CN117078684B - LED lamp visual detection method, system and storage medium - Google Patents
LED lamp visual detection method, system and storage medium Download PDFInfo
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- 238000001514 detection method Methods 0.000 title claims abstract description 94
- 230000000007 visual effect Effects 0.000 title claims abstract description 15
- 238000003860 storage Methods 0.000 title claims abstract description 8
- 230000008859 change Effects 0.000 claims abstract description 90
- 238000000034 method Methods 0.000 claims abstract description 18
- 238000003466 welding Methods 0.000 claims description 18
- 230000017525 heat dissipation Effects 0.000 claims description 15
- 230000000630 rising effect Effects 0.000 claims description 15
- 238000001931 thermography Methods 0.000 claims description 9
- 230000010365 information processing Effects 0.000 claims description 8
- 238000011179 visual inspection Methods 0.000 claims description 8
- 238000010586 diagram Methods 0.000 claims description 7
- 238000010438 heat treatment Methods 0.000 claims description 4
- 230000004044 response Effects 0.000 claims description 4
- 238000004590 computer program Methods 0.000 claims description 3
- 230000035484 reaction time Effects 0.000 claims description 3
- 238000007689 inspection Methods 0.000 claims 3
- 230000008569 process Effects 0.000 description 4
- 238000012986 modification Methods 0.000 description 3
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- 238000004519 manufacturing process Methods 0.000 description 2
- 208000003464 asthenopia Diseases 0.000 description 1
- 239000011324 bead Substances 0.000 description 1
- 239000003990 capacitor Substances 0.000 description 1
- 239000000969 carrier Substances 0.000 description 1
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- 238000005516 engineering process Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J1/00—Photometry, e.g. photographic exposure meter
- G01J1/42—Photometry, e.g. photographic exposure meter using electric radiation detectors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M11/00—Testing of optical apparatus; Testing structures by optical methods not otherwise provided for
- G01M11/02—Testing optical properties
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- 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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J1/00—Photometry, e.g. photographic exposure meter
- G01J1/42—Photometry, e.g. photographic exposure meter using electric radiation detectors
- G01J2001/4247—Photometry, e.g. photographic exposure meter using electric radiation detectors for testing lamps or other light sources
- G01J2001/4252—Photometry, e.g. photographic exposure meter using electric radiation detectors for testing lamps or other light sources for testing LED's
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
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- 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
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- 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
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Abstract
The invention discloses a visual detection method, a visual detection system and a storage medium for an LED lamp, belonging to the technical field of quality detection, wherein the method comprises the following steps: obtaining target detection images of the LED lamps to be detected in an unlit state and a lit state; based on a first target detection image in an unlit state, checking each component on the LED lamp to be detected, and comparing the components with a standard LED lamp to obtain a component deviation value; if the deviation value of the device is larger than the deviation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified, and executing the next step; based on a second target detection image in a lighting state, acquiring a brightness value and a temperature value of the LED lamp to be detected in unit time in real time, drawing a brightness-time change chart and a temperature-time change chart, and predicting a light attenuation value; if the light attenuation value is larger than the light attenuation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified.
Description
Technical Field
The invention relates to the technical field of quality detection, in particular to a visual detection method, a visual detection system and a visual detection storage medium for an LED lamp.
Background
In recent years, as one of important carriers of multimedia technology, an LED lamp plays an increasingly important role in work, life and entertainment of people, and is attracting attention. Since the LED has low operating voltage, impact resistance, vibration resistance and long service life, no other display mode can be compared with the LED display mode in a large display device.
The quality detection of the LED lamp is usually carried out manually, the detection mode is easily affected by visual fatigue of detection personnel to generate errors, and the detection precision is not high. In the detection process, detection in a plurality of directions is involved, on one hand, whether the LED lamp is in the production process or not is detected, and on the other hand, the change condition of the LED lamp light attenuation of the LED lamp in the actual use is detected. The detection actions are originally completed manually, detection omission easily occurs in detection, detection standards are fuzzy, and detection efficiency is low, so that the quality of products is greatly affected.
Therefore, how to provide a visual detection method, so that the detection efficiency is improved, the product quality stability is improved, the labor cost is saved, and the detection means is automated is a technical problem to be solved by the person skilled in the art.
