An online detection method, intelligent terminal and storage medium for an LED soft light bar

Abstract

The application relates to an online detection method, an intelligent terminal and a storage medium for an LED soft light bar, and belongs to the technical field of testing. 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 light bar state comprises a stable state and an unstable state; if the light bar state of the LED soft light bar is the stable state, a test current passing through the LED soft light bar is increased to a preset target current through the current measurement system, and a temperature change value of the LED soft light bar is obtained; whether the temperature change value is within a preset temperature change range is judged; if the temperature change value is within the temperature change range, a light bar power of the LED soft light bar is detected in real time through a power meter; whether the light bar power is stable is judged; if the light bar power is stable, a detection result of the LED soft light bar is generated, and the detection of the LED soft light bar is completed. The application has the effect of effectively improving the test accuracy of the LED soft light bar.

Description

TECHNICAL FIELD

[0001] The present 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

[0002] The LED soft light bar is widely used as a lighting lamp for background lighting of walls, staircases, roofs or other spaces. The LED light bar is composed of LEDs assembled on a flexible circuit board or a PCB hard board. When the LED soft light bar is shipped, a tester tests the brightness, color and temperature of the LEDs to determine whether the LED soft light bar meets the shipping requirements.

[0003] In the prior art, when the LED soft light bar is shipped, the tester first connects the LED soft light bar to a power supply and uses a power meter to detect the power of the LED soft light bar. If the power of the LED soft light bar is the specified power, the LED soft light bar is shipped.

[0004] For the prior art described above, the applicant believes that the power of the soft light bar is constant when it is shipped, i.e. only the power of the LED soft light bar under the power supply voltage is measured, and the performance of the LED soft light bar under other conditions is not tested, resulting in low testing accuracy of the LED soft light bar. SUMMARY

[0005] In order to effectively improve the testing accuracy of the LED soft light bar, the present application provides an online detection method for an LED soft light bar, an intelligent terminal and a storage medium.

[0006] In a first aspect, the present application provides an online detection method for an LED soft light bar, which adopts the following technical solution:

[0007] An online detection method for an LED soft light bar, comprising:

[0008] According to a preset current measurement system, a current detection result of the LED soft light bar is obtained, and a light bar state of the LED soft light bar is obtained according to the current detection result; the light bar state includes a stable state and an unstable state;

[0009] If the light bar state of the LED soft light bar is the stable state, the test current passing through the LED soft light bar is increased to a preset target current through the current measurement system, and a temperature change value of the LED soft light bar is obtained;

[0010] It is determined whether the temperature change value is within a preset temperature change range;

[0011] If it is within the temperature change range, the light bar power of the LED soft light bar is detected in real time by a power meter.

[0012] determining whether the strip power is stable;

[0013] if the strip power is stable, generating a detection result of the LED soft strip, and completing the detection of the LED soft strip.

[0014] By adopting the technical scheme, firstly, the current of the LED soft strip is detected, and when the strip state of the LED soft strip is in a stable state, the temperature change of the LED soft strip is detected, and when the temperature change value is within a temperature change range, the strip power of the LED soft strip is detected, and when the strip power is stable, the detection of the LED soft strip is completed. The power of the LED soft strip is not only detected under the condition of the power supply voltage, so that the performance of the LED soft strip is detected in multiple dimensions, and the test accuracy of the LED soft strip is effectively improved.

[0015] Optionally, before the temperature change value of the LED soft strip is acquired, the method further includes:

[0016] the LED soft strip in different detection states is analyzed by a preset pyroelectric detection system to obtain a detection report of the LED soft strip; the detection states include a static state and a working state;

[0017] according to the detection report, temperature change conditions of the LED soft strip in different detection states are obtained;

[0018] it is determined whether the temperature change condition in one detection state is abnormal;

[0019] if the temperature change condition is abnormal, the detection is terminated, and the LED soft strip is determined as a defective soft strip;

[0020] if the temperature change condition is not abnormal, the step of acquiring the temperature change value of the LED soft strip is performed.

