Elevator Door Component Monitoring via Acoustic and Motion Analysis
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Solution Overview
Problem
Monitoring operations of components in conveyance systems, such as elevator systems, is difficult and costly due to the complexity of detecting anomalies in motion and sound data.
Innovation Solution
A component monitoring system that uses a combination of cameras and microphones, potentially within or outside a mobile computing device, to capture and analyze motion and sound data from conveyance apparatus components, allowing for the evaluation of their performance and detection of abnormalities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional monitoring methods are used for conveyance system components, then measurement precision can be maintained, but device complexity and cost increase significantly
Solution Approach 1:
The patent combines multiple sensing modalities (acoustic sensors, vibration sensors, current sensors, temperature sensors) into an integrated monitoring system that collects and analyzes data from multiple sources simultaneously. This merging approach enables comprehensive anomaly detection while sharing processing infrastructure, thereby maintaining high measurement precision without proportionally increasing device complexity
Solution Approach 2:
The monitoring system is designed to perform multiple functions: detecting acoustic anomalies, analyzing vibration patterns, monitoring current consumption, and tracking temperature variations. By creating a multi-functional system that can detect various types of component failures through different sensing modalities, the patent achieves high measurement precision across multiple parameters without requiring separate specialized systems for each function
2Reliability
If comprehensive monitoring of component operations is implemented, then reliability improves, but ease of operation deteriorates due to complex data analysis requirements
Solution Approach 1:
The system continuously monitors component operations and provides real-time feedback through processed anomaly scores and alerts. The processor analyzes sensor data and generates actionable feedback about component health status, enabling operators to respond to issues as they develop. This feedback mechanism maintains high reliability by enabling proactive maintenance while simplifying operation by presenting processed, actionable information rather than raw data
Solution Approach 2:
The monitoring system performs self-diagnosis and automated anomaly detection through algorithmic analysis of sensor data. The processor automatically identifies patterns indicating component failures without requiring manual intervention for data interpretation. This self-service capability enhances reliability through continuous automated monitoring while improving ease of operation by eliminating the need for operators to manually analyze complex sensor data
3Measurement precision
If multiple sensors and data processing capabilities are added to detect anomalies, then measurement precision improves, but loss of time increases due to extensive data processing
Solution Approach 1:
The system continuously collects and pre-processes sensor data during normal operation, maintaining a baseline of component performance. By performing preliminary data collection and analysis during idle periods and normal operations, the system is prepared to quickly detect and respond to anomalies when they occur. This preliminary action enables high measurement precision through continuous monitoring while minimizing time loss during actual anomaly detection events
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient evaluation of component performance by processing motion and sound data to identify any deviations from normal operation, facilitating timely maintenance and improving the overall reliability of conveyance systems.
Implementation Method 1
a microphone configured to detect sound data emitted by the elevator door
Data Source
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AI summary
A component monitoring system (200) for monitoring a component (104) of a conveyance system including a conveyance apparatus (103) including: a camera (490) configured to capture a sequence images of the component (104), the sequence of images being motion data (310); and a processor (282; 420) configured to determine an evaluation summary of the component in response to at least the motion data (310).