Gas Turbine Rotor Balancing via Component Stacking Optimization
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Solution Overview
Problem
Gas turbine engines face challenges in balancing rotary components, leading to vibration issues due to concentricity and parallelism deviations, which are not effectively addressed by existing methods, resulting in time-consuming and resource-intensive re-balancing processes.
Innovation Solution
A method involving the measurement of concentricity and parallelism of main and intermediate components, generating assembly unbalance for various stacking positions, and determining optimal stacking positions to minimize overall unbalance, using a computer-processed iterative optimization process to align components for minimal imbalance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional assembly methods are used without precise measurement and optimization, then assembly process is simpler and faster, but rotor assembly unbalance and vibration increase
Solution Approach 1:
The patent applies preliminary action by measuring concentricity and parallelism of individual components before assembly, and calculating optimal stacking positions in advance using a computer system. This pre-planning allows components to be assembled in predetermined positions that minimize assembly unbalance, avoiding the need for time-consuming re-balancing operations after assembly.
Solution Approach 2:
The patent implements feedback by using measured geometric data (concentricity and parallelism deviations) to calculate and determine optimal stacking positions. The measurement results directly inform the positioning decisions, creating a closed-loop process where actual component variations are compensated through intelligent arrangement, thereby minimizing overall assembly unbalance.
2Reliability
If components are assembled without optimizing stacking positions, then assembly process is quicker, but vibration acceptance test failure rate increases leading to re-balancing
Solution Approach 1:
The system performs preliminary calculation of optimal stacking positions based on measured component geometry before assembly. By determining the best arrangement in advance, the patent ensures high probability of passing vibration acceptance tests on first attempt, eliminating time-consuming re-balancing and re-testing cycles.
Solution Approach 2:
The patent creates a digital model or representation of component geometric variations through measurement, and uses this copied information to calculate optimal stacking positions. This virtual modeling allows prediction and optimization of assembly balance without physical trial-and-error, saving significant time and resources.
3Manufacturing precision
If precise measurement of concentricity and parallelism is performed, then assembly unbalance is minimized, but measurement complexity and time increase
Solution Approach 1:
The patent employs measurement devices that can simultaneously measure multiple geometric parameters (concentricity and parallelism) of different components. This multi-functional measurement capability reduces overall measurement time and complexity while providing comprehensive data needed for optimal stacking position calculation.
Solution Approach 2:
The patent replaces complex manual measurement and calculation processes with an automated computer system. The computer receives measurement data, performs iterative optimization calculations, and determines optimal stacking positions automatically, substituting mechanical/manual operations with computational processes that are faster and more accurate.
4Manufacturing precision
If iterative optimization process is used to determine stacking positions, then assembly unbalance is significantly reduced, but computational complexity increases
Solution Approach 1:
The patent replaces complex iterative optimization calculations with a computer-based computational system. The computer efficiently performs the iterative process by receiving measurement data, evaluating different stacking configurations, and identifying optimal positions through algorithmic processing, making the complex computation practical and efficient.
Solution Approach 2:
The patent changes the state of component positioning parameters to minimize assembly unbalance. By systematically varying stacking positions based on measured geometric parameters and using computer optimization, the system identifies the parameter combination (stacking positions) that achieves minimum assembly unbalance.
Data Source
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AI summary
A method of balancing an assembly of rotary parts of a gas turbine engine (10) comprising measuring at least one of the concentricity and parallelism of each component and considering globally all possible component stacking positions to generate an optimized stacking position for each component of the assembly to minimize assembly unbalance.