Inspection Apparatus Lighting Calibration via Histogram Analysis
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Solution Overview
Problem
The reliability of inspection processes for printed circuit boards (PCBs) is compromised due to hardware condition changes in inspection probes over time and variations in PCB characteristics, leading to reduced inspection accuracy and precision.
Innovation Solution
An automated test program is used to check the hardware condition of inspection probes and adjust lighting intensity based on histogram analysis and visibility information to optimize measurement variables for specific PCB characteristics, enhancing inspection precision and reducing setup time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the inspection apparatus is used for a long time, then productivity is maintained, but the hardware condition of the inspection probe changes and inspection reliability is reduced
Solution Approach 1:
The patent implements preliminary calibration actions by capturing reference images of calibration boards with known patterns before actual inspection. These reference images establish baseline characteristics for lighting conditions, camera response, and probe performance. By performing this calibration in advance, the system compensates for hardware drift and maintains inspection reliability without requiring frequent manual adjustments during prolonged usage periods.
Solution Approach 2:
The system continuously monitors inspection results and compares them against reference data from calibration boards. When deviations are detected indicating hardware condition changes, the system automatically adjusts inspection parameters or triggers recalibration. This feedback mechanism ensures that inspection reliability is maintained throughout the probe's operational life by detecting and correcting drift in real-time.
2Reliability
If the same inspection condition is used for various PCBs, then device complexity is reduced, but inspection reliability is reduced due to variations in PCB characteristics
Solution Approach 1:
The patent automatically adjusts inspection parameters such as lighting intensity, exposure time, and gain based on the specific characteristics of each PCB being inspected. By capturing images of calibration boards and analyzing their statistical properties, the system determines optimal parameter settings for different PCB types, colors, and reflectances. This dynamic parameter adaptation maintains high inspection reliability across diverse PCB characteristics without requiring complex manual configuration.
Solution Approach 2:
The inspection apparatus performs self-calibration by automatically capturing and analyzing images of calibration boards. The system independently determines optimal inspection conditions for different PCB types without requiring external intervention or complex user setup. This self-service capability simplifies operation while maintaining reliability across various PCB characteristics.
3Measurement precision
If manual setup of measurement variables is performed, then measurement precision can be optimized, but loss of time occurs in setting up job files
Solution Approach 1:
The system automatically captures images of calibration boards and performs statistical analysis to determine optimal measurement variables such as lighting intensity, exposure parameters, and histogram adjustments. This self-calibration process eliminates the need for manual setup of inspection parameters, maintaining measurement precision while significantly reducing the time required to configure job files for different PCB inspection tasks.
Solution Approach 2:
The patent performs preliminary automated calibration by capturing reference images and establishing optimal measurement variables before actual inspection begins. These pre-determined parameters are stored and automatically applied when inspecting similar PCB types, eliminating repetitive manual setup while maintaining precision. The calibration board analysis provides baseline data that guides subsequent inspection parameter selection.
4Measurement precision
If lighting intensity is not optimized, then device complexity is reduced, but measurement precision is reduced due to dark or bright regions in captured images
Solution Approach 1:
The system captures images of calibration boards and analyzes the histogram distribution of pixel intensities to determine whether lighting is too strong or too weak. Based on this feedback, the system automatically adjusts lighting intensity and camera exposure parameters to achieve optimal image quality with balanced histogram distribution. This closed-loop control ensures measurement precision without requiring complex manual lighting adjustments.
Solution Approach 2:
The inspection apparatus performs self-adjustment of lighting and exposure parameters by analyzing calibration board images. The system independently determines optimal lighting conditions based on histogram analysis and automatically configures capture settings, eliminating the need for complex manual lighting control while achieving precise image capture.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method effectively judges the current working condition of inspection apparatuses and automatically adjusts measurement variables, improving inspection precision and reliability by ensuring optimal lighting conditions for diverse PCB characteristics, thus enhancing user convenience and reducing measurement errors.
Implementation Method 1
providing light to the inspection board while changing a lighting intensity of the inspection apparatus, acquiring the light reflected by the inspection board through a camera of the inspection apparatus
Data Source
AI summary
In order to establish a lighting intensity of an inspection apparatus, an inspection board is installed in an inspection apparatus. Then, a width of a histogram of a captured image acquired through a camera of the inspection apparatus is adjusted to avoid from a dark region and a bright region. Thereafter, a lighting intensity of the inspection apparatus is adjusted by adjusting the histogram to be near a middle of a graph. Thus, a setting time of an inspection condition stored in a job file may be reduced to increase the user's convenience, and measurement error due to mis-establishment may be reduced to enhance inspection precision.