior type of the user at each monitoring time point, the spectral demand adjustment measurement value at each monitoring time point is obtained through processing.

[0091] The spectral demand adjustment metering threshold in the database is extracted and compared with the spectral demand adjustment metering value at each monitoring time point. If the spectral demand adjustment metering value at a certain time point is higher than the spectral demand adjustment metering threshold, the time point is recorded as the adjustment time point.

[0092] At each adjustment time point, environmental information of the operating area to which the ceiling lamp belongs is collected, wherein the environmental information includes light intensity, temperature and humidity.

[0093] Specifically, the spectrum demand adjustment measurement value at each monitoring time point represents the quantitative result obtained by monitoring the user behavior in the subordinate operation area of ​​the ceiling lamp, which is used to analyze the degree of adjustment of the spectrum demand of the ceiling lamp due to user behavior, and serves as the basis for analyzing the spectrum adjustment parameters of the subordinate operation area of ​​the ceiling lamp.

[0094] It should be noted that this embodiment is based on time zone information, user behavior information and environmental information. On the basis of the chip of 415nm near-ultraviolet light-emitting diode, the light-emitting circuit of the lamp is regulated by an intelligent method, and the circuit current of the light-emitting components of different nano-fluorescent materials is regulated to obtain a rhythmic intelligent lighting spectrum, which is used to enhance the cyan light spectrum to achieve a high melatonin illumination M / P ratio and enhance the deep red light spectrum to achieve healthy lighting. This spectrum excites narrow-band quantum rod materials, modulates the spectrum of 465nm, 525nm, 550nm, 575nm, 625nm, 650nm and near-infrared 700nm, 750nm peak wavelengths (half-peak width is about 40nm), and uses nano-fluorescent materials to produce low blue light, deep red enhanced low M / P ratio (i.e. melatonin illumination ratio; M / P ratio is less than 0.45) warm light source, suitable for night, rest or health care period / place. The M / P ratio of the ordinary 3500K color temperature spectrum is about 0.63. And this intelligent healthy lighting spectrum has the advantage of high light efficiency.

[0095] It should be noted that the present invention also provides an intelligent ecological dimming system and integrates it into the ceiling lamp, so that people can have the modern life experience of smart home entertainment and rhythmic healthy lighting. The intelligent ecological dimming can be set according to people's living habits, or voice interaction can be achieved. In addition, it can also integrate artificial intelligence functions, and has a self-learning function for people's living habits. It can automatically adjust to the lighting spectrum in various living environments according to people's life patterns. For example, during daytime activities, the spectrum is adjusted to a cold white spectrum with a high melatonin illumination M / P ratio; when people enter a leisure sleep, the spectrum is adjusted to a warm color spectrum with a low melatonin illumination M / P ratio; in other living environments, the dimming system can be used to adjust the mixed light ratio of the two spectral light sources to obtain the spectrum and color temperature of the lighting light in different comfortable environments.

[0096] It should also be noted that this embodiment uses full-spectrum technology of blue light plus quantum rod fluorescent materials, has simple packaging, realizes the spectral band of deep red light, and has a much higher light efficiency than traditional red fluorescent materials.

[0097] It should also be noted that the cost of blue light plus quantum rod fluorescent materials is low, and it is an ideal technical solution for achieving rhythmic lighting spectrum.

[0098] Specifically, the spectral adjustment parameters of the subordinate operating area of ​​the ceiling lamp are obtained. The specific process is: count the light intensity of the subordinate operating area of ​​the ceiling lamp at each adjustment time point, and match it with the adapted wavelength intensity corresponding to each light intensity interval in the database to obtain the adapted wavelength intensity of the ceiling lamp at each adjustment time point.

[0099] The color temperature value of the ceiling lamp at each adjustment time point is extracted, and compared with the regional adaptation temperature and regional adaptation humidity corresponding to each color temperature interval stored in the database to obtain the regional adaptation temperature and regional adaptation humidity of the ceiling lamp at each adjustment time point.

[0100] The temperature of the operating area of ​​the ceiling lamp at each adjustment time point is counted, and the difference is processed with the regional adaptation temperature corresponding to each color temperature interval to obtain the regional temperature deviation value at each adjustment time point, and the first color temperature adjustment value of the ceiling lamp at each adjustment time point is obtained by processing.

