CN116430271A - Online detection method for LED soft light bar, intelligent terminal and storage medium - Google Patents

Online detection method for LED soft light bar, intelligent terminal and storage medium Download PDF

Info

Publication number
CN116430271A
CN116430271A CN202310239777.2A CN202310239777A CN116430271A CN 116430271 A CN116430271 A CN 116430271A CN 202310239777 A CN202310239777 A CN 202310239777A CN 116430271 A CN116430271 A CN 116430271A
Authority
CN
China
Prior art keywords
light bar
soft light
led soft
led
detection
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310239777.2A
Other languages
Chinese (zh)
Inventor
王春涛
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Ledmy Co ltd
Original Assignee
Shenzhen Ledmy Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenzhen Ledmy Co ltd filed Critical Shenzhen Ledmy Co ltd
Priority to CN202310239777.2A priority Critical patent/CN116430271A/en
Publication of CN116430271A publication Critical patent/CN116430271A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/44—Testing lamps
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
    • G01K13/00—Thermometers specially adapted for specific purposes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
    • G01K3/00—Thermometers giving results other than momentary value of temperature
    • G01K3/08—Thermometers giving results other than momentary value of temperature giving differences of values; giving differentiated values
    • G01K3/10—Thermometers giving results other than momentary value of temperature giving differences of values; giving differentiated values in respect of time, e.g. reacting only to a quick change of temperature
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
    • G01R19/0092—Arrangements for measuring currents or voltages or for indicating presence or sign thereof measuring current only
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R21/00—Arrangements for measuring electric power or power factor
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B20/00—Energy efficient lighting technologies, e.g. halogen lamps or gas discharge lamps
    • Y02B20/40—Control techniques providing energy savings, e.g. smart controller or presence detection

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Led Devices (AREA)

Abstract

The application relates to an online detection method for an LED soft light bar, an intelligent terminal and a storage medium, which belong to the technical field of testing, and the method comprises the following steps: obtaining a current detection result of the LED soft light bar according to a preset current measurement system, and obtaining a light bar state of the LED soft light bar according to the current detection result; the lamp status includes steady state and unsteady state; if the state of the LED soft light bar is a stable state, increasing the test current passing through the LED soft light bar to a preset target current through a current measurement system, and acquiring a temperature change value of the LED soft light bar; judging whether the temperature change value is within a preset temperature change range; if the power of the LED soft light bar is within the temperature variation range, detecting the light bar power of the LED soft light bar in real time through a power meter; judging whether the power of the lamp strip is stable or not; if so, generating a detection result of the LED soft light bar, and finishing the detection of the LED soft light bar. The LED soft light bar testing device has the effect of effectively improving testing accuracy of the LED soft light bar.

