Pivot Leaf Door Actuator Learning User Interaction Patterns
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Solution Overview
Problem
Existing door systems require complex on-site adjustments to adapt to specific usage conditions, leading to suboptimal operation and user interaction, particularly for pivot leaf doors.
Innovation Solution
A learning door actuator that optimizes its operation over time by recording and storing correction values based on interactions with users, adjusting parameters such as opening and closing times, speeds, and angles to minimize user interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If door systems are provided with factory pre-setting, then installation is simplified, but the door system cannot adapt to specific usage conditions at the point of use
Solution Approach 1:
The door actuator automatically adjusts its operating parameters by detecting user interactions (manual opening/closing actions) and storing correction values in its memory. This self-learning capability allows the system to adapt to specific usage conditions without requiring manual configuration or complex on-site adjustments, thus maintaining ease of installation while achieving high adaptability
Solution Approach 2:
The system continuously monitors user interactions with the door and uses this feedback information to automatically refine its operating behavior. By detecting when users manually override the automatic door function, the system learns from these interactions and adjusts future operations accordingly, enabling adaptation to specific usage patterns without external intervention
2Adaptability or versatility
If complex on-site adjustments are made to adapt door systems to specific usage conditions, then adaptability is improved, but installation complexity and time increase
Solution Approach 1:
The door actuator performs automatic self-configuration by detecting and learning from user interactions during the initial period of operation. This eliminates the need for complex on-site adjustments by installers, as the system autonomously adapts to the specific usage conditions through its built-in learning algorithm and memory storage capability
Solution Approach 2:
The patent replaces complex mechanical adjustment mechanisms with an electronic learning system. Instead of requiring physical adjustments of mechanical components to adapt to usage conditions, the system uses electronic sensors, processors, and memory to detect, learn, and store operational patterns, significantly simplifying the adaptation process
3Ease of operation
If the door opens wider and stays open longer to accommodate more people, then user convenience is improved, but energy loss and operational inefficiency increase
Solution Approach 1:
The system uses sensor feedback to detect the presence, number, and movement of users approaching the door. Based on this real-time information, the control unit dynamically adjusts the door opening angle and duration to match the actual user needs, preventing excessive energy loss while maintaining user convenience
Solution Approach 2:
The door actuator dynamically adjusts its operating parameters (opening angle, holding time, closing speed) in real-time based on detected user interactions and environmental conditions. This dynamic adaptation allows the system to optimize the balance between user convenience and energy efficiency for each specific situation
Data Source
AI summary
A method for operating a door actuator of a pivot leaf door, having a pivotable door leaf, includes at least the following steps: performing a pivot movement of the door leaf; and identifying an interaction between the door leaf and a person and determining a correction value for the pivot movement of the door leaf based on the interaction and correcting future pivot movements of the door leaf by the correction value. A door actuator of a door system is configured to carry out the method.