[0101] It should be noted that the first color temperature adjustment value of the ceiling lamp at each adjustment time point can use the temperature of the subordinate operation area of ​​the ceiling lamp at each adjustment time point, analyze the temperature data of the subordinate operation area of ​​the ceiling lamp at each adjustment time point with the adaptation temperature, and obtain the temperature difference as the first color temperature adjustment value, which is obtained by the following calculation method in this embodiment. The specific calculation method is as follows:

[0102]

[0103] In the formula, Q irepresents the first color temperature adjustment value of the ceiling lamp at the i-th adjustment time point, g i represents the color temperature value of the ceiling lamp at the i-th adjustment time point, ΔT i is the regional temperature deviation value at the i-th adjustment time point, τ1 is the color temperature loss value per unit temperature difference, τ2 is the color temperature supplement value per unit temperature difference, i represents the number of each adjustment time point, i=1,2,3,...,n, and n represents the total number of adjustment time points.

[0104] It should be understood that the regional temperature deviation value is the difference between the temperature of the operating area to which the ceiling lamp belongs at each adjustment time point and the regional adaptation temperature corresponding to each color temperature interval. The regional temperature deviation value can be 0, greater than 0 or less than 0.

[0105] In a specific embodiment, as shown in Table 4, Table 4 is example data of color temperature loss value and color temperature supplement value of unit area temperature deviation value, which lists example data of different temperature deviation range intervals.

[0106] Table 4 Example data of color temperature loss and supplementary values ​​in each temperature deviation range

[0107] Temperature deviation range Color temperature loss per unit temperature difference Supplementary value per unit temperature difference Less than 1℃ 0.92 0.52 1℃-10℃ 0.8 0.63 21℃-30℃ 0.93 0.7 More than 30℃ 1.58 0.41

[0108] The humidity of the operating area of ​​the ceiling lamp at each adjustment time point is counted, and the difference is processed with the regional adaptation humidity corresponding to each color temperature interval to obtain the regional humidity deviation value at each adjustment time point, and the second color temperature adjustment value of the ceiling lamp at each adjustment time point is obtained by processing.

[0109] The first color temperature adjustment value of the ceiling lamp at each adjustment time point and the second color temperature adjustment value of the ceiling lamp at each adjustment time point are accumulated and averaged to obtain the target color temperature adjustment value of the ceiling lamp at each adjustment time point.

[0110] It should be noted that the second color temperature adjustment value of the ceiling lamp at each adjustment time point is obtained by the following calculation method in this embodiment. The specific calculation method is as follows:

[0111]

[0112] In the formula, R i represents the second color temperature adjustment value of the ceiling lamp at the i-th adjustment time point, h i represents the humidity of the ceiling lamp at the i-th adjustment time point, Δu i is the regional humidity deviation value at the i-th adjustment time point, τ3 is the color temperature loss value per unit humidity difference, and τ4 is the color temperature supplement value per unit humidity difference.

[0113] It should be understood that the regional humidity deviation value is the difference between the humidity of the operating area to which the ceiling lamp belongs at each adjustment time point and the regional adaptation humidity corresponding to each color temperature interval. The regional humidity deviation value can be 0, greater than 0 or less than 0.

[0114] In a specific embodiment, as shown in Table 5, Table 5 is example data of color temperature loss value and color temperature supplement value of humidity deviation value per unit area, wherein example data of different humidity deviation range intervals are listed.