[0021] By adopting the technical scheme, the detection of the temperature change condition of the LED soft strip is increased, and when the temperature change condition of the LED soft strip is normal, the step of acquiring the temperature change value of the LED soft strip is performed. Whether the temperature change value of the soft strip is acquired is determined by the temperature change condition of the LED soft strip, and the test accuracy of the LED soft strip is further effectively improved.

[0022] Optionally, the analysis of the LED soft strip in different detection states by the preset pyroelectric detection system to obtain the detection report of the LED soft strip includes:

[0023] by the pyroelectric detection system, the static temperature data of the LED soft strip in the static state and the working temperature data of the LED soft strip in the working state are collected every preset time interval;

[0024] generating a static temperature variation trend of the LED soft light bar in the static state according to the static temperature data;

[0025] generating a working temperature variation trend of the LED soft light bar in the working state according to the working temperature data;

[0026] generating a detection report of the LED soft light bar according to the static temperature variation trend and the working temperature variation trend.

[0027] By adopting the technical solution, the detection report of the LED soft light bar is composed of the working temperature variation trend of the LED soft light bar in the working state and the temperature variation 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 variation trends of the LED soft light bar in different detection states.

[0028] Optionally, before the generating of the detection result of the LED soft light bar, the method further comprises:

[0029] adjusting the working temperature of the LED soft light bar to a preset target temperature through the pyroelectric detection system;

[0030] detecting the working data of the LED soft light bar in real time through a preset power supply detection system, and recording the duration of the LED soft light bar in the target temperature when the working data is in a preset working data range;

[0031] generating a durability evaluation report of the LED soft light bar.

[0032] By adopting the technical solution, the working temperature of the LED soft light bar is first adjusted to the target temperature, and the duration of the LED soft light bar in the target temperature is detected, which is beneficial to test the durability of the LED soft light bar at different temperatures, thereby further improving the test accuracy of the LED soft light bar.

[0033] Optionally, after the generating of the durability evaluation report of the LED soft light bar, the method further comprises:

[0034] obtaining working environment data of the LED soft light bar;

[0035] obtaining life data of the LED soft light bar at the target temperature according to the durability evaluation report;

[0036] calculating a reliability of the LED soft light bar according to the working environment data and the life data;

[0037] According to the reliability and the working environment data, a predicted service life of the LED soft light bar is calculated.

[0038] By adopting the technical scheme, first, 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 calculated through the service life data and the working environment data, and finally the predicted service life of the LED soft light bar is calculated according to the reliability and the working environment data, so that the predicted service life of the LED soft light bar under different working environments is obtained, the LED soft light bar is effectively and comprehensively tested, and the accuracy of the LED soft light bar test is further improved.

[0039] Optionally, the calculating the reliability of the LED soft light bar according to the working environment data and the service life data comprises:

[0040] matching the working environment data based on a preset environment database to obtain an environment grade corresponding to the working environment data;

[0041] multiplying the environment grade and the service life data to obtain the reliability of the LED soft light bar.

[0042] By adopting the technical scheme, the reliability is calculated from the environment grade and the service life data, and the accuracy of the calculation of the reliability of the LED soft light bar is effectively improved.

[0043] Optionally, the calculating the predicted service life of the LED soft light bar according to the reliability and the working environment data comprises:

[0044] acquiring normal service life data matched with the working environment data in a preset historical service life database;

[0045] multiplying the reliability and the normal service life data to obtain the predicted service life of the LED soft light bar.

[0046] By adopting the technical scheme, the predicted service life of the LED soft light bar is calculated from the reliability and the normal service life data, and the accuracy of the calculation of the predicted service life of the LED soft light bar is effectively improved.

[0047] In the second aspect, the intelligent terminal adopts the technical scheme as follows:

[0048] An intelligent terminal comprises a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor loads and executes the computer program, the online detection method for the LED soft light bar is adopted.

[0049] By adopting the technical scheme, the computer program of the online detection method for the LED soft light bar is generated, stored in the memory, loaded by the processor and executed, so that the intelligent terminal is made according to the memory and the processor, and use is facilitated.

[0050] In a third aspect, the computer readable storage medium provided by the application adopts the technical scheme as follows:

[0051] The computer readable storage medium stores the computer program, and the computer program is loaded by the processor and executed, and the online detection method for the LED soft light bar is adopted.

