Analysis of Propagation of Errors Due to Sensor Faults in a Flow Process for Design of Fault Isolation

2018 ◽  
Author(s):  
Santhosh Kv ◽  
Nanditha Nair ◽  
Sneha Nayak
Keyword(s):  
Fault Isolation ◽  
Sensor Faults ◽  
Flow Process ◽  
Propagation Of Errors

scholarly journals Model Based Fuzzy Logic Sensor Fault Accommodation

1997 ◽  
Author(s):  
Timothy A. Healy ◽  
Laura J. Kerr ◽  
Louis J. Larkin
Keyword(s):  
Fuzzy Logic ◽  
Fault Isolation ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Sensor Faults ◽  
Fault Accommodation ◽  
Engine Model ◽  
Dual Channel ◽  
Sensor Channel ◽  
Channel Control

Sensor in-range fault accommodation is a fundamental challenge of dual channel control systems in modem aircraft gas turbine engines. An on-board real-time engine model can be used to provide an analytical third sensor channel which may be used to detect and isolate sensor faults. A fuzzy logic based accommodation approach is proposed which enhances the effectiveness of the analytical third channel in the control system’s fault isolation and accommodation scheme. Simulation studies show the fuzzy accommodation scheme to be superior to current accommodation techniques.

A Unified Nonlinear Approach to Fault Diagnosis of Aircraft Engines

2013 ◽  
Author(s):  
Xiaodong Zhang ◽  
Remus C. Avram ◽  
Liang Tang ◽  
Michael J. Roemer
Keyword(s):  
Fault Detection ◽  
Adaptive Estimation ◽  
Fault Isolation ◽  
Nonlinear Observer ◽  
Aircraft Engines ◽  
Sensor Faults ◽  
Actuator Faults ◽  
Engine Model ◽  
Fault Type ◽  
Component Faults

Many existing aircraft engine diagnostic methods are based on linearized engine models. However, the dynamics of aircraft engines are highly nonlinear and rapidly changing. Future engine health management designs will benefit from new methods that are directly based on intrinsic nonlinearities of the engine dynamics. In this paper, a fault detection and isolation (FDI) method is developed for aircraft engines by utilizing nonlinear adaptive estimation and nonlinear observer techniques. Engine sensor faults, actuator faults and component faults are considered under one unified nonlinear framework. The fault diagnosis architecture consists of a fault detection estimator and a bank of nonlinear fault isolation estimators. The fault detection estimator is used for detecting the occurrence of a fault, while the bank of fault isolation estimators is employed to determine the particular fault type or location after fault detection. Each isolation estimator is designed based on the functional structure of a particular fault type under consideration. Specifically, adaptive estimation techniques are used for designing the isolation estimators for engine component faults and actuator faults, while nonlinear observer techniques are used for designing the isolation estimators for sensor faults. The FDI architecture has been integrated with the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) engine model developed by NASA researchers in recent years. The engine model is a realistic representation of the nonlinear aero thermal dynamics of a 90,000-pound thrust class turbofan engine with high-bypass ratio and a two-spool configuration. Representative simulation results and comparative studies are shown to verify the effectiveness of the nonlinear FDI method.

Sensor fault isolation for DC-DC converters via switched affine systems

2020 ◽  
pp. 095965182093969
Author(s):  
Jian Li ◽  
Kunpeng Pan ◽  
Qingyu Su
Keyword(s):  
Sliding Mode ◽  
Fault Isolation ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Primary Industry ◽  
Affine Systems ◽  
Estimation Function ◽  
Model Observers ◽  
Sliding Mode Observers

The main purpose of this article is to study the sensor fault isolation for DC-DC converters, taking the single-ended primary industry converter as an example. To achieve the purpose of the research, we model the DC-DC converters as switched affine systems and design a bank of sliding mode observers for each corresponding sensor fault. By comparing the threshold with the residual estimation function produced by each sliding model observers, we can diagnose which sensor faults are occurring. Finally, three sensor faults are given as simulation examples to verify the feasibility of the proposed scheme.

scholarly journals An Integrated FDD Approach for an Intensified HEX/Reactor

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Mei Zhang ◽  
Ze-tao Li ◽  
Michel Cabassud ◽  
Boutaïeb Dahhou
Keyword(s):  
High Gain ◽  
Fault Isolation ◽  
Fault Detection And Diagnosis ◽  
Fluid Flow Rate ◽  
Sensor Faults ◽  
Unified Framework ◽  
Isolation And Identification ◽  
Sensor Actuator ◽  
Overall Heat Transfer Coefficient ◽  
Detection And Diagnosis

In this paper, a fault detection and diagnosis (FDD) scheme is developed for a class of intensified HEX/reactor, in which faults caused by sensor, actuator, and process are taken into account in the unified framework. By considering overall heat transfer coefficient as a function of fouling and fluid flow rate, a dynamic model which is capable of identifying these two faults simultaneously is derived. Sensor measurements, together with estimation by adaptive high gain observers, are processed, aimed at identifying sensor faults and providing adequate estimation to substitute faulty measurements. Then reliable measurements are fed to several banks of interval filters to generate several banks of residuals; each bank of residuals is sensitive to a particular process parameter/actuator. By evaluating these residuals, process/actuator fault isolation and identification are achieved. The proposed strategy is applied to actual data retrieved from a new intensified heat exchanger reactor. Simulation results confirm the applicability and robustness of the proposed methodology.

