Determining Water Content at Saturation for Three Common Wind Turbine Gearbox Oils: Mobilgear SHC XMP 320, AMSOIL EP Gear Lube ISO-320 and Castrol Optigear A320

2013 ◽  
Author(s):  
Matthew S. Whitten ◽  
Kim A. Stelson
Keyword(s):  
Relative Humidity ◽  
Service Life ◽  
Wind Turbine ◽  
Water Content ◽  
Energy Demand ◽  
Operating Conditions ◽  
Energy Output ◽  
Wind Turbine Gearbox ◽  
Saturation Limit ◽  
Field Samples

To meet America’s growing energy demand, wind turbines will need to become larger and more cost effective [1]. However, estimates show that the average wind farm energy output is 10 percent less than predicted and that half of this short fall is due to gearbox downtime [2]. Increasing service life of the gearbox begins with monitoring the oil and controlling contamination by both particles and water. When online relative humidity monitoring is not available, oil samples from the gearbox need to be analyzed for quality and remaining service life. Field samples sent to a lab for testing often report water content as parts per million (ppm). Because the gearbox oil should be dried or replaced before the relative humidity reaches 100 percent (saturation limit), a relationship between ppm and the oil’s saturation limit needs to be established. The present research characterizes this relationship using an environmental chamber to simulate operating conditions and Karl Fischer titration to measure the water content. The resulting plots are of water content (ppm) at saturation versus temperature for three common wind turbine gearbox oils: Mobilgear SHC XMP 320, AMSOIL EP Gear Lube ISO-320 and Castrol Optigear A320.

The Effect of Operational Parameters on Vibration Signals of Wind Turbine Gearboxes

2019 ◽  
Author(s):  
Sofia Koukoura ◽  
Eric Bechhoefer ◽  
James Carroll ◽  
Alasdair McDonald
Keyword(s):  
Wind Turbine ◽  
Operating Conditions ◽  
Operating Costs ◽  
Normal Operation ◽  
Operational Parameters ◽  
Wind Turbine Gearbox ◽  
Vibration Signals ◽  
Gearbox Vibration ◽  
Maintenance Decisions ◽  
Yaw Angle

Abstract Vibration signals are widely used in wind turbine drivetrain condition monitoring with the aim of fault detection, optimization of maintenance actions and therefore reduction of operating costs. Signals are most commonly sampled by accelerometers at high frequency for a few seconds. The behavior of these signals varies significantly, even within the same turbine and depends on different parameters. The aim of this paper is to explore the effect of operational and environmental conditions on the vibration signals of wind turbine gearboxes. Parameters such as speed, power and yaw angle are taken into account and the change in vibration signals is examined. The study includes examples from real wind turbines of both normal operation and operation with known gearbox faults. The effects of varying operating conditions are removed using kalman filtering as a state observer. The findings of this paper will aid in understanding wind turbine gearbox vibration signals, making more informed decisions in the presence of faults and improving maintenance decisions.

scholarly journals The Enhancement of Weak Bearing Fault Signatures by Stochastic Resonance with a Novel Potential Function

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6348
Author(s):  
Chao Zhang ◽  
Haoran Duan ◽  
Yu Xue ◽  
Biao Zhang ◽  
Bin Fan ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Stochastic Resonance ◽  
Operating Conditions ◽  
Detection Accuracy ◽  
Wind Turbine Gearbox ◽  
Resonance Model ◽  
Function Type ◽  
Vibration Signals ◽  
Fourier Decomposition ◽  
Bearing Fault

As the critical parts of wind turbines, rolling bearings are prone to faults due to the extreme operating conditions. To avoid the influence of the faults on wind turbine performance and asset damages, many methods have been developed to monitor the health of bearings by accurately analyzing their vibration signals. Stochastic resonance (SR)-based signal enhancement is one of effective methods to extract the characteristic frequencies of weak fault signals. This paper constructs a new SR model, which is established based on the joint properties of both Power Function Type Single-Well and Woods-Saxon (PWS), and used to make fault frequency easy to detect. However, the collected vibration signals usually contain strong noise interference, which leads to poor effect when using the SR analysis method alone. Therefore, this paper combines the Fourier Decomposition Method (FDM) and SR to improve the detection accuracy of bearing fault signals feature. Here, the FDM is an alternative method of empirical mode decomposition (EMD), which is widely used in nonlinear signal analysis to eliminate the interference of low-frequency coupled signals. In this paper, a new stochastic resonance model (PWS) is constructed and combined with FDM to enhance the vibration signals of the input and output shaft of the wind turbine gearbox bearing, make the bearing fault signals can be easily detected. The results show that the combination of the two methods can detect the frequency of a bearing failure, thereby reminding maintenance personnel to urgently develop a maintenance plan.

