Elevator Monitoring With Sensor-Based Type Identification
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Solution Overview
Problem
Existing elevator monitoring systems face challenges in accurately determining the type of elevator, leading to poor data quality and incorrect analytics due to reliance on manual labor or metadata, which results in inefficient maintenance and incorrect condition assessments.
Innovation Solution
A method and system that utilizes sensors to monitor elevator movement and position data, comparing it to pre-defined elevator type classifications to determine the elevator type accurately, allowing for tailored monitoring and diagnostics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual labor is used to determine elevator type by asking maintenance personnel, then accuracy of elevator type information is improved, but cost and time consumption increase
Solution Approach 1:
The patent replaces manual determination methods (mechanical inquiry of maintenance personnel) with an automated sensor-based system that uses accelerometers, gyroscopes, and other sensors to automatically detect and determine elevator type through movement pattern analysis, thereby eliminating manual labor while maintaining high accuracy
Solution Approach 2:
The elevator system performs self-diagnosis and self-identification by automatically collecting its own movement data through embedded sensors and processing this data to determine its own type, eliminating the need for external manual intervention while providing continuous automated monitoring
2Ease of operation
If metadata is used to determine elevator type, then process simplicity is improved, but data quality and reliability deteriorate
Solution Approach 1:
The patent replaces reliance on static metadata with dynamic sensor-based detection systems that actively measure elevator movement characteristics, providing real-time empirical data that is both simple to collect and highly reliable for determining elevator type
Solution Approach 2:
The system continuously collects movement data from sensors, compares it against known elevator type profiles, and uses this feedback loop to automatically update and refine elevator type identification, ensuring both simplicity and high reliability through ongoing validation
3Productivity
If incorrect elevator type information is used in analytics solutions, then development speed is improved, but diagnostic accuracy and condition assessment deteriorate
Solution Approach 1:
The patent implements preliminary automated elevator type identification using sensor data before deploying analytics solutions, ensuring that the correct elevator type is established in advance, which enables subsequent analytics to be accurately tailored to the specific elevator type without compromising development speed
Solution Approach 2:
The system automatically adjusts monitoring parameters, thresholds, and analytics algorithms based on the detected elevator type, allowing analytics solutions to be optimized for each specific elevator type (e.g., traction vs. hydraulic) while maintaining rapid deployment through automated parameter configuration
Data Source
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AI summary
A method for determining a type of elevator (200), an elevator monitoring system (20), and an elevator (200) are disclosed. The method comprises obtaining (110) data related to movement and/or position of a component of a hoisting system, such as an elevator car (10), of the elevator (200), determining (120) from the data at least one characteristic value related to the movement and/or position, and determining (130) the type based on pre-defined elevator types of an elevator type classification and the characteristic value.