Disclosure of Invention
Therefore, the invention provides a visual detection method, a visual detection system and a visual detection storage medium for an LED lamp, which are used for solving the problems that in the prior art, the detection precision is low and the detection efficiency is low due to manual detection, so that the quality of a product is affected.
In order to achieve the above object, the present invention provides the following technical solutions:
according to a first aspect of the present invention, there is provided a visual inspection method for an LED lamp, including:
step S1: obtaining target detection images of the LED lamps to be detected in an unlit state and a lit state;
step S2: based on a first target detection image in an unlit state, checking each component on the LED lamp to be detected, and comparing the components with a standard LED lamp to obtain a component deviation value of the LED lamp to be detected;
step S3: if the device deviation value of the LED lamp to be detected is larger than the deviation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified, and executing the next step;
step S4: based on a second target detection image in a lighting state, acquiring a brightness value and a temperature value of the LED lamp to be detected in unit time in real time, and drawing a brightness-time change chart and a temperature-time change chart;
step S5: obtaining a brightness change rate based on a brightness-time change chart, and obtaining a heating change rate and a heat dissipation change rate based on a temperature-time change chart;
step S6: predicting the light attenuation value of the LED lamp to be detected based on a brightness change rate, a temperature rise change rate, a heat dissipation change rate and a light attenuation prediction formula;
step S7: if the light attenuation value of the LED lamp to be detected is larger than the light attenuation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified.
Further, the step S2 specifically includes the following steps:
s201: dividing the first target detection image in the unlit state into different detection areas, selecting components on the LED lamp to be detected in the detection areas, and obtaining the gap distance of the welding gap of the components on the LED lamp to be detected；
S202: dividing a standard LED lamp image into different detection areas according to the step S201, selecting components on the standard LED lamp in the detection areas, and obtaining the gap distance of welding gaps of the components on the standard LED lamp；
S203: formula according to welding gap deviation valueAnd obtaining a welding gap deviation value theta.
Further, the second object detection image includes a luminaire image and an infrared thermal imaging map.
Further, in the step S4, the luminance value of the LED lamp to be detected in unit time is obtained in real time, and a luminance-time variation graph is drawn, which specifically includes:
acquiring a lamp image of the LED lamp to be detected in a lighting state in real time until the LED lamp to be detected is completely lighted, wherein the lamp image at least comprises an initial image and a final image;
acquiring the frame number of the interval image and the brightness value of each frame of the interval image according to the interval image between the initial image and the final image;
and obtaining the response time according to the frame number of the interval image, obtaining the brightness value of the unit time of the LED lamp to be detected according to the brightness value of each frame of the interval image, and drawing a brightness-time change chart.
Further, in the step S4, a temperature value of the LED lamp to be detected in unit time is obtained in real time, and a temperature-time change chart is drawn, which specifically includes:
and acquiring an infrared thermal imaging diagram of the LED lamp to be detected in unit time based on the LED lamp to be detected in the lighting state, acquiring a temperature value in unit time according to the infrared thermal imaging diagram, and drawing a temperature-time change diagram.
Further, the luminance-time variation graph includes a rising section and a stationary section, and the luminance variation rate is a luminance variation per unit time from the rising section to the stationary section.
Further, the temperature-time variation graph includes a rising section, a stationary section, and a falling section, the temperature increase variation rate is a temperature variation per unit time from the rising section to the stationary section, and the heat radiation variation rate is a temperature variation per unit time from the stationary section to the falling section.
Further, the light attenuation prediction formula is:
；
wherein,for the light attenuation value k of the LED lamp to be detected 1 The weight is preset for light attenuation corresponding to brightness change, t is the reaction time of the LED lamp to be detected when the LED lamp is completely on, and f 1 For the brightness change rate k of the LED lamp to be detected 2 Preset weight for light attenuation corresponding to temperature change, f 2 F is the temperature rise change rate of the LED lamp to be detected 3 Radiating for LED lamp to be detectedRate of change.
