Fault Recognition in a Four Stroke Internal Combustion (IC) Engine. An Artificial Neural Network (ANN) Based Approach PDF Download
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Author: Shankar Dandare
Publisher: GRIN Verlag
ISBN: 3668396752
Category : Technology & Engineering
Languages : en
Pages : 97
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Book Description
Research Paper (postgraduate) from the year 2015 in the subject Engineering - Automotive Engineering, , course: Engineering and Technology, language: English, abstract: In recent times, research on effective Acoustic Emission (AE)-based methods for condition monitoring and fault recognition has attracted many researchers. They recognize that the advanced methods of supervision, fault recognition become increasingly important for many technical processes, for the improvement of reliability, safety and efficiency. The use of acoustic signals for fault diagnosis in four-strokes Internal Combustion Engine has grown significantly due to advances in the progress of digital signal processing algorithms and implementation techniques. The classical approaches are limited to checking of some measurable output variables and does not provide a deeper insight and usually do not allow a fault diagnosis. Engine problems are caused primarily by improper maintenance or fatigue caused by normal wear and tear and also worn out or clogged vehicle parts. The main cause of overheating of the engine, engine surging and other problems is noticed as worn out parts. The faults in Internal Combustion (IC) engine, reduces the performance, fuel average, smoothness also a change in engine sound is observed. The faults in IC engines can be recognized and repaired based on engine sound and past experience. But as the engines are becoming more and more complex, getting expertise in fault recognition and localization is difficult, so there is a need of assistance system for fault recognition in IC engine, which will tell you about the possible fault based on the data provided to it.
Author: Shankar Dandare
Publisher: GRIN Verlag
ISBN: 3668396752
Category : Technology & Engineering
Languages : en
Pages : 97
Get Book Here
Book Description
Research Paper (postgraduate) from the year 2015 in the subject Engineering - Automotive Engineering, , course: Engineering and Technology, language: English, abstract: In recent times, research on effective Acoustic Emission (AE)-based methods for condition monitoring and fault recognition has attracted many researchers. They recognize that the advanced methods of supervision, fault recognition become increasingly important for many technical processes, for the improvement of reliability, safety and efficiency. The use of acoustic signals for fault diagnosis in four-strokes Internal Combustion Engine has grown significantly due to advances in the progress of digital signal processing algorithms and implementation techniques. The classical approaches are limited to checking of some measurable output variables and does not provide a deeper insight and usually do not allow a fault diagnosis. Engine problems are caused primarily by improper maintenance or fatigue caused by normal wear and tear and also worn out or clogged vehicle parts. The main cause of overheating of the engine, engine surging and other problems is noticed as worn out parts. The faults in Internal Combustion (IC) engine, reduces the performance, fuel average, smoothness also a change in engine sound is observed. The faults in IC engines can be recognized and repaired based on engine sound and past experience. But as the engines are becoming more and more complex, getting expertise in fault recognition and localization is difficult, so there is a need of assistance system for fault recognition in IC engine, which will tell you about the possible fault based on the data provided to it.
Author: American Society of Mechanical Engineers. Internal Combustion Engine Division. Technical Conference
Publisher:
ISBN:
Category : Internal combustion engines
Languages : en
Pages : 744
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Book Description
Author: Rolf Isermann
Publisher: Springer
ISBN: 3642399347
Category : Technology & Engineering
Languages : en
Pages : 646
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Book Description
The increasing demands for internal combustion engines with regard to fuel consumption, emissions and driveability lead to more actuators, sensors and complex control functions. A systematic implementation of the electronic control systems requires mathematical models from basic design through simulation to calibration. The book treats physically-based as well as models based experimentally on test benches for gasoline (spark ignition) and diesel (compression ignition) engines and uses them for the design of the different control functions. The main topics are: - Development steps for engine control - Stationary and dynamic experimental modeling - Physical models of intake, combustion, mechanical system, turbocharger, exhaust, cooling, lubrication, drive train - Engine control structures, hardware, software, actuators, sensors, fuel supply, injection system, camshaft - Engine control methods, static and dynamic feedforward and feedback control, calibration and optimization, HiL, RCP, control software development - Control of gasoline engines, control of air/fuel, ignition, knock, idle, coolant, adaptive control functions - Control of diesel engines, combustion models, air flow and exhaust recirculation control, combustion-pressure-based control (HCCI), optimization of feedforward and feedback control, smoke limitation and emission control This book is an introduction to electronic engine management with many practical examples, measurements and research results. It is aimed at advanced students of electrical, mechanical, mechatronic and control engineering and at practicing engineers in the field of combustion engine and automotive engineering.
Author: David W. Aha
Publisher: Springer Science & Business Media
ISBN: 9401720533
Category : Computers
Languages : en
Pages : 421
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Book Description
This edited collection describes recent progress on lazy learning, a branch of machine learning concerning algorithms that defer the processing of their inputs, reply to information requests by combining stored data, and typically discard constructed replies. It is the first edited volume in AI on this topic, whose many synonyms include `instance-based', `memory-based'. `exemplar-based', and `local learning', and whose topic intersects case-based reasoning and edited k-nearest neighbor classifiers. It is intended for AI researchers and students interested in pursuing recent progress in this branch of machine learning, but, due to the breadth of its contributions, it should also interest researchers and practitioners of data mining, case-based reasoning, statistics, and pattern recognition.
Author: L. Ashok Kumar
Publisher: Springer Nature
ISBN: 3030240517
Category : Technology & Engineering
Languages : en
Pages : 943
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Book Description
Due to the complexity, and heterogeneity of the smart grid and the high volume of information to be processed, artificial intelligence techniques and computational intelligence appear to be some of the enabling technologies for its future development and success. The theme of the book is “Making pathway for the grid of future” with the emphasis on trends in Smart Grid, renewable interconnection issues, planning-operation-control and reliability of grid, real time monitoring and protection, market, distributed generation and power distribution issues, power electronics applications, computer-IT and signal processing applications, power apparatus, power engineering education and industry-institute collaboration. The primary objective of the book is to review the current state of the art of the most relevant artificial intelligence techniques applied to the different issues that arise in the smart grid development.
