Elevator Control Device Learning Validation
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Solution Overview
Problem
Conventional elevator control devices lack measures to handle excessive, low-speed, or stop values resulting from computed speed command values, leading to unreliable learning algorithm validity and elevator operation.
Innovation Solution
Incorporating a learning-function check section to validate running control parameters by comparing calculated values against predetermined ranges, allowing for immediate detection of abnormalities and switching to rated running mode or stopping service as needed, while maintaining high efficiency and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the learning function dynamically adjusts running control parameters without validation, then the elevator can operate with high efficiency adapted to building conditions, but the reliability of the learning result cannot be ensured when excessive or abnormal values occur
Solution Approach 1:
The patent implements a feedback mechanism where the learning result determination section validates learned parameters by comparing them against predetermined ranges. When parameters fall outside acceptable ranges (excessive values, low-speed values, or stop values), the system detects these as abnormal and prevents erroneous operation, thus ensuring reliability while maintaining the adaptive efficiency benefits of dynamic parameter adjustment
Solution Approach 2:
The patent applies preliminary action by establishing predetermined ranges for running control parameters before the learning process occurs. This pre-established validation framework allows the system to proactively identify and reject abnormal learned values (excessive, low-speed, or stop values) before they can cause harmful effects, ensuring reliable operation while preserving the efficiency gains from adaptive learning
2Adaptability or versatility
If the learning algorithm is applied without determining validity of learned parameters, then automatic adaptation to building conditions is achieved, but harmful effects may occur from excessive or abnormal speed command values
Solution Approach 1:
The patent converts the potentially harmful effect of unvalidated learned parameters into a beneficial validation mechanism. By establishing predetermined ranges and using the learning result determination section to compare learned values against these ranges, the system transforms the risk of excessive or abnormal speed values into an opportunity to detect and correct learning errors, thereby ensuring safe adaptation to building conditions
Data Source
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AI summary
Provided is an elevator control device having a learning function, with enhanced reliability of the result of learning and high performance. An elevator control device for optimizing variable-speed driving includes: a learning function section for updating running control parameters based on a result of identification of running state quantities during a normal operation after an elevator is installed; and a learning-function check section for performing one of stop of elevator service and rated running using predetermined running control parameters when the running control parameters obtained by the learning function section are out of allowable ranges of the running control parameters, which are estimated from allowable fluctuation rates of basic apparatus specification values of the elevator, and for determining that the learning function section is normal when the running control parameters are within the allowable ranges of the running control parameters.