According to a second aspect of the present invention, there is provided an LED luminaire vision detection system for implementing the LED luminaire vision detection method described in any one of the above, comprising:
the image acquisition unit is used for acquiring target detection images of the LED lamps to be detected in the unlit state and the lit state;
the first image information processing unit is used for obtaining the device deviation value of the LED lamp to be detected based on the first target detection image in the unlit state;
the first judging unit is used for judging whether the quality of the LED lamp to be detected is qualified or not according to the device deviation value and the deviation threshold value;
the second image information processing unit is used for predicting the light attenuation value of the LED lamp to be detected based on a second target detection image in the lighting state;
and the second judging unit is used for judging whether the quality of the LED lamp to be detected is qualified or not according to the light attenuation value and the light attenuation threshold value.
According to a third aspect of the present invention, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the LED luminaire vision detection method of any one of the above.
The invention has the following advantages:
the method and the device acquire target detection images of the LED lamps to be detected in the unlit state and the lit state. And checking each component on the LED lamp to be detected based on the first target detection image in the unlit state, and comparing the component with the standard LED lamp to obtain a component deviation value of the LED lamp to be detected. If the device deviation value of the LED lamp to be detected is larger than the deviation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified, and executing the next step.
And acquiring the brightness value and the temperature value of the unit time of the LED lamp to be detected in real time based on the second target detection image in the lighting state, and drawing a brightness-time change chart and a temperature-time change chart. And obtaining the brightness change rate based on the brightness-time change graph, and obtaining the temperature rise change rate and the heat dissipation change rate based on the temperature-time change graph. And predicting the light attenuation value of the LED lamp to be detected based on the brightness change rate, the temperature rise change rate, the heat dissipation change rate and the light attenuation prediction formula. If the light attenuation value of the LED lamp to be detected is larger than the light attenuation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified.
According to the invention, the target detection images of the LED lamp to be detected in the unlit state and the lit state are obtained, and the first target detection image in the unlit state and the second target detection image in the lit state are analyzed, so that whether the quality of the LED lamp to be detected is qualified can be judged. The detection means is automatic, the detection efficiency is improved, the product quality stability is improved, and the labor cost is saved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those of ordinary skill in the art that the drawings in the following description are exemplary only and that other implementations can be obtained from the extensions of the drawings provided without inventive effort.
The structures, proportions, sizes, etc. shown in the present specification are shown only for the purposes of illustration and description, and are not intended to limit the scope of the invention, which is defined by the claims, so that any structural modifications, changes in proportions, or adjustments of sizes, which do not affect the efficacy or the achievement of the present invention, should fall within the ambit of the technical disclosure.
FIG. 1 is a flow chart of a visual detection method of an LED lamp provided by the invention;
FIG. 2 is a flowchart showing the step S2 in the method according to the present invention;
FIG. 3 is a connection block diagram of a visual inspection system for LED lamps provided by the invention;
FIG. 4 is a graph showing luminance versus time in the method provided by the present invention;
fig. 5 is a graph of temperature versus time in the method provided by the present invention.
Detailed Description
Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to solve the problems of low detection precision, low detection efficiency and influence on product quality caused by manual detection in the prior art, according to a first aspect of the present invention, there is provided a visual detection method for an LED lamp, as shown in fig. 1, including:
step S1: obtaining target detection images of the LED lamps to be detected in an unlit state and a lit state;
step S2: based on a first target detection image in an unlit state, checking each component on the LED lamp to be detected, and comparing the components with a standard LED lamp to obtain a component deviation value of the LED lamp to be detected;
step S3: if the device deviation value of the LED lamp to be detected is larger than the deviation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified, and executing the next step;
step S4: acquiring a brightness value and a temperature value of an LED lamp to be detected in real time based on a second target detection image in a lighting state, and drawing a brightness-time change chart and a temperature-time change chart, wherein the second target detection image comprises a lamp image and an infrared thermal imaging chart;
step S5: obtaining a brightness change rate based on a brightness-time change chart, and obtaining a heating change rate and a heat dissipation change rate based on a temperature-time change chart;
step S6: predicting the light attenuation value of the LED lamp to be detected based on the brightness change rate, the temperature rise change rate, the heat dissipation change rate and the light attenuation prediction formula;
step S7: if the light attenuation value of the LED lamp to be detected is larger than the light attenuation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified.