Description

Online detection method for LED soft light bar, intelligent terminal and storage medium
Technical Field
The application relates to the technical field of testing, in particular to an online detection method for an LED soft light bar, an intelligent terminal and a storage medium.
Background
The LED soft light bar is widely applied to background illumination of walls, stairs, roofs or other spaces as a lighting lamp. The LED light bar is composed of LEDs assembled on a strip-shaped flexible circuit board or a PCB hard board, and when the LED light bar leaves a factory, a tester can test indexes such as brightness, color, temperature and the like of the LEDs to judge whether the LED light bar meets the factory requirement.
In the prior art, when the LED soft light bar leaves the factory, a tester firstly accesses the LED soft light bar into a power supply, detects the power of the LED soft light bar by using a power meter, and leaves the factory when the power of the LED soft light bar is specified.
Aiming at the prior art, the applicant believes that when the soft light bar leaves the factory, the power of the soft light bar of the LED under the condition of the power supply voltage is only measured as the power supply voltage is unchanged, and the performance of the soft light bar of the LED under other conditions is not tested, so that the testing accuracy of the soft light bar of the LED is lower.
Disclosure of Invention
In order to effectively improve the test accuracy of the LED soft light bar, the application provides an online detection method, an intelligent terminal and a storage medium for the LED soft light bar.
In a first aspect, the present application provides an online detection method for an LED soft light bar, which adopts the following technical scheme:
an on-line detection method for an LED soft light bar, comprising the following steps:
obtaining a current detection result of an LED soft light bar according to a preset current measurement system, and obtaining a light bar state of the LED soft light bar according to the current detection result; the lamp status includes steady state and unsteady state;
if the light bar state of the LED soft light bar is the stable state, increasing the test current passing through the LED soft light bar to a preset target current through the current measurement system, and acquiring a temperature change value of the LED soft light bar;
judging whether the temperature change value is in a preset temperature change range or not;
if the temperature is within the temperature variation range, detecting the lamp strip power of the LED soft lamp strip in real time through a power meter;
judging whether the power of the lamp strip is stable or not;
and if so, generating a detection result of the LED soft light bar, and finishing the detection of the LED soft light bar.
Through adopting above-mentioned technical scheme, at first carry out the electric current to the soft lamp strip of LED to when the lamp strip state of the soft lamp strip of LED is steady state, carry out temperature variation detection to the soft lamp strip of LED, and when the temperature variation value is in temperature variation range, detect the lamp strip power of the soft lamp strip of LED, and accomplish the detection to the soft lamp strip of LED when the lamp strip power is steady, not only carry out power detection to the soft lamp strip of LED under the power supply voltage condition, thereby detect the performance of the soft lamp strip of LED in a plurality of dimensions, and then effectively improved the test accuracy of the soft lamp strip of LED.
Optionally, before the obtaining the temperature change value of the soft LED light bar, the method further includes:
analyzing the LED soft light bars in different detection states through a preset pyroelectric detection system to obtain a detection report of the LED soft light bars; the detection state comprises a static state and a working state;
obtaining temperature change conditions of the LED soft light bar under different detection states according to the detection report;
judging whether the temperature change condition in one detection state is abnormal or not;
if yes, stopping detection, and judging the LED soft light bar as a flaw soft light bar;
and if not, executing the step of acquiring the temperature change value of the LED soft light bar.
Through adopting above-mentioned technical scheme, increase the detection to the soft lamp strip temperature variation condition of LED to carry out the step of the soft lamp strip's of LED temperature variation value when the soft lamp strip temperature variation condition of LED is normal, confirm whether acquire the temperature variation value of soft lamp strip through the temperature variation condition to the soft lamp strip of LED, further effectively improved the test accuracy of the soft lamp strip of LED.
Optionally, the analyzing, by a preset pyroelectric detection system, the soft LED light bar in different detection states to obtain a detection report of the soft LED light bar includes:
acquiring static temperature data of the LED soft light bar in the static state and working temperature data of the LED soft light bar in the working state by the pyroelectric detection system at intervals of preset time intervals;
generating a static temperature change trend of the LED soft light bar in the static state according to the static temperature data;
generating a working temperature change trend of the LED soft light bar in the working state according to the working temperature data;
and generating a detection report of the LED soft light bar according to the static temperature change trend and the working temperature change trend.
By adopting the technical scheme, the detection report of the LED soft light bar consists of the working temperature change trend of the LED soft light bar in the working state and the temperature change trend of the LED soft light bar in the static state, and the test accuracy of the LED soft light bar is effectively improved by testing the temperature change trend of the LED soft light bar in different detection states.
Optionally, before the generating the detection result of the LED soft light bar, the method further includes:
the working temperature of the LED soft light bar is regulated to a preset target temperature through the pyroelectric detection system;
detecting working data of the LED soft light bar in real time through a preset power supply detection system, and recording duration time of the LED soft light bar in the target temperature when the working data are in a preset working data range;
and generating a durability evaluation report of the LED soft light bar.
Through adopting above-mentioned technical scheme, at first with the operating temperature of the soft lamp strip of LED to target temperature to detect the duration of the soft lamp strip of LED in target temperature, be favorable to testing the durability of the soft lamp strip of LED under different temperatures, thereby further improved the test accuracy of the soft lamp strip of LED.
Optionally, after the generating the durability evaluation report of the LED soft light bar, the method includes:
acquiring working environment data of the LED soft light bar;
obtaining life data of the LED soft light bar at the target temperature according to the durability evaluation report;
according to the working environment data and the service life data, calculating the reliability of the LED soft light bar;
and calculating the expected service life of the LED soft light bar according to the reliability and the working environment data.
According to the technical scheme, firstly, the service life data of the LED soft light bar is obtained according to the durability evaluation report, then the reliability of the LED soft light bar is obtained through calculation according to the service life data and the working environment data, and finally the expected service life of the LED soft light bar is obtained through calculation according to the reliability and the working environment data, so that the expected service lives of the LED soft light bar under different working environments can be conveniently obtained, the LED soft light bar is effectively and comprehensively tested, and the accuracy of the LED soft light bar test is further improved.
