阅读说明：本技术 基于双层次控制并实现数据智能匹配的灯具控制方法 (Lamp control method based on double-level control and capable of achieving intelligent data matching ) 是由 李小龙 于 2021-10-14 设计创作，主要内容包括：本发明涉及灯具控制技术领域,具体地说,涉及基于双层次控制并实现数据智能匹配的灯具控制方法。其包括对室外环境中的温度参数和天气参数进行采集步骤；根据外环境数据对室内的灯具形成主层次控制步骤；对室内环境中的声音参数、光强参数、热感参数进行采集步骤；根据内环境数据对室内的灯具进行协调层次的控制步骤。本发明中根据外环境数据对室内的灯具形成主层次控制,具体包括暖光控制和冷光控制,以提高用户进入家中打开灯具的舒适感,实现灯具的人性化控制,在主层次控制的基础上进行协调层次的控制,以协调灯具根据不同的感知场景进行变化。(The invention relates to the technical field of lamp control, in particular to a lamp control method based on double-level control and capable of achieving intelligent data matching. The method comprises the steps of collecting temperature parameters and weather parameters in an outdoor environment; forming a primary level control step for indoor lamps according to external environment data; collecting sound parameters, light intensity parameters and thermal sensing parameters in an indoor environment; and performing coordination level control on indoor lamps according to the internal environment data. According to the invention, main level control is formed on indoor lamps according to external environment data, specifically comprising warm light control and cold light control, so that the comfort of opening the lamps when a user enters the house is improved, humanized control of the lamps is realized, and control of a coordination level is performed on the basis of the main level control so as to coordinate the lamps to change according to different perception scenes.)

1. The lamp control method based on double-level control and capable of achieving intelligent data matching is characterized by comprising the following steps:

collecting temperature parameters and weather parameters in an outdoor environment, and then forming external environment data;

forming main level control on indoor lamps according to external environment data, and controlling main light of the lamps;

collecting sound parameters, light intensity parameters and thermal sensing parameters in an indoor environment, and then forming internal environment data;

the indoor lamps are controlled in a coordinated level according to internal environment data, the control is used for performing coordinated control on main light of the lamps, and in addition:

and forming correction parameters according to the internal environment data while coordinating the control of the level so as to correct the control of the primary level.

2. The lamp control method based on double-level control and realizing intelligent data matching according to claim 1, characterized in that: the primary level control comprises warm light control and cold light control, and specifically comprises the following steps:

the outdoor environment temperature parameter in the warm light control is-15 ℃ to +15 ℃, and the weather parameter is rainy days or cloudy days;

the cold light control medium outdoor environment temperature parameter is +15 ℃ to +45 ℃, and the weather parameter is sunny day or cloudy day.

3. The lamp control method based on double-level control and realizing intelligent data matching according to claim 2, characterized in that: and analyzing and judging the mood of the user by the sound parameter, the light intensity parameter and the thermal sensing parameter, and forming a correction parameter according to the mood of the user to correct the primary control.

4. The lamp control method based on the double-level control and realizing the intelligent data matching according to claim 3, wherein: still link the indoor equipment end through thing networking when main hierarchy control is revised for improve user's mood through the cooperation of many equipment linkage, wherein:

the indoor equipment end comprises a television, a curtain and a sound box.

5. The lamp control method based on the double-level control and realizing the intelligent data matching according to any one of claims 1-4, wherein: the control of the coordination level adopts a multi-sensing network algorithm, and the algorithm steps are as follows:

first of all to a sound perception matrixAnd lighting perception matrixAnd a thermal sensing matrixA random number to form a sample pair of an input layer and to perform initialization setting on a perception network;

extracting a sample pair, and calculating an output result of the input sample pair;

and integrating all the perception matrixes, and detecting the complete condition of the sample.

6. The lamp control method based on double-level control and realizing intelligent data matching according to claim 5, characterized in that: the perceptual network initialization setting comprises setting a sample mode counter and a training frequency counter to be 1, setting a perceptual error to be 0, setting a learning rate to be a decimal between 0 and 1, and setting the precision achieved after network training to be a positive decimal.