Author: Society of Automotive Engineers
Publisher: SAE International
ISBN: 9780768003826
Category : Diesel motor
Languages : en
Pages : 0
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Book Description
Author: Gerhard Greeff
Publisher: Elsevier
ISBN: 0080473857
Category : Business & Economics
Languages : en
Pages : 476
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Book Description
New technologies are revolutionising the way manufacturing and supply chain management are implemented. These changes are delivering manufacturing firms the competitive advantage of a highly flexible and responsive supply chain and manufacturing system to ensure that they meet the high expectations of their customers, who, in today's economy, demand absolutely the best service, price, delivery time and product quality.To make e-manufacturing and supply chain technologies effective, integration is needed between various, often disparate systems. To understand why this is such an issue, one needs to understand what the different systems or system components do, their objectives, their specific focus areas and how they interact with other systems. It is also required to understand how these systems evolved to their current state, as the concepts used during the early development of systems and technology tend to remain in place throughout the life-cycle of the systems/technology. This book explores various standards, concepts and techniques used over the years to model systems and hierarchies in order to understand where they fit into the organization and supply chain. It looks at the specific system components and the ways in which they can be designed and graphically depicted for easy understanding by both information technology (IT) and non-IT personnel.Without a good implementation philosophy, very few systems add any real benefit to an organization, and for this reason the ways in which systems are implemented and installation projects managed are also explored and recommendations are made as to possible methods that have proven successful in the past. The human factor and how that impacts on system success are also addressed, as is the motivation for system investment and subsequent benefit measurement processes.Finally, the vendor/user supply/demand within the e-manufacturing domain is explored and a method is put forward that enables the reduction of vendor bias during the vendor selection process.The objective of this book is to provide the reader with a good understanding regarding the four critical factors (business/physical processes, systems supporting the processes, company personnel and company/personal performance measures) that influence the success of any e-manufacturing implementation, and the synchronization required between these factors.· Discover how to implement the flexible and responsive supply chain and manufacturing execution systems required for competitive and customer-focused manufacturing· Build a working knowledge of the latest plant automation, manufacturing execution systems (MES) and supply chain management (SCM) design techniques· Gain a fuller understanding of the four critical factors (business and physical processes, systems supporting the processes, company personnel, performance measurement) that influence the success of any e-manufacturing implementation, and how to evaluate and optimize all four factors
Author: Mohammed Serrhini
Publisher: Springer Nature
ISBN: 3030367789
Category : Technology & Engineering
Languages : en
Pages : 659
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Book Description
This book provides glimpses into contemporary research in information systems & technology, learning, artificial intelligence (AI), machine learning, and security and how it applies to the real world, but the ideas presented also span the domains of telehealth, computer vision, the role and use of mobile devices, brain–computer interfaces, virtual reality, language and image processing and big data analytics and applications. Great research arises from asking pertinent research questions. This book reveals some of the authors’ “beautiful questions” and how they develop the subsequent “what if” and “how” questions, offering readers food for thought and whetting their appetite for further research by the same authors.
Author: Mohamed Haddar
Publisher: Springer Science & Business Media
ISBN: 3642371434
Category : Technology & Engineering
Languages : en
Pages : 653
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Book Description
The 5th International Congress on Design and Modeling of Mechanical Systems (CMSM) was held in Djerba, Tunisia on March 25-27, 2013 and followed four previous successful editions, which brought together international experts in the fields of design and modeling of mechanical systems, thus contributing to the exchange of information and skills and leading to a considerable progress in research among the participating teams. The fifth edition of the congress (CMSM ́2013), organized by the Unit of Mechanics, Modeling and Manufacturing (U2MP) of the National School of Engineers of Sfax, Tunisia, the Mechanical Engineering Laboratory (MBL) of the National School of Engineers of Monastir, Tunisia and the Mechanics Laboratory of Sousse (LMS) of the National School of Engineers of Sousse, Tunisia, saw a significant increase of the international participation. This edition brought together nearly 300 attendees who exposed their work on the following topics: mechatronics and robotics, dynamics of mechanical systems, fluid structure interaction and vibroacoustics, modeling and analysis of materials and structures, design and manufacturing of mechanical systems. This book is the proceedings of CMSM ́2013 and contains a careful selection of high quality contributions, which were exposed during various sessions of the congress. The original articles presented here provide an overview of recent research advancements accomplished in the field mechanical engineering.
Author: Sonali Agarwal
Publisher: Springer Nature
ISBN: 981151366X
Category : Technology & Engineering
Languages : en
Pages : 464
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Book Description
This book features selected high-quality research papers presented at the International Conference on Machine Intelligence and Signal Processing (MISP 2019), held at the Indian Institute of Technology, Allahabad, India, on September 7–10, 2019. The book covers the latest advances in the fields of machine learning, big data analytics, signal processing, computational learning theory, and their real-time applications. The topics covered include support vector machines (SVM) and variants like least-squares SVM (LS-SVM) and twin SVM (TWSVM), extreme learning machine (ELM), artificial neural network (ANN), and other areas in machine learning. Further, it discusses the real-time challenges involved in processing big data and adapting the algorithms dynamically to improve the computational efficiency. Lastly, it describes recent developments in processing signals, for instance, signals generated from IoT devices, smart systems, speech, and videos and addresses biomedical signal processing: electrocardiogram (ECG) and electroencephalogram (EEG).