[0052] By adopting the technical scheme, the computer program of the online detection method for the LED soft light bar is generated, stored in the computer readable storage medium, loaded by the processor and executed, and the computer readable storage medium facilitates the readability and storage of the computer program.

[0053] In summary, the application has at least one of the following beneficial technical effects:

[0054] 1. First, the current of the LED soft light bar is detected, and when the light bar state of the LED soft light bar is in a stable state, the temperature change of the LED soft light bar is detected, and when the temperature change value is within the 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 the power of the LED soft light bar is not detected under the condition of the power voltage, so that the performance of the LED soft light bar is detected in multiple dimensions, and the test accuracy of the LED soft light bar is effectively improved.

[0055] 2. First, the working temperature of the LED soft light bar is adjusted to the target temperature, and the duration of the LED soft light bar at the target temperature is detected, which is beneficial to test the durability of the LED soft light bar at different temperatures, and further improves the test accuracy of the LED soft light bar.

[0056] 3. The detection of the temperature change of the LED soft light bar is increased, and the step of obtaining the temperature change value of the LED soft light bar is executed when the temperature change of the LED soft light bar is normal, whether the temperature change value of the soft light bar is obtained is determined by the temperature change of the LED soft light bar, and the test accuracy of the LED soft light bar is further effectively improved. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 is a flowchart of one of the embodiments of the online detection method for the LED soft light bar.

[0058] Figure 2is a flowchart of one embodiment of a method for online detection of an LED soft light bar.

[0059] Figure 3 is a flowchart of one embodiment of a method for online detection of an LED soft light bar.

[0060] Figure 4 is a flowchart of one embodiment of a method for online detection of an LED soft light bar.

[0061] Figure 5 is a flowchart of one embodiment of a method for online detection of an LED soft light bar.

[0062] Figure 6 is a flowchart of one embodiment of a method for online detection of an LED soft light bar.

[0063] Figure 7 is a flowchart of one embodiment of a method for online detection of an LED soft light bar. DETAILED DESCRIPTION

[0064] The following will be described in detail with reference to the accompanying drawings. Figures 1 to 7 The application will be further described in detail.

[0065] The embodiments of the present application disclose a method for online detection of an LED soft light bar.

[0066] Referring to Figure 1 A method for online detection of an LED soft light bar comprises the following steps:

[0067] S101, according to a preset current measurement system, obtaining a current detection result of the LED soft light bar, and obtaining a light bar state of the LED soft light bar according to the current detection result; the light bar state comprises a stable state and an unstable state.

[0068] The current detection system refers to a system for measuring and detecting the current of the LED soft light bar, and is used for current testing of the LED soft light bar. The current detection system comprises a power supply, a current sensor, a signal processor, a data collector, 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 obtained from the current sensor, and converting the current data into a signal that can be recognized and displayed by the display; and the data collector is used for recording and storing the current data obtained from the current sensor.

[0069] The current detection result refers to an actual current value of the LED soft light bar, and the light bar state is used to indicate a current change of the LED soft light bar at the n+1 moment relative to the n moment, where n is a positive integer. If the light bar state is a stable state, it indicates that the current change of the LED soft light bar at the n+1 moment relative to the n moment is within a preset change range. If the light bar state is an unstable state, it indicates that the current change of the LED soft light bar at the n+1 moment relative to the n moment is beyond the preset current change range. The current change range can be artificially set according to the specification parameters of the LED soft light bar.

[0070] In S102, if the light bar state of the LED soft light bar is a stable state, the test current passing through the LED soft light bar is increased to a preset target current by the current measurement system, and a temperature change value of the LED soft light bar is obtained.

[0071] If the light bar state of the LED soft light bar is a stable state, it indicates that the LED soft light bar passes the current test. In this embodiment, the power supply in the current measurement system can be used to increase the current passing through the LED soft light bar, that is, to increase the test current of the LED soft light bar to the target current, so as to test the LED soft light bar. The temperature change value refers to the difference between the first temperature when the test current passes through the LED soft light bar and the second temperature when the target current passes through the LED soft light bar, that is, temperature change value = |second temperature-first temperature|. The temperature of the LED soft light bar is obtained by a temperature sensor.