scholarly journals Evaluating the Performances of Interval Starting Accessibility Drying (ISAD) through Protein and Total Polyphenol Contents of Blue Crabmeat (Portunus segnis)

Processes ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1698
Author(s):  
Hela Gliguem ◽  
Wafa Hajji ◽  
Chaima Rekik ◽  
Karim Allaf ◽  
Sihem Bellagha
Keyword(s):  
Relative Humidity ◽  
Water Content ◽  
Evaporation Rate ◽  
Quality Parameters ◽  
Operating Conditions ◽  
Convective Drying ◽  
Residual Water ◽  
Fishing Activity ◽  
Total Polyphenol ◽  
Portunus Segnis

Blue crab (Portunus segnis) proliferation on Tunisian coasts started in 2014/2015. It has heavily impacted the balance of other species, local biodiversity, and fishing activity. Limiting these drawbacks may be achieved through ways promoting crabmeat. For this purpose, two different drying modes were tested: Conventional convective drying (CCD) and interval starting accessibility drying (ISAD) under 45 °C and relative humidity of 40%. Several air velocities were assayed under CCD: 1.5, 2.5, 3.5, and 5 m.s−1. Two different ISAD tests were run with different time-related conditions: drying period of 15 s and tempering period of 15 or 60 s. Drying modes and operating conditions performances were compared through proteins and total polyphenol contents (TPCs) evolution during the treatment. Important polyphenol and protein losses were observed between raw and processed crabmeat. Airflow velocities have a significant effect on crabmeat quality preservation. ISAD method under 15 s/60 s allowed the best preservation of these quality parameters. TPC and proteins losses and kinetics during drying under CCD or ISAD were modelled and correlations were established between the quality parameters, the residual water content at all drying times, and the evaporation rate.

scholarly journals Operating Behavior of Sliding Planet Gear Bearings for Wind Turbine Gearbox Applications—Part II: Impact of Structure Deformation

Lubricants ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 98
Author(s):  
Thomas Hagemann ◽  
Huanhuan Ding ◽  
Esther Radtke ◽  
Hubert Schwarze
Keyword(s):  
Wind Turbine ◽  
Peak Load ◽  
Planetary Gear ◽  
Operating Conditions ◽  
Wind Turbine Gearbox ◽  
Structure Deformation ◽  
Drive Trains ◽  
Planet Gear ◽  
The Impact ◽  
Bearing Analysis

The use of planetary gear stages intends to increase power density in drive trains of rotating machinery. Due to lightweight requirements on this type of machine elements, structures are comparably flexible while mechanical loads are high. This study investigates the impact of structure deformation on sliding planet gear bearings applied in the planetary stages of wind turbine gearboxes with helical gears. It focuses on three main objectives: (i) development of a procedure for the time-efficient thermo-elasto-hydrodynamic (TEHD) analysis of sliding planet gear bearing; (ii) understanding of the specific deformation characteristics of this application; (iii) investigation of the planet gear bearing’s modified operating behavior, caused by the deformation of the sliding surfaces. Generally, results indicate an improvement of predicted operating conditions by consideration of structure deformation in the bearing analysis for this application. Peak load in the bearing decreases because the loaded proportion of the sliding surface increases. Moreover, tendencies of single design measures, determined for rigid geometries, keep valid but exhibit significantly different magnitudes under consideration of structure deformation. Results show that consideration of structure flexibility is essential for sliding planet gear bearing analysis if quantitative assertions on load distributions, wear phenomena, and interaction of the bearing with other components are required.

