CN111654952B - Method and system for calculating residual service life of LED lamp - Google Patents
Method and system for calculating residual service life of LED lamp Download PDFInfo
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Abstract
The invention belongs to the technical field of intelligent lighting equipment, and particularly relates to a method and a system for calculating the residual service life of an LED lamp. The method comprises the following steps: step a: initializing the LED lamp, calibrating the light intensity data of the illumination sensor and the intelligent PWM power, and sending sample point data to a server; step b: the server performs least square normal fitting according to the sample point data to construct light intensity data models under different powers; step c: the server converts the sensor data received by the LED lamp from opening to closing each time by adopting a light intensity data model, and stores the converted sensor data and the acquisition time in a corresponding relation data table of the LED lamp to form sequence data parameters; step d: and constructing a light attenuation model according to the sequence data parameters, and estimating the residual service life of the LED lamp through the light attenuation model. The invention can improve the calculation accuracy of the residual service life of the LED lamp, thereby better protecting the eye health of the family of consumers.
Description
The invention is a divisional application of the Chinese invention patent application with the patent application number of 202010253432.9.
Technical Field
The invention relates to the technical field of intelligent lighting equipment, in particular to a method and a system for calculating the residual service life of an LED lamp.
Background
Currently, traditional light fixtures are gradually replaced by intelligent LED light fixtures. The service life of the intelligent LED lamp is long, and the service life of the intelligent LED lamp provided by an LED light source manufacturer can reach more than 10 ten thousand hours under proper voltage and current. In fact, the service life of the intelligent LED lamp depends on external environmental factors such as heat dissipation materials, aluminum substrate plates, driving power supplies, power factors, product structures, and the like, which also causes the service life differentiation of the intelligent LED lamp in the market. According to the inspection standard of LED lighting manufacturers, the indoor lighting lumen maintenance rate L70 is required to be more than or equal to 25000 hours, and the outdoor and commercial lighting lumen maintenance rates L70 are required to be more than or equal to 35000 hours. Indoor lighting has been shown to exhibit significant light decay when lumen maintenance reaches L90 and is irreversible, with LM-80-15 defining L90 as the failure criterion.
The inspection standard is only the inspection standard of an LED lighting manufacturer, but for a consumer, the information obtained when the consumer purchases a product is only the number of hours or more of what the product can be used in a nominal way from a purchase specification, and as time goes by, the consumer cannot accurately calculate how long the lamp is actually used to judge whether the service life of the lamp is up; secondly, the test time of the experimental data is continuous working time at a stable working temperature, and the aging degree of the product caused by factors such as environmental humidity, electromagnetic interference, static electricity and the like exists during working or non-working in actual use; thirdly, the theoretical life of the LED is long, even if the light is attenuated to L50, the LED can be continuously turned on, but the light at this time cannot meet the requirement of illumination, and is not suitable for continuous use, and may affect the health of human eyes to a certain extent.
Disclosure of Invention
The invention provides a method and a system for calculating the residual service life of an LED lamp, and aims to solve at least one of the technical problems in the prior art to a certain extent.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: a method for calculating the residual service life of an LED lamp is characterized by comprising the following steps:
step a: initializing the LED lamp, calibrating the light intensity data of the illumination sensor and the intelligent PWM power, and sending sample point data to a server;
step b: the server performs least square normal fitting according to the sample point data to construct light intensity data models under different powers;
step c: the server converts the sensor data received by the LED lamp from opening to closing each time by adopting a light intensity data model, and stores the converted sensor data and the acquisition time in a corresponding relation data table of the LED lamp to form sequence data parameters;
step d: and constructing a light attenuation model according to the sequence data parameters, and estimating the residual service life of the LED lamp through the light attenuation model.
The technical scheme adopted by the embodiment of the invention also comprises the following steps: the step a specifically comprises the following steps: when the LED lamp is started for the first time, detecting whether the LED lamp is activated, if the LED lamp is activated, acquiring sensor data of the LED lamp such as temperature and light intensity in a default power mode through the WIFI module, and uploading the acquired data to a server; if the LED lamp is not activated, the WIFI module starts a calibration mode, and light intensity data calibration is carried out on the LED lamp according to a defined calibration sample point, so that the server constructs a mathematical model of normalized power and light intensity data under different powers; and sending an activation request to the server after the calibration is finished, and sending sample point data to the server after the activation is successful.
