Optoelectronic Sensor Signal Analysis for Soiling Adaptation
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Solution Overview
Problem
Existing optoelectronic sensors face challenges in reliably detecting objects due to signal fluctuations and soiling, which can lead to false switching events, as they lack a robust method to differentiate between signal changes caused by contamination and object coverage.
Innovation Solution
The use of a feature space with moments of the received signal distribution, allowing for the formation of feature vectors that include mean and variance, enables precise classification of signal states, thereby adapting the switching threshold to distinguish between object presence and contamination, improving detection reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a static switching threshold is set during assembly, then the sensor can operate with simple configuration, but the sensor cannot adapt to signal changes caused by soiling, leading to false switching
Solution Approach 1:
The sensor performs self-diagnosis by analyzing the statistical properties (mean and variance) of the received signal to detect soiling conditions and automatically adjusts the switching threshold without external intervention. The evaluation unit monitors signal characteristics and adapts the threshold dynamically based on detected contamination levels.
Solution Approach 2:
The switching threshold is changed dynamically based on the detected soiling degree. The evaluation unit modifies the threshold parameter in response to changes in signal mean and variance, allowing the sensor to adapt to varying environmental conditions and maintain reliable object detection despite contamination.
2Measurement precision
If the switching threshold is set narrowly for transparent objects, then detection precision improves, but the sensor becomes more sensitive to signal fluctuations from soiling, causing false triggers
Solution Approach 1:
The evaluation unit continuously monitors the received signal characteristics and provides feedback to adjust the switching threshold. By analyzing the mean and variance of the signal, the system determines the degree of soiling and dynamically modifies the threshold to maintain both precision for transparent objects and reliability against false triggers from contamination.
Solution Approach 2:
The switching threshold transitions from a static value to a dynamic parameter that adapts in real-time based on soiling conditions. The evaluation unit continuously adjusts the threshold according to the current signal characteristics, enabling the sensor to maintain high detection precision while compensating for the increased sensitivity to soiling.
3Reliability
If multiple switching thresholds are set and adjusted based on switching event frequency, then the sensor can counter pollution effects, but the method is limited in robustness of readjustment
Solution Approach 1:
The evaluation moves from one-dimensional threshold adjustment to two-dimensional analysis by considering both the mean and variance of the received signal. This additional dimension (variance) provides more information about soiling conditions, enabling more robust and reliable threshold adjustment while managing complexity through statistical characterization.
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 enhances the robustness and accuracy of object detection, particularly in cases of transparent objects and soiling, by providing a more reliable switching signal and adapting the threshold to specific conditions, reducing false triggers and maintaining detection performance.
Implementation Method 1
reflection light barriers in which the light transmitter and light receiver are arranged on the same side and the light beam is reflected back with the aid of a reflector, often a retroreflector
Implementation Method 2
The incident transmitted light beam is converted in the light receiver 26 into an electrical received signal
Data Source
Figure 1~2
Figure 3~4
Figure 5a~6
AI summary
The sensor (10) has a light transmitter (12) for emitting a light beam (14). A light receiver (26) produces a reception signal from the received light beam. An evaluation unit (32) outputs a binary switching signal based on presence or absence of an object (36) in a monitored area (22) re-painted by the light beam. The evaluation unit extracts two feature vectors of a multidimensional feature space from a time series of the reception signal, where the multidimensional feature space is stretched by two moments of the time series. An independent claim is also included for a method for outputting a binary switching signal based on presence or absence of an object in a light beam.