The LED lamp is provided with various components, such as a lamp bead, a resistor, a capacitor, a transformer and the like, and the various components are welded on the PCB, so that a passage is formed, the LED lamp is powered, and the LED lamp emits light. During detection, the appearance of the LED lamp to be detected is firstly checked, and whether all components on the LED lamp are correctly welded on the PCB or not is checked. If the detection result is unqualified, the quality of the LED lamp is unqualified. And if the detection result is qualified, the LED lamp can be further detected. And the photometric parameter information of the LED lamp in the lighting state is acquired in multiple aspects, and the light attenuation condition of the LED lamp is predicted.
As shown in fig. 2, step S2 specifically includes the following steps:
s201: dividing a first target detection image in an unlit state into different detection areas, selecting components on the LED lamp to be detected in the detection areas, and obtaining the gap distance of a welding gap of the components on the LED lamp to be detected；
S202: dividing the standard LED lamp image into different detection areas according to the step S201, selecting components on the standard LED lamp in the detection areas, and obtaining the gap distance of the welding gap of the components on the standard LED lamp；
S203: formula according to welding gap deviation valueAnd obtaining a welding gap deviation value theta.
The quality of the lamp is judged through the detected welding seam deviation value of the components, the quality of the lamp during production can be reflected, the service life of the lamp can be reflected to a certain extent, namely when the welding seam deviation value is larger than a deviation threshold value, the welding seam is larger, and the problems of welding off and the like can be caused in the expected service time.
And detecting welding gap distances at pins of the components on the basis that the positions of the components are correctly welded. If the deviation value between the welding gap distance and the standard distance is too large, the component is in an open circuit state, a passage cannot be formed, and therefore a working environment cannot be provided for the LED lamp, and therefore the quality of the LED lamp is judged to be unqualified.
Specifically, in step S4, the luminance value of the LED lamp to be detected in unit time is obtained in real time, and a luminance-time variation chart is drawn, which specifically includes:
acquiring a lamp image of the LED lamp to be detected in a lighting state in real time until the LED lamp to be detected is completely lighted, wherein the lamp image at least comprises an initial image and a final image;
acquiring the frame number of the interval image and the brightness value of each frame of the interval image according to the interval image between the initial image and the final image;
and obtaining the response time according to the frame number of the interval image, obtaining the brightness value of the unit time of the LED lamp to be detected according to the brightness value of each frame of the interval image, and drawing a brightness-time change chart.
The time for the LED lamp to fully light is transient and can be calculated by reading a time frame. The initial image is an image with brightness of 0, and the final image is an image with maximum brightness. The LED lamp has 24 frames of images in one second, the brightness of the lamp of each frame of images can be obtained according to the number of frames of the interval images, and the response time for completely lighting the LED lamp is calculated.
As shown in fig. 4, the luminance-time variation graph includes a rising section and a stationary section, and the image is made to approach stationary by the zero point rising. Zero is the initial image brightness and the plateau is the final image brightness. The luminance change rate is a change in luminance per unit time from the rising section to the stationary section. The number of time frames from the zero point of the luminance-time variation graph to the image stationary point is the number of frames separating the images.
Specifically, in step S4, a temperature value of the LED lamp to be detected in unit time is obtained in real time, and a temperature-time change chart is drawn, which specifically includes:
and acquiring an infrared thermal imaging image of the LED lamp to be detected in unit time based on the LED lamp to be detected in the lighting state, acquiring a temperature value in unit time according to the infrared thermal imaging image, and drawing a temperature-time change chart.
As shown in fig. 5, the temperature-time variation graph includes a rising section, a stationary section, and a falling section. The rising interval is the process of gradually heating the LED lamp, the stable interval is the process of reaching the highest temperature of the LED lamp, and the falling interval is the process of gradually radiating and cooling the LED lamp. The temperature of the LED lamp gradually rises due to light emission. In order to reduce the light attenuation of the LED lamp, the LED lamp needs to be cooled, and therefore, the temperature-time variation graph has a rising section, a stable section and a falling section. The temperature rise change rate is the temperature change per unit time from the rising section to the stationary section, and the heat dissipation change rate is the temperature change per unit time from the stationary section to the falling section.
The light attenuation prediction formula is:
；
wherein,for the light attenuation value k of the LED lamp to be detected 1 The weight is preset for light attenuation corresponding to brightness change, t is the reaction time of the LED lamp to be detected when the LED lamp is completely on, and f 1 For the brightness change rate k of the LED lamp to be detected 2 Preset weight for light attenuation corresponding to temperature change, f 2 F is the temperature rise change rate of the LED lamp to be detected 3 The heat dissipation change rate of the LED lamp to be detected is obtained.