Optionally, the calculating, according to the working environment data and the life data, the reliability of the LED soft light bar includes:
matching the working environment data based on a preset environment database to obtain an environment grade corresponding to the working environment data;
and taking the product of the environment grade and the service life data as the reliability of the LED soft light bar.
By adopting the technical scheme, the reliability is calculated by the environmental grade and life data, and the accuracy of calculating the reliability of the LED soft light bar is effectively improved.
Optionally, the calculating, according to the reliability and the working environment data, the expected lifetime of the soft LED light bar includes:
acquiring normal service life data matched with the working environment data from a preset historical service life database;
multiplying the reliability by the normal service life data to obtain the expected service life of the LED soft light bar.
By adopting the technical scheme, the expected service life of the LED soft light bar is calculated by the reliability and normal service life data, and the accuracy of calculating the expected service life of the LED soft light bar is effectively improved.
In a second aspect, the present application provides an intelligent terminal that adopts the following technical scheme:
the intelligent terminal comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the online detection method for the LED soft light bar is adopted when the processor loads and executes the computer program.
By adopting the technical scheme, the computer program is generated by the on-line detection method for the LED soft light bar and is stored in the memory to be loaded and executed by the processor, so that the intelligent terminal is manufactured according to the memory and the processor, and the use is convenient.
In a third aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
a computer readable storage medium having a computer program stored therein, the computer program when loaded and executed by a processor employing the above-described on-line detection method for LED soft light bars.
By adopting the technical scheme, the on-line detection method for the LED soft light bar generates a computer program, and the computer program is stored in a computer readable storage medium to be loaded and executed by a processor, and the computer program is convenient to read and store by the computer readable storage medium.
In summary, the present application has at least one of the following beneficial technical effects:
1. firstly, current detection is carried out on the LED soft light bar, when the light bar state of the LED soft light bar is in a stable state, temperature change detection is carried out on the LED soft light bar, when a temperature change value is in a temperature change range, the light bar power of the LED soft light bar is detected, and when the light bar power is stable, the detection of the LED soft light bar is completed, and not only the power detection is carried out on the LED soft light bar under the condition of power supply voltage, so that the performance of the LED soft light bar is detected in multiple dimensions, and further the test accuracy of the LED soft light bar is effectively improved.
2. Firstly, the working temperature of the LED soft light bar is adjusted to the target temperature, and the duration time of the LED soft light bar in the target temperature is detected, so that the durability of the LED soft light bar at different temperatures is tested, and the testing accuracy of the LED soft light bar is further improved.
3. The method comprises the steps of detecting the temperature change condition of the soft LED light bar, executing the temperature change value of the soft LED light bar when the temperature change condition of the soft LED light bar is normal, determining whether to acquire the temperature change value of the soft LED light bar or not according to the temperature change condition of the soft LED light bar, and further effectively improving the test accuracy of the soft LED light bar.
Drawings
Fig. 1 is a schematic flow chart of one implementation of an online detection method for an LED soft light bar according to an embodiment of the present application.
Fig. 2 is a flow chart of one implementation of an online detection method for an LED soft light bar according to an embodiment of the present application.
Fig. 3 is a flow chart of one implementation of an online detection method for an LED soft light bar according to an embodiment of the present application.
Fig. 4 is a flow chart of one implementation of an online detection method for an LED soft light bar according to an embodiment of the present application.
Fig. 5 is a flow chart of one implementation of an online detection method for an LED soft light bar according to an embodiment of the present application.
Fig. 6 is a flow chart of one of the on-line detection methods for the LED soft light bar according to the embodiment of the present application.
Fig. 7 is a flowchart of one implementation of an online detection method for an LED soft light bar according to an embodiment of the present application.
Detailed Description
The present application is described in further detail below in conjunction with figures 1 to 7.
The embodiment of the application discloses an online detection method for an LED soft light bar.
Referring to fig. 1, an on-line detection method for an LED soft light bar includes the steps of:
s101, acquiring a current detection result of an LED soft light bar according to a preset current measurement system, and acquiring a light bar state of the LED soft light bar according to the current detection result; the lamp status includes steady state and unsteady state.
The current detection system is used for measuring and detecting the current of the LED soft light bar and is used for carrying out current test on the LED soft light bar. The current detection system comprises a power supply, a current sensor, a signal processor, a data acquisition unit, a display and the like, wherein the power supply is used for providing power for the LED soft light bar; the current sensor is used for detecting current data passing through the LED soft light bar; the signal processor is used for processing the current data acquired from the current sensor and converting the current data into a signal which can be recognized and displayed by the display; the data collector is used for recording and storing current data acquired from the current sensor.
The current detection result refers to an actual current value of the LED soft light bar, and the light bar is used for representing current change of the LED soft light bar at the n+1th moment and current change of the LED soft light bar at the n th moment, wherein n is a positive integer. If the state of the light bar is a stable state, indicating that the current of the LED soft light bar at the n+1th moment and the current change at the n moment are in a preset change range; if the state of the light bar is an unstable state, the current change of the LED soft light bar at the n+1th moment and the current change of the LED soft light bar at the n-th moment exceed a preset current change range, and the current change range can be artificially set according to the specification parameters of the LED soft light bar.
S102, if the state of the light bar of the LED soft light bar is a stable state, increasing the test current passing through the LED soft light bar to a preset target current through a current measurement system, and obtaining the temperature change value of the LED soft light bar.
