Optoelectronic Object Detection Using Pre-Classification
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Solution Overview
Problem
Existing object detection methods fail to accurately recognize interruptions in light beams due to interfering light signals from objects, particularly those with reflecting surfaces, leading to erroneous non-detection of objects.
Innovation Solution
A method that classifies light objects incident on a receiver outside the detection region as either a reflector image or an interfering light object based on determined object properties, and generates an object detection signal only when the interfering light object moves into the detection region, preventing false negatives by evaluating the movement and properties of these light objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If polarization filters are used to reduce interfering light signals, then the reliability of object detection is improved, but objects with depolarizing or polarization-changing materials cannot be reliably recognized
Solution Approach 1:
The system performs preliminary detection of light objects outside the detection region before they enter the detection region. By classifying objects based on their properties (reflecting, remitting, or polarizing characteristics) in advance, the system prepares appropriate evaluation criteria before the objects potentially interfere with reflector image evaluation, thereby maintaining detection reliability for all object types including depolarizing materials
Solution Approach 2:
The evaluation criteria are dynamically adjusted based on the classification of detected light objects. When polarizing objects are detected outside the detection region, the system adapts its evaluation method accordingly, switching between different detection strategies to maintain reliability across varying object properties and conditions
2Measurement precision
If the detection region is used to evaluate reflector images, then spatial resolution is achieved, but interfering light objects incident on the detection region simulate uninterrupted beam paths
Solution Approach 1:
The system detects and classifies light objects outside the detection region before they enter it. By identifying reflecting, remitting, or polarizing objects in advance and determining their movement trajectories, the system can anticipate when they will enter the detection region and adjust the evaluation criteria accordingly, preventing false simulations of uninterrupted beam paths
Solution Approach 2:
The system continuously monitors the detection region and adjusts its evaluation of reflector images based on feedback from detected light objects. When objects are classified outside the detection region, their properties feed back into the evaluation process, allowing the system to differentiate between genuine reflector images and interfering light signals even when both are present in the detection region
3Reliability
If light objects outside the detection region are detected and classified, then false negatives are prevented, but device complexity increases
Solution Approach 1:
The detection process is segmented into distinct stages: detection of light objects outside the detection region, classification based on properties (reflecting, remitting, polarizing), determination of movement trajectories, and conditional adjustment of reflector image evaluation. This segmentation allows the system to manage complexity by handling different object types through dedicated processing paths rather than a single complex evaluation system
Solution Approach 2:
The system introduces an intermediary classification mechanism that processes detected light objects before they reach the final evaluation stage. This intermediary layer categorizes objects based on their optical properties and determines their potential to interfere with reflector image evaluation, simplifying the overall system by preprocessing information rather than requiring complex real-time differentiation during final evaluation
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 effectively prevents false negatives in object detection by accurately distinguishing between reflector images and interfering light objects, ensuring reliable recognition of beam interruptions even with objects having reflecting regions, thereby maintaining the 'object detected' state before the reflector image evaluation is interrupted.
Implementation Method 1
light is transmitted by a transmitter in the direction of a reflector, the transmitted light is reflected at the reflector and is imaged as a reflector image on a detection region of a receiver
Implementation Method 2
detected by said receiver and the detected reflector image is evaluated
Data Source
AI summary
A method for the detection of an object includes transmitting light in the direction of a reflector by a transmitter. The transmitted light is reflected by the reflector and is imaged as a reflector image and is detected by the receiver. The reflector image is evaluated and an object detection signal is generated if an at least partial interruption of the transmitted light is recognized. A light object incident onto the receiver outside the detection region is detected by the receiver, is examined for predetermined object properties and is classified as a reflector image or as an interfering light object based on the object properties. In the case of a classification as an interfering light object, a movement of the interfering light object on the receiver is determined and the generation of the object detection signal is executed based on the determined movement of the interfering light object.