Improving Aircraft Engine Maintenance Effectiveness And Reliability Using Intelligent Based Health Monitoring
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Improving Aircraft Engine Maintenance Effectiveness and Reliability Using Intelligent Based Health Monitoring
Engine Health monitoring (EHM) has been a very popular subject to increase aircraft availability with minimum maintenance cost. The study is aimed at providing a method to monitor the aircraft engine health during the flight with the aim of providing an opportunity for early fault detection to improve airline maintenance effectiveness and reliability. Since the impending engine failures may cause to change the engine parameters such as Fuel Flow (FF), Exhaust Gas Temperature (EGT), engine fan speed (N1), engine compressor speed (N2), etc., engine deteriorations or faults may be identified before they occur by monitoring them. So as to monitor engine health in flight, the automation of current work for EHM which is done manually by airlines is developed by using fuzzy logic (FL) and neural network (NN) models. FL is selected to develop an Automated EHM system (AEHMS), since it is very useful method for automation health monitoring. The fuzzy rule inference system for different engine faults is based on the expert knowledge and real life data in Turkish Airlines fleet. The complete loop of EHM is automatically performed by visual basic programs and Fuzzy Logic Toolbox in MATLAB. Finally, the method is utilized to run for monitoring the engines in Turkish Airlines fleet. This study has shown that AEHMS can be used by airlines or engine manufacturers efficiently to simplify the EHM system and minimize the drawbacks of it, such as extra labor hour, human error and requirement for engineering expertise. This method may also be applicable other than aircraft engines such as auxiliary power unit, structures. Since every engine type has different characters, it is required to revise the fuzzy rules for the concerning engine types.
Artificial Intelligence and Human Performance in Transportation
Artificial Intelligence (AI) is a major technological advancement in the 21st century. With its influence spreading to all aspects of our lives and the engineering sector, establishing well-defined objectives is crucial for successfully integrating AI in the field of transportation. This book presents different ways of adopting emerging technologies in transportation operations, including security, safety, online training, and autonomous vehicle operations on land, sea, and air. This guide is a dynamic resource for senior management and decision-makers, with essential practical advice distilled from the expertise of specialists in the field. It addresses the most critical issues facing transportation service providers in adopting AI and investigates the relationship between the human operator and the technology to navigate what is and is not feasible or impossible. Case studies of actual implementation provide context to common scenarios in the transportation sector. This book will serve the reader as the starting point for practical questions regarding the deployment and safety assurance of new and emergent technologies in the transportation domains. Artificial Intelligence and Human Performance in Transportation is a beneficial read for professionals in the fields of Human Factors, Engineering (Aviation, Maritime and Land), Logistics, Manufacturing, Accident Investigation and Safety, Cybersecurity and Human Resources.
Equipment Intelligent Operation and Maintenance
The proceedings of the First International Conference on Equipment Intelligent Operation and Maintenance (ICEIOM 2023) offer invaluable insights into the processes that ensure safe and reliable operation of equipment and guarantee the improvement of product life cycles. The book touches upon a wide array of topics including equipment condition monitoring, fault diagnosis, and remaining useful life prediction. With special emphasis on the integration of big data and machine learning, the papers contained in this publication highlight how these technologies make the equipment operation process highly automated and ingenious. Intelligent operation and maintenance is set to act as the driving force behind a new generation of smart manufacturing and equipment upgradation, and promote demand for intelligent product services and management. This is a highly beneficial guide to students, researchers, working professionals and enthusiasts who wish to stay updated on innovative research contributions and practical applications of state-of-the-art technologies in equipment operation and maintenance.