Analytics-Based Anomaly Detection Using Compression Rate Thresholds
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Solution Overview
Problem
Existing computing devices lack effective methods for real-time anomaly detection in component operations, leading to potential failures and inefficiencies due to inadequate monitoring and alert systems.
Innovation Solution
An analytics-based anomaly detection system utilizing a processor and non-volatile memory to receive measurement data, apply a compression algorithm, and generate alerts when a threshold compression rate is met, indicating abnormal operating states, while also employing machine learning for predictive analytics and cost estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional monitoring methods are used, then device operation is maintained, but anomaly detection capability is insufficient leading to potential failures
Solution Approach 1:
The patent extracts the anomaly detection function from comprehensive system monitoring and focuses specifically on component health parameters. By isolating and monitoring only critical parameters (temperature, voltage, current) and using compression rate as a proxy indicator, the system achieves reliable anomaly detection without requiring complex multi-parameter monitoring infrastructure.
Solution Approach 2:
The compression rate serves as an intermediary indicator that indirectly reflects component health status. Instead of directly monitoring multiple complex parameters, the system uses data compression to transform raw measurement data into a compression rate metric that captures anomaly information, simplifying the monitoring approach while maintaining detection reliability.
2Reliability
If real-time monitoring is implemented, then anomaly detection is improved, but computational resources are consumed
Solution Approach 1:
The patent applies partial action by monitoring only selected critical parameters rather than all possible device metrics. It uses a subset of essential measurements (temperature, voltage, current) and processes data in batches rather than continuously, achieving real-time anomaly detection while reducing computational resource consumption through selective monitoring and batch processing.
Solution Approach 2:
The system changes the parameter being monitored from raw multi-dimensional measurement data to a single derived parameter - the compression rate. This parameter transformation consolidates multiple measurement dimensions into one metric that captures anomaly information, reducing computational complexity while maintaining real-time detection capability.
3Measurement precision
If comprehensive component monitoring is performed, then detection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent extracts the essential anomaly detection function from complex multi-parameter monitoring. By focusing on a limited set of critical parameters and using compression rate as a proxy indicator, it achieves accurate component condition monitoring without the data processing complexity of comprehensive multi-parameter analysis.
Solution Approach 2:
The system creates a simplified representation of component health through the compression rate metric. This copy or proxy indicator captures the essential anomaly information from complex raw data without requiring complex processing, maintaining measurement precision while reducing data processing complexity.
Data Source
AI summary
Apparatuses, methods, systems, and program products are disclosed for analytics-based anomaly detection. An apparatus includes a processor and a memory that stores code executable by the processor. The code is executable by the processor to receive measurement data for a component of a device, determine a compression rate of the received measurement data by applying a compression algorithm to the measurement data, and generate an alert indicating a possible anomaly in an operation of the component represented by the measurement data in response to the determined compression rate satisfying a threshold compression rate for the at least one condition of the component.