Steady-state and vibration analysis of a WindPACT 1.5-MW turbine blade

Abdzaid, Enas Khazem; Ibraheem, Oday Abdullah; Sabri, Laith Abed

doi:10.5937/fmet1901195k

Cited by 14 publications

(11 citation statements)

References 9 publications

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“…It was shown that the VAWT of eggbeater types with thicker profiles is more suitable than thinner profiles because of the lift forces [5]. There are other researchers [6][7][8][9][10][11][12] who studied that rotating blade from a different point of view, where they investigated the stresses and vibration characteristics of a rotating blade that works under different kinds of conditions in general and especially the wind speed.…”

Section: Introductionmentioning

confidence: 99%

Design and Optimization of Vertical Axis Wind Turbines Using QBlade

Altmimi¹,

Alaskari

Abdullah

et al. 2021

ASI

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Wind energy is considered one of the most important sources of renewable energy in the world, because it contributes to reducing the negative effects on the environment. The most important types of wind turbines are horizontal and vertical axis wind turbines. This work presents the full details of design for vertical axis wind turbine (VAWT) and how to find the optimal values of necessary factors. Additionally, the results shed light on the efficiency and performance of the VAWT under different working conditions. It was taken into consideration the variety of surrounding environmental conditions (such as density and viscosity of fluid, number of elements of the blade, etc.) to simulate the working of vertical wind turbines under different working conditions. Furthermore, the effect of the design factors was investigated such as the number and size of the blades on the behavior and performance of VAWT. It was assumed that the vertical wind blade works in different sites of Iraq. QBlade software (Version 8) was used to achieve the calculations and optimization processes to obtain the optimal design of vertical axis wind turbines that is suitable for the promising sites. The results proved that accurate results can be obtained by using QBlade software.

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Section: Introductionmentioning

confidence: 99%

Design and Optimization of Vertical Axis Wind Turbines Using QBlade

Altmimi¹,

Alaskari

Abdullah

et al. 2021

ASI

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“…Vibration analysis is necessary for analyzing structures and preventing failure. It contains information about the structure'smode shapes and natural frequencies, which are widely used for fault detection purposes [6][7][8].Time-domain and frequency-domain vibration techniques are used separately or in combination for bearing performance analysis. Features such as Root Mean Square, Crest Factor, Kurtosis, and others are used in the time-domain analysis, whereas the Fourier Transform technique is used in the frequencydomain analysis [9].Also, control charts are a good example of a statistical process control system.The Shewhart X map is widely used for mean shift detection due to its ease of use.The exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) graphs are commonly used to detect relatively minor changes.…”

Section: Introductionmentioning

confidence: 99%

Rolling bearing fault detection based on vibration signal analysis and cumulative sum control chart

Mohammed¹,

Abdulhady²

2021

FME Transactions

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Monitoring the condition of rotating machines is essential for the systems' safety, reducing maintenance costs, and increasing reliability. In this research, a fault detection system for bearings was developed using the vibration analysis technique with the statistical control chart approach. A test rig was first designed and constructed; then, various bearing faults, such as inner race and outer race faults, were simulated and examined in the test rig. After capturing the vibration signals at different bearing health conditions, the time-domain signal analysis technique was employed for extracting different indicative features. The obtained time domain features were then analyzed to find out the most fault-significant feature. Then, only one feature was selected to design the control chart for bearing health condition monitoring. The cumulative sum control chart (CUSUM was utilized since it can detect the small changes in bearing health states. The results showed the effectiveness of utilizing this method, and it was found that the percentage of the out-of-control points in the event of the combined cage and ball fault to the number of tested samples is greater than the other fault types.

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“…Besides, the authors in [14] studied the optimal location of wind turbines and their per-formance in Iraq considering the costs and maximum possible capacities from the wind turbines in different sites. Furthermore, the steady-state deformation and stress that occur in wind turbine blades were investigated in [15]. A review of studies involving the design, optimization and techniques of different wind turbine blades were reported in [16].…”

Section: Introductionmentioning

confidence: 99%

Short term prediction of wind speed based on long-short term memory networks

Salman¹,

Rehman²,

Alawode³

et al. 2021

FME Transactions

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Power utilities, developers, and investors are pushing towards larger penetrations of wind and solar energy-based power generation in their existing energy mix. This study, specifically, looks towards wind power deployment in Saudi Arabia. For profitable development of wind power, accurate knowledge of wind speed both in spatial and time domains is critical. The wind speed is the most fluctuating and intermittent parameter in nature compared to all the meteorological variables. This uncertain nature of wind speed makes wind power more difficult to predict ahead of time. Wind speed is dependent on meteorological factors such as pressure, temperature, and relative humidity and can be predicted using these meteorological parameters. The forecasting of wind speed is critical for grid management, cost of energy, and quality power supply. This study proposes a short-term, multi-dimensional prediction of wind speed based on Long-Short Term Memory Networks (LSTM). Five models are developed by training the networks with measured hourly mean wind speed values from1980 to 2019 including exogenous inputs (temperature and pressure). The study found that LSTM is a powerful tool for a short-term prediction of wind speed. However, the accuracy of LSTM may be compromised with the inclusion of exogenous features in the training sets and the duration of prediction ahead.

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Steady-state and vibration analysis of a WindPACT 1.5-MW turbine blade

Cited by 14 publications

References 9 publications

Design and Optimization of Vertical Axis Wind Turbines Using QBlade

Design and Optimization of Vertical Axis Wind Turbines Using QBlade

Rolling bearing fault detection based on vibration signal analysis and cumulative sum control chart

Short term prediction of wind speed based on long-short term memory networks

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