The technical scheme adopted by the embodiment of the invention also comprises the following steps: in step b, the light intensity data model is constructed as follows:I （p）=I 0 +K p *I p : wherein, in the step (A),K p is the power factor;I p in order to normalize the power values, I 0 is a reference light intensity value.
The technical scheme adopted by the embodiment of the invention also comprises the following steps: the step b further comprises the following steps: storing the calibration parameters in a relation data table of the LED lamp, and meanwhile, storing a service life early warning threshold valueI 80 (p)And end of life thresholdI 70 （p）Stored in a database, the life warning threshold valueI 80 (p)Defined as the attenuation of the light intensity data reaching 80% under the maximum normalized power of the factory, and the end-of-life threshold valueI 70 （p）Defined as the attenuation of the light intensity data reaching 70 percent under the maximum normalized power of the factory。
The technical scheme adopted by the embodiment of the invention also comprises the following steps: the step c further comprises: when the LED lamp is started for the first time, the initial working time of the LED lamp is collected through the WIFI module on the LED lampt 0 Initial temperature valueT c0 Light intensity valueI 0 (p)Normalized current power valueI p0 Marking parameters{t 0 ，T c0 ，I 0 (p)，I p0 }And waiting for initial sensor data, and sending the acquired initial sensor data to a server.
The technical scheme adopted by the embodiment of the invention also comprises the following steps: the step c further comprises: when the LED lamp is normally started, sensor data under a stable temperature are collected through the WIFI module according to a preset sampling interval time interval, and the obtained sensor data are sent to the server.
The technical scheme adopted by the embodiment of the invention also comprises the following steps: the acquisition mode of the sensor data is specifically as follows: assuming that the first interval time is 5 minutes, the WIFI module acquires the temperature once every 5 minutesT c As a temperature reference point, comparing the temperature difference of the temperatures obtained in the previous three times, and storing the current sensor data when the temperature difference range of the temperatures obtained in the three times in 15 minutes is less than the preset temperature{t 1 ，T c1 ，I 1 (p)，I p1 }(ii) a Then, the sampling interval time is increased to 10 minutes, and when the temperature difference range of the temperature obtained three times within 30 minutes is smaller than the preset temperature, the current sensor data are stored{t 2 ，T c2 ，I 2 (p)，I p2 }(ii) a Then, the stable temperature values are acquired every 30 minutes as the reference to sequentially store the sensor data{t n ，T cn ，I n (p)，I pn }，When the WIFI module is disconnected with the server, a timestamp parameter is added into each piece of sensor data, the sensor data are sent to the server after connection is restored, and then the local cache is emptied to release the storage space.
The technical scheme adopted by the embodiment of the invention also comprises the following steps: the step c further comprises the following steps: after the server receives the light intensity data under different power modes, the server can obtain the light intensity data according to the light intensityThe power model converts the light intensity data to convert the light intensity data in the full power modeI(p)And after normalization processing, uniformly storing the normalized data and the acquisition time.
The technical scheme adopted by the embodiment of the invention also comprises the following steps: the step d specifically comprises: constructing a light attenuation model according to the sequence data parameters, and taking the last sample data of the minimum unit as a sampling point; when the working time is less than half a year but the using time is more than 2000 hours, using data sample point data of continuous 15 days for estimation; obtaining attenuation slope and intercept according to least square curve fitting to obtain light attenuation model about dateI(m)=βe -αm WhereinβIs the initial value of the light intensity after normalization,αin order to attenuate the slope of the light,min parts per month; the server calculates the corresponding remaining usage date at the bottom 24 of the month as definedI 70 = ln(β/0.7)/α-Δ(D t )WhereinΔ(D t )Is the number of months that have been used, and saves the calculation result in the server.