[0115] Table 5 Example data of color temperature loss and supplementary values ​​for each humidity deviation range

[0116] Humidity difference deviation range Color temperature loss per unit humidity Supplementary value of unit humidity Less than 30% 0.82 0.71 31％-50％ 0.34 0.46 51％-70％ 0.93 1.03 Higher than 71% 0.97 0.98

[0117] It should be noted that the color temperature loss value per unit humidity lists the color temperature loss value corresponding to each unit humidity change. In actual environments, changes in humidity will affect the color temperature of the light source, resulting in changes in spectral characteristics. The color temperature loss value corresponding to a unit humidity change indicates the color temperature change caused by each increase or decrease in humidity by one unit. For example, when the humidity deviation is within a range below 30%, the color temperature will be reduced by 0.82 units for each increase in humidity. Similarly, the supplementary value per unit humidity lists the supplementary value corresponding to each unit humidity change. Similarly, changes in humidity will also affect the brightness and intensity of the light source. For example, when the humidity deviation is within a range below 30%, the light intensity will be supplemented by 0.71 units for each increase in humidity. Through the color temperature loss value and supplementary value of each humidity deviation range, it is possible to understand the impact of humidity changes on the color temperature and light intensity of the light source within different humidity deviation ranges and use it in light source design and regulation to help ceiling lamps provide stable and appropriate lighting effects under different humidity environments.

[0118] The adapted wavelength intensity of the ceiling lamp at each adjustment time point and the target color temperature adjustment value of the ceiling lamp at each adjustment time point are combined as the spectrum adjustment parameters of the subordinate operation area of ​​the ceiling lamp.

[0119] Specifically, the first color temperature adjustment value of the ceiling lamp at each adjustment time point and the second color temperature adjustment value of the ceiling lamp at each adjustment time point, the specific processing process includes: extracting the regional temperature deviation value at each adjustment time point, if the regional temperature deviation value at a certain adjustment time point is equal to 0, then defining the color temperature value of the ceiling lamp at the adjustment time point as the first color temperature adjustment value, if the regional temperature deviation value at a certain adjustment time point is greater than 0 or the regional temperature deviation value is less than 0, then extracting the set color temperature reduction value and color temperature supplement value of the unit temperature difference, processing to obtain the first color temperature adjustment value of the ceiling lamp at the adjustment time point, and traversing and counting the first color temperature adjustment values ​​of the ceiling lamp at each adjustment time point in turn.

[0120] The regional humidity deviation value at each adjustment time point is extracted. If the regional humidity deviation value at a certain adjustment time point is equal to 0, the color temperature value of the ceiling lamp at the adjustment time point is defined as the second color temperature adjustment value. If the regional humidity deviation value at a certain adjustment time point is greater than 0 or the regional humidity deviation value is less than 0, the color temperature loss value and color temperature supplement value of the set unit humidity difference are extracted, and the second color temperature adjustment value of the ceiling lamp at the adjustment time point is obtained by processing. The second color temperature adjustment value of the ceiling lamp at each adjustment time point is traversed and counted in turn.

[0121] It should be noted that the color temperature loss value and color temperature supplement value per unit humidity difference are set through a large number of experiments and actual use data to determine the specific impact of color temperature changes under different humidity conditions. These data can come from statistical information in different seasons and different geographical locations. For example, the specific numerical values ​​of the color temperature loss value and supplement value in an environment with low humidity (such as less than 30%) are 0.82 for the loss value and 0.71 for the supplement value.

[0122] Specifically, the required spectrum adjustment parameters of the ceiling lamp are analyzed and the wavelength intensity and color temperature of the ceiling lamp are controlled. The specific analysis process is: according to the preset first spectrum composition parameters of the ceiling lamp and the spectrum adjustment parameters of the subordinate operating area of ​​the ceiling lamp, wherein the preset first spectrum composition parameters include preset wavelength intensity and preset color temperature value, and the spectrum adjustment parameters include the adapted wavelength intensity and target color temperature adjustment value of the ceiling lamp at each adjustment time point.

[0123] The execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point and the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point are obtained in sequence through numerical processing.

[0124] According to the execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point, the specified wavelength intensity corresponding to each execution wavelength intensity adjustment coefficient interval stored in the database is compared to obtain the specified wavelength intensity of the ceiling lamp at each adjustment time point.

[0125] According to the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point, the specified color temperature value of the ceiling lamp at each adjustment time point is obtained by comparing it with the specified color temperature value corresponding to each execution color temperature adjustment coefficient interval stored in the database.

[0126] According to the specified wavelength intensity of the ceiling lamp at each adjustment time point and the specified color temperature value of the ceiling lamp at each adjustment time point, the required spectrum adjustment parameters of the ceiling lamp are obtained, thereby adjusting the wavelength intensity and color temperature value of the ceiling lamp at each adjustment time point.

