Elevator Sheave Groove Wear Prediction Using Rope Tension and Slip
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Solution Overview
Problem
Existing elevator wear amount measurement devices can only estimate current wear amounts of sheave grooves and cannot predict future wear amounts accurately.
Innovation Solution
An elevator monitoring device that calculates future wear amounts of sheave grooves using a wear prediction expression, which takes into account the tension of car-side and counterweight-side portions of ropes, slippage amount, and material hardness of sheaves, to provide accurate predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If wear amount is estimated based on rotation amount and reference distance, then current wear amount can be calculated, but future wear amount cannot be predicted accurately
Solution Approach 1:
The patent applies preliminary action by calculating and storing wear prediction values in advance for different travel distances. The wear prediction unit pre-computes wear amounts based on the wear prediction expression using tension data, slippage amounts, and sheave material hardness, creating a database of predicted wear values before actual wear occurs. This allows accurate prediction of future wear states without requiring real-time measurement of wear progression.
Solution Approach 2:
The patent implements feedback by using actual wear measurement data to validate and refine the wear prediction expression. The system compares predicted wear amounts with actual wear measurements and adjusts the prediction model accordingly. This feedback loop continuously improves the accuracy of future wear predictions by learning from actual wear patterns and refining the computational model.
2Productivity
If simple estimation methods are used, then current wear can be calculated easily, but accurate future wear prediction is not achieved
Solution Approach 1:
The patent applies parameter changes by transforming the wear prediction from a simple function of rotation amount to a comprehensive model that incorporates multiple dynamic parameters: tension of car-side and counterweight-side rope portions, slippage amounts, and sheave material hardness. The wear prediction expression integrates these varying parameters to calculate accurate future wear amounts, significantly improving prediction reliability while maintaining computational efficiency through structured calculation methods.
Data Source
AI summary
In an elevator monitoring device, a wear prediction unit calculates a wear amount prediction value through use of a wear prediction expression which uses, as inputs, a tension of a car-side portion and a tension of a counterweight-side portion in each of a plurality of ropes suspending a car and a counterweight, a slippage amount of each of the plurality of ropes, and material hardness of a sheave. The wear amount prediction value is a prediction value of a future wear amount that occurs in a set period in each of a plurality of sheave grooves.