The embodiment of the invention adopts another technical scheme that: a system for calculating the residual service life of an LED lamp comprises an LED lamp source panel, a temperature sensor, an illumination sensor, a WIFI module, an APP control module and a server; the temperature sensor, the illumination sensor and the WIFI module are respectively arranged on the LED lamp source panel, and the WIFI module and the APP control module are respectively connected with the server; the LED lamp source panel performs initialization operation on the LED lamp and calibrates the light intensity data of the illumination sensor and the intelligent PWM power; the temperature sensor and the illumination sensor are respectively used for acquiring temperature data and light intensity data when the LED lamp is in a starting state; the WIFI module is used for acquiring sensor data acquired by the temperature sensor and the illumination sensor and sending the sensor data to the server; the server performs least square normal fitting according to the sample point data to construct light intensity data models under different powers; converting sensor data received by the LED lamp from the on to the off each time by adopting a light intensity data model, and storing the converted sensor data and acquisition time in a corresponding relation data table of the LED lamp to form sequence data parameters; and constructing a light attenuation model according to the sequence data parameters, and estimating the residual service life of the LED lamp through the light attenuation model.
Compared with the prior art, the invention has the following beneficial effects: according to the method and the system for calculating the remaining service life of the LED lamp, the server receives the data of the illumination sensor of the LED lamp at the stable working temperature in real time, the light attenuation model is constructed through the data of the illumination sensor, the remaining service life of the LED lamp is calculated according to the light attenuation model, and the APP control module is used for visually displaying the remaining service life. Compared with the prior art, the invention has the advantages that at least:
1. considering the actual use environment of the consumer from the perspective of the consumer, and estimating the remaining service life through multiple paths;
2. the real remaining service life of the lamp (the time of the discontinuous working time) is estimated by using a large amount of collected data, and the remaining service life is more reasonably defined so as to be in line with the understanding of consumers;
3. the visual window is provided for the consumer with the residual service life, and the early warning information that the service life of the consumer is rapidly due and the information prompt that the LED lamp needs to be replaced in time are intelligently pushed by the server, so that the eye health of the family of the consumer can be better protected;
4. the temperature rise information of the LED lamp is provided every time, so that a consumer can really know the current working temperature of the LED lamp and whether the temperature is too high, and meanwhile, the reference can be provided for LED lamp manufacturers to optimally design the heat dissipation under various environments.
Drawings
FIG. 1 is a flowchart of a method for calculating remaining useful life of an LED lamp according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating an initialization operation of an LED lamp according to an embodiment of the present invention;
FIG. 3 is a flow chart of sensor data processing by a server according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating the remaining lifetime calculation according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a remaining service life calculation system of an LED lamp according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
Fig. 1 is a flowchart of a method for calculating the remaining service life of an LED lamp according to an embodiment of the present invention. The method for calculating the residual service life of the LED lamp comprises the following steps:
s100: initializing the LED lamp, calibrating the light intensity data of the illumination sensor and the intelligent PWM power, and sending sample point data to a server;
in this step, the initialization operation flow of the LED lamp is as shown in fig. 2, and the specific operation process includes: when the LED lamp is started for the first time, firstly detecting whether the LED lamp is activated, if the LED lamp is activated, acquiring sensor data of the LED lamp such as temperature and light intensity in a default power mode through a WIFI module, and uploading the acquired data to a server; if the LED lamp is not activated, the WIFI module starts a calibration mode, and light intensity data calibration is carried out on the LED lamp according to defined calibration sample points (in order to ensure accuracy, the embodiment of the invention adopts 15 calibration sample points, and the specific number can be set according to actual operation), so that a server can conveniently construct mathematical models of normalized power and light intensity data under different powers; and sending an activation request to the server after the calibration is finished, and sending sample point data to the server after the activation is successful.
