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Nonintrusive Condition Monitoring And Fault Diagnosis For Wind Turbine Gearboxes Using Generator Current Signals
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Book Synopsis Nonintrusive Condition Monitoring and Fault Diagnosis for Wind Turbine Gearboxes Using Generator Current Signals by : Dingguo Lu
Download or read book Nonintrusive Condition Monitoring and Fault Diagnosis for Wind Turbine Gearboxes Using Generator Current Signals written by Dingguo Lu and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this dissertation research is to develop nonintrusive condition monitoring and fault diagnosis methods for wind turbine gearboxes. The proposed methods use only the current signals measured from the terminals or used in the control system of wind turbine generators. Current-based gearbox fault diagnosis has advantages over traditional vibration-based methods in terms of cost, hardware complexity, implementation, and reliability.
Book Synopsis Final Technical Report Recovery Act by :
Download or read book Final Technical Report Recovery Act written by and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The penetration of wind power has increased greatly over the last decade in the United States and across the world. The U.S. wind power industry installed 1,118 MW of new capacity in the first quarter of 2011 alone and entered the second quarter with another 5,600 MW under construction. By 2030, wind energy is expected to provide 20% of the U.S. electricity needs. As the number of wind turbines continues to grow, the need for effective condition monitoring and fault detection (CMFD) systems becomes increasingly important [3]. Online CMFD is an effective means of not only improving the reliability, capacity factor, and lifetime, but it also reduces the downtime, energy loss, and operation and maintenance (O & M) of wind turbines. The goal of this project is to develop novel online nonintrusive CMFD technologies for wind turbines. The proposed technologies use only the current measurements that have been used by the control and protection system of a wind turbine generator (WTG); no additional sensors or data acquisition devices are needed. Current signals are reliable and easily accessible from the ground without intruding on the wind turbine generators (WTGs) that are situated on high towers and installed in remote areas. Therefore, current-based CMFD techniques have great economic benefits and the potential to be adopted by the wind energy industry. Specifically, the following objectives and results have been achieved in this project: (1) Analyzed the effects of faults in a WTG on the generator currents of the WTG operating at variable rotating speed conditions from the perspective of amplitude and frequency modulations of the current measurements; (2) Developed effective amplitude and frequency demodulation methods for appropriate signal conditioning of the current measurements to improve the accuracy and reliability of wind turbine CMFD; (3) Developed a 1P-invariant power spectrum density (PSD) method for effective signature extraction of wind turbine faults with characteristic frequencies in the current or current demodulated signals, where 1P stands for the shaft rotating frequency of a WTG; (4) Developed a wavelet filter for effective signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (5) Developed an effective adaptive noise cancellation method as an alternative to the wavelet filter method for signature extraction of wind turbine faults without characteristic frequencies in the current or current demodulated signals; (6) Developed a statistical analysis-based impulse detection method for effective fault signature extraction and evaluation of WTGs based on the 1P-invariant PSD of the current or current demodulated signals; (7) Validated the proposed current-based wind turbine CMFD technologies through extensive computer simulations and experiments for small direct-drive WTGs without gearboxes; and (8) Showed, through extensive experiments for small direct-drive WTGs, that the performance of the proposed current-based wind turbine CMFD technologies is comparable to traditional vibration-based methods. The proposed technologies have been successfully applied for detection of major failures in blades, shafts, bearings, and generators of small direct-drive WTGs. The proposed technologies can be easily integrated into existing wind turbine control, protection, and monitoring systems and can be implemented remotely from the wind turbines being monitored. The proposed technologies provide an alternative to vibration-sensor-based CMFD. This will reduce the cost and hardware complexity of wind turbine CMFD systems. The proposed technologies can also be combined with vibration-sensor-based methods to improve the accuracy and reliability of wind turbine CMFD systems. When there are problems with sensors, the proposed technologies will ensure proper CMFD for the wind turbines, including their sensing systems. In conclusion, the proposed technologies offer a ...