And if the light bar state of the LED soft light bar is a stable state, indicating that the LED soft light bar passes the current test. In this embodiment, the power supply in the current measurement system may be used to increase the current passing through the LED soft light bar, i.e. increase the test current of the LED soft light bar to the target current, in addition to providing power for the LED soft light bar, so as to test the LED soft light bar. The temperature change value refers to the difference between a first temperature when the LED soft light bar passes through the test current and a second temperature when the LED soft light bar passes through the target current, namely the temperature change value= |second temperature-first temperature|. The temperature of the LED soft light bar is obtained through a temperature sensor.
S103, judging whether the temperature change value is within a preset temperature change range.
For example, if the temperature variation range is [3,5], if the temperature variation value a is 4, the temperature variation value is within the temperature variation range, and if the temperature variation value a is 6, the temperature variation value is not within the temperature variation range.
And S104, if the temperature is in the temperature change range, detecting the power of the LED soft light bar in real time through a power meter.
If the temperature change value is in the temperature change range, the LED soft light bar passes the temperature test when the current changes, and the light bar power of the LED soft light bar is detected in real time through a power meter at the moment, and the power meter is used for measuring and displaying the power of the LED soft light bar.
If the LED soft light bar is not in the temperature change range, the detection of the LED soft light bar is stopped, and the LED soft light bar is judged to be a flaw soft light bar.
S105, judging whether the power of the lamp strip is stable.
If the power of the LED soft light bar at the n+1th moment and the power at the n moment are not changed beyond the preset power change range, judging that the light bar power is stable; otherwise, if the power of the LED soft light bar at the n+1th moment and the power variation of the LED soft light bar at the n moment exceed the preset power variation range, judging that the power of the light bar is unstable.
And S106, if the LED soft light bar is stable, generating a detection result of the LED soft light bar, and finishing the detection of the LED soft light bar.
If the light bar power is stable, the LED soft light bar passes the power test, and a detection result of the LED soft light bar is generated at the moment, wherein the detection result comprises detection indexes such as the light bar state, the temperature change value, the light bar power stability and the like of the LED soft light bar. And generating a detection result to indicate that the detection of the LED soft light bar is completed.
If the power of the light bar is unstable, the detection of the LED soft light bar is stopped, and the LED soft light bar is judged to be a defective soft light bar.
The implementation principle of the embodiment is as follows: firstly, current detection is carried out on the LED soft light bar, when the light bar state of the LED soft light bar is in a stable state, temperature change detection is carried out on the LED soft light bar, when a temperature change value is in a temperature change range, the light bar power of the LED soft light bar is detected, and when the light bar power is stable, the detection of the LED soft light bar is completed, and not only the power detection is carried out on the LED soft light bar under the condition of power supply voltage, so that the performance of the LED soft light bar is detected in multiple dimensions, and further the test accuracy of the LED soft light bar is effectively improved.
Before the temperature change value of the soft LED light bar is obtained in step S102 in the embodiment shown in fig. 1, the temperature change condition of the soft LED light bar may be first determined. The embodiment shown in fig. 2 is specifically described in detail.
Referring to fig. 2, before obtaining the temperature variation value of the LED soft light bar, the method further includes the following steps:
s201, analyzing the LED soft light bars in different detection states through a preset pyroelectric detection system to obtain a detection report of the LED soft light bars; the detection state includes a stationary state and an operating state.
The pyroelectric detection system is a system for detecting the temperature change of the LED soft light bar by using a pyroelectric technology and mainly comprises a pyroelectric sensor, a display, a signal processor, a data acquisition device and other devices, wherein the pyroelectric sensor is a sensor which uses the pyroelectric effect of pyroelectric ceramics as an infrared detection principle and is used for detecting the temperature change of the LED soft light bar; the display is used for displaying the temperature change of the LED soft light bar, and the signal processor is used for converting the electric signal acquired from the pyroelectric sensor into a signal readable by the display; the data collector is used for recording and storing the temperature change signals acquired from the pyroelectric sensor.
The detection report refers to a report obtained by analyzing the LED soft light bar according to the pyroelectric detection system, specifically, the pyroelectric sensor senses the temperature change of the LED soft light bar and outputs an electric signal in the form of voltage or current, the electric signal is used as a temperature change signal, and the detection report is generated according to the temperature change signal.
The static state refers to the state after the LED soft light bar is powered off, and the working state refers to the state after the LED soft light bar is powered on.
S202, according to the detection report, obtaining the temperature change condition of the LED soft light bar under different detection states.
The temperature change condition refers to the temperature change condition of the LED soft light bar in a detection state. For example, the two temperature change conditions are adopted, the first is that when the LED soft light bar is in a static state, the LED soft light bar starts at the moment of turning off the power supply, and the recorded temperature change of the LED soft light bar is recorded; and the second is that when the soft light bar is in a working state, the LED soft light bar starts at the moment of turning on the power supply, and the recorded temperature change of the LED soft light bar is recorded.
S203, judging whether the temperature change condition in one detection state is abnormal.
If the voltage signal or the current signal output by the pyroelectric sensor is larger than the manually set signal threshold, judging that the temperature change condition of the LED soft light bar is abnormal. The temperature change conditions of the LED soft light bar are divided into two types according to the detection states, namely, one type is the temperature change condition when the LED soft light bar is in a static state, and the other type is the temperature change condition when the LED soft light bar is in a working state, so that the temperature change conditions of the LED soft light bar in different detection states are respectively detected.
S204, if the LED soft light bar exists, the detection is stopped, and the LED soft light bar is judged to be a defective soft light bar.
If the temperature change condition in one of the two detection states is abnormal, the detection of the LED soft light bar is stopped, and the LED soft light bar is judged to be a flaw soft light bar, so that the LED soft light bar is convenient for staff to process.
S205, if the LED soft light bar does not exist, executing the step of acquiring the temperature change value of the LED soft light bar.
