Condition monitoring wind turbine gearboxes using on-line/in-line oil analysis techniques

Paper examining condition monitoring wind turbine gearboxes using on-line/in-line oil analysis techniques

Detailed state of the art review for the different on-line/in-line oil analysis techniques in context of wind turbine gearboxes

The main driver behind developing advanced condition monitoring (CM) systems for the wind energy industry is the delivery of improved asset management regarding the operation and maintenance of the gearbox and other wind turbine components and systems. Current gearbox CM systems mainly detect faults by identifying ferrous materials, water, and air within oil by changes in certain properties such as electrical fields. In order to detect oil degradation and identify particles, more advanced devices are required to allow a better maintenance regime to be established. Current technologies available specifically for this purpose include Fourier transform infrared (FTIR) spectroscopy and ferrography. There are also several technologies that have not yet been or have been recently applied to CM problems. After reviewing the current state of the art, it is recommended that a combination of sensors would be used that analyze different characteristics of the oil. The information individually would not be highly accurate but combined it is fully expected that greater accuracy can be obtained. The technologies that are suitable in terms of cost, size, accuracy, and development are online ferrography, selective fluorescence spectroscopy, scattering measurements, FTIR, photoacoustic spectroscopy, and solid state viscometers

Mechanical Wear Debris Feature, Detection, and Diagnosis: A Review

Mechanical debris is an important product of friction wear, which is also a crucial approach to know the running status of a machine. Many studies have been conducted on mechanical debris in related fields such as tribology, instrument, and diagnosis. This paper presents a comprehensive review of these studies, which summarizes wear mechanisms (e.g., abrasive wear, fatigue wear, and adhesive wear) and debris features (e.g., concentration (number), size, morphology, and composition), analyzes detection methods principles (e.g., offline: spectrograph and ferrograph, and online: optical method, inductive method, resistive-capacitive method, and acoustic method), reviews developments of online inductive methods, and investigates the progress of debris-based diagnosis. Finally, several notable problems are discussed for further studies. (C) 2017 Chinese Society of Aeronautics and Astronautics

Magnetic properties of ferromagnetic particles under alternating magnetic fields: Focus on particle detection sensor applications

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. The electromagnetic wear particles detection sensor has been widely studied due to its ability to monitor the wear status of equipment in real time. To precisely estimate the change of the magnetic energy of the sensor coil caused by the wear particles, the magnetic property models of wear particles under the alternating magnetic field was established. The models consider the hysteresis effect and the eddy current effect of the wear particles. The analysis and experimental results show that with the increase of the effective field frequency, the change of the magnetic energy caused by the wear particles gradually decrease, which makes the induced electromotive force output by the sensor reduce with the decrease of the particle speed, so a signal compensation method is presented to obtain a unified signal when the same wear particle passing through the sensor in different speeds. The magnetic coupling effect between the two adjacent wear particles is analyzed. The result illustrates that the change of the magnetic energy caused by the dual wear particles system is larger than the sum of the energy variation caused by two independent wear particles, and with the increase of the interparticle distance, the magnetic coupling effect gradually weakens and disappears