7. The lamp control method based on double-level control and realizing intelligent data matching according to claim 5, characterized in that: the sample pair calculation formula of the input layer is as follows:

；

；

wherein the content of the first and second substances,is as followsThe output result of each perception neuron;is as followsFrom an input layer toA perceptual matrix between the hidden layers;is as followsA perceptual threshold of the individual hidden layers;is as followsPerceptual threshold of an input layerIs as followsFrom hidden layer to secondA perception matrix between the output layers;the total number of perception neurons.

8. The lamp control method based on the double-level control and realizing the intelligent data matching according to claim 7, wherein: the multi-sensing network algorithm further comprises the step of calculating error signals of each layer, wherein the calculation formula is as follows:

；

；

wherein the content of the first and second substances,is as followsThe error signal of the output result of each perception neuron;is the error ratio;is a perceptual error;is as followsError signal of the hidden layer perception threshold.

9. The lamp control method based on the double-level control and realizing the intelligent data matching according to claim 7, wherein: the first mentionedError signal of output result of individual sensing neuron andand stopping integration when the sum of the error signals of the perception threshold values of the hidden layers reaches the precision after the network training, and if not, assigning values again and continuing integration until the precision after the network training is reached.

10. The lamp control method based on the double-level control and realizing the intelligent data matching according to claim 7, wherein: the integration of the perception matrix adopts a perception integration learning algorithm, and the algorithm formula is as follows:

；

；

wherein the content of the first and second substances,to sense learning rate;is as followsThe perception expectation vector of each perception neuron.

Technical Field

The invention relates to the technical field of lamp control, in particular to a lamp control method based on double-level control and capable of achieving intelligent data matching.

Background

The lamp is a general name of lighting tools, and is divided into a ceiling lamp, a desk lamp, a wall lamp, a floor lamp and the like, and particularly relates to an appliance capable of transmitting light, distributing and changing light distribution of a light source.

The lamp light generated by the lamp comprises cold light and warm light, and the cold light comprises green light, blue light, purple light and the like; the warm light includes red, yellow and orange light.

The existing light color selection is usually selected according to the signal of the user, or one lamp is provided with adjustment of different light colors, the adjustment needs manual control and cannot be set in combination with the external environment, namely, the light color of the current environment is adapted to the user once the user cannot turn on the lamp after entering the room outdoors, so that the humanization degree of the lamp is greatly reduced, and the existing lamp cannot be corrected in combination with the mood of the user and cannot be linked with other equipment ends at home according to the mood of the user.

Disclosure of Invention

The invention aims to provide a lamp control method based on double-level control and realizing intelligent data matching, so as to solve the problem that the device change in a scene cannot be sensed and cannot be changed along with the device change in the scene in the background technology.

In order to achieve the purpose, the invention provides a lamp control method based on double-level control and realizing intelligent data matching, which comprises the following steps:

collecting temperature parameters and weather parameters in an outdoor environment, and then forming external environment data;

forming main level control on indoor lamps according to external environment data, and controlling main light of the lamps;

collecting sound parameters, light intensity parameters and thermal sensing parameters in an indoor environment, and then forming internal environment data;

the indoor lamps are controlled in a coordinated level according to internal environment data, the control is used for performing coordinated control on main light of the lamps, and in addition:

and forming correction parameters according to the internal environment data while coordinating the control of the level so as to correct the control of the primary level.

As a further improvement of the technical solution, the primary and secondary controls include warm light control and cold light control, specifically:

the outdoor environment temperature parameter in the warm light control is-15 ℃ to +15 ℃, and the weather parameter is rainy days or cloudy days;

the cold light control medium outdoor environment temperature parameter is +15 ℃ to +45 ℃, and the weather parameter is sunny day or cloudy day.

As a further improvement of the technical scheme, the sound parameters, the light intensity parameters and the thermal sensing parameters are analyzed to judge the mood of the user, and then correction parameters are formed according to the mood of the user to correct the primary control.

As a further improvement of this technical scheme, still through thing networking linkage indoor equipment end when main hierarchy control is revised for improve user's mood through the multi-device linkage cooperation, wherein:

the indoor equipment end comprises a television, a curtain and a sound box.

