Wind Turbine Reliability Improvement by Fault Tolerant Control

This thesis investigates wind turbine reliability improvement, utilizing model-based fault tolerant control, so that the wind turbine continues to operate satisfactorily with the same performance index in the presence of faults as in fault-free situations. Numerical simulations are conducted on the wind turbine bench mark model associated with the considered faults and comparison is made between the performance of the proposed controllers and industrial controllers illustrating the superiority of the proposed ones

Analysis of electrical signatures in synchronous generators characterized by bearing faults

Synchronous generators play a vital role in power systems. One of the major mechanical faults in synchronous generators is related to bearings. The popular vibration analysis method has been utilized to detect bearing faults for years. However, bearing health monitoring based on vibration analysis is expensive. One of the reasons is because vibration analysis requires costly vibration sensors and the extra costs associated with its proper installation and maintenance. This limitation prevents continuous bearing condition monitoring, which gives better performance for rolling element bearing fault detection, compared to the periodic monitoring method that is a typical practice for bearing maintenance in industry. Therefore, a cost effective alternative is necessary. In this study, a sensorless bearing fault detection method for synchronous generators is proposed based on the analysis of electrical signatures, and its bearing fault detection capability is demonstrated. Experiments with staged bearing faults are conducted to validate the effectiveness of the proposed fault detection method. First, a generator test bed with an in- situ bearing damage device is designed and built. Next, multiple bearing damage experiments are carried out in two vastly different operating conditions in order to obtain statistically significant results. During each experiment, artificially induced bearing current causes accelerated damage to the front bearing of the generator. This in-situ bearing damage process entirely eliminates the necessity of disassembly and reassembly of the experimental setup that causes armature spectral distortions. The electrical fault indicator is computed based on stator voltage signatures without the knowledge of machine and bearing specific parameters. Experimental results are compared using the electrical indicator and a vibration indicator that is calculated based on measured vibration data. The results indicate that the electrical indicator can be used to analyze health degradation of rolling element bearings in synchronous generators in most instances. Though the vibration indicator enables early bearing fault detection, it is found that the electrical fault indicator is also capable of detecting bearing faults well before catastrophic bearing failure

Machine Learning based Early Fault Diagnosis of Induction Motor for Electric Vehicle Application

Electrified vehicular industry is growing at a rapid pace with a global increase in production of electric vehicles (EVs) along with several new automotive cars companies coming to compete with the big car industries. The technology of EV has evolved rapidly in the last decade. But still the looming fear of low driving range, inability to charge rapidly like filling up gasoline for a conventional gas car, and lack of enough EV charging stations are just a few of the concerns. With the onset of self-driving cars, and its popularity in integrating them into electric vehicles leads to increase in safety both for the passengers inside the vehicle as well as the people outside. Since electric vehicles have not been widely used over an extended period of time to evaluate the failure rate of the powertrain of the EV, a general but definite understanding of motor failures can be developed from the usage of motors in industrial application. Since traction motors are more power dense as compared to industrial motors, the possibilities of a small failure aggravating to catastrophic issue is high. Understanding the challenges faced in EV due to stator fault in motor, with major focus on induction motor stator winding fault, this dissertation presents the following: 1. Different Motor Failures, Causes and Diagnostic Methods Used, With More Importance to Artificial Intelligence Based Motor Fault Diagnosis. 2. Understanding of Incipient Stator Winding Fault of IM and Feature Selection for Fault Diagnosis 3. Model Based Temperature Feature Prediction under Incipient Fault Condition 4. Design of Harmonics Analysis Block for Flux Feature Prediction 5. Flux Feature based On-line Harmonic Compensation for Fault-tolerant Control 6. Intelligent Flux Feature Predictive Control for Fault-Tolerant Control 7. Introduction to Machine Learning and its Application for Flux Reference Prediction 8. Dual Memorization and Generalization Machine Learning based Stator Fault Diagnosi

