Dynamic Reference Value Adaptation for Reliable Entrapment Detection
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Solution Overview
Problem
Existing mechanical adjustment systems with electric motors face challenges in reliably differentiating trapping situations from other force changes, such as those caused by temperature changes or contamination, leading to potential false detection of trapped objects.
Innovation Solution
A method where the reference value and threshold value are continuously approximated to match the changing force values during the adjustment movement, using a limiting value to filter out mechanical fluctuations and extract changes due to trapping processes, allowing for real-time detection of trapping situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the absolute value of the calculated closing force is used as the criterion for trapping detection, then trapping situations can be detected, but false detections occur due to force changes caused by temperature changes, frictional forces, and contamination
Solution Approach 1:
The reference value is no longer static but dynamically adapted during the adjustment movement. The system continuously updates the reference value based on the actual force profile, allowing it to track changes in frictional forces and temperature effects while maintaining sensitivity to actual trapping events.
Solution Approach 2:
The system changes the reference parameter from a fixed pre-defined value to a dynamically adjusting value that adapts to changing mechanical conditions. This parameter transformation allows the system to differentiate between normal operational variations and actual trapping events.
2Measurement precision
If the difference between closing force at specific time and closing force at preceding time is used as criterion, then static influences are eliminated and small changes are filtered out, but large buffering space is required and information from further back in time is not used
Solution Approach 1:
The system extracts only the essential information needed for reference value adaptation - the current force value and its deviation from the reference. By focusing on the relevant force profile characteristics rather than storing all historical data, the system achieves adaptive detection with minimal buffering requirements.
Solution Approach 2:
The reference value is continuously prepared and updated during normal operation before trapping detection is needed. This preliminary adaptation ensures that the system is always ready to detect trapping events without requiring post-processing of large data buffers.
3Ease of operation
If a constant reference value is predefined as basis for comparison, then trapping detection can be performed, but the real force profile moves away from the anticipated force profile due to changed conditions, leading to false trapping detection
Solution Approach 1:
The system uses feedback from the actual force measurements to continuously update the reference value. This closed-loop approach allows the system to learn from actual operational conditions and adjust its expectations accordingly, maintaining high detection accuracy despite changing environmental conditions.
Data Source
AI summary
To detect an entrapment situation when a driven component is adjusted using a mechanical adjustment system which has an electric motor (2), a value (Fakt) relating to the force acting upon the driven component is compared with a threshold value (FTh) relating to a reference value (FRef). The reference value (FRef), and thus the threshold value (FTh), are continuously matched, for the purpose of force tracking, with the force value which changes during the movement of adjustment depending on the mechanical system.