As a further improvement of the technical solution, the control of the coordination level adopts a multi-sensing network algorithm, and the algorithm steps are as follows:

first of all to a sound perception matrixLighting perception matrix and thermal perception matrixA random number to form a sample pair of an input layer and to perform initialization setting on a perception network;

extracting a sample pair, and calculating an output result of the input sample pair;

and integrating all the perception matrixes, and detecting the complete condition of the sample.

As a further improvement of the technical solution, the initialization setting of the sensing network includes setting a sample mode counter and a training frequency counter to be 1, setting a sensing error to be 0, setting a learning rate to be a decimal between 0 and 1, and setting the accuracy achieved after the network training to be a positive decimal.

As a further improvement of the present technical solution, a calculation formula of the sample pair of the input layer is as follows:

；

；

wherein the content of the first and second substances,is as followsThe output result of each perception neuron;is as followsFrom an input layer toA perceptual matrix between the hidden layers;is as followsA perceptual threshold of the individual hidden layers;is as followsPerceptual threshold of an input layerIs as followsFrom hidden layer to secondA perception matrix between the output layers;the total number of perception neurons.

As a further improvement of the technical solution, the multi-sensing network algorithm further includes calculating an error signal of each layer, and a calculation formula thereof is as follows:

；

；

wherein the content of the first and second substances,is as followsThe error signal of the output result of each perception neuron;is the error ratio;is a perceptual error;is as followsError signal of the hidden layer perception threshold.

As a further improvement of the present invention, the first stepError signal of output result of individual perception neuronNumber and numberAnd stopping integration when the sum of the error signals of the perception threshold values of the hidden layers reaches the precision after the network training, and if not, assigning values again and continuing integration until the precision after the network training is reached.

As a further improvement of the technical solution, the integration of the perception matrix adopts a perception integration learning algorithm, and an algorithm formula thereof is as follows:

；

；

wherein the content of the first and second substances,to sense learning rate;is as followsThe perception expectation vector of each perception neuron.

Compared with the prior art, the invention has the beneficial effects that:

1. in the lamp control method based on double-level control and realizing intelligent data matching, firstly, temperature parameters and weather parameters in an outdoor environment are collected, and then external environment data are formed; according to the method, main level control is formed on indoor lamps according to external environment data, and the method specifically comprises warm light control and cold light control, so that the comfort of opening the lamps when a user enters the home is improved, humanized control of the lamps is realized, and control of coordination levels is performed on the basis of the main level control, so that the lamps are coordinated to change according to different perception scenes.

2. According to the lamp control method based on the double-level control and capable of achieving intelligent data matching, the mood of a user is judged through analysis of sound parameters, light intensity parameters and thermal inductance parameters, correction parameters are formed according to the mood of the user to correct primary level control, the humanization degree of lamp control is further improved, and in addition, the lamp control method can be linked with other indoor equipment ends through the Internet of things to improve the mood of the user.

Drawings

FIG. 1 is an overall flow chart of embodiment 1 of the present invention;

FIG. 2 is a flow chart of the multi-sensor network algorithm steps of embodiment 1 of the present invention;

fig. 3 is a schematic diagram of the distribution in the sleep sensing environment according to embodiment 2 of the present invention;

fig. 4 is a second schematic diagram illustrating distribution in the sleep sensing environment according to embodiment 2 of the present invention;

FIG. 5 is a schematic diagram of distribution in a viewing and perception environment according to embodiment 3 of the present invention;

fig. 6 is a flowchart of the error signal calculating step according to embodiment 4 of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Example 1

Referring to fig. 1, the present invention provides a technical solution:

the invention provides a lamp control method based on double-level control and realizing intelligent data matching, which comprises the following steps:

collecting temperature parameters and weather parameters in an outdoor environment, and then forming external environment data;

form main level control to indoor lamps and lanterns according to outer environmental data for main light to lamps and lanterns controls, and main level control is including warm light control and cold light control, and is specific:

the outdoor environment temperature parameter in the warm light control is-15 ℃ to +15 ℃, and the weather parameter is rainy days or cloudy days;

the cold light control middle outdoor environment temperature parameter is from +15 ℃ to +45 ℃, and the weather parameter is sunny day or cloudy day;

collecting sound parameters, light intensity parameters and thermal inductance parameters in an indoor environment, wherein each data is collected by a corresponding sensor, the sound data is collected by a sound sensor, the lighting data is collected by an optical sensor, and the thermal inductance data is collected by a thermal sensor to form internal environment data;

the indoor lamps are controlled in a coordinated level according to internal environment data, the control is used for performing coordinated control on main light of the lamps, and in addition:

while the control of the level is coordinated, correction parameters are formed according to the internal environment data so as to correct the control of the primary level

