Barrier Operator Anomaly Detection With Wavelet Data Backfilling
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Solution Overview
Problem
Existing barrier operator systems lack effective methods to leverage data for predicting and detecting anomalies, leading to potential operational failures and reduced service life due to neglect of maintenance and unnoticed damages.
Innovation Solution
A barrier operator monitoring system that includes a movable barrier, sensors, a controller, and a cloud processing platform for data collection, anomaly detection, and notification, utilizing machine learning to analyze operational and measured data, and implementing models to predict and report anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If barrier operators store data locally and use it in real-time operations, then control operations are efficient and responsive, but the data cannot be leveraged for predictive maintenance or fleet-wide analysis
Solution Approach 1:
The patent extracts data from the barrier operator's local memory and transmits it to an external server or cloud platform. This allows the barrier operator to maintain its simple local storage for real-time operations while enabling predictive maintenance capabilities through external data analysis. The server receives operational data, cycle counts, and sensor information from multiple barrier operators and performs fleet-wide analytics to predict failures and schedule maintenance.
Solution Approach 2:
The patent introduces a server or cloud platform as an intermediary between barrier operators and maintenance personnel. This intermediary collects data from multiple barrier operators, performs predictive analytics, and generates maintenance recommendations. The intermediary enables predictive maintenance capabilities without requiring complex local infrastructure at each barrier operator site.
2Measurement precision
If barrier operators transmit all operational data continuously, then comprehensive monitoring is achieved, but data transmission bandwidth and processing requirements increase significantly
Solution Approach 1:
The patent implements partial data transmission by selectively sending only relevant data points to the server. Instead of transmitting all operational data continuously, the system transmits data at specific intervals, transmits only when anomalies are detected, or transmits aggregated summaries. This reduces transmission bandwidth and energy consumption while maintaining sufficient data for anomaly detection and predictive maintenance.
Solution Approach 2:
The patent applies local quality by having the barrier operator perform local preprocessing and filtering of data before transmission. The controller identifies and transmits only the most relevant data points, such as anomaly indicators, critical operational parameters, or aggregated statistics. This reduces the overall data transmission volume while preserving the quality of information needed for remote monitoring and predictive maintenance.
3Reliability
If barrier operators perform frequent maintenance based on traditional schedules, then operational reliability is maintained, but service life is reduced due to unnecessary maintenance interventions
Solution Approach 1:
The patent implements preliminary action by detecting and addressing potential failures before they occur. The system analyzes operational data, cycle counts, and sensor information to predict when components may fail. Maintenance is scheduled proactively based on predicted failure timelines rather than waiting for actual failures or following fixed schedules. This extends service life by maintaining components only when necessary while ensuring operational reliability through advance intervention.
Solution Approach 2:
The patent enables self-service through automated predictive maintenance capabilities. The system automatically monitors operational data, detects anomalies, predicts failures, and generates maintenance recommendations without requiring manual inspection or intervention. This reduces unnecessary maintenance interventions while ensuring that maintenance is performed when actually needed, thereby extending service life while maintaining reliability.
4Reliability
If barrier operators use simple local control logic, then device complexity is minimized, but the ability to detect and predict anomalies is limited
Solution Approach 1:
The patent segments the anomaly detection functionality between the barrier operator's local controller and an external server. The local controller performs basic real-time control operations and simple anomaly detection using minimal processing power. The server performs more complex predictive analytics, fleet-wide comparisons, and advanced anomaly detection using aggregated data from multiple barrier operators. This segmentation enables enhanced anomaly detection capability without requiring high processing power at each local device.
Data Source
AI summary
A barrier operator monitoring system includes a barrier operator system and a cloud processing platform. The barrier operator system includes a movable barrier, sensors configured to measure data regarding the barrier operator system, and a barrier operator. The barrier operator is configured to move the movable barrier, detect a loss of a data connection between the barrier operator and the cloud processing platform, collect measured data from the sensors, perform wavelet transformation on the measured data, store coefficients of the wavelet transformation, and transmit, upon restoration of the data connection, the coefficients. The cloud processing platform is configured to receive the coefficients, reconstruct a representation of the measured data, compare the representation of the measured data to model data, detect an anomaly in the barrier operator system based on the comparison, and transmit a notification from the cloud processing platform to a user device.