If the temperature change conditions in the two detection states are not abnormal, the temperature change value of the LED soft light bar is obtained at the moment.
According to the online detection method for the LED soft light bar, detection of the temperature change condition of the LED soft light bar is increased, and the step of executing the temperature change value of the LED soft light bar when the temperature change condition of the LED soft light bar is normal is performed.
In step S201 of the embodiment shown in fig. 2, the pyroelectric detection system may collect the rest temperature data of the LED soft light bar in the rest state and the working temperature data in the working state, so as to obtain a detection report. The embodiment shown in fig. 3 is specifically described in detail.
Referring to fig. 3, the soft LED light bars in different detection states are analyzed by a preset pyroelectric detection system to obtain a detection report of the soft LED light bars, which comprises the following steps:
s301, collecting static temperature data of the LED soft light bar in a static state and working temperature data of the LED soft light bar in a working state through a pyroelectric detection system every preset time interval.
In this embodiment, the pyroelectric detection system includes a temperature sensor in addition to a pyroelectric sensor, a display, a signal processor, and a data collector, where the temperature sensor is used to detect a temperature value of the soft LED light bar. Specifically, every preset time interval, the temperature sensor is used for collecting the static temperature data of the LED soft light bar in a static state and the working temperature data of the LED soft light bar in a working state.
S302, generating a static temperature change trend of the LED soft light bar in a static state according to the static temperature data.
The static temperature data of the LED soft light bar in a static state, which is collected by the temperature sensor, is generated into a static temperature change trend through MATLAB.
S303, generating the working temperature change trend of the LED soft light bar in the working state according to the working temperature data.
Working temperature data of the LED soft light bar in a working state, which is collected by the temperature sensor, is generated into a working temperature change trend through MATLAB.
S304, generating a detection report of the LED soft light bar according to the static temperature change trend and the working temperature change trend.
The detection report of the LED soft light bar comprises a static temperature change line graph and an operating temperature change line graph.
According to the online detection method for the LED soft light bar, the detection report of the LED soft light bar is composed of the working temperature change trend of the LED soft light bar in the working state and the temperature change trend of the LED soft light bar in the static state, and the test accuracy of the LED soft light bar is effectively improved by testing the temperature change trend of the LED soft light bar in different detection states.
The LED soft light bar may be subjected to a durability test before the detection result of the LED soft light bar is generated in step S106 of the embodiment shown in fig. 2. The embodiment shown in fig. 4 is specifically described in detail.
Referring to fig. 4, before generating the detection result of the LED soft light bar, the method further includes the following steps:
s401, adjusting the working temperature of the LED soft light bar to a preset target temperature through a pyroelectric detection system.
In this embodiment, the pyroelectric detection system includes a pyroelectric sensor, a display, a signal processor, a data collector, and a temperature sensor, and further includes a temperature controller, where the temperature controller adjusts the working temperature of the soft LED light bar to a target temperature by adjusting the power supply voltage and current of the soft LED light bar.
S402, detecting working data of the LED soft light bar in real time through a preset power supply detection system, and recording duration time of the LED soft light bar in a target temperature when the working data are in a preset working data range.
The power supply detection system comprises a power supply sensor, a display, a signal processor, a data acquisition unit and other devices and is used for detecting and monitoring working data of the LED soft light bar, wherein the power supply sensor is used for detecting the voltage of the LED soft light bar; the display is used for displaying the voltage of the LED soft light bar; the signal processor is used for converting the electric signals acquired from the pyroelectric sensor into signals readable by the display; the data collector is used for recording and storing the voltage acquired from the power supply sensor. The working data refer to the voltage of the LED soft light bar.
The working data range is preset for a person, and the duration time of the LED soft light bar in the target temperature is recorded through the time recorder under the condition that the working data of the LED soft light bar is located in the working data range. A time recorder refers to a device for recording time.
S403, generating a durability evaluation report of the LED soft light bar.
The durability evaluation report includes the operation data of the LED soft light bar and the duration of the LED soft light bar in the target temperature is recorded by the time recorder under the condition that the operation data of the LED soft light bar is located in the operation data range.
According to the online detection method for the LED soft light bar, firstly, the working temperature of the LED soft light bar is adjusted to the target temperature, and the duration of the LED soft light bar in the target temperature is detected, so that the durability of the LED soft light bar at different temperatures is tested, and the testing accuracy of the LED soft light bar is further improved.
After step S403 of the embodiment shown in fig. 4, the expected lifetime of the LED soft light bar may be obtained by the durability evaluation report. The embodiment shown in fig. 5 is specifically described in detail.
Referring to fig. 5, after generating a durability evaluation report of the LED soft light bar, the method includes the steps of:
s501, working environment data of the LED soft light bar are obtained.
The working environment data refer to the data of the external environment where the LED soft light bar is located, and in the embodiment, the working environment data are humidity data. Specifically, the working environment data is acquired by a humidity sensor.
S502, obtaining service life data of the LED soft light bar at a target temperature according to the durability evaluation report.
The durability evaluation report includes the operation data of the LED soft light bar and the duration of the LED soft light bar in the target temperature, the life data of the LED soft light bar at the target temperature referring to the duration, under the condition that the operation data of the LED soft light bar is located in the operation data range, by the time recorder.
S503, calculating the reliability of the LED soft light bar according to the working environment data and the service life data.
The reliability of the soft LED light bar refers to the time that the soft LED light bar can work normally, and in this embodiment, the duration of the soft LED light bar at the target temperature and the environmental humidity where the soft LED light bar is located are known, and the normal working time of the soft LED light bar can be calculated through Reliability Calculator for LEDs software, which can calculate the time of the soft LED light bar working normally according to the working environment data and the life data.
S504, according to the reliability and the working environment data, calculating to obtain the expected service life of the LED soft light bar.
