Optical Sensing Device Abnormality Detection via Dynamic Laser Scanning
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Solution Overview
Problem
Current LiDAR systems face difficulties in efficiently detecting abnormalities in inspection targets, such as steel materials used in railroad tracks or buildings, despite being able to detect the presence or absence of obstacles.
Innovation Solution
An optical sensing device that acquires first and second point cloud data using laser reflection light, specifies a region associated with the inspection target, and detects abnormalities by emitting laser light to multiple positions within that region, allowing for efficient monitoring and detection of changes in the target's shape.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If LiDAR systems emit laser light to a plurality of positions in a region to acquire point cloud data, then the ability to detect obstacles is improved, but the ability to detect abnormalities in inspection targets deteriorates
Solution Approach 1:
The patent divides the inspection process into two distinct phases: a scanning phase that acquires comprehensive point cloud data of the entire region (including obstacles), and an inspection phase that focuses laser light on specific regions of interest to detect abnormalities. This segmentation allows the system to maintain both obstacle detection capability and abnormality detection capability by performing each function in its optimal phase.
Solution Approach 2:
The patent applies different laser emission strategies to different regions: during the scanning phase, laser light is emitted to multiple positions across the entire region for comprehensive coverage; during the inspection phase, laser light is concentrated on specific regions where abnormalities are suspected. This local quality approach enables the system to optimize detection capability for each specific task.
2Ease of operation
If LiDAR systems use fixed scanning ranges and scanning arrangements, then the system operation is simplified, but the detection precision for abnormalities in specific regions deteriorates
Solution Approach 1:
The patent implements dynamic adjustment of the scanning arrangement and scanning range based on the inspection requirements. The control unit changes the scanning parameters adaptively, transitioning from a fixed comprehensive scan during the scanning phase to a focused dynamic scan during the inspection phase. This dynamic approach maintains operational simplicity through automated control while significantly improving measurement precision for abnormality detection in specific regions.
Solution Approach 2:
The patent changes key parameters of the laser emission system, including the scanning range, scanning arrangement, and laser emission positions, based on the operational phase and inspection requirements. By dynamically adjusting these parameters, the system achieves both simplified operation through automated parameter management and enhanced measurement precision through optimized parameter selection for each phase.
3Area of stationary object
If LiDAR systems acquire comprehensive point cloud data of the entire region, then the coverage is improved, but the efficiency of abnormality detection deteriorates
Solution Approach 1:
The patent segments the detection process into two phases: a scanning phase that acquires comprehensive point cloud data of the entire region to establish a baseline, and an inspection phase that processes only the specific regions of interest for abnormality detection. This segmentation allows the system to maintain comprehensive region coverage during scanning while improving abnormality detection efficiency by focusing computational resources on relevant areas during inspection.
Solution Approach 2:
The patent performs preliminary scanning to acquire comprehensive point cloud data of the entire region before the inspection phase. This preliminary action creates a reference database of the region's geometry and identifies regions of interest where abnormalities are likely to occur. By preparing this comprehensive data structure in advance, the system can efficiently focus on specific regions during the inspection phase, thereby maintaining coverage while improving detection efficiency.
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
Enables efficient detection of abnormalities in inspection targets by acquiring and comparing point cloud data, improving the accuracy and efficiency of monitoring compared to traditional LiDAR systems.
Implementation Method 1
a light source configured to emit laser light to a plurality of positions in a region
Implementation Method 2
based on first laser reflection light being reflection light of first laser light emitted from the light source
Data Source
AI summary
An optical sensing device includes a first point cloud data acquisition unit for acquiring first point cloud data associated with a first object and a second object that are included in a first region, a region specification unit for specifying a second region associated with the first object in the first region, a second point cloud data acquisition unit for acquiring second point cloud data associated with the first object by emitting second laser light from the light source to a plurality of second positions associated with the second region, based on second laser reflection light being reflection light of the second laser light, and a first abnormality detection unit for detecting abnormality of the first object, by using the second point cloud data.