[0072] In S103, it is determined whether the temperature change value is within a preset temperature change range.

[0073] For example, if the temperature change range is [3, 5], if the temperature change value A is 4, the temperature change value is within the temperature change range at this time, and if the temperature change value A is 6, the temperature change value is not within the temperature change range at this time.

[0074] In S104, if the temperature change value is within the temperature change range, the light bar power of the LED soft light bar is detected in real time by a power meter.

[0075] If the temperature change value is within the temperature change range, it indicates that the LED soft light bar passes the temperature test when the current changes. At this time, the light bar power of the LED soft light bar is detected in real time by the power meter, and the power meter is used to measure and display the power of the LED soft light bar.

[0076] If the temperature change value is not within the temperature change range, the detection of the LED soft light bar is terminated, and the LED soft light bar is determined to be a defective soft light bar.

[0077] In S105, it is determined whether the light bar power is stable.

[0078] If the change of the power of the LED soft light bar at the n+1 moment and the power at the n moment does not exceed the preset power change range, it is determined that the light bar power is stable; otherwise, if the change of the power of the LED soft light bar at the n+1 moment and the power at the n moment exceeds the preset power change range, it is determined that the light bar power is unstable.

[0079] S106, if stable, generating the detection result of the LED soft light bar, and completing the detection of the LED soft light bar.

[0080] If the light bar power is stable, it indicates that the LED soft light bar passes the power test, at this time, the detection result of the LED soft light bar is generated, and the detection result includes the light bar state, the temperature change value, the light bar power and the light bar power stability of the LED soft light bar and other detection indexes. Generating the detection result indicates that the detection of the LED soft light bar is completed.

[0081] If the light bar power is unstable, the detection of the LED soft light bar is terminated, and the LED soft light bar is determined to be a defective soft light bar.

[0082] The implementation principle of the embodiment is that: first, the current of the LED soft light bar is detected, and when the light bar state of the LED soft light bar is in a stable state, the temperature change of the LED soft light bar is detected, and when the temperature change value is within the 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. It is not only to detect the power of the LED soft light bar under the condition of the power voltage, so as to detect the performance of the LED soft light bar in multiple dimensions, and thus effectively improve the test accuracy of the LED soft light bar.

[0083] In the step S102 of the embodiment shown in the figure, the temperature change value of the LED soft light bar is obtained before the temperature change of the LED soft light bar is judged. Figure 1 The temperature change of the LED soft light bar is judged first before the temperature change value of the LED soft light bar is obtained in the step S102 of the embodiment shown in the figure. The specific process is described in detail through the embodiment shown in the figure. Figure 2

[0084] Referring to the embodiment shown in the figure, Figure 2 Before the temperature change value of the LED soft light bar is obtained, the following steps are further included:

[0085] S201, analyzing the LED soft light bar in different detection states through a preset pyroelectric detection system to obtain a detection report of the LED soft light bar; the detection states include a static state and a working state.

[0086] ​The pyroelectric detection system refers to a system for detecting temperature change of the LED soft light bar by using pyroelectric technology, mainly including a pyroelectric sensor, a display, a signal processor, a data collector and the like, wherein the pyroelectric sensor is a sensor using the pyroelectric effect of pyroelectric ceramic as the infrared detection principle, for detecting temperature change of the LED soft light bar; the display is used for displaying temperature change of the LED soft light bar, the signal processor is used for converting the electrical signal obtained from the pyroelectric sensor into a signal readable by the display; the data collector is used for recording and storing the temperature change signal obtained from the pyroelectric sensor.

[0087] The detection report refers to a report obtained by analyzing the LED soft light bar by using the pyroelectric detection system, specifically, the pyroelectric sensor senses temperature change of the LED soft light bar and outputs an electrical signal in the form of voltage or current, taking the electrical signal as the temperature change signal, and generating the detection report according to the temperature change signal.

[0088] The static state refers to the state of the LED soft light bar after the power is turned off, and the working state refers to the state of the LED soft light bar after the power is turned on.

[0089] S202, obtaining temperature change conditions of the LED soft light bar in different detection states according to the detection report.