[0127] Specifically, the spectrum needs to adjust the measurement value at each monitoring time point, and the specific analysis conditions are:

[0128]

[0129] In the formula, ω j represents the spectral demand adjustment measurement value at the jth monitoring time point, F j represents the spectral factor of the ceiling lamp at the jth monitoring time point, represents the spectrum demand adjustment factor corresponding to the predicted behavior type of the user at the jth monitoring time point, j represents the number of each monitoring time point, j=1,2,3,...,m, and m represents the total number of monitoring time points.

[0130] Specifically, the execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point and the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point are specifically processed as follows: according to the following numerical processing conditions:

[0131]

[0132] Wherein, Y1i represents the execution wavelength intensity adjustment coefficient of the ceiling lamp at the i-th adjustment time point, E1 represents the preset wavelength intensity of the ceiling lamp, Ei2 represents the adaptation wavelength intensity of the ceiling lamp at the i-th adjustment time point, σ1 represents the weight factor corresponding to the preset wavelength intensity, σ2 represents the weight factor corresponding to the set adaptation wavelength intensity, i represents the number of each adjustment time point, i=1,2,3,...,n, n represents the total number of adjustment time points, according to the following numerical processing conditions:

[0133]

[0134] Wherein, Y2i represents the execution color temperature adjustment coefficient of the ceiling lamp at the i-th adjustment time point, E3 represents the preset color temperature value of the ceiling lamp, Ei4 represents the target color temperature adjustment value of the ceiling lamp at the i-th adjustment time point, σ3 represents the weight factor corresponding to the set preset color temperature value, and σ4 represents the weight factor corresponding to the set target color temperature adjustment value.

[0135] The weight factors corresponding to the preset wavelength intensity, the weight factors corresponding to the adapted wavelength intensity, the weight factors corresponding to the preset color temperature value, and the weight factors corresponding to the target color temperature adjustment value are set by setting different spectral combinations and color temperature values ​​to record the user's reaction and comfort in different environments. Their value range is between 0 and 1, and the importance of different indicators can be adjusted according to actual conditions. Certain wavelengths or color temperatures require stronger spectral regulation in specific periods of time, so they can be given higher weights. For example, in many experiments, it was found that the wavelength intensity at a certain time has a smaller impact on the user's visual comfort, while the color temperature adjustment value has a greater impact. Therefore, the weight factor of the preset wavelength intensity can be set to 0.06, and the weight factor of the target color temperature adjustment value can be set to 0.43.

[0136] In a specific embodiment, the execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point and the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point represent the adjustment ratio of wavelength intensity and color temperature. For example, if the basic wavelength intensity during the "sunrise" time period is 600lm and the execution wavelength intensity adjustment coefficient is 0.8, the actual wavelength intensity is 600*0.8=480l m.

[0137] In a specific embodiment, as shown in Table 6, Table 6 is example data of the weight factor in the execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point and the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point.

[0138] Table 6 Example data of weight factors for each implementation wavelength intensity adjustment coefficient and implementation color temperature adjustment coefficient

[0139] Preset wavelength intensity corresponding weight factor 0.06 Weight factor corresponding to the wavelength intensity 0.12 Weight factors corresponding to preset color temperature values 0.23 Weight factor corresponding to the target color temperature adjustment value 0.43

[0140] It should be noted that Table 6 lists the weight factors of the various wavelength intensity adjustment coefficients and color temperature adjustment coefficients used to adjust the ceiling lamp. Each weight factor represents the importance and contribution ratio of the corresponding parameter in the overall adjustment process. The higher the value of the weight factor, the greater the impact of the parameter on the final result. Therefore, the spectrum and color temperature of the ceiling lamp at different time points can be adjusted to ensure that the lighting environment can flexibly adapt to environmental changes and provide the best lighting effect.