S200: the server performs least square normal fitting according to the sample point data, constructs light intensity data models under different powers, and calibrates parametersK p AndI 0 stored in a relation data table of the LED lamp and simultaneously used for storingI 80 (p)(life warning threshold value) andI 70 （p）(end-of-life threshold) stored in a database;
in this step, because the PWM adjustable light output mode is adopted, the light intensity data under different normalized power modes needs to be collected, and the least square method curve fitting is performed through the data to construct the light intensity data models under different normalized powers, so that the data conversion under different normalized powers can be obtained. The constructed light intensity data model is as follows:
I（p）=I 0 +K p *I p （1）
in the formula (1), the first and second groups,K p is the power factor;I p the power value is normalized, the parameter range is 0-1, and the precision is 0.001;I 0 is a reference light intensity value.
In this step, the life warning threshold valueI 80 (p)Defined as the light intensity data attenuation reaching 80% under the maximum normalized power of factory leaving, and the end-of-life threshold valueI 70 （p）The attenuation of the light intensity data under the maximum normalized power of the factory is defined to reach 70%.
S300: when the LED lamp is started for the first time, the initial working time of the LED lamp is collected through the WIFI module on the LED lampt 0 (unit: hour) initial temperature valueT c0 Light intensity valueI 0 (p)Normalized current power valueI p0 Marking parameters{t 0 ，T c0 ， I 0 (p)，I p0 }Waiting for initial sensor data, and sending the acquired initial sensor data to a server;
in this step, the LED lamp is provided with a WIFI module, a temperature sensor and an illumination sensor, the temperature sensor and the illumination sensor respectively collect temperature data and light sensation data of the LED lamp, and the WIFI module acquires the sensor data and sends the sensor data to the server.
S400: when the LED lamp is normally started, acquiring sensor data at a stable temperature through the WIFI module according to a preset sampling interval time interval, and sending the acquired sensor data to a server;
in the step, as the LED light source generates obvious light attenuation along with the continuous increase of the P-N junction temperature, the acquisition of the sensor data takes the stable temperature as a reference point, and the acquired sensor data is ensured to be more consistent with actual data. The temperature difference of the stable temperature needs to be less than 2 ℃, the temperature acquisition adopts a time slicing mode, the aim of the time slicing acquisition is to fully record the heating effect of the LED lamp, and after the stable temperature works, basically similar temperature data does not need to be frequently sent to a server, so that the pressure of the server is reduced. When the LED lamp is started from the ambient temperature, no obvious light attenuation exists, and the obvious light attenuation begins to exist after the temperature of the LED light source continuously rises, so that the data of the sensor is acquired after the temperature is stabilized, and the reliability of the acquired data can be ensured.
In the embodiment of the present invention, the acquisition mode of the sensor data specifically includes: assuming that the first interval time is 5 minutes, the WIFI module acquires the temperature once every 5 minutesT c As a temperature reference point, comparing the temperature difference of the temperatures obtained in the previous three times, and storing the current sensor data when the temperature difference range of the temperatures obtained in the three times in 15 minutes is less than the preset temperature (2℃){t 1 ，T c1 ，I 1 (p)，I p1 }(ii) a Then, the sampling interval time is increased to 10 minutes (specifically, the sampling interval time can be set according to actual operation), and when the temperature difference range of the temperature obtained three times within 30 minutes is smaller than the preset temperature, the current sensor data is stored{t 2 ，T c2 ，I 2 (p)， I p2 }(ii) a Then, stable temperature values (the temperature difference is less than 2 ℃) are obtained once every 30 minutes and are used as references to sequentially store sensor data{t n ，T cn ，I n (p)，I pn }. When the WIFI module is disconnected with the server, a timestamp parameter is added into each piece of sensor data (the initial time value is not obtained when the power supply is turned off due to special conditions, if the initial time value is not obtained when the power supply is not synchronized, the initial time value is represented by 0, the server receives the data and processes the data according to the latest time so that the server can accurately record the data), the sensor data are sent to the server after the connection is restored, and then the local cache is emptied to release the storage space.
In the above, there are two situations when the LED lamp is turned off: through power supply shutdown or intelligent equipment shutdown, when a user shuts down the LED lamp through the power supply, the WIFI module cannot normally communicate with the server, so that the server cannot acquire the latest data, the server is connected to send the data stored in the FLASH storage space after the LED lamp is required to be restarted, and meanwhile, the cache data are emptied; when a user closes the lamp through the intelligent equipment, the WIFI module sends the cache data in the FLASH storage space to the server, and meanwhile, the cache data are emptied.