Finite Element Analysis of Composite Offshore Wind Turbine Blades Under Operating Conditions

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
M. Tarfaoui ◽  
M. Nachtane ◽  
H. Boudounit
Keyword(s):  
Finite Element ◽  
Wind Turbine ◽  
Energy Demand ◽  
Fossil Fuels ◽  
Renewable Energy Sources ◽  
Turbine Blades ◽  
Operating Conditions ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Element Analysis

Abstract World energy demand has increased immediately and is expected to continue to grow in the foreseeable future. Therefore, an overall change of energy consumption continuously from fossil fuels to renewable energy sources, and low service and maintenance price are the benefits of using renewable energies such as using wind turbines as an electricity generator. In this context, offshore wind power refers to the development of wind parks in bodies of water to produce electricity from wind. Better wind speeds are available offshore compared to on land, so offshore wind power's contribution in terms of electricity supplied is higher. However, these structures are very susceptible to degradation of their mechanical properties considering various hostile loads. The scope of this work is the study of the damage noticed in full-scale 48 m fiberglass composite blades for offshore wind turbine. In this paper, the most advanced features currently available in finite element (FE) abaqus/Implicit have been employed to simulate the response of blades for a sound knowledge of the mechanical behavior of the structures and then localize the susceptible sections.

Gaining Insight in Wind Turbine Drivetrain Dynamics by Means of Automatic Operational Modal Analysis Combined With Machine Learning Algorithms

2019 ◽  
Author(s):  
Nicoletta Gioia ◽  
P. J. Daems ◽  
C. Peeters ◽  
P. Guillaume ◽  
J. Helsen ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Operating Conditions ◽  
Machine Learning Algorithms ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Detailed Knowledge ◽  
Wind Turbine Gearbox ◽  
Modal Model ◽  
Modal Behavior ◽  
Gaining Insight

Abstract Detailed knowledge about the modal model is essential to enhance the NVH behavior of (rotating) machines. To have more realistic insight in the modal behavior of the machines, observation of modal parameters must be extended to a significant amount of time, in which all the significant operating conditions of the turbine can be investigated, together with the transition events from one operating condition to another. To allow the processing of a large amount of data, automated OMA techniques are used: once frequency and damping values can be characterized for the important resonances, it becomes possible to gain insights in their changes. This paper will focus on processing experimental data of an offshore wind turbine gearbox and investigate the changes in resonance frequency and damping over time.

Characteristic Analysis of Wind Turbine Gearbox Considering Non-Torque Loading

2013 ◽  
Vol 135 (4) ◽  
Author(s):  
Young-Jun Park ◽  
Geun-Ho Lee ◽  
Jin-Seop Song ◽  
Yong-Yun Nam
Keyword(s):  
Service Life ◽  
Wind Turbine ◽  
Load Distribution ◽  
Load Sharing ◽  
Characteristic Analysis ◽  
Wind Turbine Gearbox ◽  
Gear Mesh ◽  
Design Load ◽  
Static Conditions ◽  
External Loads

In the design of wind turbine gearboxes, the most important objective is to improve the durability to guarantee a service life of more than 20 years. This work investigates how external loads caused by wind fluctuation influence both the load distribution over the gear tooth flank and the planet load sharing. A whole system model is developed to analyze a wind turbine gearbox (WTG) that consists of planetary gearsets. Two models for different design loads are employed to quantify how external loads acting on the input shaft of the WTG affect the load distribution of the gears and the load sharing among the planets under quasi-static conditions. One model considers only the torque for the design load, whereas the other model also considers non-torque loads. For two models, the results for the gear mesh misalignment, contact pattern, load distribution, and load sharing are different, and this leads to different gear safety factors. Therefore, the results indicate that it is appropriate to consider the non-torque loads in addition to the torque as the design load for a WTG, and that this is very important to accurately determine the design load that guarantee the service life of a WTG.

scholarly journals Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

2019 ◽  
Author(s):  
Alexandre Mauricio ◽  
Shuangwen Sheng ◽  
Konstantinos Gryllias
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Frequency Band ◽  
Operating Conditions ◽  
Center Frequency ◽  
False Alarms ◽  
Spectral Coherence ◽  
Wind Turbine Gearbox ◽  
Data Set ◽  
Monitoring Techniques