The light attenuation prediction formula is combined with the brightness change condition, the temperature rise change condition and the heat dissipation change condition of the LED lamp to comprehensively predict the light attenuation of the LED lamp. Setting a light attenuation threshold, judging that the quality of the LED lamp is unqualified if the calculated light attenuation value is larger than the light attenuation threshold, otherwise, judging that the quality is qualified.
According to a second aspect of the present invention, there is provided an LED luminaire vision detection system for implementing an LED luminaire vision detection method, as shown in fig. 3, comprising:
the image acquisition unit is used for acquiring target detection images of the LED lamps to be detected in the unlit state and the lit state;
the first image information processing unit is used for obtaining a device deviation value of the LED lamp to be detected based on the first target detection image in the unlit state;
the first judging unit is used for judging whether the quality of the LED lamp to be detected is qualified or not according to the device deviation value and the deviation threshold value;
the second image information processing unit is used for predicting the light attenuation value of the LED lamp to be detected based on a second target detection image in the lighting state;
and the second judging unit is used for judging whether the quality of the LED lamp to be detected is qualified or not according to the light attenuation value and the light attenuation threshold value.
Specifically, the image acquisition unit acquires target detection images of the LED lamp to be detected in the unlit state and the lit state. And the first image information processing unit is used for checking each component on the LED lamp to be detected based on a first target detection image in an unlit state, and comparing the component with a standard LED lamp to obtain a component deviation value of the LED lamp to be detected. If the device deviation value of the LED lamp to be detected is larger than the deviation threshold value, the first judging unit judges that the quality of the LED lamp to be detected is unqualified, otherwise, the quality is qualified, and the next step is executed.
The second image information processing unit acquires the brightness value and the temperature value of the LED lamp to be detected in unit time in real time based on the second target detection image in the lighting state, and draws a brightness-time change chart and a temperature-time change chart. And obtaining the brightness change rate based on the brightness-time change graph, and obtaining the temperature rise change rate and the heat dissipation change rate based on the temperature-time change graph. And predicting the light attenuation value of the LED lamp to be detected based on the brightness change rate, the temperature rise change rate, the heat dissipation change rate and the light attenuation prediction formula. If the light attenuation value of the LED lamp to be detected is larger than the light attenuation threshold value, the second judging unit judges that the quality of the LED lamp to be detected is unqualified, otherwise, the quality is qualified.
According to a third aspect of the present invention, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements a method of visual inspection of an LED luminaire.
While the invention has been described in detail in the foregoing general description and specific examples, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
Claims (9)
1. The visual detection method for the LED lamp is characterized by comprising the following steps of:
step S1: obtaining target detection images of the LED lamps to be detected in an unlit state and a lit state;
step S2: based on a first target detection image in an unlit state, checking each component on the LED lamp to be detected, and comparing the components with a standard LED lamp to obtain a component deviation value of the LED lamp to be detected;
step S3: if the device deviation value of the LED lamp to be detected is larger than the deviation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified, and executing the next step;
step S4: based on a second target detection image in a lighting state, acquiring a brightness value and a temperature value of the LED lamp to be detected in unit time in real time, and drawing a brightness-time change chart and a temperature-time change chart;
step S5: obtaining a brightness change rate based on a brightness-time change chart, and obtaining a heating change rate and a heat dissipation change rate based on a temperature-time change chart;
step S6: predicting the light attenuation value of the LED lamp to be detected based on a brightness change rate, a temperature rise change rate, a heat dissipation change rate and a light attenuation prediction formula;
step S7: if the light attenuation value of the LED lamp to be detected is larger than the light attenuation threshold value, judging that the quality of the LED lamp to be detected is unqualified, otherwise, judging that the quality is qualified;
the light attenuation prediction formula is as follows:
；
wherein,for the light attenuation value k of the LED lamp to be detected 1 The weight is preset for light attenuation corresponding to brightness change, t is the reaction time of the LED lamp to be detected when the LED lamp is completely on, and f 1 For the brightness change rate k of the LED lamp to be detected 2 Preset weight for light attenuation corresponding to temperature change, f 2 F is the temperature rise change rate of the LED lamp to be detected 3 The heat dissipation change rate of the LED lamp to be detected is obtained.