S500: the server converts the sensor data received by the LED lamp from opening to closing each time by adopting a light intensity data model, and stores the converted sensor data and the acquisition time in a corresponding relation data table of the LED lamp to form a sequence data parameter{D tn ，ΔT，t wn ,T wcn ，I wn (p)}WhereinD tn To be the current server system timestamp when the sensor data was received,ΔTin order to provide temperature-raising data,t wn is the working time parameter of the LED lamp,T wcn to correspond tot wn The operating temperature of the process;
in this step, since the luminous flux of the LED lamp source is directed to a certain lamp source, and the LED lamp is formed by connecting a plurality of LED lamp sources in parallel or in series, the luminous flux of the lamp source cannot be simply converted in a quantitative manner. After the server receives the light intensity data under different power modes, the light intensity data needs to be converted according to the light intensity power modelThe light intensity data in the full power modeI (p)And after normalization processing, uniformly storing the normalized data and the acquisition time. The acquisition time is different from the actual data storage time of the server, and the actual data storage time of the server is the sum of the last work finishing time of the LED lamp and the acquisition time, so that the server can record the work time sample of the LED lamp completely.
Specifically, the processing flow of the server on the sensor data is shown in fig. 3, and specifically includes: the working time of the LED lamp is recorded, and the working time when the WIFI module is firstly connected with the server for activationt w Set to 0 in hours; when the LED lamp is normally started, the server will sequentially receive stable sensor data{t 0 ,T c0 ,I 0 (p),I p0 }、{t 1 ,T c1 ,I 1 (p), I p1 }、...、 {t n ,T cn ,I n (p),I pn }(ii) a The server stores the sensor data as a period according to the condition that the LED lamp is turned on to be turned off every time; temperature raising parameterΔT = T c1 - T c0 (ii) a LED lamp working time parametert wn = t wp + t n Whereint wp The working time of the LED lamp after the last working is finished,t n the working time obtained this time; intensity data according to parametersI n (p)AndI pn and converted into light intensity data at full power by the light intensity data modelI wn （p）Finally, a sequence data parameter is formed{D tn ，ΔT，t wn ,T wcn ，I wn (p)}。
S600: based on sequence data parameters{D tn ，ΔT，t wn ,T wcn ，I wn (p)}Constructing a light attenuation model, and estimating the residual service life of the LED lamp through the light attenuation model;
in this step, the fundamental reason for influencing the light attenuation of the LED light source is the increase of PN junction temperature, which is related to the factors of heat sink, power, ambient temperature, etc., so that different operating time zones of the LED lamp may have different light attenuation degrees. The service life of the LED lamp after leaving factory and being activated is defined to be 2000 hours or the activation service date reaches more than half a year (the specific service life or the activation service date can be set according to different lamps), and enough data distribution points are accumulated at the moment to be used for constructing a light attenuation model, so that the remaining service life is estimated. The server confirms the light attenuation relation between the date of use and the light intensity data through the received sensor dataI(m)Measuring the light attenuation degree by the attenuation of the light intensity data; defining a quantified value of life asNAnd the mobile APP end displays the service life usage (corresponding to the indication icon):N% at this time, the remaining life duration, the default '-' is displayed to represent no estimation:
N =(I wn (p) - I 70 (p))/(I 0 (p) - I 70 (p)) （2）
in the formula (2), the first and second groups of the compound,I 0 (p)in order to acquire the initial light intensity value,I 70 (p)in order to be the end-of-life threshold value,I wn (p)the light intensity value of the last work.
