Rotor Vibration Adjustment via Sensor Data Matching
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Solution Overview
Problem
Current methods for reducing vibrations in helicopter rotors, such as rotor trimming and mechanical balancing, face challenges in diagnosing and correcting uneven air loads and mass imbalances, leading to ambiguity in interpreting vibration data and requiring cumbersome user input for optimization techniques.
Innovation Solution
A computer-implemented method evaluates current sensor data to select the best match from pre-determined sets of sensor data, associated with option sets for adjusting rotor blades, using normalized distances weighted by covariance and preference to determine optimal adjustments for reducing vibrations, including weight, pitch control rod, and tab adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If trial and error methods of rotor trimming are used to adjust blade weights, tabs, and pitch control rods, then vibration reduction may be achieved, but the process becomes cumbersome and may not converge to an acceptable state due to interdependence of adjustments
Solution Approach 1:
The system pre-calculates and stores optimal adjustment settings for various vibration conditions in a database. When vibration data is received, the system queries the database for pre-determined adjustments rather than performing trial and error, eliminating the need for iterative manual adjustments while accounting for the interdependence of blade weight, tab, and pitch control rod adjustments
Solution Approach 2:
The system uses measured vibration data from sensors as feedback to query the database and determine appropriate adjustments. This closed-loop approach ensures that adjustments are based on actual vibration measurements rather than guesswork, improving convergence to an acceptable state while reducing operational complexity
2Measurement precision
If optical tracking methods are used to make blade tracks identical, then tracking faults are corrected, but the interpretation of vibration signatures becomes ambiguous due to inadequate channel processing
Solution Approach 1:
The system processes multiple types of sensor data (vibration, tracking, shaft phase reference) through a unified database query approach. The same database stores and retrieves information for multiple data types, allowing the system to handle diverse sensor inputs without the ambiguity of separate processing channels while maintaining accurate interpretation of vibration signatures
3Reliability
If QR decomposition and constrained optimization techniques are used to determine adjustments, then vibration reduction can be calculated, but the operator must provide multiple input selections making the process intimidating for inexperienced users
Solution Approach 1:
The system automatically queries the database using measured vibration data without requiring the operator to manually select optimization goals, sensor data types, or other complex parameters. The database self-services by providing appropriate adjustments based on the vibration condition, eliminating the need for inexperienced users to understand complex optimization techniques while maintaining calculation accuracy
Data Source
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AI summary
Described are techniques for selecting options used with current sensor data characterizing vibration caused by rotating blades. Sets of other sensor data are evaluated to determine a first of the sets of other sensor data that is a best match for said current sensor data. Each of the sets of other sensor data is associated with one of a plurality of option sets. Each option set includes options used in determining one or more adjustments that may be applied to the blades to reduce vibration. The one or more sets of other sensor data are evaluated to determine a first of the sets of other sensor data that is a best match for said current sensor data. A first of the plurality of option sets associated with said first set of sensor data is used in determining adjustment(s) that may be applied to the blades.