Failure Detection Device Using Condition-Based Data Mapping
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Solution Overview
Problem
Existing failure detection systems for machines struggle with accurately identifying issues in real-time due to noisy and inaccurate sensor data, often leading to delayed detection and increased downtime, as they do not effectively account for various operational issues or facilitate preventative maintenance.
Innovation Solution
A failure detection device that processes operations data using a condition-based processing technique, which maps initial values to mapped values based on satisfaction of thresholds, detects possible issues by analyzing these mapped values over time, and triggers alarms and actions to address the issues, thereby reducing noise and improving detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional failure detection systems use sensor data directly, then the system structure is simple, but the detection accuracy is low due to noisy and inaccurate data
Solution Approach 1:
The patent segments the failure detection process into distinct processing stages: data collection from sensors, noise filtering, pattern recognition, and failure determination. Each stage processes specific aspects of the data independently, improving detection accuracy while maintaining manageable system complexity through modular processing steps.
Solution Approach 2:
The system performs preliminary actions by collecting and preprocessing sensor data before actual failure detection occurs. It continuously monitors and filters data in advance, so when a failure condition arises, the system can quickly identify it using pre-processed information rather than raw noisy data, thereby improving detection accuracy without proportionally increasing complexity.
2Loss of time
If failure detection waits for significant impact, then the detection system is simpler, but the loss of time increases due to machine downtime
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors sensor data, compares it against established patterns and thresholds, and adjusts its detection criteria based on accumulated information. This continuous feedback loop enables early detection of developing issues before they cause significant machine impact, reducing downtime while maintaining reliable identification through adaptive pattern recognition.
Solution Approach 2:
The system performs preliminary detection actions by continuously analyzing sensor data for early signs of failure patterns before actual breakdown occurs. It establishes baseline patterns during normal operation and detects deviations in advance, enabling proactive maintenance scheduling that reduces downtime while ensuring reliable issue identification through continuous monitoring.
3Adaptability or versatility
If the system monitors multiple operational parameters, then the detection coverage is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent segments the monitoring of multiple operational parameters by assigning specific sensors to detect particular conditions (voltage for spark plugs, temperature for turbine inlets, etc.). Each sensor and processing module focuses on specific parameters independently, then integrates results for comprehensive detection coverage without overwhelming processing complexity through structured modular monitoring.
Solution Approach 2:
The system uses pattern recognition algorithms as intermediaries that translate complex multi-parameter sensor data into interpretable failure patterns. These intermediary processing layers convert raw data from multiple sources into standardized diagnostic information, expanding detection coverage across various machine components while managing processing difficulty through abstraction and pattern standardization.
Data Source
AI summary
A failure detection device is disclosed. The failure detection device may receive operations data related to operations of a set of parts of a machine. The failure detection device may process the operations data using a condition-based processing technique. The condition-based processing technique may be associated with mapping initial values of data elements of the operations data to binary values based on satisfaction of a first set of conditions by the initial values. The failure detection device may detect a presence of a possible issue with the operations of the set of parts based on a second set of conditions, associated with the binary values and the initial values, being satisfied during a time period. The failure detection device may perform, after detecting the presence of the possible issue, a set of actions related to addressing the possible issue.