[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Razakarivony et al., 2025 - Google Patents

A Comprehensive Literature Review on the Resolution of Turbine Engine Performances' Inverse Problems

Razakarivony et al., 2025

View PDF
Document ID
15787100147133846700
Author
Razakarivony S
Marnissi Y
Nocture M
Publication year
Publication venue
Journal of Engineering for Gas Turbines and Power

External Links

Snippet

Turbine engine monitoring is a well-known and well-studied subject that proves to be essential for the aeronautic industry. A popular approach in engine monitoring is constructing indicators that reflect systems' health states by leveraging operational …
Continue reading at asmedigitalcollection.asme.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
    • G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
    • G05B23/0254—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0275—Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
    • G05B23/0278—Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models

Similar Documents

Publication Publication Date Title
Hanachi et al. Performance-based gas turbine health monitoring, diagnostics, and prognostics: A survey
Wei et al. Gas turbine aero-engines real time on-board modelling: A review, research challenges, and exploring the future
Rahme et al. Adaptive sliding mode observer for sensor fault diagnosis of an industrial gas turbine
Xu et al. Improved hybrid modeling method with input and output self-tuning for gas turbine engine
Volponi et al. Development of an information fusion system for engine diagnostics and health management
Vanini et al. Fault detection and isolation of a dual spool gas turbine engine using dynamic neural networks and multiple model approach
Ntantis et al. Diagnostic Methods for an Aircraft Engine Performance.
Nyulászi et al. Fault detection and isolation of an aircraft turbojet engine using a multi-sensor network and multiple model approach
Borguet et al. Coupling principal component analysis and Kalman filtering algorithms for on-line aircraft engine diagnostics
Hanachi et al. Hybrid sequential fault estimation for multi-mode diagnosis of gas turbine engines
Lu et al. Hybrid state estimation for aircraft engine anomaly detection and fault accommodation
Jin et al. Life cycle gas path performance monitoring with control loop parameters uncertainty for aeroengine
Lu et al. Gas path on-line fault diagnostics using a nonlinear integrated model for gas turbine engines
Sun et al. Fault detection for aircraft turbofan engine using a modified moving window KPCA
Liu et al. Aero-engine health degradation estimation based on an underdetermined extended Kalman filter and convergence proof
Ullah et al. An investigation of exhaust gas temperature of aircraft engine using LSTM
Xu et al. An adaptive on-board real-time model with residual online learning for gas turbine engines using adaptive memory online sequential extreme learning machine
Loboda et al. A benchmarking analysis of a data-driven gas turbine diagnostic approach
Feng et al. A multi-rate sensor fusion approach using information filters for estimating aero-engine performance degradation
Liu et al. A digital twin modeling method for turbofan engine real-time test data analysis and performance monitoring
Fentaye et al. Hybrid model-based and data-driven diagnostic algorithm for gas turbine engines
Devakumar et al. Critical measurement parameters estimation in liquid rocket engine using LSTM-based soft sensor
Wang et al. Direct thrust control for variable cycle engine based on fractional order PID-nonlinear model predictive control under off-nominal operation conditions
Wang et al. A multi-input based full envelope acceleration schedule design method for gas turbine engine based on multilayer perceptron network
Razakarivony et al. A Comprehensive Literature Review on the Resolution of Turbine Engine Performances’ Inverse Problems