Coaxial Rotary Wing Abnormality Detection via Correlation Analysis
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Solution Overview
Problem
Existing unmanned rotorcraft with coaxially disposed rotary wing units face challenges in accurately detecting abnormalities, as the interdependence of these wings complicates individual fault detection.
Innovation Solution
An abnormality detection device and control system that acquires correlations between operation parameters during normal and abnormal operations, allowing for precise detection of issues by comparing actual operational data against pre-accumulated normal operation patterns, and includes a controller to perform necessary control actions upon detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If individual monitoring of each rotary wing is performed, then simple detection method is used, but abnormality detection accuracy deteriorates due to interdependence of coaxially disposed wings
Solution Approach 1:
The patent combines the monitoring of multiple rotary wings into a unified detection system that evaluates the collective behavior of coaxially disposed wings. By merging individual wing parameters into a comprehensive operational pattern analysis, the system achieves accurate abnormality detection while avoiding the complexity of individual fault isolation.
Solution Approach 2:
The detection system is designed to handle multiple functions: monitoring individual rotary wings, detecting abnormalities in coaxially disposed wings, and identifying operational patterns. This multi-functional approach allows a single system to address various detection needs without requiring separate specialized devices for each function.
2Measurement precision
If correlation-based detection method is implemented, then abnormality detection accuracy is improved, but computational complexity and data processing requirements increase
Solution Approach 1:
The system performs preliminary accumulation of operational patterns during normal operation phases, storing baseline correlation data before actual abnormality detection is needed. This preliminary action reduces the computational burden during critical detection phases, as the heavy lifting of pattern establishment is completed in advance during routine operations.
Solution Approach 2:
The detection system continuously compares actual operational parameters against accumulated operational patterns, providing feedback that guides further detection efforts. This feedback mechanism allows the system to focus computational resources on identifying deviations from normal patterns rather than processing all data equally, thereby reducing overall computational complexity.
Data Source
AI summary
Provided is an abnormality detection device for a rotary wing unit. The rotary wing unit includes a plurality of rotary wings that is coaxially disposed. The abnormality detection device includes a controller configured to acquire at least one of a correlation at the time of normal operation between operation parameters related to the rotary wings and a correlation at the time of abnormal operation between the operation parameters and detect abnormality of the rotary wing unit, based on a correlation at the time of actual operation between the operation parameters and at least one of the correlation at the time of normal operation and the correlation at the time of abnormal operation.