In specific implementation, a standard environment index of the soft LED light bar can be set, for example, the standard environment index of the soft LED light bar is 42% rh, the standard environment index is used as an intermediate environment grade, and the environment grade is reduced by 1 when the humidity of 2% rh is increased; the environmental rating is increased by 1 for each reduction in humidity of 2% rh. For example, the environmental rating is classified as 1 to 100, the intermediate environmental rating is 50, and if the environmental rating where the LED soft light bar is located is 40 and the reliability is 90, the expected lifetime=40×90=3600 h. The environmental level can be set according to the specific specification and model of the LED soft light bar.
According to the on-line detection method for the LED soft light bar, firstly, the service life data of the LED soft light bar is obtained according to the durability evaluation report, then the reliability of the LED soft light bar is obtained through calculation through the service life data and the working environment data, and finally, the expected service life of the LED soft light bar is obtained through calculation according to the reliability and the working environment data, so that the expected service lives of the LED soft light bar under different working environments can be conveniently obtained, the LED soft light bar can be effectively and comprehensively tested, and the accuracy of the LED soft light bar test is further improved.
In step S503 of the embodiment shown in fig. 5, the reliability of the LED soft light bar is calculated by the environmental level and the lifetime data corresponding to the working environment data. The embodiment shown in fig. 6 is specifically described in detail.
Referring to fig. 6, according to the working environment data and the life data, the reliability of the LED soft light bar is calculated, which includes the following steps:
s601, matching working environment data based on a preset environment database to obtain an environment grade corresponding to the working environment data.
The environment database comprises environment grades corresponding to the working environment data and the working environment data, wherein the environment grades are used for representing the advantages and disadvantages of the environments of the LED soft light bars, namely, the higher the environment grade is, the more suitable the environments of the LED soft light bars are.
S602, taking the product of the environmental grade and the service life data as the reliability of the LED soft light bar.
For example, if the environmental rating is 2 and the lifetime data is 30, the reliability of the LED soft light bar is 60.
According to the on-line detection method for the LED soft light bar, the reliability is calculated by the environment grade and service life data, and the accuracy of calculating the reliability of the LED soft light bar is effectively improved.
In step S504 of the embodiment shown in fig. 5, the expected lifetime of the soft LED light bar is calculated from the normal lifetime data and the reliability corresponding to the operating environment data. The embodiment shown in fig. 7 is specifically described.
Referring to fig. 7, according to the reliability and the working environment data, the expected life of the LED soft light bar is calculated, which comprises the following steps:
s701, acquiring normal service life data matched with working environment data in a preset historical service life database.
The historical service life database stores normal service life data of normal operation of the LED soft light bar used by different users in different working environments, namely the historical service life database records actual service life data of the LED soft light bar in actual use.
S702, multiplying the reliability by the normal service life data to obtain the expected service life of the LED soft light bar.
For example, if the reliability is 60 and the normal service life data is 1000h, the expected life of the soft LED light bar=60×1000h=60000 h.
According to the on-line detection method for the LED soft light bar, the expected service life of the LED soft light bar is calculated by reliability and normal service life data, and accuracy of calculating the expected service life of the LED soft light bar is effectively improved.
The embodiment of the application also discloses an intelligent terminal, which comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein when the processor executes the computer program, the online detection method for the LED soft light bar in the embodiment is adopted.
The intelligent terminal may adopt a computer device such as a desktop computer, a notebook computer or a cloud server, and the intelligent terminal includes, but is not limited to, a processor and a memory, for example, the intelligent terminal may further include an input/output device, a network access device, a bus, and the like.
The processor may be a Central Processing Unit (CPU), or of course, according to actual use, other general purpose processors, digital Signal Processors (DSP), application Specific Integrated Circuits (ASIC), ready-made programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc., and the general purpose processor may be a microprocessor or any conventional processor, etc., which is not limited in this application.
The memory may be an internal storage unit of the intelligent terminal, for example, a hard disk or a memory of the intelligent terminal, or may be an external storage device of the intelligent terminal, for example, a plug-in hard disk, a Smart Memory Card (SMC), a secure digital card (SD) or a flash memory card (FC) provided on the intelligent terminal, or the like, and may be a combination of an internal storage unit of the intelligent terminal and an external storage device, where the memory is used to store a computer program and other programs and data required by the intelligent terminal, and the memory may be used to temporarily store data that has been output or is to be output, which is not limited in this application.
The on-line detection method for the LED soft light bar in the embodiment is stored in the memory of the intelligent terminal through the intelligent terminal, and is loaded and executed on the processor of the intelligent terminal, so that the on-line detection method for the LED soft light bar is convenient to use.
The embodiment of the application also discloses a computer readable storage medium, and the computer readable storage medium stores a computer program, wherein the computer program is executed by a processor, and the online detection method for the LED soft light bar in the embodiment is adopted.
The computer program may be stored in a computer readable medium, where the computer program includes computer program code, where the computer program code may be in a source code form, an object code form, an executable file form, or some middleware form, etc., and the computer readable medium includes any entity or device capable of carrying the computer program code, a recording medium, a usb disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a Random Access Memory (RAM), an electrical carrier signal, a telecommunication signal, a software distribution medium, etc., where the computer readable medium includes, but is not limited to, the above components.
The on-line detection method for the LED soft light bar in the embodiment is stored in the computer readable storage medium through the computer readable storage medium, and is loaded and executed on a processor, so that the storage and the application of the method are convenient.
The foregoing are all preferred embodiments of the present application, and are not intended to limit the scope of the present application in any way, therefore: all equivalent changes in structure, shape and principle of this application should be covered in the protection scope of this application.