Industrial and Technological Applications of Power Electronics Systems

The Special Issue "Industrial and Technological Applications of Power Electronics Systems" focuses on: - new strategies of control for electric machines, including sensorless control and fault diagnosis; - existing and emerging industrial applications of GaN and SiC-based converters; - modern methods for electromagnetic compatibility. The book covers topics such as control systems, fault diagnosis, converters, inverters, and electromagnetic interference in power electronics systems. The Special Issue includes 19 scientific papers by industry experts and worldwide professors in the area of electrical engineering

Maintenance Management of Wind Turbines

“Maintenance Management of Wind Turbines” considers the main concepts and the state-of-the-art, as well as advances and case studies on this topic. Maintenance is a critical variable in industry in order to reach competitiveness. It is the most important variable, together with operations, in the wind energy industry. Therefore, the correct management of corrective, predictive and preventive politics in any wind turbine is required. The content also considers original research works that focus on content that is complementary to other sub-disciplines, such as economics, finance, marketing, decision and risk analysis, engineering, etc., in the maintenance management of wind turbines. This book focuses on real case studies. These case studies concern topics such as failure detection and diagnosis, fault trees and subdisciplines (e.g., FMECA, FMEA, etc.) Most of them link these topics with financial, schedule, resources, downtimes, etc., in order to increase productivity, profitability, maintainability, reliability, safety, availability, and reduce costs and downtime, etc., in a wind turbine. Advances in mathematics, models, computational techniques, dynamic analysis, etc., are employed in analytics in maintenance management in this book. Finally, the book considers computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques that are expertly blended to support the analysis of multi-criteria decision-making problems with defined constraints and requirements

Reverse engineering and refurbishing of an Mi-24 helicopter main gear box

The Mi-24 helicopter is one of the most famous heavy lift helicopters designed with a net weight of 8.4 tonnes, while its gross weight is 12.5 tonnes. This helicopter is powered by two TV3-117 turbo-engines, coupled to a VR-24 main rotor transmission gearbox, which reduces the engine speed from 15000 Revolutions Per Minute (RPM) to the main rotor speed of 240 RPM. This research aims to show the functionality of the Mi-24 helicopter main gear box, to find the opportunities to extend the running hours (before maintenance) and to refurbish the gear box locally in South Africa. The research follows the principles of Reverse Engineering (RE) and Refurbishing. The principles involve the extraction of information from an existing product in order to establish its function and to re-create specifications which can be used to make, maintain or refurbish a similar or superior item. This dissertation has exposed some of the theory of the design of the Mi-24 main gearbox components and their functionality; including similar selected helicopters’ main drive mechanisms. The probable defects that are common to helicopter transmissions, the specifications and the Computer Aided Design (CAD) drawings are also presented. The research concludes that, with the cooperation of the local aerospace industry (including the army), the academic institutions and government; it is possible to get the necessary certification, licensing, training, specialised equipment and to establish a Maintenance Organisation, to refurbish the Mi-24 helicopter gearbox locally in South Africa

Reverse engineering and refurbishing of an Mi-24 helicopter main gear box

The Mi-24 helicopter is one of the most famous heavy lift helicopters designed with a net weight of 8.4 tonnes, while its gross weight is 12.5 tonnes. This helicopter is powered by two TV3-117 turbo-engines, coupled to a VR-24 main rotor transmission gearbox, which reduces the engine speed from 15000 Revolutions Per Minute (RPM) to the main rotor speed of 240 RPM. This research aims to show the functionality of the Mi-24 helicopter main gear box, to find the opportunities to extend the running hours (before maintenance) and to refurbish the gear box locally in South Africa. The research follows the principles of Reverse Engineering (RE) and Refurbishing. The principles involve the extraction of information from an existing product in order to establish its function and to re-create specifications which can be used to make, maintain or refurbish a similar or superior item. This dissertation has exposed some of the theory of the design of the Mi-24 main gearbox components and their functionality; including similar selected helicopters’ main drive mechanisms. The probable defects that are common to helicopter transmissions, the specifications and the Computer Aided Design (CAD) drawings are also presented. The research concludes that, with the cooperation of the local aerospace industry (including the army), the academic institutions and government; it is possible to get the necessary certification, licensing, training, specialised equipment and to establish a Maintenance Organisation, to refurbish the Mi-24 helicopter gearbox locally in South Africa