Sensor fault diagnosis in a wastewater treatment process

2006 ◽  
Vol 53 (1) ◽  
pp. 251-257 ◽  
Author(s):  
C. Lee ◽  
S.W. Choi ◽  
I.-B. Lee
Keyword(s):  
Wastewater Treatment ◽  
Treatment Process ◽  
Principal Component ◽  
Early Time ◽  
Previous Method ◽  
Fault Isolation ◽  
Sensor Faults ◽  
Sensor Fault ◽  
Wastewater Treatment Process ◽  
Reconstruction Methods

There are many sensors in a wastewater treatment process (WWTP) plant for monitoring process performance and condition. Sensor validation is essential to the success of process monitoring. In this paper, various sensor faults which can occur in WWTP are identified for taking proper remedial action at an early time. A proposed sensor fault isolation method is based on the variable reconstruction using principal component analysis (PCA). Even though several methods have been developed to identify sensor faults, they are only applicable to a static process. In other words, they cannot be successfully used to monitor severe dynamic processes such as WWTPs. We have removed this limitation by developing reconstruction methods based on a dynamic version of PCA. Artificial scenarios of sensor faults generated from the simulation benchmark have been used to validate the proposed sensor identifying methodology. Also, it is compared to a previous method to show its relative superiority in sensor fault validation in the WWTP.

Fuzzy robust fault estimation scheme for fault tolerant flight control systems based on unknown input observer

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gulay Unal
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fault Detection ◽  
Flight Control ◽  
Fault Tolerant ◽  
Fault Isolation ◽  
Fault Detection And Isolation ◽  
Sensor Faults ◽  
Flight Control System ◽  
Content Type

Purpose The purpose of this study is to present a new integrated structure for a fault tolerant aircraft control system because fault diagnosis of flight control systems is extremely important in obtaining healthy flight. An approach to detect and isolate aircraft sensor faults is proposed, and a new integrated structure for a fault tolerant aircraft control system is presented. Design/methodology/approach As disturbance and sensor faults are mixed together in a flight control system, it is difficult to isolate any fault from the disturbance. This paper proposes a robust unknown input observer for state estimation and fault detection as well as isolation using fuzzy logic. Findings The dedicated observer scheme (DOS) and generalized observer scheme (GOS) are used for fault detection and isolation in an observer-based approach. Using the DOS, it has been shown through simulation that sensor fault detection and isolation can be made, but here the threshold value must be well chosen; if not, the faulty sensor cannot be correctly isolated. On the other hand, the GOS is more usable and flexible than the DOS and allows isolation of faults more correctly and for a fuzzy logic-based controller to be used to realize fault isolation completely. Originality/value The fuzzy logic approach applied to the flight control system adds an important key for sensor fault isolation because it reduces the effect of false alarms and allows the identification of different kinds of sensor faults. The proposed approach can be used for similar systems.

Model Based Fuzzy Logic Sensor Fault Accommodation

1998 ◽  
Vol 120 (3) ◽  
pp. 533-536 ◽  
Author(s):  
T. A. Healy ◽  
L. J. Kerr ◽  
L. J. Larkin
Keyword(s):  
Fuzzy Logic ◽  
Fault Isolation ◽  
Turbine Engines ◽  
Gas Turbine Engines ◽  
Sensor Faults ◽  
Fault Accommodation ◽  
Engine Model ◽  
Dual Channel ◽  
Sensor Channel ◽  
Channel Control

Sensor in-range fault accommodation is a fundamental challenge of dual channel control systems in modern aircraft gas turbine engines. An on-board, real-time engine model can be used to provide an analytical third sensor channel that may be used to detect and isolate sensor faults. A fuzzy-logic-based accommodation approach is proposed that enhances the effectiveness of the analytical third channel in the control system’s fault isolation and accommodation scheme. Simulation studies show the fuzzy accommodation scheme to be superior to current accommodation techniques.

scholarly journals A Method for the Diagnosis of Gas Turbine Sensor Faults in Presence of Measurement Noise

1999 ◽  
Author(s):  
R. Bettocchi ◽  
P. R. Spina
Keyword(s):  
Time Series ◽  
Fault Detection ◽  
Gas Turbine ◽  
Digital Filters ◽  
Fault Isolation ◽  
Measurement Noise ◽  
Canonical Structure ◽  
Sensor Faults ◽  
Single Output ◽  
Auto Regressive

This paper presents a method for the detection and isolation of single gas turbine sensor faults, in presence of model inaccuracy and measurement noise. The method uses a fault matrix with a column-canonical structure (i.e., each matrix column having the same number of zeroes, but in different positions), in order to obtain the unambiguous fault isolation. The fault matrix was obtained by using a number of ARX (Auto Regressive exogenous) MISO (Multi-Input/Single-Output) models equal to the number of measured gas turbine outputs, each model calculating an estimate of one measurable output as a function of other inputs or outputs measured on the machine. Moreover, in order to reduce the threshold of fault detection and, therefore, the minimal detectable faults, digital filters were used, applied to the time series of data measured on the machine and computed by the models. Finally, tests were performed in order to find the minimal sensor faults that can be detected and isolated.

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