Sensors and Tribological Systems: Applications for Industry 4.0

Purpose: The involvement of wear, friction and lubrication in engineering systems and industrial applications makes it imperative to study the various aspects of tribology in relation with advanced technologies and concepts. The concept of Industry 4.0 and its implementation further faces a lot of barriers particularly in the developing economies. Real-time and reliable data is an important enabler for implementation of the concept of Industry 4.0. For availability of reliable and real-time data about various tribological systems is crucial in applying the various concepts of Industry 4.0. This paper attempts to highlight the role of sensors related to friction, wear and lubrication in implementing Industry 4.0 in various tribology related industries and equipment. Design/methodology/approach: A through literature review has been done to study the interrelationships between the availability of tribology related data and implementation of Industry 4.0 are also discussed. Relevant and recent research papers from prominent databases have been included. A detailed overview about the various types of sensors employed in generating tribological data is also presented. Some studies related to application of machine learning and Artificial Intelligence are also included in the paper. A discussion on fault diagnosis and cyber physical systems in connection with tribology has also been included. Findings: Industry 4.0 and tribology are interconnected through various means and the various pillars of industry 4.0 such as big data, Artificial Intelligence can effectively be implemented in various tribological systems. Data is an important parameter in effective application of concepts of industry 4.0 in the tribological environment. Sensors have a vital role to play in the implementation of industry 4.0 in tribological systems. Determining the machine health, carrying out maintenance in off-shore and remote mechanical systems is possible by applying online-real-time data acquisition. Originality: The paper tries to relate the pillars of Industry 4.0 with various aspects of tribology. The paper is a first of its kind wherein the interdisciplinary field of tribology has been linked with industry 4.0. The paper also highlights the role of sensors in generating tribological data related to the critical parameters such as wear rate, coefficient of friction, surface roughness which is critical in implementing the various pillars of industry 4.0

Real-time and online lubricating oil condition monitoring enabled by triboelectric nanogenerator

An intelligent monitoring lubricant is essential for the development of smart machines because unexpected and fatal failures of critical dynamic components in the machines happen every day, threatening the life and health of humans. Inspired by the triboelectric nanogenerators (TENGs) work on water, we present a feasible way to prepare a self-powered triboelectric sensor for real-time monitoring of lubricating oils via the contact electrification process of oil-solid contact (O-S TENG). Typical intruding contaminants in pure base oils can be successfully monitored. The O-S TENG has very good sensitivity, which even can respectively detect at least 1 mg mL-1 debris and 0.01 wt % water contaminants. Furthermore, the real-time monitoring of formulated engine lubricating oil in a real engine oil tank is achieved. Our results show that electron transfer is possible from an oil to solid surface during contact electrification. The electrical output characteristic depends on the screen effect from such as wear debris, deposited carbons, and age-induced organic molecules in oils. Previous work only qualitatively identified that the output ability of liquid can be improved by leaving less liquid adsorbed on the TENG surface, but the adsorption mass and adsorption speed of liquid and its consequences for the output performance were not studied. We quantitatively study the internal relationship between output ability and adsorbing behavior of lubricating oils by quartz crystal microbalance with dissipation (QCM-D) for liquid-solid contact interfaces. This study provides a real-time, online, self-powered strategy for intelligent diagnosis of lubricating oils

Active Lubricant Condition Monitoring

Lubrication in a mechanical system is like blood flowing through a human body. It is a great source to detect in advance any troubles in the system. As blood analysis shows the diseases in our body in a machine the oil analysis shows the fault in a system. Active lubricant condition monitoring is a great prediction technique which would help improve the reliability and reduce the maintenance costs for a system. The paper discusses about how to develop an Active oil condition monitoring where oil condition can be monitored online and how to achieve an active maintenance action. It discusses the design and setup of an oil condition monitoring system on a test bench provided. Different oil degradation parameters are analysed and sensors are introduced to monitor this parameters. Integration of microcontroller for wireless communication and use of different software’s to acquire and process the data from the sensors to provide the real time condition of the system is discussed. This includes different actuation system that can be introduced to help the maintenance of the system to minimum and reduce the maintenance or damaging of the system components

On-Line Oil Condition Monitoring for Marine Gearboxes : This thesis addresses the importance of oil condition monitoring in marine reduction gearboxes and compares the sensitivity and usage of three different sensors, each with its own working principle

