Turbine Blade Damage Evaluation via Dynamic Survival Rate Modeling
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Solution Overview
Problem
Conventional methods for predicting blade damage in turbines due to solid particle erosion (SPE) are inadequate for dynamically changing operating conditions, requiring frequent and extensive inspections, which is impractical for adjustable thermal power operations.
Innovation Solution
A blade damage evaluation system utilizing computers to acquire and analyze design, maintenance, and operation data from sensors, calculating a survival rate to predict when the erosion amount of turbine blades will not exceed a predetermined threshold, allowing for accurate damage assessment under varying conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional thickness-loss measurement methods are used during major inspections, then blade damage can be assessed, but a considerable number of processes and construction period are required
Solution Approach 1:
The patent replaces mechanical measurement methods (physical thickness measurements during inspections) with an information processing system that uses sensors, data acquisition units, and prediction algorithms to calculate blade thickness-loss amounts based on operational data, thereby eliminating the need for time-consuming physical inspections
Solution Approach 2:
The patent creates a virtual model of blade degradation by collecting and processing operational data (temperature, pressure, flow rates) to simulate and predict thickness-loss amounts, allowing assessment without physical measurement
2Adaptability or versatility
If conventional prediction methods based on baseload operation are used, then thickness-loss can be estimated, but they cannot be applied to dynamically changing operating conditions such as adjustable thermal power operations
Solution Approach 1:
The patent transitions from static prediction models (based on fixed baseload conditions) to dynamic prediction models that continuously update thickness-loss calculations based on real-time operational data including temperature, pressure, and flow rate variations, enabling accurate predictions under dynamically changing conditions
Solution Approach 2:
The patent changes the operational parameters used in prediction from fixed baseload values to variable parameters that reflect actual operating conditions, allowing the system to adapt to different load levels and operational modes while maintaining prediction accuracy
3Reliability
If frequent inspections are conducted to accurately assess blade damage, then prediction reliability improves, but productivity and operational efficiency decrease
Solution Approach 1:
The patent implements continuous monitoring and prediction by continuously collecting operational data from sensors and continuously updating thickness-loss predictions, replacing intermittent inspections with ongoing assessment that maintains high reliability without disrupting operations
Solution Approach 2:
The patent establishes a feedback loop where operational data is continuously fed into the prediction system, which updates thickness-loss estimates and provides ongoing assessments, allowing reliable prediction without frequent stoppages for inspection
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate and timely evaluation of blade damage, improving operational efficiency and reducing maintenance costs by providing a predictive model for blade replacement and maintenance planning under dynamic operating conditions.
Implementation Method 1
acquire operation data related to respective operating states of the turbine and the peripheral component from sensors that are provided in the turbine and the peripheral component
Implementation Method 2
When the solid particles mixed in the steam or gas collide with the surfaces of the respective blades, the blades are thinned from the surfaces. This is due to occurrence of SPE (Solid Particle Erosion), i.e., phenomenon in which the surface is eroded or worn by the collision of the solid particles
Data Source
AI summary
According to one embodiment, a blade damage evaluation system comprising one or more computers configured to: evaluate inflow and collision of solid particles into a turbine based on design data, maintenance data, and operation data; and calculate a survival rate by applying at least one data included in at least one of the design data, the maintenance data, and the operation data as at least one factor to a formula that models the turbine by survival time analysis, the survival rate indicating that erosion amount of at least one of a plurality of blades does not reach a predetermined threshold at arbitrary time in future.