Gas Turbine Fault Identification by Fusing Vibration Trending and Gas Path Analysis

2009 ◽  
Author(s):  
A. Kyriazis ◽  
A. Tsalavoutas ◽  
K. Mathioudakis ◽  
M. Bauer ◽  
O. Johanssen
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Fault Identification ◽  
Sources Of Information ◽  
Vibration Measurements ◽  
Data Process ◽  
Diagnostic Decision ◽  
Turbine Component ◽  
Different Sources ◽  
Health Parameters

A fusion method that utilizes performance data and vibration measurements for gas turbine component fault identification is presented. The proposed method operates during the diagnostic processing of available data (process level) and adopts the principles of certainty factors theory. Both performance and vibration measurements are analyzed separately, in a first step, and their results are transformed into a common form of probabilities. These forms are interweaved, in order to derive a set of possible faulty components prior to deriving a final diagnostic decision. Then, in the second step, a new diagnostic problem is formulated and a final set of faulty health parameters are defined with higher confidence. In the proposed method the non-linear gas path analysis is the core diagnostic method, while information provided by vibration measurements trends is used to narrow the domain of unknown health parameters and lead to a well defined solution. It is shown that the presented technique combines effectively different sources of information, by interpreting them into a common form and may lead to improved and safer diagnosis.

Enhanced Fault Localization Using Probabilistic Fusion With Gas Path Analysis Algorithms

2009 ◽  
Vol 131 (5) ◽  
Author(s):  
A. Kyriazis ◽  
K. Mathioudakis
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Fault Localization ◽  
Fault Identification ◽  
Diagnostic Problem ◽  
Two Stage ◽  
Precise Location ◽  
Stage Process ◽  
Engine Components ◽  
Probabilistic Fusion

A method for gas turbine fault identification from gas path data, in situations with a limited number of measurements, is presented. The method consists of a two stage process: (a) localization of the component or group of components with a fault and (b) fault identification by determining the precise location and magnitude of component performance deviations. The paper focuses on methods that allow improved localization of the faulty components. Gas path analysis (GPA) algorithms are applied to diagnostic sets comprising different combinations of engine components. The results are used to derive fault probabilities, which are then fused to derive a conclusion as to the location of a fault. Once the set of possible faulty components is determined, a well defined diagnostic problem is formulated and the faulty parameters are determined by means of a suitable algorithm. It is demonstrated that the method has an improved effectiveness when compared with previous GPA based methods.

Enhanced Fault Localization Using Probabilistic Fusion With Gas Path Analysis Algorithms

2008 ◽  
Author(s):  
A. Kyriazis ◽  
K. Mathioudakis
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Fault Localization ◽  
Fault Identification ◽  
Diagnostic Problem ◽  
Two Stage ◽  
Precise Location ◽  
Stage Process ◽  
Engine Components ◽  
Probabilistic Fusion

A method for gas turbine fault identification from gas path data, in situations with a limited number of measurements, is presented. The method consists of a two stage process: (a) localization of the component or group of components where the fault is located and (b) fault identification, by determining the precise location and magnitude of component performance deviations. The paper focuses on methods that allow improved localization of the faulty components. Gas path analysis algorithms are applied to diagnostic sets comprising different combinations of engine components. The results are used to derive fault probabilities, which are then fused to derive a conclusion as to the location of a fault. Once the set of possible faulty components is determined, a well defined diagnostic problem is formulated and the faulty parameters are determined by means of a suitable algorithm. It is demonstrated that the method has an improved effectiveness when compared to previous GPA based methods.

Determinants Considered by Consumers for Brand Selection - with Reference to Laptops in Albania

2014 ◽  
Vol 4 (2) ◽  
Author(s):  
Margret Plloçi ◽  
Macit Koc
Keyword(s):  
Primary Data ◽  
Battery Life ◽  
Decision Making Process ◽  
Light Weight ◽  
Sources Of Information ◽  
Technical Features ◽  
The Relationship ◽  
The City ◽  
Different Sources ◽  
Core Features

Abstract Purpose of the article There is relatively a big number of brands in the market of laptops nowadays in Albania. It appears that the number of brands offered in this market could easily be compared to the number of brands in Europe and even broader. The purpose of this study is to help Albanian vendors understand the criteria that consumers take into consideration when they make the decision to purchase a laptop. Methodology/methods The research is based on the collection and the analyses of the primary data collected through interviews to people like managers or employees who work in the sector of trading laptops or in businesses like education where laptops are broadly used recently; then a survey is done through a questionnaire delivered to customers who already own and use a laptop and customers who are potential buyers of laptops. Scientific aim The aim of the research is to identify if there are any relationships between the demographics of the consumers and the criteria of buying a laptop; on the other hand, to find out how is the relationship between the demographics and the features of different brands. Findings The study found out that Albanian consumers have good knowledge of laptops and their brands, and they use different sources of information for making their decisions in buying a laptop; it is found that there are relationships between some demographics like age or gender and the appraisal for some attributes of the laptops like price, design and high graphics card; it is also found that some technical features and other attributes of using laptops are some of the determinants that influence the laptops’ purchases. Conclusions It is realized that one of the most important demographics of the consumers is their age. Some core features like RAM, ROM, battery life, processor quality, light weight or attributes that are connected to the purposes of using the laptop computers like practicality and mobility in using them, work and studying processes, quick access to the internet are determinant factors which influence the decision making process of purchasing a laptop. I would recommend that future researches be focused also on the relationship between the customers’ income and their preferred brand or ranking brands according to the customers’ preferences. Such studies should also extend outside the city of Tirana.