Claims (9)

1. An on-line detection method for an LED soft light bar is characterized by comprising the following steps:
obtaining a current detection result of an LED soft light bar according to a preset current measurement system, and obtaining a light bar state of the LED soft light bar according to the current detection result; the lamp status includes steady state and unsteady state;
if the light bar state of the LED soft light bar is the stable state, increasing the test current passing through the LED soft light bar to a preset target current through the current measurement system, and acquiring a temperature change value of the LED soft light bar;
judging whether the temperature change value is in a preset temperature change range or not;
if the temperature is within the temperature variation range, detecting the lamp strip power of the LED soft lamp strip in real time through a power meter;
judging whether the power of the lamp strip is stable or not;
and if so, generating a detection result of the LED soft light bar, and finishing the detection of the LED soft light bar.
2. The on-line detection method for LED soft light bars according to claim 1, further comprising, prior to said obtaining the temperature variation value of the LED soft light bars:
analyzing the LED soft light bars in different detection states through a preset pyroelectric detection system to obtain a detection report of the LED soft light bars; the detection state comprises a static state and a working state;
obtaining temperature change conditions of the LED soft light bar under different detection states according to the detection report;
judging whether the temperature change condition in one detection state is abnormal or not;
if yes, stopping detection, and judging the LED soft light bar as a flaw soft light bar;
and if not, executing the step of acquiring the temperature change value of the LED soft light bar.
3. The on-line detection method for soft LED light bars according to claim 2, wherein the analyzing the soft LED light bars in different detection states by a preset pyroelectric detection system to obtain a detection report of the soft LED light bars comprises:
acquiring static temperature data of the LED soft light bar in the static state and working temperature data of the LED soft light bar in the working state by the pyroelectric detection system at intervals of preset time intervals;
generating a static temperature change trend of the LED soft light bar in the static state according to the static temperature data;
generating a working temperature change trend of the LED soft light bar in the working state according to the working temperature data;
and generating a detection report of the LED soft light bar according to the static temperature change trend and the working temperature change trend.
4. The method for on-line detection of LED soft light bars according to claim 2, further comprising, prior to said generating the detection result of the LED soft light bars:
the working temperature of the LED soft light bar is regulated to a preset target temperature through the pyroelectric detection system;
detecting working data of the LED soft light bar in real time through a preset power supply detection system, and recording duration time of the LED soft light bar in the target temperature when the working data are in a preset working data range;
and generating a durability evaluation report of the LED soft light bar.
5. The on-line detection method for LED soft light bars according to claim 4, wherein after said generating a durability assessment report for said LED soft light bars, comprising:
acquiring working environment data of the LED soft light bar;
obtaining life data of the LED soft light bar at the target temperature according to the durability evaluation report;
according to the working environment data and the service life data, calculating the reliability of the LED soft light bar;
and calculating the expected service life of the LED soft light bar according to the reliability and the working environment data.
6. The method for online detection of LED soft light bars according to claim 5, wherein the calculating the reliability of the LED soft light bars according to the working environment data and the lifetime data comprises:
matching the working environment data based on a preset environment database to obtain an environment grade corresponding to the working environment data;
and taking the product of the environment grade and the service life data as the reliability of the LED soft light bar.
7. The method for online detection of LED soft light bars according to claim 5, wherein the calculating the expected lifetime of the LED soft light bars according to the reliability and the operating environment data comprises:
acquiring normal service life data matched with the working environment data from a preset historical service life database;
multiplying the reliability by the normal service life data to obtain the expected service life of the LED soft light bar.
8. A smart terminal comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, characterized in that the method according to any one of claims 1 to 7 is used when the computer program is loaded and executed by the processor.
9. A computer readable storage medium having a computer program stored therein, characterized in that the method of any of claims 1 to 7 is employed when the computer program is loaded and executed by a processor.
CN202310239777.2A 2023-03-06 2023-03-06 Online detection method for LED soft light bar, intelligent terminal and storage medium Pending CN116430271A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310239777.2A CN116430271A (en) 2023-03-06 2023-03-06 Online detection method for LED soft light bar, intelligent terminal and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310239777.2A CN116430271A (en) 2023-03-06 2023-03-06 Online detection method for LED soft light bar, intelligent terminal and storage medium

