Passenger Conveyor Module Health Monitoring With ML Diagnostics
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Solution Overview
Problem
Technicians face difficulties in determining the operational health of modules in passenger conveyor systems, such as elevators and escalators, during site visits, as it is challenging to assess whether other system components are functioning properly.
Innovation Solution
A diagnostic controller receives signals from modules containing operational data, uses machine learning models trained on legacy data to analyze the operational influence of modules on each other, and issues alerts for malfunctions, with sensor data indicating fluctuations outside predetermined thresholds, and allows for retraining based on inspected conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If technicians visit the site to address reported issues, then they can directly inspect the system, but it is difficult to determine whether other aspects of the system are working properly
Solution Approach 1:
The system enables self-diagnosis by automatically collecting operational data from multiple modules, analyzing inter-module operational influences, and generating health condition assessments without requiring technician intervention. The diagnostic controller autonomously determines which modules are functioning properly and which require attention.
Solution Approach 2:
A diagnostic controller acts as an intermediary between modules and technicians. It collects data from modules, analyzes operational influences between them, and provides comprehensive system health information, eliminating the need for technicians to manually assess each component during site visits.
2Reliability
If manual inspection is performed during site visits, then technicians can identify issues, but it requires frequent on-site visits and time consumption
Solution Approach 1:
The system continuously collects and analyzes operational data from modules in advance, identifying potential issues before they become critical problems requiring technician intervention. This preliminary monitoring reduces the frequency and necessity of on-site visits.
Solution Approach 2:
The diagnostic controller continuously monitors module operations and provides real-time feedback on system health conditions. When anomalies are detected, the system generates alerts, enabling proactive maintenance and reducing the need for routine technician visits.
3Loss of information
If comprehensive system assessment is conducted, then all module conditions can be evaluated, but the complexity of analysis increases
Solution Approach 1:
The diagnostic system is segmented into modular components: data collection from individual modules, analysis of operational influences between specific module pairs, and aggregate system health assessment. This segmentation makes the complex analysis manageable and scalable.
Solution Approach 2:
The diagnostic controller performs multiple functions: collecting data from various module types, analyzing different operational parameters, evaluating inter-module influences, and generating comprehensive health reports. This multi-functionality consolidates complex diagnostic capabilities into a single system.
Data Source
AI summary
A passenger conveyor system having: a passenger conveyor disposed in a building; one or more modules, including a first module, operationally coupled to the passenger conveyor; a diagnostic controller configured to receive a first signal from the first module containing first data indicative of an operational condition of the first module, wherein the diagnostic controller is configured to: determine a health condition of each of the one or more modules from the first signal; and issue an alert when the health condition of the one or more modules is indicative of a malfunction.