Abstract Digitally enhanced services for wind power could reduce Operations and Maintenance (O&M) costs as well as the Levelised Cost Of Energy (LCOE). Therefore, there is a continuous need for advanced monitoring techniques which can exploit the opportunities of Internet of Things (IoT) and Big Data Analytics, revolutionizing the future of the energy sector. The heart of wind turbines is a rather complex epicyclic gearbox. Among others, extremely critical gearbox components which are often responsible for machinery stops are the rolling element bearings. The vibration signatures of bearings are rather weak compared to other components, such as gears, and as a result an extended number of signal processing techniques and tools have been proposed during the last decades, focusing towards accurate, early, and on time bearing fault detection with limited false alarms and missed detections. Envelope Analysis is one of the most important methodologies, where an envelope of the vibration signal is estimated usually after filtering around a frequency band excited by impacts due to the bearing faults. Different tools, such as Kurtogram, have been proposed in order to accurately select the optimum filter parameters (center frequency and bandwidth). Cyclic Spectral Correlation and Cyclic Spectral Coherence, based on Cyclostationary Analysis, have been proved as very powerful tools for condition monitoring. The monitoring techniques seem to have reached a mature level in case a machinery operates under steady speed and load. On the other hand, in case the operating conditions change, it is still unclear whether the change of the monitoring indicators is due to the change of the health of the machinery or due to the change of the operating parameters. Recently, the authors have proposed a new tool called IESFOgram, which is based on Cyclic Spectral Coherence and can automatically select the filtering band. Furthermore, the Cyclic Spectral Coherence is integrated along the selected frequency band leading to an Improved Envelope Spectrum. In this paper, the performance of the tool is evaluated and further extended on cases operating under different speeds and different loads. The effectiveness of the methodology is tested and validated on the National Renewable Energy Laboratory (NREL) wind turbine gearbox vibration condition monitoring benchmarking data set which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.

scholarly journals Condition Monitoring of Wind Turbine Planetary Gearboxes Under Different Operating Conditions

2020 ◽  
Vol 142 (3) ◽  
Author(s):  
Alexandre Mauricio ◽  
Shuangwen Sheng ◽  
Konstantinos Gryllias
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Frequency Band ◽  
Operating Conditions ◽  
Center Frequency ◽  
False Alarms ◽  
Spectral Correlation ◽  
Wind Turbine Gearbox ◽  
Monitoring Techniques ◽  
Envelope Spectrum

Abstract Digitally enhanced services for wind power could reduce operations and maintenance costs as well as the levelized cost of energy. Therefore, there is a continuous need for advanced monitoring techniques, which can exploit the opportunities of internet of things and big data analytics, revolutionizing the future of the energy sector. The heart of wind turbines is a rather complex epicyclic gearbox. Among others, extremely critical gearbox components, which are often responsible for machinery stops, are the rolling element bearings. The vibration signatures of bearings are rather weak compared to other components, such as gears, and as a result, an extended number of signal processing techniques and tools have been proposed during the last decades, focusing toward accurate, early, and on time bearing fault detection with limited false alarms and missed detections. Envelope analysis is one of the most important methodologies, where an envelope of the vibration signal is estimated usually after filtering around a frequency band excited by impacts due to the bearing faults. Different tools, such as Kurtogram, have been proposed in order to accurately select the optimum filter parameters (center frequency and bandwidth). Cyclic spectral correlation (CSC) and cyclic spectral coherence (CSCoh), based on cyclostationary analysis, have been proved as very powerful tools for condition monitoring. The monitoring techniques seem to have reached a mature level in case a machinery operates under steady speed and load. On the other hand, in case the operating conditions change, it is still unclear whether the change of the monitoring indicators is due to the change of the health of the machinery or due to the change of the operating parameters. Recently, the authors have proposed a new tool called improved envelope spectrum via feature optimization-gram (IESFOgram), which is based on CSCoh and can automatically select the filtering band. Furthermore, the CSCoh is integrated along the selected frequency band leading to an improved envelope spectrum (IES). In this paper, the performance of the tool is evaluated and further extended on cases operating under different speeds and different loads. The effectiveness of the methodology is tested and validated on the National Renewable Energy Laboratory (NREL) wind turbine gearbox vibration condition monitoring benchmarking dataset, which includes various faults with different levels of diagnostic complexity as well as various speed and load operating conditions.

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