Feature-based multi-criteria recommendation system using a weighted approach with ranking correlation

2021 ◽  
Vol 25 (4) ◽  
pp. 1013-1029
Author(s):  
Zeeshan Zeeshan ◽  
Qurat ul Ain ◽  
Uzair Aslam Bhatti ◽  
Waqar Hussain Memon ◽  
Sajid Ali ◽  
...  
Keyword(s):  
Recommendation System ◽  
Sources Of Information ◽  
Multiple Features ◽  
Recommendation Algorithms ◽  
Label Correlations ◽  
Feature Based ◽  
Multicriteria Model ◽  
Implicit And Explicit ◽  
Hybrid Recommendation ◽  
Different Sources

With the increase of online businesses, recommendation algorithms are being researched a lot to facilitate the process of using the existing information. Such multi-criteria recommendation (MCRS) helps a lot the end-users to attain the required results of interest having different selective criteria – such as combinations of implicit and explicit interest indicators in the form of ranking or rankings on different matched dimensions. Current approaches typically use label correlation, by assuming that the label correlations are shared by all objects. In real-world tasks, however, different sources of information have different features. Recommendation systems are more effective if being used for making a recommendation using multiple criteria of decisions by using the correlation between the features and items content (content-based approach) or finding a similar user rating to get targeted results (Collaborative filtering). To combine these two filterings in the multicriteria model, we proposed a features-based fb-knn multi-criteria hybrid recommendation algorithm approach for getting the recommendation of the items by using multicriteria features of items and integrating those with the correlated items found in similar datasets. Ranks were assigned to each decision and then weights were computed for each decision by using the standard deviation of items to get the nearest result. For evaluation, we tested the proposed algorithm on different datasets having multiple features of information. The results demonstrate that proposed fb-knn is efficient in different types of datasets.

A comparative study of data-driven and physics-based gas turbine fault recognition approaches

2021 ◽  
pp. 1748006X2198964
Author(s):  
Juan Luis Pérez-Ruiz ◽  
Igor Loboda ◽  
Iván González-Castillo ◽  
Víctor Manuel Pineda-Molina ◽  
Karen Anaid Rendón-Cortés ◽  
...  
Keyword(s):  
Anomaly Detection ◽  
Gas Turbine ◽  
Recognition Accuracy ◽  
Data Driven ◽  
Fault Identification ◽  
Fault Recognition ◽  
Data Driven Approach ◽  
Diagnostic Approaches ◽  
Artificial Neural Network Ann ◽  
Two Stages

The present paper compares the fault recognition capabilities of two gas turbine diagnostic approaches: data-driven and physics-based (a.k.a. gas path analysis, GPA). The comparison takes into consideration two differences between the approaches, the type of diagnostic space and diagnostic decision rule. To that end, two stages are proposed. In the first one, a data-driven approach with an artificial neural network (ANN) that recognizes faults in the space of measurement deviations is compared with a hybrid GPA approach that employs the same type of ANN to recognize faults in the space of estimated fault parameter. Different case studies for both anomaly detection and fault identification are proposed to evaluate the diagnostic spaces. They are formed by varying the classification, type of diagnostic analysis, and deviation noise scheme. In the second stage, the original GPA is reconstructed replacing the ANN with a tolerance-based rule to make diagnostic decisions. Here, two aspects are under analysis: the comparison of GPA classification rules and whole approaches. The results reveal that for simple classifications both spaces are equally accurate for anomaly detection and fault identification. However, for complex scenarios, the data-driven approach provides on average slightly better results for fault identification. The use of a hybrid GPA with ANN for a full classification instead of an original GPA with tolerance-based rule causes an increase of 12.49% in recognition accuracy for fault identification and up to 54.39% for anomaly detection. As for the whole approach comparison, the application of a data-driven approach instead of the original GPA can lead to an improvement of 12.14% and 53.26% in recognition accuracy for fault identification and anomaly detection, respectively.

Modelling of Coating Thickness, Heat Transfer and Fluid Flow and It's Correlation with the TBC Microstructure for a Plasma Sprayed Gas Turbine Application

1998 ◽  
Author(s):  
P. Nylen ◽  
J. Wigren ◽  
L. Pejryd ◽  
M.-O. Hansson
Keyword(s):  
Heat Transfer ◽  
Fluid Flow ◽  
Gas Turbine ◽  
Coating Thickness ◽  
Spray Deposition ◽  
Temperature History ◽  
Particle Model ◽  
Barrier Coating ◽  
Discrete Particle Model ◽  
Turbine Component

Abstract The plasma spray deposition of a zirconia thermal barrier coating (TBC) on a gas turbine component has been examined using analytical and experimental techniques. The coating thickness was simulated by the use of commercial off-line programming software. The impinging jet was modelled by means of a finite difference elliptic code using a simplified turbulence model. Powder particle velocity, temperature history and trajectory were calculated using a stochastic discrete particle model. The heat transfer and fluid flow model were then used to calculate transient coating and substrate temperatures using the finite element method. The predicted thickness, temperature and velocity of the particles and the coating temperatures were compared with these measurements and good correlations were obtained. The coating microstructure was evaluated by optical and scanning microscopy techniques. Special attention was paid to the crack structures within the top coating. Finally, the correlation between the modelled parameters and the deposit microstructure was studied.

