Object Detection Sensor Using Segmented Temporal Integration
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Solution Overview
Problem
Existing object detection systems face challenges in achieving precise indication of object presence or absence within a monitored area for varying switching distances, particularly due to limitations in resolution and interference suppression across different distance ranges.
Innovation Solution
The method involves sending a light pulse into a monitoring area and detecting it with photosensitive elements, using a temporal integration window divided into sub-integration windows with specific factors to differentiate between object presence and absence, effectively suppressing interference and maintaining accuracy across different distance ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a light pulse with predetermined duration is sent into the monitoring area and detected by photosensitive elements, then object detection is enabled, but interference from non-modulated and sinusoidal light sources cannot be suppressed
Solution Approach 1:
The integration window is divided into multiple sub-integration windows (first, second, third, etc.) with different weighting factors. Each sub-integration window processes a specific time segment of the detected light signal, allowing differential integration that suppresses interference while maintaining object detection capability. The weighting factors assigned to different sub-integration windows create a selective integration scheme that eliminates constant and sinusoidal interference components.
Solution Approach 2:
The method employs periodic modulation of the light source and corresponds periodic sub-integration windows with specific weighting factors. By synchronizing the integration periods with the modulation frequency and using alternating weighting factors (positive and negative), the system selectively integrates modulated light signals while rejecting non-modulated and sinusoidal interference at different frequencies.
2Measurement precision
If the integration window is defined longer than the pulse duration to ensure complete light pulse integration, then measurement accuracy is improved, but temporal resolution and distance dynamics are reduced
Solution Approach 1:
The extended integration window is segmented into multiple sub-integration windows with different weighting factors. This segmentation allows the system to maintain a long total integration time for improved signal-to-noise ratio while using the differential weighting scheme to preserve temporal information. The weighted sum of segmented intervals recovers distance dynamics that would otherwise be lost in a simple long integration.
Solution Approach 2:
The method changes the temporal parameters of signal processing by applying different weighting factors to different time segments. This parameter transformation allows the system to simultaneously achieve high integration gain (long effective integration time) and maintain sensitivity to temporal variations in light return, thereby preserving distance dynamics despite the extended integration window.
3Object-affected harmful factors
If multiple sub-integration windows with different weighting factors are used to suppress interference, then interference suppression is improved, but device complexity increases
Solution Approach 1:
The weighting factors for each sub-integration window are predetermined and stored in memory before the actual measurement process. This preliminary preparation of integration parameters allows the complex weighted integration to be performed efficiently during operation, reducing real-time computational complexity while maintaining the interference suppression benefits of multiple weighted sub-integration windows.
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 provides precise object detection by ensuring the total integration signal is zero when the object is within the switching distance, effectively suppressing non-modulated and sinusoidal interference, and allowing for flexible evaluation based on desired accuracy and distance dynamics.
Implementation Method 1
a light pulse with a predetermined pulse duration is sent into the monitoring area and the light pulse possibly reflected on an object is detected
Implementation Method 2
at least one row of photosensitive elements is provided for receiving light pulses reflected from the monitoring area
Implementation Method 3
the detected signal is integrated over a temporal integration window in order to produce an integration signal
Data Source
Figure 1
Figure 2
Figure 3a~3d
AI summary
The object identifying method involves limiting a monitoring area (310,312) on one side by a selected sensing distance (320,322). A light pulse is sent to the monitoring area, where the light pulse reflected on an object, is detected with a row (18) of a photosensitive element (20). The detected signal is integrated by a temporal integration window for the photosensitive element which receives a reflected light pulse, when an object is located in the sensing distance. The temporal integration window comprises two temporal successive sub-integration windows. An independent claim is included for an object identifying sensor for identifying an object in a monitoring area.