2. The method for visual inspection of an LED lamp according to claim 1, wherein the step S2 specifically comprises the steps of:
s201: dividing the first target detection image in the unlit state into different detection areas, selecting components on the LED lamp to be detected in the detection areas, and obtaining the gap distance of the welding gap of the components on the LED lamp to be detected；
S202: dividing a standard LED lamp image into different detection areas according to the step S201, selecting components on the standard LED lamp in the detection areas, and obtaining the gap distance of welding gaps of the components on the standard LED lamp；
S203: formula according to welding gap deviation valueAnd obtaining a welding gap deviation value theta.
3. The LED luminaire vision inspection method of claim 1, in which the second object detection image comprises a luminaire image and an infrared thermal imaging map.
4. The method for visual inspection of LED lamps in claim 3, wherein in step S4, the luminance value of the LED lamp to be inspected in unit time is obtained in real time, and a luminance-time variation graph is drawn, which specifically includes:
acquiring a lamp image of the LED lamp to be detected in a lighting state in real time until the LED lamp to be detected is completely lighted, wherein the lamp image at least comprises an initial image and a final image;
acquiring the frame number of the interval image and the brightness value of each frame of the interval image according to the interval image between the initial image and the final image;
and obtaining the response time according to the frame number of the interval image, obtaining the brightness value of the unit time of the LED lamp to be detected according to the brightness value of each frame of the interval image, and drawing a brightness-time change chart.
5. The method for visual inspection of LED lamps in claim 3, wherein in step S4, the temperature value of the LED lamp to be inspected in unit time is obtained in real time, and a temperature-time change chart is drawn, specifically comprising:
and acquiring an infrared thermal imaging diagram of the LED lamp to be detected in unit time based on the LED lamp to be detected in the lighting state, acquiring a temperature value in unit time according to the infrared thermal imaging diagram, and drawing a temperature-time change diagram.
6. The LED luminaire visual inspection method of claim 4, wherein the luminance-time variation graph includes a rising interval and a plateau interval, the rate of change of luminance being a change in luminance per unit time from the rising interval to the plateau interval.
7. The LED luminaire visual inspection method of claim 5, wherein the temperature-time variation graph includes a rising interval, a plateau interval, and a falling interval, the rate of change of temperature rise is a temperature variation per unit time from the rising interval to the plateau interval, and the rate of change of heat dissipation is a temperature variation per unit time from the plateau interval to the falling interval.
8. An LED luminaire vision inspection system for implementing the LED luminaire vision inspection method of any one of claims 1-7, comprising:
the image acquisition unit is used for acquiring target detection images of the LED lamps to be detected in the unlit state and the lit state;
the first image information processing unit is used for obtaining the device deviation value of the LED lamp to be detected based on the first target detection image in the unlit state;
the first judging unit is used for judging whether the quality of the LED lamp to be detected is qualified or not according to the device deviation value and the deviation threshold value;
the second image information processing unit is used for predicting the light attenuation value of the LED lamp to be detected based on a second target detection image in the lighting state;
and the second judging unit is used for judging whether the quality of the LED lamp to be detected is qualified or not according to the light attenuation value and the light attenuation threshold value.
9. A storage medium having stored thereon a computer program, which when executed by a processor, implements the LED luminaire visual detection method as claimed in any one of claims 1-7.
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| CN116109592A (en) * | 2023-02-14 | 2023-05-12 | 天津博世丰通科技有限公司 | Visual inspection method, system and storage medium for defect at discharging side |
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| CN114819627A (en) * | 2022-04-25 | 2022-07-29 | 武汉万驰机械设备租赁有限公司 | High-definition electronic screen production quality intelligent monitoring analysis system based on machine vision |
| CN116109592A (en) * | 2023-02-14 | 2023-05-12 | 天津博世丰通科技有限公司 | Visual inspection method, system and storage medium for defect at discharging side |
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Denomination of invention: A visual inspection method, system, and storage medium for LED lighting fixtures Granted publication date: 20231215 Pledgee: Bank of Communications Limited Shenzhen Branch Pledgor: Shenzhen xingbiao Electronic Technology Co.,Ltd. Registration number: Y2024980019821 |