Dependence of LPBF Surface Roughness on Laser Incidence Angle and Component Build Orientation

2021 ◽  
Author(s):  
Ramesh Subramanian ◽  
David Rule ◽  
Onur Nazik
Keyword(s):  
Surface Roughness ◽  
Gas Turbine ◽  
High Efficiency ◽  
Surface Defects ◽  
Incidence Angle ◽  
Turbine Component ◽  
Potential Applicability ◽  
Process Qualification ◽  
Process Signature ◽  
Manufacturing Technologies

Abstract Laser Powder Bed Fusion (LPBF) of metallic components is unlocking new design options for high efficiency gas turbine component designs not possible by conventional manufacturing technologies. Surface roughness is a key characteristic of LPBF components that impacts heat transfer correlations and crack initiation from co-located surface defects — both are critical for gas turbine component durability and performance. However, even for a single material, there is an increasing diversity in laser machines (single vs multi-laser), layer thicknesses (∼20–80 microns) and orientations to the build plate (upskin, vertical and downskin) that result in significant variability in surface roughness. This study systematically compares the surface roughness across the above-mentioned variables to further develop a repeatable correlation of surface roughness to the angle between the substrate normal and laser incidence direction. This presented data will be discussed in detail, to show potential applicability of this process signature curve across materials, machines, and substrate orientations. Future steps to a rapid process qualification standard for surface roughness, across Siemens Energy’s global manufacturing footprint will also be discussed.

scholarly journals Microstructure and Properties of a Repair Weld in a Nickel Based Superalloy Gas Turbine Component

2017 ◽  
Vol 17 (2) ◽  
pp. 55-63 ◽  
Author(s):  
Ł. Rakoczy ◽  
M. Grudzień ◽  
L. Tuz ◽  
K. Pańcikiewicz ◽  
A. Zielińska-Lipiec
Keyword(s):  
Electron Microscopy ◽  
Gas Turbine ◽  
Arc Welding ◽  
Aged Condition ◽  
Hastelloy X ◽  
Gas Tungsten Arc ◽  
Nickel Based Superalloy ◽  
Transmission Electron ◽  
Turbine Component ◽  
Scanning Electron

AbstractThe aim of the present study was to characterize the repair weld of serviced (aged) solid-solution Ni-Cr-Fe-Mo alloy: Hastelloy X. The repair welding of a gas turbine part was carried out using Gas Tungsten Arc Welding (GTAW), the same process as for new parts. Light microscopy, scanning electron microscopy, transmission electron microscopy, microhardness measurements were the techniques used to determine the post repair condition of the alloy. Compared to the solution state, an increased amount of M6C carbide was detected, but M23C6carbides, sigma and mu phases were not. The aged condition corresponds to higher hardness, but without brittle regions that could initiate cracking.

scholarly journals Analysis of corporate political activity strategies of the food industry: evidence from France

2018 ◽  
Vol 21 (18) ◽  
pp. 3407-3421 ◽  
Author(s):  
Melissa Mialon ◽  
Jonathan Mialon
Keyword(s):  
Public Health ◽  
Food Industry ◽  
Evidence Base ◽  
Political Activity ◽  
Health Issues ◽  
Sources Of Information ◽  
Corporate Political Activity ◽  
The Public ◽  
Health Related ◽  
Different Sources

AbstractObjectiveTo identify the corporate political activity (CPA) of major food industry actors in France.DesignWe followed an approach based on information available in the public domain. Different sources of information, freely accessible to the public, were monitored.Setting/SubjectsData were collected and analysed between March and August 2015. Five actors were selected: ANIA (Association Nationale des Industries Agroalimentaires/National Association of Agribusiness Industries); Coca-Cola; McDonald’s; Nestlé; and Carrefour.ResultsOur analysis shows that the main practices used by Coca-Cola and McDonald’s were the framing of diet and public health issues in ways favourable to the company, and their involvement in the community. ANIA primarily used the ‘information and messaging’ strategy (e.g. by promoting deregulation and shaping the evidence base on diet- and public health-related issues), as well as the ‘policy substitution’ strategy. Nestlé framed diet and public health issues, and shaped the evidence base on diet- and public health-related issues. Carrefour particularly sought involvement in the community.ConclusionsWe found that, in 2015, the food industry in France was using CPA practices that were also used by other industries in the past, such as the tobacco and alcohol industries. Because most, if not all, of these practices proved detrimental to public health when used by the tobacco industry, we propose that the precautionary principle should guide decisions when engaging or interacting with the food industry.

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