Infrared Sensor Module Auto Calibration for Touch Positioning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional infrared sensor modules in touch screens face issues with touch sensitivity and accurate touch position detection due to deviations in position, leading to erroneous detection, and enlarging the light receiving area increases the thickness and volume of the sensor module, complicating noise processing.
Innovation Solution
The solution involves dividing the light receiving region of the infrared sensor module into 'm x n' blocks, where each block contains multiple light receiving pixels, allowing for auto calibration by selecting and activating blocks with maximum optical signal output, thereby adjusting the light receiving area without physical changes and reducing noise processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the light receiving area is enlarged to cover positional deviations, then touch detection reliability is improved, but the sensor module thickness and volume increase
Solution Approach 1:
The light receiving region is divided into multiple blocks (e.g., 3x3 grid), allowing selective activation of specific blocks based on optical signal strength. This segmentation enables the system to maintain a compact physical structure while achieving effective coverage of positional deviations by activating only the necessary blocks.
Solution Approach 2:
The system dynamically selects and activates specific blocks within the light receiving region based on real-time optical signal measurements. This dynamic adaptation allows the sensor to compensate for positional deviations without requiring a permanently enlarged light receiving area, thus maintaining thin module thickness while ensuring reliable touch detection.
2Reliability
If the light receiving area is enlarged to cover positional deviations, then touch detection reliability is improved, but noise processing complexity increases
Solution Approach 1:
Dividing the light receiving region into discrete blocks enables independent processing of signals from each block. This segmentation simplifies noise processing by allowing the system to identify and eliminate noise through block-by-block comparison, rather than processing the entire enlarged light receiving area as a single complex region.
Solution Approach 2:
The system applies different processing strategies to different blocks based on their local characteristics. Blocks with strong optical signals are identified as valid touch regions, while blocks with weak or inconsistent signals are treated as noise and excluded. This local quality approach reduces overall processing complexity by focusing computational resources only on relevant regions.
3Manufacturing precision
If the light receiving region is fixed physically, then manufacturing precision is improved, but adaptability to positional deviations deteriorates
Solution Approach 1:
The system transitions from a static, physically fixed light receiving region to a dynamic, software-configurable block selection mechanism. This allows the system to maintain simple, precise physical manufacturing while adapting to positional deviations through automated calibration and dynamic block activation, effectively decoupling manufacturing precision from operational adaptability.
Solution Approach 2:
The system performs self-calibration by automatically detecting the optimal block configuration through optical signal measurement and comparison. This self-service capability eliminates the need for complex manual calibration procedures while maintaining adaptability to positional deviations, allowing the sensor to automatically adjust to its actual installed position.
4Measurement precision
If all blocks in the light receiving region are processed, then measurement precision is improved, but data transmission and processing volume increase
Solution Approach 1:
The system extracts and processes only the essential information from the light receiving blocks - specifically, identifying which blocks contain valid optical signals versus noise. By extracting only this critical information rather than processing all block data in full detail, the system maintains accurate touch position detection while significantly reducing data transmission volume and processing requirements.
Solution Approach 2:
The system performs partial processing by focusing computational resources only on blocks that are likely to contain valid touch signals, rather than uniformly processing all blocks in the light receiving region. This selective approach maintains measurement precision for relevant areas while reducing overall data processing volume.
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
This approach ensures consistent optical signal coverage, improves touch sensitivity, maintains a slim module thickness, and reduces data transmission and processing complexity by focusing on specific blocks with concentrated optical signals, effectively addressing positional deviations and noise interference.
Implementation Method 1
infrared sensor module, which includes a sensor block having a light receiving region
Data Source
Figure 1~2
Figure 3~4
Figure 5
AI summary
An infrared sensor module (21A), a touch sensing method thereof, and an auto calibration method applied to the same are disclosed, the touch sensing method includes turning on the infrared sensor module (21A) which includes a sensor block (2100) with a light receiving region (210) and is arranged to be perpendicular to a surface of a display panel (10), the light receiving region (210) being divided into m x n blocks (where, each of m and n is a natural number of two or more) arranged in m rows by n columns, each of the blocks having a plurality of light receiving pixels (215) arranged in a row direction, scanning optical signals of each block, selecting the block having maximum output optical signals with respect to the blocks of each column, and summing the optical signals of the light receiving pixels (215) of the block selected from the column.