[0090] The temperature change condition refers to temperature change of the LED soft light bar in the detection state. For example, the temperature change condition is two kinds, the first kind is that when the LED soft light bar is in the static state, the temperature change of the LED soft light bar is recorded at the moment when the power is turned off; the second kind is that when the soft light bar is in the working state, the temperature change of the LED soft light bar is recorded at the moment when the power is turned on.

[0091] S203, judging whether the temperature change condition in one detection state is abnormal.

[0092] If the voltage signal or the current signal output by the pyroelectric sensor is greater than the signal threshold set by human, it is determined that the temperature change condition of the LED soft light bar is abnormal. Since the temperature change condition of the LED soft light bar is divided into two kinds according to the detection state, i.e. one kind is the temperature change condition when the LED soft light bar is in the static state, and one kind is the temperature change condition when the LED soft light bar is in the working state, the temperature change conditions of the LED soft light bar in different detection states are detected respectively.

[0093] S204, if there is, terminating the detection and determining the LED soft light bar as a defective soft light bar.

[0094] If the temperature change in one of the two detection states is abnormal, the detection of the LED soft light bar is terminated, and the LED soft light bar is determined as a defective soft light bar for the staff to handle.

[0095] S205, if not, the step of obtaining the temperature change value of the LED soft light bar is performed.

[0096] If the temperature change in both detection states is not abnormal, the temperature change value of the LED soft light bar is obtained at this time.

[0097] The online detection method for the LED soft light bar provided by the embodiment increases the detection of the temperature change of the LED soft light bar, and performs the step of obtaining the temperature change value of the LED soft light bar when the temperature change of the LED soft light bar is normal. By determining whether to obtain the temperature change value of the soft light bar according to the temperature change of the LED soft light bar, the test accuracy of the LED soft light bar is further improved effectively.

[0098] In Figure 2 In step S201 of the embodiment shown, the pyroelectric detection system can collect the static temperature data of the LED soft light bar in the static state and the working temperature data in the working state, and then obtain a detection report. Specifically, the pyroelectric detection system is used to collect the static temperature data of the LED soft light bar in the static state and the working temperature data in the working state. Figure 3 The embodiment shown is described in detail.

[0099] Referring to Figure 3 , the LED soft light bar in different detection states is analyzed by the preset pyroelectric detection system to obtain a detection report of the LED soft light bar, including the following steps:

[0100] S301, by the pyroelectric detection system, the static temperature data of the LED soft light bar in the static state and the working temperature data in the working state are collected every preset time interval.

[0101] In this embodiment, the pyroelectric detection system includes a pyroelectric sensor, a display, a signal processor, a data collector, and a temperature sensor for detecting the temperature value of the LED soft light bar. Specifically, the temperature sensor collects the static temperature data of the LED soft light bar in the static state and the working temperature data in the working state every preset time interval.

[0102] S302, according to the static temperature data, the static temperature change trend of the LED soft light bar in the static state is generated.

[0103] The static temperature data of the LED soft light bar in the static state collected by the temperature sensor is generated into a static temperature change trend by MATLAB, and in this embodiment, the static temperature change trend is a static temperature change broken line graph, the X-axis of the static temperature change broken line graph is time, and the Y-axis is the static temperature data at each time point.

[0104] S303, generating a working temperature change trend of the LED soft light bar in the working state according to the working temperature data.

[0105] The working temperature data of the LED soft light bar in the working state collected by the temperature sensor is generated into a working temperature change trend by MATLAB, and in this embodiment, the working temperature change trend is a working temperature change broken line graph, the X-axis of the working temperature change broken line graph is time, and the Y-axis is the working temperature data at each time point.

[0106] S304, generating a detection report of the LED soft light bar according to the static temperature change trend and the working temperature change trend.

[0107] The detection report of the LED soft light bar includes a static temperature change broken line graph and a working temperature change broken line graph.

[0108] The online detection method for the LED soft light bar provided by the embodiment comprises the steps of: collecting static temperature data of the LED soft light bar in a static state by a temperature sensor; collecting working temperature data of the LED soft light bar in a working state by the temperature sensor; 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.

