Wind turbine technology is well known around the globe as an eco-friendly and effective renewable power source. However, this technology often faces reliability problems due to structural vibration. This study proposes a smart semi-active vibration control system using Magnetorheological (MR) dampers where feedback controllers are optimized with nature-inspired algorithms. Proportional integral derivative (PID) and Proportional integral (PI) controllers are designed to achieve the optimal desired force and current input for MR the damper. PID control parameters are optimized using an Ant colony optimization (ACO) algorithm. The effectiveness of the ACO algorithm is validated by comparing its performance with Ziegler-Nichols (Z-N) and particle swarm optimization (PSO). The placement of the MR damper on the tower is also investigated to ensure structural balance and optimal desired force from the MR damper. The simulation results show that the proposed semi-active PID-ACO control strategy can significantly reduce vibration on the wind turbine tower under different frequencies (i.e., 67%, 73%, 79% and 34.4% at 2 Hz, 3 Hz, 4.6 Hz and 6 Hz, respectively) and amplitudes (i.e. 50%, 58% and 67% for 50 N, 80 N, and 100 N, respectively). In this study, the simulation model is validated with an experimental study in terms of natural frequency, mode shape and uncontrolled response at the 1st mode. The proposed PID-ACO control strategy and optimal MR damper position is also implemented on a lab-scaled wind turbine tower model. The results show that the vibration reduction rate is 66% and 73% in the experimental and simulation study, respectively, at the 1st mode.
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Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data from different observation modes were analysed to determine (1) which observation mode most accurately retrieves tropical forest biomass information and (2) whether different modes, when considered together, yield improved results in comparison to identical data-sets analysed independently. We performed regression analysis to estimate above-ground forest biomass using PALSAR backscatter data for natural and planted forests in south-eastern Bangladesh. The coefficient of determination (r 2) was lower or equal to 0.499 (n = 70) when PALSAR data from different observation modes were separately considered, but increased sharply when one class (rubber) is dropped and average backscatter of fine beam single (FBS) and polrimetric (PLR) modes are used in the analysis. The results presented in this article are useful for both regional and global forest biomass inventories and fixing acquisition modes for planned L-band SAR missions. 相似文献
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The study examined the capability of dual-polarization SAR data for forest cover mapping and change assessment in the Brazilian Amazon Forest regions. Shuttle Imaging Radar (SIR)-C and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data were analysed to map and quantify deforestation. The images were classified using hybrid classifier, where each land cover was grouped in various spectral sub-classes interpreted on the imagery and later merged together to generate the desired land cover classes. The classification accuracy for forest was reasonably high (>90%). The technique applied in this study can be extended for operational mapping and monitoring of deforestation in the tropics, particularly for those regions which are often covered by cloud. 相似文献
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Dipankar Chakraborti Mohammad Mahmudur Rahman Bhaskar Das Amit Chatterjee Dipankar Das Biswajit Nayak Arup Pal Uttam Kumar Chowdhury Sad Ahmed Bhajan Kumar Biswas Mrinal Kumar Sengupta Md. Amir Hossain Gautam Samanta M. M. Roy Rathindra Nath Dutta Khitish Chandra Saha Subhas Chandra Mukherjee Shyamapada Pati Probir Bijoy Kar Adreesh Mukherjee Manoj Kumar 《Hydrogeology Journal》2017,25(4):1165-1181
During a 28-year field survey in India (1988–2016), groundwater arsenic contamination and its health effects were registered in the states of West Bengal, Jharkhand, Bihar and Uttar Pradesh in the Ganga River flood plain, and the states of Assam and Manipur in the flood plain of Brahamaputra and Imphal rivers. Groundwater of Rajnandgaon village in Chhattisgarh state, which is not in a flood plain, is also arsenic contaminated. More than 170,000 tubewell water samples from the affected states were analyzed and half of the samples had arsenic >10 μg/L (maximum concentration 3,700 μg/L). Chronic exposure to arsenic through drinking water causes various health problems, like dermal, neurological, reproductive and pregnancy effects, cardiovascular effects, diabetes mellitus, diseases of the respiratory and gastrointestinal systems, and cancers, typically involving the skin, lungs, liver, bladder, etc. About 4.5% of the 8,000 children from arsenic-affected villages of affected states were registered with mild to moderate arsenical skin lesions. In the preliminary survey, more than 10,000 patients were registered with different types of arsenic-related signs and symptoms, out of more than 100,000 people screened from affected states. Elevated levels of arsenic were also found in biological samples (urine, hair, nails) of the people living in affected states. The study reveals that the population who had severe arsenical skin lesions may suffer from multiple Bowens/cancers in the long term. Some unusual symptoms, such as burning sensation, skin itching and watering of eyes in the presence of sun light, were also noticed in arsenicosis patients. 相似文献
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Dipankar Chakraborti Mohammad Mahmudur Rahman Bhaskar Das Bishwajit Nayak Arup Pal Mrinal Kumar Sengupta Md. Amir Hossain Sad Ahamed Manabendranath Sahu Kshitish Chandra Saha Subhash Chandra Mukherjee Shyamapada Pati Rathindra Nath Dutta Quazi Quamruzzaman 《Environmental Earth Sciences》2013,70(5):1993-2008
The authors’ survey of the Ganga–Meghna–Brahmaputra (GMB) plain (area 569,749 km2; population >500 million) over the past 20 years and analysis of more than 220,000 hand tube-well water samples revealed groundwater arsenic contamination in the floodplains of the Ganga–Brahmaputra river (Uttar Pradesh, Bihar, Jharkhand, West Bengal, and Assam) in India and the Padma–Meghna–Brahmaputra river in Bangladesh. On average, 50 % of the water samples contain arsenic above the World Health Organization guideline value of 10 μg/L in India and Bangladesh. More than 100 million people in the GMB plain are potentially at risk. The authors’ medical team screened around 155,000 people from the affected villages and registered 16,000 patients with different types of arsenical skin lesions. Arsenic neuropathy and adverse pregnancy outcomes have been recorded. Infants and children drinking arsenic-contaminated water are believed to be at high risk. About 45,000 biological samples analyzed from arsenic-affected villages of the GMB plain revealed an elevated level of arsenic present in patients as well as non-patients, indicating that many are sub-clinically affected. In West Bengal and Bangladesh, there are huge surface water in rivers, wetlands, and flooded river basins. In the arsenic-affected GMB plain, the crisis is not over water scarcity but about managing the available water resources. 相似文献
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