[0141] It should also be noted that the current full-spectrum technology improves the "blue fault" of ordinary white light by adding blue light (about 480nm) lamp beads, which requires packaging two chips on the LED substrate, a blue light chip and a blue light chip. The complex packaging increases the cost, and the efficiency of the blue light LED chip is low, and the reliability is relatively poor at high currents. In addition, the addition of red powder with a long wavelength peak (close to 650nm) to the phosphor, broadband (>70nm bandwidth) conversion, and low conversion efficiency of red powder will greatly affect the optical efficiency of white light LEDs, because the spectrum above 660nm contributes little to the photopic illumination, so the lumen brightness is low. Therefore, this project proposes a spectrum technology based on nano-fluorescent materials to achieve precise modulation and high light efficiency of the full spectrum, especially using quantum rod materials to achieve narrow-band modulation and adjustable peak wavelength of the white light spectrum, which can effectively solve the current problems of high cost and low efficiency of full-spectrum technology, and the peak wavelength of the excitation of the quantum rod material can be arbitrarily designed to achieve a narrow-band (<35nm) efficient spectrum.

[0142] The second aspect of the present invention provides a rhythmic intelligent lighting device based on nano-fluorescent materials, which also includes: a processor, and a memory and a network interface connected to the processor; the network interface is connected to a non-volatile memory in a server; when the processor is running, it retrieves a computer program from the non-volatile memory through the network interface, and runs the computer program through the memory to execute the above-mentioned rhythmic intelligent lighting method based on nano-fluorescent materials.

[0143] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0144] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. Rhythmic intelligent lighting method based on nano fluorescent materials, It is characterized in that include: Obtain the rhythmic intelligent lighting reference table in the cloud server, obtain the time zone information of the ceiling lamp, and preliminarily match and obtain the preset first spectrum composition parameter of the ceiling lamp; Monitor user behavior information and environmental information of the subordinate operation area of ​​the ceiling lamp to obtain spectrum adjustment parameters of the subordinate operation area of ​​the ceiling lamp; According to the preset first spectrum composition parameter of the ceiling lamp and the spectrum adjustment parameter of the subordinate operation area of ​​the ceiling lamp, the required spectrum adjustment parameter of the ceiling lamp is analyzed and obtained, and the wavelength intensity and color temperature of the ceiling lamp are controlled and adjusted; The wavelength intensity and color temperature of the ceiling lamp are adjusted and controlled based on the white spectrum of the blue-violet light beads of the nano fluorescent material; The analysis obtains the required spectrum adjustment parameters of the ceiling lamp, and controls the wavelength intensity and color temperature of the ceiling lamp. The specific analysis process is as follows: According to the preset first spectrum composition parameters of the ceiling lamp and the spectrum adjustment parameters of the subordinate operation area of ​​the ceiling lamp, wherein the preset first spectrum composition parameters include preset wavelength intensity and preset color temperature value, and the spectrum adjustment parameters include the adapted wavelength intensity and target color temperature adjustment value of the ceiling lamp at each adjustment time point; The execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point and the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point are obtained in sequence through numerical processing; According to the execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point, the specified wavelength intensity corresponding to each execution wavelength intensity adjustment coefficient interval stored in the database is compared to obtain the specified wavelength intensity of the ceiling lamp at each adjustment time point; According to the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point, the specified color temperature value corresponding to each execution color temperature adjustment coefficient interval stored in the database is compared to obtain the specified color temperature value of the ceiling lamp at each adjustment time point; According to the specified wavelength intensity of the ceiling lamp at each adjustment time point and the specified color temperature value of the ceiling lamp at each adjustment time point, the required spectrum adjustment parameters of the ceiling lamp are obtained, thereby adjusting the wavelength intensity and color temperature value of the ceiling lamp at each adjustment time point; The specific processing process of the execution wavelength intensity adjustment coefficient of the ceiling lamp at each adjustment time point and the execution color temperature adjustment coefficient of the ceiling lamp at each adjustment time point is: according to the following numerical processing conditions: Where, Y1i represents the execution wavelength intensity adjustment coefficient of the ceiling lamp at the i-th adjustment time point, E 1 represents the preset wavelength intensity of the ceiling lamp, Ei2 represents the adapted wavelength intensity of the ceiling lamp at the i-th adjustment time point, σ1 represents the weight factor corresponding to the preset wavelength intensity, σ2 represents the weight factor corresponding to the set adapted wavelength intensity, i represents the number of each adjustment time point, i=1,2,3,...,n, n represents the total number of adjustment time points, according to the following numerical processing conditions: Where, Y2i represents the color temperature adjustment coefficient of the ceiling lamp at the i-th adjustment time point, E 3 represents the preset color temperature value of the ceiling lamp, Ei4 represents the target color temperature adjustment value of the ceiling lamp at the i-th adjustment time point, σ3 represents the weight factor corresponding to the set preset color temperature value, and σ4 represents the weight factor corresponding to the set target color temperature adjustment value.