Specifically, referring to fig. 2, the control of the coordination level adopts a multi-sensing network algorithm, which includes the following steps:

first of all to a sound perception matrixAnd lighting perception matrixAnd a thermal sensing matrixA random number to form a sample pair of an input layer, and initializing and setting a perception network (the perception network initialization setting comprises setting a sample mode counter and a training time counter to be 1, setting a perception error to be 0, setting a learning rate to be a decimal number between 0 and 1, and setting the precision achieved after network training to be a positive decimal number);

and extracting sample pairs, wherein the calculation formula of the sample pairs of the input layer is as follows:

；

；

wherein the content of the first and second substances,is as followsThe output result of each perception neuron;is as followsFrom an input layer toA perceptual matrix between the hidden layers;is as followsA perceptual threshold of the individual hidden layers;is as followsPerceptual threshold of an input layerIs as followsFrom hidden layer to secondSensing between output layersA matrix;the number of the total perception neurons is the number,

in addition, in order to ensure the integrity of sample calculation, the completion integrity of the sample is detected after the sample calculation, if the count value of the sample mode counter is smaller than the count value of the training frequency counter, the sample mode counter is recalculated, otherwise, the perception matrix is integrated by the re-perception integration learning algorithm, and the algorithm formula is as follows:

；

；

wherein the content of the first and second substances,to sense learning rate;is as followsThe perception expectation vector of each perception neuron is integrated, after integration, each perception matrix is integrated to form a perception environment, then a perception control signal is generated according to the perception environment, the signal is sent to a lamp set in the environment, the connection is carried out through the lamp and the Internet of things (the Internet of things comprises WiFi, Bluetooth and radio frequency identification technology) built in the environment, then the control of coordination levels of the lamp is carried out through the Internet of things, the control of the lamp in different environments is achieved, and the functionality of the lamp is greatly improved.

The working principle is as follows:

assuming that the outdoor temperature is 10 ℃ and the weather parameter is rainy, the formed external environment data represents that the outdoor environment is relatively cold, and then the main level control is performed on the indoor lamp, namely: the lighting mode of the lamp is adjusted to be warm light (red light, yellow light or orange light), and the main purpose of the lamp is to keep the indoor warm light, so that a user can return to the home from a cold outdoor to feel warm, and humanized control of the lamp is realized.

After primary level control, the luminaire has established light colors, and the control scenario of the coordinated level is illustrated by the following embodiments:

example 2

In order to control the light fixture during sleep, the present embodiment is implemented on the basis of embodiment 1, and is specifically divided into the following sensing environments:

sensing an environment 1, wherein a room bed, a door, a lamp in the room, a sound sensor and a heat-sensitive sensor are not turned off during sleeping, and referring to fig. 3, wherein A is a bed in the room, B is a door, d is a lamp in the room, s is the sound sensor and r is the heat-sensitive sensor, then when a person in the bed A sleeps, firstly the sound sensor s detects snore decibels, and simultaneously the heat-sensitive sensor r detects heat consumed by the person in the bed A, and one of the snore decibel detection result of 50-80 decibels and the heat detection result of 40-55 kilocalories is obtained, so that the person in the bed A can be judged to be in a sleeping state, and at the moment, sensing and controlling signals control all lamps d in the room to be turned off, so that electric quantity is saved, and the sleeping quality of the person is guaranteed;

sensing an environment 2, if decibel detection of a sound sensor s in the environment is 0-3 decibels, judging that a person on a bed A is in a state before sleep, controlling the light intensity of two lamps d at opposite corners of the bed A to be reduced by sensing a control signal at the moment, and turning off the other lamps d, so that the problem that people are frightened due to the fact that all lights of the lamps in the front of the bed A are turned off is solved, and meanwhile, the light intensity is reduced to enable the person to quickly enter a sleep state;

sensing the environment 3, needing to go to the toilet during sleeping at night, or getting up at night, please refer to fig. 4, wherein g is an optical sensor, C is a window, when a sound sensor s detects 5-10 db decibels in the environment, the detection result of the optical sensor g is 5-50cd, and a heat-sensitive sensor r detects that a person on the bed a gets up, it is determined that the person needs to go to the toilet or get up at night, and then a sensing control signal controls all lamps d in the room to be turned on in a way of changing the light intensity from weak to strong, thereby avoiding damage to the glasses which are just opened due to instant lighting, and simultaneously providing light for the person getting up at night to avoid falling down.

