Fault Recognition in a Four Stroke Internal Combustion (IC) Engine. An Artificial Neural Network (ANN) Based Approach

Forschungsarbeit , 2015 , 91 Seiten

Ingenieurwissenschaften - Fahrzeugtechnik

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.

Inhaltsverzeichnis (Table of Contents)

• Abstract
• 1. Significance of Fault Recognition System
  • 1.1 Introduction
  • 1.2 India's Vehicle Growth
  • 1.3 The Significance of Vehicle Maintenance
• 2. Literature Survey & Objective of Research Problem
  • 2.1 Details of Literature Review
  • 2.2 Observations from Related Research Work
  • 2.3 Broad Objectives of the Proposed Systems
• 3. Data Acquisition
  • 3.1 Experimental Setup
  • 3.2 Collection of knowledge base
  • 3.3 Mathematical Representation Parameters
• 4. Engine Faults and ANN Classifiers
  • 4.0 Engine Faults Under Consideration
  • 4.1 Spark Plug Fault
  • 4.2 Piston Fault
  • 4.3 Air Filter Fault
  • 4.4 Working of Four Stroke Engine
  • 4.5 Two-stroke and Four-stroke engines Comparison
  • 4.6 Need of MATLAB and Simulink
  • 4.7 Artificial Neural Network
  • 4.8 Brief Introduction of ANN Based Classifiers

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This book focuses on the development and application of an Artificial Neural Network (ANN) based approach for fault recognition in four-stroke internal combustion engines. The aim is to provide a comprehensive overview of the technology, methodologies, and applications of this approach for detecting and diagnosing engine faults. The book provides practical guidance for researchers, engineers, and students working in the field of automotive diagnostics and machine learning.

• Fault detection and diagnosis in internal combustion engines
• Artificial neural networks (ANN) and their application in engine diagnostics
• Data acquisition and feature extraction techniques for engine fault detection
• Design and implementation of ANN-based classifiers for fault recognition
• Application of MATLAB and Simulink for engine fault analysis and simulation

Zusammenfassung der Kapitel (Chapter Summaries)

Chapter 1 provides an introduction to the significance of fault recognition systems in the context of vehicle growth and maintenance. Chapter 2 reviews existing literature on fault detection systems, focusing on research specific to preventing vehicle damage. Chapter 3 describes the data acquisition system, including signal capturing, decomposition, and feature extraction. Chapter 4 details the specific engine faults considered for fault recognition, including spark plug, piston, and air filter faults, as well as the working principles of four-stroke engines. The chapter also introduces artificial neural networks and relevant classifiers.

Schlüsselwörter (Keywords)

The primary focus of this book is fault recognition in four-stroke IC engines using ANN-based approaches. Key themes and concepts include data acquisition, signal processing, feature extraction, ANN classifiers, MATLAB, Simulink, and fault diagnosis. The book explores practical applications of these concepts within the context of automotive diagnostics.

• Veranstaltung: Engineering and Technology
• Autoren: Dr. Shankar Dandare (Autor:in), Mayur R. Parate (Autor:in)
• Erscheinungsjahr: 2015
• Seiten: 91
• Katalognummer: V346482
• ISBN (eBook): 9783668396753
• ISBN (Buch): 9783668396760
• Sprache: Englisch
• Schlagworte: fault, recognition, four, stroke, internal, combustion, engine, artificial, neural, network, based, approach