Master's thesis in Mechatronics (MAS500)Failures in marine reduction gearboxes lead to substantial costs. With the use of oil condition moni-toring, these failures can be foreseen so that preemptive measures can be taken. The development ofoil condition monitoring equipment has come a long way, and it is time to start using this technology.There are various reasons why a gearbox failure, and as most of them are a result of inadequatelubrication, several things can be done to reduce these failures. By testing 3 different sensors in agearbox lubrication system, this study goes through each sensor technology and aims to figure outwhat is important to consider when selecting a sensor for oil condition monitoring.The sensors discussed and tested are Gill 4212 Oil Condition Monitoring Sensor, Poseidon TridentQW3100, and Parker Kittiwake Metal Wear Debris Sensor. To test these sensors, several experiments,with a variety of added contaminants, are designed to find the strengths and weaknesses of each sensor.In the end, a conclusion is made on how the tested sensors meet those requirements and what can bedone in the future to find an even better sensor configuration to prevent gearbox failures

Development of novel gearbox lubrication condition monitoring sensors in the context of wind turbine gearboxes

Wind power has become established as an alternative power source that forms a significant proportion of national energy generation. An increasing proportion of turbines is being constructed offshore to exploit higher average wind speeds and to avoid development issues associated with onshore wind farms. Isolated locations and unpredictable weather conditions lead to increased access costs for operators when conducting scheduled and unscheduled maintenance and repairs. This has increased interest in condition monitoring systems which can track the current state of components within a wind turbine and provide operators with predicted future trends. Asset management can be improved through condition based maintenance regimes and preventative repairs. Development of novel condition monitoring systems that can accurately predict incipient damage can optimise operational performance and reduce the overall level of wind turbine generation costs. The work described in this thesis presents the development of novel sensors that may be applied to monitor wind turbine gearboxes, a component that experiences relatively high failure rates and causes considerable turbine downtime. Current systems and technology that may be adapted for use in wind turbine condition monitoring are evaluated. Lubrication related monitoring systems have been identified as an area that could be improved and are divided into those that track liberated wear material suspended in the lubricant and those that assess the state of the lubricant itself. This study presents two novel lubrication based gearbox monitoring sensors that potentially offer a low cost solution for continuous data capture. The first demonstrates the potential for active pixel sensors such as those found in digital cameras to capture images of wear particles within gearbox lubricants. Particle morphology was tracked in this system, allowing the type of particles to be correlated with the type of wear that is generated and a potential source. The second sensor uses a targeted form of infra-red absorption spectroscopy to track changes in the lubricant chemistry due to the increase in acidity. Ensuring the lubricant is functioning correctly decreases component stress and fatigue, reducing maintenance requirements.Wind power has become established as an alternative power source that forms a significant proportion of national energy generation. An increasing proportion of turbines is being constructed offshore to exploit higher average wind speeds and to avoid development issues associated with onshore wind farms. Isolated locations and unpredictable weather conditions lead to increased access costs for operators when conducting scheduled and unscheduled maintenance and repairs. This has increased interest in condition monitoring systems which can track the current state of components within a wind turbine and provide operators with predicted future trends. Asset management can be improved through condition based maintenance regimes and preventative repairs. Development of novel condition monitoring systems that can accurately predict incipient damage can optimise operational performance and reduce the overall level of wind turbine generation costs. The work described in this thesis presents the development of novel sensors that may be applied to monitor wind turbine gearboxes, a component that experiences relatively high failure rates and causes considerable turbine downtime. Current systems and technology that may be adapted for use in wind turbine condition monitoring are evaluated. Lubrication related monitoring systems have been identified as an area that could be improved and are divided into those that track liberated wear material suspended in the lubricant and those that assess the state of the lubricant itself. This study presents two novel lubrication based gearbox monitoring sensors that potentially offer a low cost solution for continuous data capture. The first demonstrates the potential for active pixel sensors such as those found in digital cameras to capture images of wear particles within gearbox lubricants. Particle morphology was tracked in this system, allowing the type of particles to be correlated with the type of wear that is generated and a potential source. The second sensor uses a targeted form of infra-red absorption spectroscopy to track changes in the lubricant chemistry due to the increase in acidity. Ensuring the lubricant is functioning correctly decreases component stress and fatigue, reducing maintenance requirements