Wyniki wyszukiwania - BazTech

1

Gas turbine vibration monitoring based on real data and neuro-fuzzy system

Nail Bachir, Djaidir Benrabeh, Tibermacine Imad Eddine, Napoli Christian, Haidour Nabil, Abdelaziz Rabehi

Diagnostyka

|

2024

|

Vol. 25, No. 1

art. no. 2024108

EN

The gas turbine is considered to be a very complex piece of machinery because of both its static structure and the dynamic behavior that results from the occurrence of vibration phenomena. It is required to adopt monitoring and diagnostic procedures for the identification and localization of vibration flaws in order to ensure the appropriate operation of large rotating equipment such as gas turbines. This is necessary in order to avoid catastrophic failures and deterioration and to ensure that proper operation occurs. Utilizing an approach that is based on spectrum analysis, the purpose of this study is to provide a model for the monitoring and diagnosis of vibrations in a GE MS3002 gas turbine and its driven centrifugal compressor. This will be done by utilizing the technique. Following that, the collection of vibration measurements for a model of the centrifugal compressor served as a suggestion for an additional method. This method is based on the neuro-fuzzy approach type ANFIS, and it aims to create an equivalent system that is able to make decisions without consulting a human being for the purpose of detecting vibratory defects. In spite of the fact that the compressor that was investigated has flaws, this procedure produced satisfactory results.

2

Fault detection and diagnosis of squirrel cage asynchronous motor using a new COMSOL multiphysics software 6.0.

Djaidir Benrabeh, Nail Bachir, Rouibah Abdelkader

Diagnostyka

|

2024

|

Vol. 25, No. 1

art. no. 2024102

EN

In this paper, the diagnosis of faults in squirrel cage asynchronous motor and experimental analysis process are presented. Currently there are several simulation tools, that lets users analyze and interpret the behavior of their devices. Based on this, there is a lot of researches that is working on developing models, to detect and classify 3-phase asynchronous motor faults, significantly in the early stages. This work proposed design and experimental analysis established in Comsol Multiphysics 6.0 , which implements finite element analysis software (FEM) for detecting and diagnosing broken bar rotors of this types motors and its practical application. In this case, the post processor of the COMSOL-Multiphysics makes it possible to visualize in 2D the various magnetic and mechanical quantities. Through the curves of the magnetic flux density and analysis distribution of the field with magnetic induction lines, we can draw some conclusions, where we proposed an strategy, for detecting and diagnosing faults consistent with the structure of the software.

3

On the block decomposition and spectral factors of λ-matrices

Bekhiti Belkacem, Nail Bachir, Dahimene Abdelhakim, Hariche Kamel, Fragulis George F.

Control and Cybernetics

|

2020

|

Vol. 49, No. 1

41--76

EN

In this paper we have factorized matrix polynomials into a complete set of spectral factors using a new design algorithm, and with some systematic procedures a complete set of block roots (solvents) have been obtained. The newly developed procedure is just an extension of the (scalar) Horner method to its block form for use in the computation of the block roots of matrix polynomial, the block-Horner method bringing a local iterative nature, faster convergence, nested programmable scheme, needless of any prior knowledge of the matrix polynomial, with the only one inconvenience, which is the strong dependence on the initial guess. In order to avoid this trap, we proposed a combination of two computational procedures, for which the complete program starts with the right block-Q.D. algorithm. It is then followed by a refinement of the right factor by block-Horner’s algorithm. This results in the global nature of the program, which is faster in execution, has well defined initial conditions, and good convergence in much less time.

4

A robust fault diagnosis and forecasting approach based on Kalman filter and interval type-2 fuzzy logic for efficiency improvement of centrifugal gas compressor system

Nail Bachir, Kouzou Abdellah, Hafaifa Ahmed, Hadroug Nadji, Puig Vicenç

Diagnostyka

|

2019

|

Vol. 20, No. 2

57--75

EN

The paper proposes a robust faults detection and forecasting approach for a centrifugal gas compressor system, the mechanism of this approach used the Kalman filter to estimate and filtering the unmeasured states of the studied system based on signals data of the inputs and the outputs that have been collected experimentally on site. The intelligent faults detection expert system is designed based on the interval type-2 fuzzy logic. The present work is achieved by an important task which is the prediction of the remaining time of the system under study to reach the danger and/or the failure stage based on the Auto-regressive Integrated Moving Average (ARIMA) model, where the objective within the industrial application is to set the maintenance schedules in precisely time. The obtained results prove the performance of the proposed faults diagnosis and detection approach which can be used in several heavy industrial systems.