Book Synopsis Intelligent Fault Diagnosis of Gearboxes and Its Applications on Wind Turbines by : Sajid Hussain
Download or read book Intelligent Fault Diagnosis of Gearboxes and Its Applications on Wind Turbines written by Sajid Hussain and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Electrical and Mechanical Fault Diagnosis in Wind Energy Conversion Systems by : Monia Ben Khader Bouzid
Download or read book Electrical and Mechanical Fault Diagnosis in Wind Energy Conversion Systems written by Monia Ben Khader Bouzid and published by John Wiley & Sons. This book was released on 2023-09-01 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind energy conversion systems are subject to many different types of faults and therefore fault detection is highly important to ensure reliability and safety. Monitoring systems can help to detect faults before they result in downtime. This book presents efficient methods used to detect electrical and mechanical faults based on electrical signals occurring in the different components of a wind energy conversion system. For example, in a small and high power synchronous generator and multi-phase generator, in the diode bridge rectifier, the gearbox and the sensors. This book also presents a method for keeping the frequency and voltage of the power grid within an allowable range while ensuring the continuity of power supply in the event of a grid fault. Electrical and Mechanical Fault Diagnosis in Wind Energy Conversion Systems presents original results obtained from a variety of research. It will not only be useful as a guideline for the conception of more robust wind turbines systems, but also for engineers monitoring wind turbines and researchers
Book Synopsis Vibration-Based Condition Monitoring of Wind Turbines by : Tomasz Barszcz
Download or read book Vibration-Based Condition Monitoring of Wind Turbines written by Tomasz Barszcz and published by Springer. This book was released on 2018-12-04 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes in detail different types of vibration signals and the signal processing methods, including signal resampling and signal envelope, used for condition monitoring of drivetrains. A special emphasis is placed on wind turbines and on the fact that they work in highly varying operational conditions. The core of the book is devoted to cutting-edge methods used to validate and process vibration data in these conditions. Key case studies, where advanced signal processing methods are used to detect failures of gearboxes and bearings of wind turbines, are described and discussed in detail. Vibration sensors, SCADA (Supervisory Control and Data Acquisition), portable data analyzers and online condition monitoring systems, are also covered. This book offers a timely guide to both researchers and professionals working with wind turbines (but also other machines), and to graduate students willing to extend their knowledge in the field of vibration analysis.
Book Synopsis Condition Monitoring Techniques for Wind Turbines by : Christopher James Crabtree
Download or read book Condition Monitoring Techniques for Wind Turbines written by Christopher James Crabtree and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis focuses on practical condition monitoring of wind turbines. With offshore wind playing an increasing part in UK electricity generation, prompt fault detection leading to preventative maintenance is gaining in importance. This work describes the development of a condition monitoring test rig and the innovation and application of signal processing techniques for the detection of faults in non-stationary signals. Work is supported throughout by information from wind turbine operators and their experiences of variable speed, variable load wind turbines in the field. Experimental work is carried out on a condition monitoring test rig comprising a wound rotor induction generator, gearbox and DC driving motor. The test rig operates at variable speed and allows the implementation of a number of fault-like conditions including rotor electrical asymmetry, shaft mass unbalance and gear tooth failure. Test rig instrumentation was significantly developed during this research and both electrical and mechanical condition signals are monitored. A signal processing algorithm was developed based on experience with analysis techniques and their relationship with the characteristics of a wind turbine. The algorithm is based on Fourier analysis and allows the analysis of fault-related speed-dependent frequencies within non-stationary signals such as those encountered on a wind turbine. The detection of different faults is discussed and conclusions drawn on the applicability of frequency tracking algorithms. The newly developed algorithm is compared with a published method to establish its advantages and limitations.