Publications (1)

Publication Number Publication Date
CN116430271A true CN116430271A (en) 2023-07-14

Family

ID=87082397

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310239777.2A Pending CN116430271A (en) 2023-03-06 2023-03-06 Online detection method for LED soft light bar, intelligent terminal and storage medium

Country Status (1)

Country Link
CN (1) CN116430271A (en)

Similar Documents

Publication Publication Date Title
US10852357B2 (en) System and method for UPS battery monitoring and data analysis
CN114184229A (en) Switch cabinet operation environment monitoring system
CN113783272B (en) Safety control method based on super capacitor monitoring management system
CN116879662A (en) Transformer fault detection method based on data analysis
CN112684401B (en) Method and system for processing operation error data of electric energy meter in light-load station area
CN112418687B (en) User electricity utilization abnormity identification method and device based on electricity utilization characteristics and storage medium
CN116399402B (en) Fault early warning system of wireless sensor for ecological environment monitoring
CN115015623B (en) Mining equipment operation safety evaluation system based on big data
CN111666273B (en) Meter reading system data validity analysis method and device
CN117314397A (en) Safety inspection method based on bridge construction, electronic equipment and storage medium
CN116430271A (en) Online detection method for LED soft light bar, intelligent terminal and storage medium
WO2023157373A1 (en) Battery management device and battery management program
CN110007174B (en) Power management and control detection method for data center
CN116067671A (en) Method, system and medium for testing vehicle paint quality
CN114740419A (en) Method, device, equipment and medium for analyzing error of district ammeter based on three-dimensional graph
CN113655399B (en) Intelligent perception terminal battery power consumption life detection method and system
CN115542128A (en) Real-time power consumption test evaluation device and evaluation method for digital integrated circuit
JP6024510B2 (en) Energy consumption analysis apparatus, energy consumption analysis method, and computer program
CN116878728B (en) Pressure sensor fault detection analysis processing system
CN111077453A (en) Battery electric quantity detection system and method
CN113567004B (en) Method and system for predicting temperature by double probes
CN117890214B (en) Aluminum template quality inspection detection method based on machine vision
CN112762976B (en) Automatic method and device for comprehensive test of BMC (baseboard management controller) sensor
CN114563111B (en) Method, system, device and storage medium for evaluating health degree of air temperature observation device
CN109425773A (en) A kind of current monitoring circuit, method and power supply

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination