scholarly journals Detailed State of the Art Review for the Different Online/Inline Oil Analysis Techniques in Context of Wind Turbine Gearboxes

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Andrew Hamilton ◽  
Francis Quail
Keyword(s):  
Wind Turbine ◽  
Asset Management ◽  
State Of The Art ◽  
Energy Industry ◽  
Electrical Fields ◽  
Analysis Techniques ◽  
Current State ◽  
Main Driver ◽  
Size Accuracy ◽  
Different Characteristics

The main driver behind developing advanced condition monitoring (CM) systems for the wind energy industry is the delivery of improved asset management regarding the operation and maintenance of the gearbox and other wind turbine components and systems. Current gearbox CM systems mainly detect faults by identifying ferrous materials, water, and air within oil by changes in certain properties such as electrical fields. In order to detect oil degradation and identify particles, more advanced devices are required to allow a better maintenance regime to be established. Current technologies available specifically for this purpose include Fourier transform infrared (FTIR) spectroscopy and ferrography. There are also several technologies that have not yet been or have been recently applied to CM problems. After reviewing the current state of the art, it is recommended that a combination of sensors would be used that analyze different characteristics of the oil. The information individually would not be highly accurate but combined it is fully expected that greater accuracy can be obtained. The technologies that are suitable in terms of cost, size, accuracy, and development are online ferrography, selective fluorescence spectroscopy, scattering measurements, FTIR, photoacoustic spectroscopy, and solid state viscometers.

scholarly journals Detailed State of the Art Review for the Different On-Line/In-Line Oil Analysis Techniques in Context of Wind Turbine Gearboxes

2011 ◽  
Author(s):  
Andrew Hamilton ◽  
Francis Quail
Keyword(s):  
Wind Turbine ◽  
Asset Management ◽  
State Of The Art ◽  
Electrical Fields ◽  
Analysis Techniques ◽  
Current State ◽  
Main Driver ◽  
Size Accuracy ◽  
On Line ◽  
Different Characteristics

The main driver behind developing advanced condition monitoring (CM) systems for the wind energy industry is the delivery of improved asset management regarding the operation and maintenance of the gearbox and other wind turbine components and systems. Current gearbox CM systems mainly detect faults by identifying ferrous materials, water and air within oil by changes in certain properties such as electrical fields. In order to detect oil degradation and identify particles, more advanced devices are required so allow a better maintenance regime to be established. Current technologies available specifically for this purpose include Fourier Transform Infrared (FTIR) spectroscopy and ferrography. There are also several technologies that have not yet been or have been recently applied to CM problems. After reviewing the current state of the art, it is recommended that a combination of sensors would be used that analyse different characteristics of the oil. The information individually would not be highly accurate but combined, it is fully expected that greater accuracy can be obtained. The technologies that are suitable in terms of cost, size, accuracy and development are online ferrography, selective fluorescence spectroscopy, scattering measurements, FTIR, photoacoustic spectroscopy and solid state viscometers.

Automated Diagnostics of Rotating Machinery

2003 ◽  
Author(s):  
A. El-Shafei ◽  
N. Rieger
Keyword(s):  
Asset Management ◽  
Management System ◽  
State Of The Art ◽  
Parametric Model ◽  
Rule Based ◽  
Future Developments ◽  
Current State ◽  
Condition Evaluation ◽  
Asset Management System ◽  
Model Diagnosis

This paper provides an overview of the current available technologies for automated machinery condition evaluation and fault diagnosis within an overall plant asset management system. The paper presents a basic overview of an integrated plant asset management system, and focuses on the available technologies for automated diagnostics including statistical analysis of data, parametric model diagnosis, non-parametric model diagnosis (artificial neural networks), and rule-based diagnostics including expert systems and fuzzy logic. The current state-of-the-art and the expected realistic future developments are discussed.

scholarly journals Earthquake resistant design of foundations

1996 ◽  
Vol 29 (3) ◽  
pp. 155-171 ◽  
Author(s):  
M. J. Pender
Keyword(s):  
Soil Properties ◽  
State Of The Art ◽  
Deep Foundations ◽  
Foundation Design ◽  
Analysis Techniques ◽  
Current State ◽  
Earthquake Resistant Design ◽  
Earthquake Resistant ◽  
Structural Engineers ◽  
Potential Use

This paper reviews the main issues to be addressed in the design of shallow and deep foundations which may be subject to earthquake loading. Information is presented on the soil properties required as well as the various design analysis techniques with a view to assessing the current state-of-the-art and highlighting areas in which further techniques need to be developed. The paper sets out, by way of an overview, a sequence of steps that a designer may follow in developing a foundation system. It is concluded that, at present, the greatest deficiencies lie in the areas of most potential use to designers. A secondary aim of the paper is to enhance communication between geotechnical and structural engineers on aseismic foundation design.