2. The rhythmic intelligent lighting method based on nano fluorescent materials according to claim 1, Features: The preliminary matching obtains the preset first spectrum composition parameters of the ceiling lamp, and the specific analysis process is as follows: According to the time zone information of the ceiling lamp, the time zone information includes the current time period of the region where the ceiling lamp is operated; According to the rhythmic intelligent lighting benchmark table in the cloud server, wherein the rhythmic intelligent lighting benchmark table includes spectrum composition parameters for each time period; The current time period of the area where the ceiling lamp is operating is compared with the spectral composition parameters of each time period. If the time period comparison is consistent, the spectral composition parameters obtained by the comparison are used as the preset first spectral composition parameters of the ceiling lamp, wherein the preset first spectral composition parameters include preset wavelength intensity and preset color temperature value.

3. The rhythmic intelligent lighting method based on nano fluorescent materials according to claim 2, Features: The specific process of monitoring the user behavior information and environmental information of the operating area of ​​the ceiling lamp is as follows: The time period between the current moment and the end time of the current time period in the area where the ceiling lamp is operated is marked as a designated time period, and each monitoring time point is obtained by dividing it. The user's position in the area where the ceiling lamp is operated is identified at each monitoring time point, and the acceleration data of the user at each monitoring time point is collected. The acceleration data includes acceleration values ​​in each direction, and the acceleration data is processed by Fourier transform to obtain the spectrum energy of the user at each monitoring time point, thereby fitting the acceleration data and spectrum energy of the user at each monitoring time point into a four-dimensional feature vector, and counting the four-dimensional feature vector of the user at each monitoring time point; Import the four-dimensional feature vector of the user at each monitoring time point into the machine learning model to obtain the predicted behavior type of the user at each monitoring time point; Extract the spectral demand adjustment factors corresponding to each behavior type stored in the database, screen and obtain the spectral demand adjustment factors corresponding to the predicted behavior type of the user at each monitoring time point, extract the wavelength intensity and color temperature value of the ceiling lamp at each monitoring time point, and compare them with the spectral factors corresponding to each wavelength intensity interval and the spectral factors corresponding to each color temperature value interval stored in the database, respectively, to obtain the spectral factors corresponding to the wavelength intensity and color temperature value of the ceiling lamp at each monitoring time point, and accumulate them to obtain the spectral factors of the ceiling lamp at each monitoring time point; According to the spectral factor of the ceiling lamp at each monitoring time point and the spectral demand adjustment factor corresponding to the predicted behavior type of the user at each monitoring time point, the spectral demand adjustment measurement value at each monitoring time point is obtained through processing; Extract the spectrum demand adjustment metering threshold in the database and compare it with the spectrum demand adjustment metering value at each monitoring time point. If the spectrum demand adjustment metering value at a certain time point is higher than the spectrum demand adjustment metering threshold, then record this time point as the adjustment time point; At each adjustment time point, environmental information of the operating area to which the ceiling lamp belongs is collected, wherein the environmental information includes light intensity, temperature and humidity.

4. The rhythmic intelligent lighting method based on nano fluorescent materials according to claim 3, Features: The spectral demand adjustment measurement value at each monitoring time point represents a quantitative result obtained by monitoring user behavior in the subordinate operating area of ​​the ceiling lamp, which is used to analyze the degree of adjustment of the spectral demand of the ceiling lamp due to user behavior, and serves as a basis for analyzing the spectral adjustment parameters of the subordinate operating area of ​​the ceiling lamp.