Specifically, the calculation flow of the remaining service life is shown in fig. 4, and specifically includes: according to{D tn ，I wn (p)}Constructing a light attenuation model, and taking the last sample data of a minimum unit 'month' as a sampling point (although the minimum date and even hour can be taken as a sample, the corresponding attenuation degree is very small, which is beneficial to improving the precision but can be overConsumption of computer resources); when the operating time is less than half a year but the usage time is greater than 2000 hours, an estimate is made using data sample point data for 15 consecutive days (about 0.5 months) to ensure that there are enough data sample points. Obtaining attenuation slope and intercept according to least square curve fitting to obtain light attenuation model about dateI(m)=βe -αm WhereinβIs the initial value of the light intensity after normalization,αin order to attenuate the slope of the light,min parts per month; since the month is taken as the statistical unit, the server only needs 24 months at the bottom of the month to calculate the corresponding remaining use date as the definitionI 70 =ln(β/0.7)/α-Δ(D t )WhereinΔ(D t )The number of the used months is obtained, and the calculation result is stored in the server; the calculated value will be more and more accurate as the time used by the user increases.
S700: the server sends the calculation result to the mobile terminal application APP for display, and the sending content comprises the current working temperature of the LED lamp, the temperature rise value, the used time of the lamp, the service life usage amount and the remaining service life;
in this step, the display content of the mobile terminal APP includes: the current working temperature, the temperature rise value, the used time of the lamp, the service life usage amount and the remaining service life of the LED lamp; the service life usage is displayed by an N% value, and simultaneously, icon display can be carried out according to the quantized value; the remaining service time is displayed year by year with a precision of months.
In the embodiment of the present invention, the definition of the remaining service life includes:
1. the residual service life duration is measured by years, and due to uncertainty of external environment factors, the prediction time is only displayed for more than 3 years for the user when the prediction time is more than three years, so that the user is prevented from being puzzled by inaccurate prediction; for predictions within three years, the accuracy is defined as: month;
2. measuring the service life usage by a quantized value, and displaying the current use condition by N%;
3. after the light of the LED lamp source is attenuated, the junction temperature is increased, more light energy is converted into heat energy, the light attenuation rate is higher along with the increase of time, and therefore the early warning service life threshold is established by taking I80 as a reference;
4. an end-of-life threshold and an expiration date for the remaining useful life are established based on I70.
S800: when the server detects that the LED lamp reaches a service life early warning threshold value or a service life end threshold value, sending early warning information to the APP control module, and displaying early warning through the APP control module;
in this step, APP control module in time prompts the user to change the lamp according to the early warning information after receiving the early warning information of the server, and the eye health of the user can be better protected.
Fig. 5 is a schematic structural diagram of a system for calculating remaining service life of an LED lamp according to an embodiment of the present invention. The system for calculating the remaining service life of the LED lamp comprises an LED lamp source panel, a temperature sensor, an illumination sensor, a WIFI module, an APP control module and a server. Wherein, temperature sensor, light intensity sensor and WIFI module are installed respectively on LED lamp source panel, and WIFI module and APP control module are connected with the server respectively. Specifically, the method comprises the following steps:
the temperature sensor and the illumination sensor are respectively used for acquiring temperature data and light intensity data when the LED lamp is in a starting state; in the embodiment of the invention, in order to ensure the data reliability of the temperature, the temperature sensor is arranged close to the pin of the LED light source so as to be close to the temperature of the light source test point, and meanwhile, the time for reaching the stable working temperature is more reliable in the process from closing to opening of the lamp. The illumination sensor is arranged on the central point of the aluminum substrate of the LED lamp source plane, and the light attenuation degree is indirectly counted by collecting light intensity data reflected by the lampshade.
The WIFI module is used for acquiring sensor data acquired by the temperature sensor and the illumination sensor according to a predefined communication protocol, caching the sensor data in a local FLASH storage space, and sending the sensor data to the server when the LED lamp is turned off;
the server is respectively communicated with the WIFI module and the APP control module according to an agreed protocol, is used for storing experimental data of LED lamp manufacturers, and comprisesThe APP control module manages user equipment, firstly, a light intensity data model of each LED lamp under different power is established, and LED lamp light intensity data models are definedI 80 (p)(life warning threshold value) andI 70 （p）(end-of-life threshold); then, converting sensor data received by the LED lamp from opening to closing each time by adopting a light intensity data model to form a sequence data parameter, constructing a light attenuation model according to the sequence data parameter, calculating the residual service life of the LED lamp through the light attenuation model, sending data such as the heating effect of the LED lamp, the quantized service life usage (N%) of the LED lamp, the residual service life (unit: year, precision: month) of the LED lamp and the like to an APP control module according to a calculation result, and sending corresponding early warning information to the APP control module when the residual service life reaches a service life early warning threshold value or a service life end threshold value;
the APP control module is installed on terminal equipment such as a smart phone or a tablet personal computer and used for distributing a network for the WIFI module, reporting unique identification information of the LED lamp, controlling the LED lamp, inquiring and displaying data such as the temperature rise effect, the quantitative service life consumption and the residual service life of the LED lamp sent by the server, and prompting a user to replace the lamp according to early warning information sent by the server.
