Display Module Self-Diagnosis Through Light-Based Defect Detection
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Solution Overview
Problem
Display modules are susceptible to damage from external forces, leading to defects that impair display quality and user input functionality, which existing technologies struggle to detect and address effectively.
Innovation Solution
An apparatus comprising a display module that outputs light, a detector to capture this light, and processing means to identify defects based on the detected light, using machine learning models to classify and adapt the display output accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing detection technologies are used, then device simplicity is maintained, but defect detection capability is insufficient
Solution Approach 1:
The display module serves dual functions: displaying visual content and detecting defects through its light-emitting and light-sensing capabilities. The processor analyzes light characteristics from the display module itself to detect defects, eliminating the need for separate specialized detection hardware and achieving multi-functionality that resolves the contradiction between detection capability and system complexity.
Solution Approach 2:
The display module performs self-diagnosis by using its own light output characteristics as the detection signal. The processor monitors the light emitted by the display module and identifies defects through analysis of light intensity, wavelength, or spatial distribution variations, enabling the system to detect its own defects without external intervention, thus maintaining simplicity while improving detection capability.
2Reliability
If the display module operates normally without defect detection, then user experience is maintained, but defective areas continue to impair display quality and functionality
Solution Approach 1:
The system implements continuous feedback by monitoring the light characteristics emitted by the display module in real-time. The processor compares the detected light properties against expected characteristics and automatically identifies defects, providing continuous feedback on display health. This enables the system to maintain high reliability by detecting and reporting defects while using efficient algorithms that minimize processing complexity.
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
Effectively detects and classifies defects in display modules, enabling adaptive display adjustments to maintain functionality and user input integrity, while allowing for removable and replaceable modules.
Implementation Method 1
a detector configured to detect the first light
Data Source
AI summary
An apparatus includes: a display module configured to output first light; a detector configured to detect the first light; and a defect detector for detecting one or more defects in the display module, based at least in part on the detected first light, the one or more defects including defects formed at a time of manufacturing.