The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics

1999 ◽  
Vol 121 (4) ◽  
pp. 607-612 ◽  
Author(s):  
H. R. DePold ◽  
F. D. Gass
Keyword(s):  
Neural Networks ◽  
Expert Systems ◽  
Condition Monitoring ◽  
Intelligent System ◽  
Diagnostic Tools ◽  
Diagnostic Systems ◽  
Recent Developments ◽  
Gas Generators ◽  
Internet Link ◽  
Airline Fleet

Condition monitoring of engine gas generators plays an essential role in airline fleet management. Adaptive diagnostic systems are becoming available that interpret measured data, furnish diagnosis of problems, provide a prognosis of engine health for planning purposes, and rank engines for scheduled maintenance. More than four hundred operations worldwide currently use versions of the first or second generation diagnostic tools. Development of a third generation system is underway which will provide additional system enhancements and combine the functions of the existing tools. Proposed enhancements include the use of artificial intelligence to automate, improve the quality of the analysis, provide timely alerts, and the use of an Internet link for collaboration. One objective of these enhancements is to have the intelligent system do more of the analysis and decision making, while continuing to support the depth of analysis currently available at experienced operations. This paper presents recent developments in technology and strategies in engine condition monitoring including: (1) application of statistical analysis and artificial neural network filters to improve data quality, (2) neural networks for trend change detection, and classification to diagnose performance change, and (3) expert systems to diagnose, provide alerts and to rank maintenance action recommendations.

scholarly journals The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics

1998 ◽  
Author(s):  
Hans R. DePold ◽  
F. Douglas Gass
Keyword(s):  
Neural Networks ◽  
Expert Systems ◽  
Condition Monitoring ◽  
Intelligent System ◽  
Diagnostic Tools ◽  
Diagnostic Systems ◽  
Recent Developments ◽  
Gas Generators ◽  
Internet Link ◽  
Airline Fleet

Condition monitoring of engine gas generators plays an essential role in airline fleet management. Adaptive diagnostic systems are becoming available that interpret measured data, furnish diagnosis of problems, provide a prognosis of engine health for planning purposes, and rank engines for scheduled maintenance. More than four hundred operations worldwide currently use versions of the first or second generation diagnostic tools. Development of a third generation system is underway which will provide additional system enhancements and combine the functions of the existing tools. Proposed enhancements include the use of artificial intelligence to automate, improve the quality of the analysis, provide timely alerts, and the use of an Internet link for collaboration. One objective of these enhancements is to have the intelligent system do more of the analysis and decision making, while continuing to support the depth of analysis currently available at experienced operations. This paper presents recent developments in technology and strategies in engine condition monitoring including: 1) application of statistical analysis and artificial neural network filters to improve data quality; 2) neural networks for trend change detection, and classification to diagnose performance change; and 3) expert systems to diagnose, provide alerts and to rank maintenance action recommendations.

Hybrid Legal Intelligent System Using Fuzzy and Neural Networks

2017 ◽  
Vol 5 (11) ◽  
pp. 222-231
Author(s):  
S. Sridevi ◽  
◽  
◽  
P. Venkata Subba Reddy
Keyword(s):  
Neural Networks ◽  
Intelligent System

Methods and tools of ensuring the operational reliability of complex industrial facilities.

2020 ◽  
Vol 14 (1) ◽  
pp. 34-42
Author(s):  
A. VAZHYNSKYI ◽  
◽  
S. ZHUKOV ◽  
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Artificial Neural Networks ◽  
Expert Systems ◽  
Residual Life ◽  
Full Potential ◽  
Scientific Publications ◽  
Specific Element ◽  
Industrial Facilities ◽  
Artificial Neural

Approaches and algorithms for processing experimental data and data obtained as a result of using modern means of measuring equipment, selecting diagnostic parameters, pattern recognition, which constitute the methodological basis for developing methods and designing tools for creating a service system for complex industrial facilities based on predicting their performance and residual life are described in submitted article. Along with classical methods, methods based on using the full potential of the modern elemental base of microprocessor technology and the use of artificial neural networks, machine learning, and "big data" are discovered. The given examples can serve as the basis for constructing a methodology for the application of the considered approaches for organizing predictive maintenance of complex industrial equipment. An analytical review of a number of scientific publications showed that the creation of new automated diagnostic systems that can increase fault tolerance and extend the life of sophisticated modern power equipment is extremely relevant. For this, various approaches are applied, based on mathematical models, expert systems, artificial neural networks and other algorithms. Summarizing the results of scientific publications, it can be argued that the implementation of a systematic approach to the organization of repair service at the enterprise requires a comprehensive solution to the following urgent problems: • monitoring is formulated as the task of interrogating sensors and collecting information necessary for further analysis; • diagnostics, it is solved as tasks of identifying informative signs with further detection and classification of failures and anomalies in data sets; • improving the accuracy of algorithms aimed at pattern recognition; • condition forecasting is the task of assessing the current and accumulated readings of monitoring systems for making decisions regarding either a specific element of the complex or the facilities. Thus, modern technology make it possible to arrange arbitrarily complex algorithms. However, to use the full potential that artificial neural networks, expert systems, and classical methods for identifying and diagnosing equipment it is necessary to have a conceptual development of the foundations of building systems for organizing maintenance and repair of complex energy equipment