In the embodiment of the invention, the LED lamp adopts a driving mode with adjustable PWM power.
According to the method and the system for calculating the remaining service life of the LED lamp, the server receives the data of the illumination sensor of the LED lamp at the stable working temperature in real time, the light attenuation model is constructed through the data of the illumination sensor, the remaining service life of the LED lamp is calculated according to the light attenuation model, and the APP control module is used for visually displaying the remaining service life. Compared with the prior art, the invention has the advantages that at least:
1. and (4) estimating the residual service life through multiple paths from the perspective of a consumer in consideration of the actual use environment of the consumer.
2. The real remaining service life of the lamp (the time of the discontinuous working time) is estimated by using a large amount of collected data, and the remaining service life is more reasonably defined so as to be in line with the understanding of consumers.
3. The visual window for the remaining service life of the consumer is provided, and the warning information about the quick expiration of the service life of the consumer and the information reminding that the LED lamp needs to be replaced in time are intelligently pushed by the server, so that the eye health of the family of the consumer can be better protected.
4. The temperature rise information of the LED lamp is provided every time, so that a consumer can really know the current working temperature of the LED lamp and whether the temperature is too high, and meanwhile, the reference can be provided for LED lamp manufacturers to optimally design the heat dissipation under various environments.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A method for calculating the residual service life of an LED lamp is characterized by comprising the following steps:
step a: initializing the LED lamp, calibrating the light intensity data of the illumination sensor and the intelligent PWM power, and sending sample point data to a server;
step b: the server performs least square normal fitting according to the sample point data to construct light intensity data models under different powers;
step c: the server converts the sensor data received by the LED lamp from opening to closing each time by adopting a light intensity data model, and stores the converted sensor data and the acquisition time in a corresponding relation data table of the LED lamp to form sequence data parameters;
step d: and constructing a light attenuation model according to the sequence data parameters, and estimating the residual service life of the LED lamp through the light attenuation model.
2. The method for calculating the remaining service life of the LED lamp according to claim 1, wherein the step a specifically comprises: detecting whether the LED lamp is activated or not when the LED lamp is started for the first time, if the LED lamp is activated, acquiring temperature and light intensity sensor data of the LED lamp in a default power mode through the WIFI module, and uploading the acquired data to a server; if the LED lamp is not activated, the WIFI module starts a calibration mode, and light intensity data calibration is carried out on the LED lamp according to a defined calibration sample point, so that the server constructs a mathematical model of normalized power and light intensity data under different powers; and sending an activation request to the server after the calibration is finished, and sending sample point data to the server after the activation is successful.
3. The method for calculating the remaining service life of the LED lamp as recited in claim 1, wherein in the step b, the light intensity data model is constructed by:I（p）=I 0 +K p *I p : wherein, in the step (A),K p is the power factor;I p in order to normalize the power values,I 0 is a reference light intensity value.
