Optical Sensor Triangulation Convex Hull Background Detection
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Solution Overview
Problem
Optical sensors struggle to reliably detect objects in front of backgrounds with inhomogeneous optical properties, such as conveyor belts, due to issues like multiple reflections and varying object transparency, leading to inaccurate object recognition.
Innovation Solution
The optical sensor employs multiple transmitters activated cyclically, forming triangulation probes with a position-resolving receiver, and uses an evaluation unit to calculate difference and quotient sums, which form the coordinate axes of a two-dimensional vector space. A convex hull is formed from background measurement points during a teaching process, allowing for reliable object detection by identifying points outside this hull.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple transmitters are used to increase detection sensitivity, then detection sensitivity is improved, but reliable object detection in front of inhomogeneous backgrounds is not achieved
Solution Approach 1:
The patent transforms the one-dimensional signal evaluation into a two-dimensional vector space by forming difference sums and quotient sums as coordinate axes. This dimensional transformation allows the system to separate object signals from background signals that would otherwise be indistinguishable in conventional single-parameter evaluation, thereby achieving reliable detection despite using multiple transmitters.
Solution Approach 2:
The patent implements a teaching phase before actual measurement, during which the convex hull of background measurement points is pre-calculated and stored. This preliminary characterization of the background enables the system to quickly and reliably distinguish objects from backgrounds during subsequent measurements without requiring complex real-time analysis.
2Ease of operation
If conventional triangulation probing is used, then distance measurement is simple, but objects with inhomogeneous optical properties cannot be reliably detected
Solution Approach 1:
The patent segments the evaluation of multiple triangulation probe signals by forming difference sums and quotient sums, which separate the contribution of each transmitter-receiver probe pair. This segmentation allows the system to process and evaluate individual probe contributions independently before combining them in the two-dimensional vector space, maintaining simplicity while improving reliability.
Solution Approach 2:
The patent changes the evaluation parameters from simple distance measurements to a two-dimensional parameter space defined by difference sums and quotient sums. This parameter transformation enables the system to capture additional information about the optical properties of detected objects, allowing reliable distinction between objects and inhomogeneous backgrounds while building upon the conventional triangulation principle.
3Measurement precision
If measured values are averaged to increase detection sensitivity, then sensitivity is improved, but satisfactory detection results are not obtained
Solution Approach 1:
Instead of简单地 averaging measured values, the patent transforms the data into a two-dimensional vector space where each measurement becomes a point with coordinates (difference sum, quotient sum). This dimensional change preserves the individual characteristics of each measurement while enabling statistical separation of object and background signals through convex hull analysis, achieving both sensitivity and accuracy.
Solution Approach 2:
The patent creates a reference model (convex hull) of the background based on teaching phase measurements. During actual operation, new measurement points are compared against this copied background model to determine whether they represent objects or background variations. This copying approach allows the system to maintain high sensitivity while achieving reliable accuracy by referencing the learned background characteristics.
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 method enables precise and reproducible detection of objects with varying surface properties and backgrounds, including opaque, transparent, and reflective objects, by distinguishing measurement points from the convex envelope, ensuring reliable object detection with high accuracy.
Implementation Method 1
at least one transmitter emitting light beams and a position-resolving receiver, which can be formed by a PSD (position-sensitive device) element
Implementation Method 2
working according to the triangulation principle, can determine distances from objects when objects are detected
Implementation Method 3
a position-resolving receiver, which can be formed by a PSD (position-sensitive device) element has two outputs, via which an analog output signal is output in each case
Data Source
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AI summary
The invention relates to an optical sensor (1) with several light-beam emitters (3a-c), each of which is individually activated cyclically, and with a position-resolving receiver having two terminals, each of which can output an analog signal. Each emitter (3a-c) forms a triangulation probe with the position-resolving receiver (4). An evaluation unit for evaluating the output signals of the position-resolving receiver (4) is provided. The optical sensor (1) is designed for detecting objects (8) against a background. In the evaluation unit, a difference sum and a quotient sum are calculated from the output signals of the triangulation probes. The difference sum is the sum of the absolute values of the difference values of the current output signals and an average value of the respective output signal of all triangulation probes.The quotient sum is the sum of the quotients of the differences and sums of the output signals of all triangulation probes. The quotient sum and the difference sum form the coordinate axes of a two-dimensional vector space. In a training process, the background is measured multiple times using only the triangulation probe, and for each of the measured values obtained, measurement points in the vector space are calculated by determining the quotient sum and difference sum, and a convex hull is formed for these points. During a subsequent operational phase following the training process, an object (8) against the background is recognized because its measurement points lie outside the convex hull.