Recent developments and opportunities in fighting COVID-19

Coronaviruses ◽  
2020 ◽  
Vol 01 ◽  
Author(s):  
Vikram Rao ◽  
Subrat Kumar Bhattamisra
Keyword(s):  
World Health ◽  
Diagnostic Tools ◽  
Extensive Literature ◽  
Angiotensin Converting Enzyme 2 ◽  
Recent Developments ◽  
Therapeutic Molecules ◽  
Discharged Patients ◽  
Extensive Literature Search ◽  
Repurposed Drugs ◽  
Health Organization

Background: COVID-19, a Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) was first diagnosed in the patients from Wuhan, China in December 2019. Within couple of months of infection, it was declared as pandemic by World health organization. COVID-19 has become the most contagious infection with a serious threat to global health. In this review, we aimed to discuss the pathogenesis, diagnostics, current treatments and potential vaccines for COVID-19. Methods: An extensive literature search was conducted using keywords “COVID-19”; “Coronavirus”; “SARS-Cov-2”; “SARS” in public domains of Google, Google scholar, PubMed, and ScienceDirect. Selected articles were used to construct this review. Results: SARS-Cov-2 uses the Spike (S) protein on its surface to recognize the receptor on angiotensin-converting enzyme 2 (ACE2) and bind with 10-folds greater affinity than SARS-Cov-1. Molecular assays and immunoassays are the most frequently used tests whereas computed tomography (CT) scans, Artificial intelligence enabled diagnostic tools were also used in patients. In therapeutic treatment, few drugs were repurposed and there are 23 therapeutic molecules including the repurposed drugs are in different stages of clinical trial. Similarly, development of vaccines is also in the pipeline. Few countries have managed well to contain the spread by rapid testing and identifying the clusters. Conclusion: Till now, the acute complications and mortality of COVID-19 has been linked to the pre-existing comorbid conditions or age. Besides the development of therapeutic strategies that includes drugs and vaccine, the long term implication of COVID-19 infection in terms of the disorder/disability in the cured/discharged patients is a new area to investigate.

scholarly journals Can Traditional Chinese Medicine Diagnosis Be Parameterized and Standardized? A Narrative Review

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 177
Author(s):  
Luís Carlos Matos ◽  
Jorge Pereira Machado ◽  
Fernando Jorge Monteiro ◽  
Henry Johannes Greten
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Functional Status ◽  
Control Measures ◽  
Systematic Evaluation ◽  
Diagnostic Tools ◽  
Functional Evaluation ◽  
Diagnostic Systems ◽  
Mechanical Pulse ◽  
Proof Of Efficacy

The integration of Traditional Chinese Medicine (TCM) in Western health systems and research requires a rational communicable theory, scientific proof of efficacy and safety, and quality control measures. The existence of clear definitions and the diagnosis standardization are critical factors to establish the patient’s vegetative functional status accurately and, therefore, systematically apply TCM therapeutics such as the stimulation of reflex skin areas known as acupoints. This science-based conceptualization entails using validated methods, or even developing new systems able to parameterize the diagnosis and assess TCM related effects by objective measurements. Traditionally, tongue and pulse diagnosis and the functional evaluation of action points by pressure sensitivity and physical examination may be regarded as essential diagnostic tools. Parameterizing these techniques is a future key point in the objectification of TCM diagnosis, such as by electronic digital image analysis, mechanical pulse diagnostic systems, or the systematic evaluation of acupoints’ electrophysiology. This review aims to demonstrate and critically analyze some achievements and limitations in the clinical application of device-assisted TCM diagnosis systems to evaluate functional physiological patterns. Despite some limitations, tongue, pulse, and electrophysiological diagnosis devices have been reported as a useful tool while establishing a person’s functional status.

scholarly journals A Note on Equivalence Classes of Directed Acyclic Independence Graphs

1993 ◽  
Vol 7 (3) ◽  
pp. 409-412 ◽  
Author(s):  
David Madigan
Keyword(s):  
Model Selection ◽  
Expert Systems ◽  
Equivalence Classes ◽  
Influence Diagrams ◽  
Single Class ◽  
Selection Procedures ◽  
Probabilistic Expert Systems ◽  
Recent Developments ◽  
Independence Graphs ◽  
Markov Properties

Directed acyclic independence graphs (DAIGs) play an important role in recent developments in probabilistic expert systems and influence diagrams (Chyu [1]). The purpose of this note is to show that DAIGs can usefully be grouped into equivalence classes where the members of a single class share identical Markov properties. These equivalence classes can be identified via a simple graphical criterion. This result is particularly relevant to model selection procedures for DAIGs (see, e.g., Cooper and Herskovits [2] and Madigan and Raftery [4]) because it reduces the problem of searching among possible orientations of a given graph to that of searching among the equivalence classes.

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