[0109] In the step S106 of the embodiment shown in the figure, the detection result of the LED soft light bar is generated. Figure 2 The durability test of the LED soft light bar is performed before the detection result of the LED soft light bar is generated in the step S106 of the embodiment shown in the figure. Figure 4 The durability test of the LED soft light bar is performed before the detection result of the LED soft light bar is generated in the step S106 of the embodiment shown in the figure.

[0110] Referring to the embodiment shown in the figure, Figure 4 Before the detection result of the LED soft light bar is generated, the following steps are further included:

[0111] S401, adjusting the working temperature of the LED soft light bar to a preset target temperature by a pyroelectric detection system.

[0112] In this embodiment, the pyroelectric detection system further includes a temperature controller in addition to the pyroelectric sensor, the display, the signal processor, the data collector and the temperature sensor, and the temperature controller adjusts the working temperature of the LED soft light bar to the target temperature by adjusting the power voltage and current of the LED soft light bar.

[0113] S402, detecting the working data of the LED soft light bar in real time through a preset power detection system, and recording the duration of the LED soft light bar in the target temperature when the working data is in the preset working data range.

[0114] The power detection system includes a power sensor, a display, a signal processor, a data collector and the like, which are used for detecting and monitoring the working data of the LED soft light bar, wherein the power 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 electrical signal obtained from the pyroelectric sensor into a signal readable by the display; and the data collector is used for recording and storing the voltage obtained from the power sensor. The working data refers to the voltage of the LED soft light bar.

[0115] The working data range is artificially preset, and the duration of the LED soft light bar in the target temperature is recorded by a time recorder under the condition that the working data of the LED soft light bar is in the working data range. The time recorder refers to a device for recording time.

[0116] S403, generating a durability evaluation report of the LED soft light bar.

[0117] The durability evaluation report includes the working data of the LED soft light bar and the duration of the LED soft light bar in the target temperature recorded by the time recorder under the condition that the working data of the LED soft light bar is in the working data range.

[0118] The online detection method for the LED soft light bar provided by the embodiment is first to adjust the working temperature of the LED soft light bar to the target temperature, and to detect the duration of the LED soft light bar in the target temperature, which is beneficial to test the durability of the LED soft light bar at different temperatures, thereby further improving the test accuracy of the LED soft light bar.

[0119] In Figure 4 After the step S403 of the embodiment shown, the expected service life of the LED soft light bar can be obtained through the durability evaluation report. The expected service life of the LED soft light bar is specifically explained in detail through the durability evaluation report of the embodiment shown. Figure 5

[0120] Referring to Figure 5 After the durability evaluation report of the LED soft light bar is generated, the following steps are included:

[0121] S501, obtaining working environment data of the LED soft light bar.

[0122] The working environment data refers to the data of the external environment in which the LED soft light bar is located, and in this embodiment, the working environment data is humidity data. Specifically, the working environment data is obtained through a humidity sensor.

[0123] ​S502. Based on the durability assessment report, obtain the lifespan data of the LED flexible light strip at the target temperature.

[0124] The durability assessment report includes the operating data of the LED flexible light strip and the duration of the LED flexible light strip at the target temperature, recorded by a time recorder, under the condition that the operating data of the LED flexible light strip is within the operating data range. The lifespan data of the LED flexible light strip at the target temperature refers to the duration.

[0125] S503. Based on the working environment data and lifespan data, the reliability of the LED flexible light strip is calculated.

[0126] The reliability of LED flexible light strips refers to the time during which the LED flexible light strip can work normally. In this embodiment, the duration of the LED flexible light strip at the target temperature and the ambient humidity are known. The normal working time of the LED flexible light strip can be calculated using the Reliability Calculator for LEDs software. It can calculate the normal working time of the LED flexible light strip based on the working environment data and lifespan data.

[0127] S504. Based on reliability and operating environment data, the expected lifespan of the LED flexible light strip is calculated.

[0128] In practical implementation, standard environmental indicators can be set for LED flexible light strips. For example, the standard environmental indicator for LED flexible light strips is 42% RH humidity. This standard environmental indicator is used as the intermediate environmental level. For every 2% RH increase in humidity, the environmental level decreases by 1; for every 2% RH decrease in humidity, the environmental level increases by 1. For instance, if environmental levels are divided into 1 to 100, then the intermediate environmental level is 50. If the environmental level of the LED flexible light strip is 40 and the reliability is 90%, then the expected lifespan is 40 * 90 = 3600 hours. The environmental level can be set according to the specific specifications and model of the LED flexible light strip.