Book Synopsis Online Nonintrusive Condition Monitoring and Fault Detection for Wind Turbines by : Xiang Gong
Download or read book Online Nonintrusive Condition Monitoring and Fault Detection for Wind Turbines written by Xiang Gong and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Development of Effective Gearbox Fault Diagnosis Methodologies Utilising Various Levels of Prior Knowledge by : Stephan Schmidt
Download or read book Development of Effective Gearbox Fault Diagnosis Methodologies Utilising Various Levels of Prior Knowledge written by Stephan Schmidt and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Effective fault diagnosis techniques are important to ensure that expensive assets such as wind turbines can operate reliably. Vibration condition monitoring data are rich with information pertaining to the dynamics of the rotating machines and are therefore popular for rotating machine diagnostics. However, vibration data do not only contain diagnostic information, but operating condition information as well. The performance of many conventional fault diagnosis techniques is impeded by inherent varying operating conditions encountered in machines such as wind turbines and draglines. Hence, it is not only important to utilise fault diagnosis techniques that are sensitive to faults, but the techniques should also be robust to changes in operating conditions. Much research has been conducted to address the many facets of gearbox fault diagnosis e.g. understanding the interactions of the components, the characteristics of the vibration signals and the development of good vibration analysis techniques. The aforementioned knowledge, as well as the availability of historical data, are regarded as prior knowledge (i.e. information that is available before inferring the condition of the machine) in this thesis. The available prior knowledge can be utilised to ensure that e ective gearbox fault diagnosis techniques are designed. Therefore, methodologies are proposed in this work which can utilise the available prior knowledge to e ectively perform fault diagnosis, i.e. detection, localisation and trending, under varying operating conditions. It is necessary to design di erent methodologies to accommodate the di erent kinds of historical data (e.g. healthy historical data or historical fault data) that can be encountered and the di erent signal analysis techniques that can be used. More speci cally, a methodology is developed to automatically detect localised gear damage under varying operating conditions without any historical data being available. The success of the methodology is attributed to the fact that the interaction between gear teeth in a similar condition results in data being generated which are statistically similar and this prior knowledge may be utilised. Therefore, a dissimilarity measure between the probability density functions of two teeth can be used to detect a gear tooth with localised gear damage. Three methodologies are also developed to utilise the available historical data from a healthy machine for gearbox fault diagnosis. Firstly, discrepancy analysis, a powerful novelty detection technique which has been used for gear diagnostics under varying operating conditions, is extended for bearing diagnostics under varying operating conditions. The suitability of time-frequency analysis techniques and di erent models are compared for discrepancy analysis as well. Secondly, a methodology is developed where the spectral coherence, a powerful second-order cyclostationary technique, is supplemented with healthy historical data for fault detection, localisation and trending. Lastly, a methodology is proposed which utilises narrowband feature extraction methods such as the kurtogram to extract a signal rich with novel information from a vibration signal. This is performed by attenuating the historical information in the signal. Sophisticated signal analysis techniques such as the squared envelope spectrum and the spectral coherence are also used on the novel signal to highlight the bene ts of utilising the novel signal as opposed to raw vibration signal for fault diagnosis. Even though a healthy state is the desired operating condition of rotating machines, fault data will become available during the operational life of the machine. Therefore, a methodology, centred around discrepancy analysis, is developed to utilise the available historical fault data and to accommodate fault data becoming available during the operation of the machine. In this investigation, it is recognised that the machine condition monitoring problem is in fact an open set recognition problem with continuous transitions between the healthy machine condition and the failure conditions. This is explicitly incorporated into the methodology and used to infer the condition of the gearbox in an open set recognition framework. This methodology uses a di erent approach to the conventional supervised machine learning techniques found in the literature. The methodologies are investigated on numerical and experimental datasets generated under varying operating conditions. The results indicate the bene ts of incorporating prior knowledge into the fault diagnosis process: the fault diagnosis techniques can be more robust to varying operating conditions, more sensitive to damage and easier to interpret by a non-expert. In summary, fault diagnosis techniques are more e ective when prior knowledge is utilised.
Book Synopsis Chapter The Use of Electrical Measurements of Wind Turbine Generators for Drive Train Condition Monitoring by : Estefania Artigao
Download or read book Chapter The Use of Electrical Measurements of Wind Turbine Generators for Drive Train Condition Monitoring written by Estefania Artigao and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: More modern and larger wind turbine (WT) generators are under continuous development. These exhibit more faults than smaller ones, which becomes critical offshore. Under this framework, operation and maintenance (O&M) is the key to improve reliability and availability of WTs, where condition-based maintenance (CBM) is currently seen as the preferred approach by the early detection and diagnosis of critical faults for WTs. The induction generator is one of the biggest contributors to failure rates and downtime of WTs, together with the gearbox and the drive train. In the present chapter, current signature analysis (CSA) will be introduced as a means for fault detection of WTs. CSA is a cost-effective and nonintrusive technique that can monitor both mechanical and electrical faults within the induction generator, as well as bearing- and gearbox-related faults. Different test cases of in-service wind turbine generators will be used to illustrate its usefulness.