4. The method for calculating the remaining service life of the LED lamp according to claim 3, wherein the step b further comprises: storing the calibration parameters in a relation data table of the LED lamp, and meanwhile, storing a service life early warning threshold valueI 80 (p)And end of life thresholdI 70 （p）Stored in a database, the life warning threshold valueI 80 (p)Defined as the attenuation of the light intensity data reaching 80% under the maximum normalized power of the factory, and the end-of-life threshold valueI 70 （p）Defined as the attenuation of the light intensity data reaching 70 percent under the maximum normalized power of the factory。
5. The method for calculating the remaining service life of the LED lamp according to claim 1, wherein the step c further comprises: when the LED lamp is started for the first time, the initial working time of the LED lamp is collected through the WIFI module on the LED lampt 0 Initial temperature valueT c0 Light intensity valueI 0 (p)Normalized current power valueI p0 Marking parameters{t 0 ，T c0 ，I 0 (p)，I p0 }Is the initial sensor data and sends the acquired initial sensor data to the server.
6. The method for calculating the remaining service life of the LED lamp according to claim 5, wherein the step c further comprises: when the LED lamp is normally started, sensor data under a stable temperature are collected through the WIFI module according to a preset sampling interval time interval, and the obtained sensor data are sent to the server.
7. The method for calculating the remaining service life of the LED lamp according to claim 6, wherein the sensor data is collected in a manner that: the first interval time is 5 minutes, and then the WIFI module acquires the temperature once every 5 minutesT c As a temperature reference point, comparing the temperature difference of the three acquired temperatures, and storing the current sensor data when the temperature difference range of the three acquired temperatures is less than the preset temperature within 15 minutes{t 1 ，T c1 ，I 1 (p)，I p1 }(ii) a Then, the sampling interval time is increased to 10 minutes, and when the temperature difference range of the temperature obtained three times within 30 minutes is smaller than the preset temperature, the current sensor data are stored{t 2 ， T c2 ，I 2 (p)，I p2 }(ii) a Then, the stable temperature values are acquired every 30 minutes as the reference to sequentially store the sensor data{t n ， T cn ，I n (p)，I pn }，When the WIFI module is disconnected with the server, a timestamp parameter is added into each piece of sensor data, and recovery is carried outAfter connection, the sensor data is sent to the server, and then the local cache is emptied to release the storage space.
8. The method for calculating the remaining service life of the LED lamp according to claim 1, wherein the step c is followed by further comprising: after the server receives the light intensity data in different power modes, the light intensity data is converted according to the light intensity data model, and the light intensity data in the full power mode is convertedI(p)And after normalization processing, uniformly storing the normalized data and the acquisition time.
9. The method for calculating the remaining service life of the LED lamp according to claim 1, wherein the step d specifically comprises: constructing a light attenuation model according to the sequence data parameters, and taking the last sample data of the minimum unit as a sampling point; when the working time is less than half a year but the using time is more than 2000 hours, using data sample point data of continuous 15 days for estimation; obtaining attenuation slope and intercept according to least square curve fitting to obtain light attenuation model about dateI(m)=βe -αm In whichβIs the initial value of the light intensity after normalization,αin order to attenuate the slope of the light,min parts per month; the server calculates the corresponding remaining usage date at the bottom 24 of the month as definedI 70 =ln(β/0.7)/α-Δ(D t )In whichΔ(D t )Is the number of months that have been used, and saves the calculation result in the server.
10. A system for calculating the residual service life of an LED lamp is characterized by comprising an LED lamp source panel, a temperature sensor, an illumination sensor, a WIFI module, an APP control module and a server; the temperature sensor, the illumination sensor and the WIFI module are respectively arranged on the LED lamp source panel, and the WIFI module and the APP control module are respectively connected with the server;
the LED lamp source panel performs initialization operation on the LED lamp and calibrates the light intensity data of the illumination sensor and the intelligent PWM power
The temperature sensor and the illumination sensor are respectively used for acquiring temperature data and light intensity data when the LED lamp is in a starting state;
the WIFI module is used for acquiring sensor data acquired by the temperature sensor and the illumination sensor and sending the sensor data to the server;
the server performs least square normal fitting according to the sample point data to construct light intensity data models under different powers; converting the sensor data received by the LED lamp from the on to the off each time by adopting a light intensity data model, and storing the converted sensor data and the acquisition time in a corresponding relation data table of the LED lamp to form sequence data parameters; and constructing a light attenuation model according to the sequence data parameters, and estimating the residual service life of the LED lamp through the light attenuation model.
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