Behavioral Genetics: Concepts for Research and Practice in Language Development and Disorders

1995 ◽  
Vol 38 (5) ◽  
pp. 1126-1142 ◽  
Author(s):  
Jeffrey W. Gilger
Keyword(s):  
Language Development ◽  
Behavioral Genetics ◽  
State Of The Art ◽  
Genetic Research ◽  
Great Promise ◽  
Behavioral Genetic ◽  
Fine Grained ◽  
Future Goals ◽  
Current State ◽  
Research Designs

This paper is an introduction to behavioral genetics for researchers and practioners in language development and disorders. The specific aims are to illustrate some essential concepts and to show how behavioral genetic research can be applied to the language sciences. Past genetic research on language-related traits has tended to focus on simple etiology (i.e., the heritability or familiality of language skills). The current state of the art, however, suggests that great promise lies in addressing more complex questions through behavioral genetic paradigms. In terms of future goals it is suggested that: (a) more behavioral genetic work of all types should be done—including replications and expansions of preliminary studies already in print; (b) work should focus on fine-grained, theory-based phenotypes with research designs that can address complex questions in language development; and (c) work in this area should utilize a variety of samples and methods (e.g., twin and family samples, heritability and segregation analyses, linkage and association tests, etc.).

Schizophrenia Research: Current State of the Art

1976 ◽  
Vol 21 (7) ◽  
pp. 497-498
Author(s):  
STANLEY GRAND
Keyword(s):  
State Of The Art ◽  
Current State

Umbral Calculus

10.37236/24 ◽  
2002 ◽  
Vol 1000 ◽  
Author(s):  
A. Di Bucchianico ◽  
D. Loeb
Keyword(s):  
19Th Century ◽  
Finite Differences ◽  
State Of The Art ◽  
Umbral Calculus ◽  
Current State ◽  
Logical Foundation ◽  
Complete Bibliography ◽  
The 19Th Century ◽  
Mathematical Literature

We survey the mathematical literature on umbral calculus (otherwise known as the calculus of finite differences) from its roots in the 19th century (and earlier) as a set of “magic rules” for lowering and raising indices, through its rebirth in the 1970’s as Rota’s school set it on a firm logical foundation using operator methods, to the current state of the art with numerous generalizations and applications. The survey itself is complemented by a fairly complete bibliography (over 500 references) which we expect to update regularly.

The Receptor-Dependent QSAR Paradigm: An Overview of the Current State of the Art

2009 ◽  
Vol 5 (4) ◽  
pp. 359-366 ◽  
Author(s):  
Osvaldo Santos-Filho ◽  
Anton Hopfinger ◽  
Artem Cherkasov ◽  
Ricardo de Alencastro
Keyword(s):  
State Of The Art ◽  
Current State

scholarly journals From Micro to Long: Non-Coding RNAs in Tamoxifen Resistance of Breast Cancer Cells

Cancers ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 3688
Author(s):  
Jéssica Fernanda Barazetti ◽  
Tayana Shultz Jucoski ◽  
Tamyres Mingorance Carvalho ◽  
Rafaela Nasser Veiga ◽  
Ana Flávia Kohler ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Hormone Receptor ◽  
Estrogen Receptor Alpha ◽  
Expression Patterns ◽  
Tamoxifen Resistance ◽  
Hormone Receptor Positive ◽  
Current State ◽  
Main Driver ◽  
Underlying Mechanisms ◽  
Multiple Signaling

Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer mortality among women. Two thirds of patients are classified as hormone receptor positive, based on expression of estrogen receptor alpha (ERα), the main driver of breast cancer cell proliferation, and/or progesterone receptor, which is regulated by ERα. Despite presenting the best prognosis, these tumors can recur when patients acquire resistance to treatment by aromatase inhibitors or antiestrogen such as tamoxifen (Tam). The mechanisms that are involved in Tam resistance are complex and involve multiple signaling pathways. Recently, roles for microRNAs and lncRNAs in controlling ER expression and/or tamoxifen action have been described, but the underlying mechanisms are still little explored. In this review, we will discuss the current state of knowledge on the roles of microRNAs and lncRNAs in the main mechanisms of tamoxifen resistance in hormone receptor positive breast cancer. In the future, this knowledge can be used to identify patients at a greater risk of relapse due to the expression patterns of ncRNAs that impact response to Tam, in order to guide their treatment more efficiently and possibly to design therapeutic strategies to bypass mechanisms of resistance.

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