[0129] The online testing method for LED flexible light strips provided in this embodiment first obtains the lifespan data of the LED flexible light strip based on the durability assessment report, then calculates the reliability of the LED flexible light strip using the lifespan data and working environment data, and finally calculates the expected lifespan of the LED flexible light strip based on the reliability and working environment data. This facilitates obtaining the expected lifespan of the LED flexible light strip under different working environments, effectively and comprehensively testing the LED flexible light strip, and further improving the accuracy of LED flexible light strip testing.

[0130] exist Figure 5 In step S503 of the illustrated embodiment, the reliability of the LED flexible light strip is calculated using environmental level and lifespan data corresponding to the working environment data. Specifically, through... Figure 6 The embodiments shown will be described in detail.

[0131] Referring to Figure 6 , the reliability of the LED soft light bar is calculated according to the working environment data and the life data, including the following steps:

[0132] S601, matching the working environment data based on a preset environment database to obtain an environment grade corresponding to the working environment data.

[0133] The environment database includes the working environment data and the environment grade corresponding to the working environment data, and the environment grade is used to represent the pros and cons of the environment of the LED soft light bar, that is, the higher the environment grade, the more suitable the environment of the LED soft light bar.

[0134] S602, taking the product of the environment grade and the life data as the reliability of the LED soft light bar.

[0135] For example, if the environment grade is 2 and the life data is 30, the reliability of the LED soft light bar is 60.

[0136] The online detection method for the LED soft light bar provided in the embodiment can effectively improve the accuracy of the calculation of the reliability of the LED soft light bar.

[0137] In Figure 5 In step S504 of the embodiment shown, the expected life of the LED soft light bar is calculated from the normal life data corresponding to the working environment data and the reliability. Details are described in the embodiment shown in Figure 7 .

[0138] Referring to Figure 7 , the expected life of the LED soft light bar is calculated according to the reliability and the working environment data, including the following steps:

[0139] S701, obtaining normal use life data matched with the working environment data in a preset historical life database.

[0140] The historical life database stores normal use life data of the LED soft light bar in normal working of different users in different working environments, that is, the historical life database records actual life data of the LED soft light bar in actual use.

[0141] S702, multiplying the reliability and the normal use life data to obtain the expected life of the LED soft light bar.

[0142] For example, if the reliability is 60 and the normal use life data is 1000h, the expected life of the LED soft light bar = 60*1000h = 60000h.

[0143] The online detection method for the LED soft light bar provided by the embodiment can effectively improve the accuracy of the calculation of the expected service life of the LED soft light bar.

[0144] The embodiment of the present application further discloses an intelligent terminal, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor.

[0145] The intelligent terminal can be a computer device such as a desktop computer, a notebook computer or a cloud server, and the intelligent terminal comprises but is not limited to the processor and the memory, for example, the intelligent terminal can further comprise an input / output device, a network access device and a bus.

[0146] The processor can be a central processing unit (CPU), and of course, according to the actual use, other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), ready programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. can also be used, and the general-purpose processor can be a microprocessor or any conventional processor, etc. The present application does not make any limitation in this regard.

[0147] The memory can be an internal storage unit of the intelligent terminal, for example, a hard disk or a memory of the intelligent terminal, or 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 card (FC) equipped on the intelligent terminal, and the memory can also be a combination of the internal storage unit and the external storage device of the intelligent terminal. The memory is used to store the computer program and other programs and data required by the intelligent terminal, and can also be used to temporarily store the data that has been output or will be output. The present application does not make any limitation in this regard.

[0148] The online detection method for the LED soft light bar in the above embodiment is stored in the memory of the intelligent terminal and loaded and executed on the processor of the intelligent terminal, which is convenient to use.

[0149] The embodiment of the present application further discloses a computer readable storage medium, and the computer readable storage medium stores a computer program, wherein the computer program is executed by the processor to adopt the online detection method for the LED soft light bar in the above embodiment.

