System for abnormal condition detection using nearest neighbor
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Solution Overview
Problem
Home and small business consumers face challenges in detecting and preventing costly failures of mechanical devices, as these devices often lack sensors to monitor operating parameters, making it difficult to identify when a device is starting to fail, leading to high repair or replacement costs and potential damage from malfunctions.
Innovation Solution
A system that receives sensor data from mechanical devices, correlates it with environmental conditions, and generates a correlative value to identify abnormal operating conditions, notifying users when the device is likely to fail, allowing for proactive maintenance and reducing emergency repairs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mechanical devices are monitored using traditional methods, then device operation continues, but failures are detected too late leading to costly emergency repairs
Solution Approach 1:
The system performs preliminary actions by continuously monitoring sensor data and environmental conditions to detect early signs of device degradation before actual failure occurs. The anomaly detection algorithm identifies patterns indicating impending failure, allowing users to schedule maintenance during convenient times rather than dealing with emergency breakdowns.
Solution Approach 2:
The system implements feedback by continuously comparing current sensor readings and environmental conditions against historical data and expected ranges. When deviations indicate potential failure, the system provides feedback to users through notifications, enabling proactive maintenance scheduling and improving overall device reliability.
2Difficulty of detecting and measuring
If sensors are added to mechanical devices to monitor operating parameters, then failure detection capability improves, but device complexity and cost increase
Solution Approach 1:
The system achieves universality by using a multi-functional platform that can monitor various types of mechanical devices through standardized sensor interfaces. The same core system adapts to different device types (furnaces, water heaters, air conditioners) by adjusting monitoring parameters and thresholds, reducing overall system complexity while maintaining detection capability.
Solution Approach 2:
The system acts as an intermediary between simple sensors and complex failure analysis. Rather than requiring complex sensors built into each device, the system uses basic sensors combined with sophisticated algorithms running on a separate platform to detect failures, thereby reducing device complexity while improving detection capability.
3Measurement precision
If environmental conditions are correlated with sensor data, then accuracy of failure prediction improves, but data processing complexity increases
Solution Approach 1:
The system merges sensor data from the device with environmental condition data from external sources into a unified analysis framework. By combining these data streams and analyzing them together using correlation algorithms, the system improves failure prediction accuracy while managing processing complexity through integrated data handling.
Data Source
AI summary
One embodiment provides a method, including: receiving, from at least one sensor operatively coupled to a mechanical device, sensor data corresponding to a function of the mechanical device; accessing, from an environmental database, information regarding at least one environmental condition in proximity to a geographical location of the mechanical device; generating, using a processor, a correlative value for the mechanical device, wherein the correlative value identifies a correlation between the sensor data corresponding to a function of the mechanical device and the at least one environmental condition; assigning the correlative value as a baseline correlative value to the mechanical device; monitoring the sensor data corresponding to a function of the mechanical device and the at least one environmental condition and updating the correlative value; identifying, using a processor, the correlative value for the mechanical device has exceeded a predetermined threshold as compared to the baseline correlative value; and notifying a user that the correlative value for the mechanical device has exceeded the predetermined threshold. Other aspects are described and claimed.