Book Synopsis Current-based Fault Diagnosis and Prognosis for Wind Turbine Drivetrain Gearboxes by : Fangzhou Cheng
Download or read book Current-based Fault Diagnosis and Prognosis for Wind Turbine Drivetrain Gearboxes written by Fangzhou Cheng and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this dissertation, current-based fault diagnosis methods are proposed for wind turbine drivetrain gearboxes. New signal conditioning methods are developed to extract fault features from current signals of doubly-fed induction generator (DFIG)-based wind turbines under nonstationary conditions. A deep classifier consists of stacked autoencoder and support vector machine (SVM) is proposed to improve the accuracy of fault classification results of the traditional SVM classifier. Moreover, a new fault prognosis and RUL prediction method for drivetrain gearboxes based on adaptive neuro fuzzy inference system (ANFIS) and particle filtering (PF) technique is proposed. Finally, an enhanced PF algorithm is proposed to improve the fault prognosis and RUL prediction accuracy of the ANFIS-PF method. The proposed methods have been validated by small-scale permanent magnet synchronous generator (PMSG)- and DFIG-based wind turbine drivetrain simulators in the lab and MW-scale DFIG-based wind turbines in the field.
Book Synopsis The Use of Electrical Measurements of Wind Turbine Generators for Drive Train Condition Monitoring by : Emilio Gomez-Lazaro
Download or read book The Use of Electrical Measurements of Wind Turbine Generators for Drive Train Condition Monitoring written by Emilio Gomez-Lazaro and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: More modern and larger wind turbine (WT) generators are under continuous development. These exhibit more faults than smaller ones, which becomes critical offshore. Under this framework, operation and maintenance (O&M) is the key to improve reliability and availability of WTs, where condition-based maintenance (CBM) is currently seen as the preferred approach by the early detection and diagnosis of critical faults for WTs. The induction generator is one of the biggest contributors to failure rates and downtime of WTs, together with the gearbox and the drive train. In the present chapter, current signature analysis (CSA) will be introduced as a means for fault detection of WTs. CSA is a cost-effective and nonintrusive technique that can monitor both mechanical and electrical faults within the induction generator, as well as bearing- and gearbox-related faults. Different test cases of in-service wind turbine generators will be used to illustrate its usefulness.
Book Synopsis Condition Monitoring and Faults Diagnosis of Induction Motors by : Nordin Saad
Download or read book Condition Monitoring and Faults Diagnosis of Induction Motors written by Nordin Saad and published by CRC Press. This book was released on 2018-07-11 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers various issues related to machinery condition monitoring, signal processing and conditioning, instrumentation and measurements, faults for induction motors failures, new trends in condition monitoring, and the fault identification process using motor currents electrical signature analysis. It aims to present a new non-invasive and non-intrusive condition monitoring system, which has the capability to detect various defects in induction motor at incipient stages within an arbitrary noise conditions. The performance of the developed system has been analyzed theoretically and experimentally under various loading conditions of the motor. Covers current and new approaches applied to fault diagnosis and condition monitoring. Integrates concepts and practical implementation of electrical signature analysis. Utilizes LabVIEW tool for condition monitoring problems. Incorporates real-world case studies. Paves way a technology potentially for prescriptive maintenance via IIoT.
Book Synopsis Vibration-based Condition Monitoring by : Robert Bond Randall
Download or read book Vibration-based Condition Monitoring written by Robert Bond Randall and published by John Wiley & Sons. This book was released on 2011-03-25 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Without doubt the best modern and up-to-date text on the topic, wirtten by one of the world leading experts in the field. Should be on the desk of any practitioner or researcher involved in the field of Machine Condition Monitoring" Simon Braun, Israel Institute of Technology Explaining complex ideas in an easy to understand way, Vibration-based Condition Monitoring provides a comprehensive survey of the application of vibration analysis to the condition monitoring of machines. Reflecting the natural progression of these systems by presenting the fundamental material and then moving onto detection, diagnosis and prognosis, Randall presents classic and state-of-the-art research results that cover vibration signals from rotating and reciprocating machines; basic signal processing techniques; fault detection; diagnostic techniques, and prognostics. Developed out of notes for a course in machine condition monitoring given by Robert Bond Randall over ten years at the University of New South Wales, Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications is essential reading for graduate and postgraduate students/ researchers in machine condition monitoring and diagnostics as well as condition monitoring practitioners and machine manufacturers who want to include a machine monitoring service with their product. Includes a number of exercises for each chapter, many based on Matlab, to illustrate basic points as well as to facilitate the use of the book as a textbook for courses in the topic. Accompanied by a website www.wiley.com/go/randall housing exercises along with data sets and implementation code in Matlab for some of the methods as well as other pedagogical aids. Authored by an internationally recognised authority in the area of condition monitoring.