It should be noted that if the optical sensor g determines that the state is a non-night state, the lamp d does not need to be controlled to be turned on.

Example 3

For use in a viewing state, the present embodiment is implemented on the basis of embodiment 1, and is specifically divided into the following sensing environments:

when the environment 1 is sensed and the television is watched in a living room or a bedroom, please refer to fig. 5, wherein D is a projector and E is a television, at this time, when the optical sensor g detects that the television E is in a bright state, or the sound sensor s detects that the television E makes a sound, or the heat sensor r detects that the television E makes heat, it is determined that the television E is in an open state, and then the lamps D on the two sides of the television E are controlled to be turned on, and the other lamps D are turned off, so that the brightness around the television E is improved, and the damage of the television E to the glasses for watching the images is reduced.

Sensing environment 2, please refer to fig. 5, where the optical sensor g detects that the wall surface on the opposite side of the projector D emits light or the sound sensor s detects that there is sound around the television E, and the heat sensor r detects that the projector D emits heat, at this time, the lamps D on both sides of the television E are controlled to be turned off, the two lamps opposite to the television E are turned on, and the brightness intensity of the lamps D is reduced, so that the situation that the brightness on the projection wall surface side is too strong to reduce the projection quality is avoided, and at the same time, the lamp D on the side far away from the projection wall surface is turned on to provide a light source for the personnel moving in the room, so as to avoid collision, thereby improving the safety during viewing.

Example 4

In order to reduce the error generated by the multi-sensor network algorithm, the present embodiment is different from embodiment 1 in that, referring to fig. 6, the multi-sensor network algorithm further includes calculating the error signal of each layer, and the calculation formula is as follows:

；

；

wherein the content of the first and second substances,is as followsThe error signal of the output result of each perception neuron;is the error ratio;is a perceptual error;is as followsError signal of the hidden layer perception threshold.

In addition, the firstError signal of output result of individual sensing neuron andand stopping integration when the sum of the error signals of the perception threshold values of the hidden layers reaches the precision after the network training, and if not, assigning values again and continuing integration until the precision after the network training is reached, so that the errors generated by the perception network algorithm are reduced, and the accuracy of the perception scene is improved.

Example 5

Considering that the individual moods of users sometimes conflict with the current light color, for example: in a sunny day, the lamp controlled by the primary layer is cold light, the mood of the user is not good due to the user, if the user returns to home or keeps the cold light, the mood of the user is further damaged, the mood of the user is judged through analysis of the sound parameter, the light intensity parameter and the thermal sensing parameter, and then the primary layer control is corrected according to the mood of the user, namely the correction parameter.

The working principle is as follows:

the working state of the equipment end in the indoor environment is analyzed through the collection of the sound parameters, the light intensity parameters and the thermal inductance parameters, for example, a user sits on a sofa by one person after going home, the thermal inductance parameters can sense that the user sits on the sofa by one person, the user does not watch television and listen to music, the correction parameters are formed at the moment, indoor lamps are controlled through the Internet of things, and cold light is converted into warm light.

Further, still through thing networking linkage indoor equipment end when main hierarchy control is revised for improve user's mood through the cooperation of many equipment linkage, wherein:

the indoor equipment end comprises a television, a curtain and a sound box.

If the user is outdoors on a sunny day, the curtain is linked through the Internet of things and is opened, the Internet of things is used for sending a signal to control the sound equipment to broadcast the owner, the outside weather is just right, the user can enjoy beautiful scenery bars by opening the curtain and dispel careless things, and the music is played after the broadcast, so that the mood of the user is relieved, and the improvement effect is achieved.

The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and the preferred embodiments of the present invention are described in the above embodiments and the description, and are not intended to limit the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.