[0150] The computer program can be stored in a computer readable medium, the computer program includes computer program code, the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc., the computer readable medium includes any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read only memory (ROM), random access memory (RAM), electric carrier wave signal, telecommunication signal and software distribution medium, etc., it needs to be explained that the computer readable medium includes but is not limited to the above components.

[0151] The computer readable storage medium stores the online detection method for the LED soft light bar in the above embodiment in the computer readable storage medium, and is loaded and executed on the processor to facilitate the storage and application of the method.

[0152] The above are preferred embodiments of the present application, not limited to the protection scope of the present application, therefore: all equivalent changes made according to the structure, shape, principle of the present application should be covered in the protection scope of the present application.

Claims

1. An online detection method for LED soft light bar, characterized in that, The method comprises the following steps: According to the preset current measurement system, the current detection result of the LED soft light bar is obtained, and the light bar state of the LED soft light bar is obtained according to the current detection result; the light bar state includes a stable state and an unstable state; If the light bar state of the LED soft light bar is the stable state, the test current passing through the LED soft light bar is increased to a preset target current through the current measurement system, and the temperature change value of the LED soft light bar is obtained; Determine whether the temperature change value is within a preset temperature change range; If it is within the temperature change range, the light bar power of the LED soft light bar is detected in real time through a power meter; Determine whether the light bar power is stable; If it is stable, the detection result of the LED soft light bar is generated, and the detection of the LED soft light bar is completed; Before the temperature change value of the LED soft light bar is obtained, the method further comprises the following steps: The LED soft light bar in different detection states is analyzed through a preset pyroelectric detection system to obtain a detection report of the LED soft light bar; the detection states include a static state and a working state; According to the detection report, the temperature change of the LED soft light bar in different detection states is obtained; Determine whether the temperature change in one detection state is abnormal; If it is, terminate the detection and determine the LED soft light bar as a defective soft light bar; If not, execute the step of obtaining the temperature change value of the LED soft light bar; The method of analyzing the LED soft light bar in different detection states through the preset pyroelectric detection system to obtain the detection report of the LED soft light bar comprises the following steps: The pyroelectric detection system collects 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 every preset time interval; According to the static temperature data, the static temperature change trend of the LED soft light bar in the static state is generated; According to the working temperature data, the working temperature change trend of the LED soft light bar in the working state is generated; According to the static temperature change trend and the working temperature change trend, the detection report of the LED soft light bar is generated; Before the detection result of the LED soft light bar is generated, the method further comprises the following steps: The working temperature of the LED soft light bar is adjusted to a preset target temperature through the pyroelectric detection system; The working data of the LED soft light bar is detected in real time through a preset power supply detection system, and the duration of the LED soft light bar at the target temperature when the working data is within a preset working data range is recorded; A durability evaluation report of the LED soft light bar is generated.

2. The online detection method for LED soft light bar according to claim 1, characterized in that, After the durability evaluation report of the LED soft light bar is generated, the method comprises the following steps: Obtain the working environment data of the LED soft light bar; According to the durability evaluation report, the life data of the LED soft light bar at the target temperature is obtained; According to the working environment data and the life data, the reliability of the LED soft light bar is calculated. According to the reliability and the working environment data, a predicted service life of the LED soft light bar is calculated.

3. The online detection method for LED soft light bar according to claim 2, characterized in that, The reliability of the LED soft light bar is calculated according to the working environment data and the service life data, including: The working environment data is matched with a preset environment database to obtain an environment grade corresponding to the working environment data; A product of the environment grade and the service life data is taken as the reliability of the LED soft light bar.

4. The online detection method for LED soft light bar according to claim 2, characterized in that, The predicted service life of the LED soft light bar is calculated according to the reliability and the working environment data, including: In a preset historical service life database, normal service life data matched with the working environment data is obtained; The reliability is multiplied by the normal service life data to obtain the predicted service life of the LED soft light bar.

5. 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 processor loads and executes the computer program by using the method in any one of claims 1 to 4.

6. A computer-readable storage medium having stored therein a computer program, characterized in that, The computer program is loaded and executed by the processor by using the method in any one of claims 1 to 4.

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