Book Synopsis Electrical System Condition Monitoring and Fault Diagnosis in Wind Turbines by : Mohd Faiz Sufian
Download or read book Electrical System Condition Monitoring and Fault Diagnosis in Wind Turbines written by Mohd Faiz Sufian and published by . This book was released on 2016 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Condition Monitoring and Nonlinear Frequency Analysis Based Fault Detection of Mechanical Vibration Systems by : Hogir Rafiq
Download or read book Condition Monitoring and Nonlinear Frequency Analysis Based Fault Detection of Mechanical Vibration Systems written by Hogir Rafiq and published by Springer Nature. This book was released on 2023-08-26 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hogir Rafiq proposes two approaches, the signal processing based condition monitoring approaches with applications to fault detection in gear systems, and application of deep mathematical and system theoretical methods to fault detection. The author develops the multivariate empirical mode decomposition (MEMD) algorithm to enhance the capability of extracting fault features and theoretical problems in nonlinear frequency analysis methods, respectively. The effectiveness has been demonstrated by an experimental study on a wind turbine gearbox test rig.
Book Synopsis Wind Turbine Gearbox Diagnostics Using Artificial Intelligence by : Sofia Koukoura
Download or read book Wind Turbine Gearbox Diagnostics Using Artificial Intelligence written by Sofia Koukoura and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: To meet the latest strike price, the cost of energy from wind turbines needs to decrease.One of the biggest cost contributors to wind energy is the operation and maintenance cost. If this cost is driven down, the cost of energy of wind will substantially decrease and the reliability of the wind turbine assets need to increase. For that reason, condition monitoring systems are installed in modern wind turbines. These systems collect data and in abnormal conditions trigger alarms that are an indication of a fault. Maintenance actions can be scheduled accordingly that way, and faulty components can be replaced before catastrophic failures and large downtimes occur.Therefore, the aim of this thesis is to utilise vibration and performance data collected from wind turbine gearboxes, in order to perform fault detection and diagnosis.The data is collected at various times prior to gearbox component failures and advanced signal processing techniques are applied to reveal fault signatures. Machine learning models are trained based on features extracted from vibration spectra and operational data separately, but also a combination of these two types of data is investigated. The output is fault detection and isolation on gearbox component level. Both unit-specific and fleet-based methods are examines. The models are trained on specific turbines,but the generalization to other turbines is also examined.The above will provide a exible but robust framework for the early detection of emerging wind turbine faults. This will lead to minimisation of the wind turbine downtime and increase of the wind turbines reliability and income through operational enhancement.
Book Synopsis Automated Fault Detection for Wind Farm Condition Monitoring by : Ammar S. Zaher
Download or read book Automated Fault Detection for Wind Farm Condition Monitoring written by Ammar S. Zaher and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind turbines are becoming more established as an economically viable alternative to fossil-fuelled power generation. Recently wind farms consisting of hundreds of units are being built in various locations around the country adding a significant amount of electrical generating capacity. As the size of wind farms continues to increase, business economics dictate the need for effective condition monitoring systems that allow for careful asset management to minimise downtime and maximise availability and profits. Most modern turbines are built with integrated condition monitoring systems that acquire data and store this through Supervisory Control and Data Acquisition (SCADA) Systems. This data quickly becomes unmanageable and brings with it the problems of managing and interpreting it. This thesis considers the development of an automated SCADA data analysis system that aims to interpret the large volumes of data that are generated, with the intention of identifying faults in their early stages before they manifest into more serious catastrophic failures. A number of different analysis techniques for interpreting the SCADA are considered and a methodology of identifying faults in their incipient stages in the gearbox and generator using basic SCADA temperature data is described. Most CM techniques in the research literature focus on one aspect of a wind turbine with regards to identifying faults that may manifest within it. This research also puts forward the development of a multi-agent platform capable of combing multiple data sources and analysis techniques into one system to improve the opportunity of extracting and interpreting interesting information found in the SCADA and present it through a single point of contact for the operator. This provides the possibility of developing a more complete condition monitoring system that can monitor all of the main components of each turbine across a complete wind farm using both, existing and future condition monitoring techniques developed for the interpretation of wind farm data.