5. The rhythmic intelligent lighting method based on nano fluorescent materials according to claim 3, Features: The specific process of obtaining the spectrum adjustment parameters of the subordinate operation area of ​​the ceiling lamp is as follows: The light intensity of the operating area of ​​the ceiling lamp at each adjustment time point is counted, and matched with the adapted wavelength intensity corresponding to each light intensity interval in the database to obtain the adapted wavelength intensity of the ceiling lamp at each adjustment time point; Extract the color temperature value of the ceiling lamp at each adjustment time point, and compare it with the regional adaptation temperature and regional adaptation humidity corresponding to each color temperature interval stored in the database to obtain the regional adaptation temperature and regional adaptation humidity of the ceiling lamp at each adjustment time point; The temperature of the operating area of ​​the ceiling lamp at each adjustment time point is counted, and the difference is processed with the regional adaptation temperature corresponding to each color temperature interval to obtain the regional temperature deviation value at each adjustment time point, and the first color temperature adjustment value of the ceiling lamp at each adjustment time point is obtained by processing; The humidity of the operating area of ​​the ceiling lamp at each adjustment time point is counted, and the difference is processed with the regional adaptation humidity corresponding to each color temperature interval to obtain the regional humidity deviation value at each adjustment time point, and the second color temperature adjustment value of the ceiling lamp at each adjustment time point is obtained by processing; The first color temperature adjustment value of the ceiling lamp at each adjustment time point and the second color temperature adjustment value of the ceiling lamp at each adjustment time point are accumulated and averaged to obtain the target color temperature adjustment value of the ceiling lamp at each adjustment time point; The adapted wavelength intensity of the ceiling lamp at each adjustment time point and the target color temperature adjustment value of the ceiling lamp at each adjustment time point are combined as the spectrum adjustment parameters of the subordinate operation area of ​​the ceiling lamp.

6. The rhythmic intelligent lighting method based on nano fluorescent materials according to claim 5, Features: The first color temperature adjustment value of the ceiling lamp at each adjustment time point and the second color temperature adjustment value of the ceiling lamp at each adjustment time point are specifically processed as follows: Extract the regional temperature deviation value at each adjustment time point. If the regional temperature deviation value at a certain adjustment time point is equal to 0, define the color temperature value of the ceiling lamp at the adjustment time point as the first color temperature adjustment value. If the regional temperature deviation value at a certain adjustment time point is greater than 0 or the regional temperature deviation value is less than 0, extract the color temperature loss value and color temperature supplement value of the set unit temperature difference, process to obtain the first color temperature adjustment value of the ceiling lamp at the adjustment time point, and traverse and count the first color temperature adjustment values ​​of the ceiling lamp at each adjustment time point in turn. The regional humidity deviation value at each adjustment time point is extracted. If the regional humidity deviation value at a certain adjustment time point is equal to 0, the color temperature value of the ceiling lamp at the adjustment time point is defined as the second color temperature adjustment value. If the regional humidity deviation value at a certain adjustment time point is greater than 0 or the regional humidity deviation value is less than 0, the color temperature loss value and color temperature supplement value of the set unit humidity difference are extracted, and the second color temperature adjustment value of the ceiling lamp at the adjustment time point is obtained by processing. The second color temperature adjustment value of the ceiling lamp at each adjustment time point is traversed and counted in turn.

7. The rhythmic intelligent lighting method based on nano fluorescent materials according to claim 3, Features: The spectrum demand adjustment measurement value at each monitoring time point, the specific analysis conditions are: In the formula, ω j represents the spectral demand adjustment measurement value at the jth monitoring time point, F j represents the spectral factor of the ceiling lamp at the jth monitoring time point, represents the spectrum demand adjustment factor corresponding to the predicted behavior type of the user at the jth monitoring time point, j represents the number of each monitoring time point, j=1,2,3,...,m, and m represents the total number of monitoring time points.

8. An application as claimed in any one of claims 1 to 7 for a rhythmic intelligent lighting device based on nano fluorescent materials, It is characterized in that include: A processor, and memory and network interfaces connected to the processor; The network interface is connected to a non-volatile memory in the server; When running, the processor retrieves a computer program from the non-volatile memory through the network interface, and runs the computer program through the memory to execute the method described in any one of claims 1 to 7.

Images