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Abstract: Gyroscope is a rotation rate sensor. Olden days gyroscopes includes mechanical parts like motors, gimbals etc. which has suffered with noises and low accuracy. Developments in fiber optics have made the interferometric FOG practically realizable and reliable compared to mechanical gyroscopes. The fiber optics based gyro results in good stability, high disturbance rejection and ensure good tolerance to noises. Different noises like photon shot noise, quantization noise, filter noise, thermal noise and bias error many other noises degrades the gyro performance. Significant effect of these noise s result in random walk, bias unstability , power fluctuations etc .To overcome these noises denoising of gyro data play a crucial role in FOG. In this study kalman filter algorithm is used to denoise the FOG signal . The algorithm implemented here performs efficiently in both static and dynamic conditions. The existing KF algorithm is hybridized with adaptive moving average based dual gain kalman filter.In this study comparative study is made between different kf algorithms in both static and dynamic condition. In static condition three algorithms KF,ARMA KF & hybrid KF models are used for denoising the gyro data . Among all three algorithms hybrid model is provided to be more efficient. In case of dynamic condition kf algorithm is fails. ARMA model is used to identify the noise but fails in denoising the noise, where as hybrid kf model work efficiently this case. The denoising performance of hybrid model algorithm is validated on single axis FOG and three axis FOG with different input rotation rates.
Keywords: Adaptive moving average, auto regressive moving average ,fiber optic gyroscope, kalman filter
References:
1. S.Sabat,N.Giribabu,J.Nayak,K. Krishna Prasad , Characterization of fiber optic gyro and noise compensation using discrete wavelet transform of the 2nd international conferencing on emerging trends in engineering and technology (ICETET),2009,PP,909-913
2. C.Kownacki, optimization approach to adapt kalman filters for real time application of accelerometer and gyroscope signal filtering, Digit ,Signal process.21(1)(2011) 131-140.
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4. Yang Y.adaptively Robust Kalman filter with applications in navigation.science of geodesy-I.Guo chang Xu (ed),springier ,2010;49-82. ISBN-978-3-642-11740-4.
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Abstract: In order to perform its basic function of safeguarding life and property, every power system needs an earthing profile that is effective and efficient. Recent studies carried out in the Niger Delta show that its soil is corrosive and frequently attacks the earthing system thereby rendering same ineffective thus posing a great danger to human life and property. This paper reviewed several scholarly literature related to the study for possible causes of earthing system failures and found that corrosive soils, poor workmanship, wrong choice of earthing materials, lack of maintenance etc. were dominant factors hindering effective and sustainable earthing system in the Niger Delta. The paper, therefore, recommends the regular use of experienced workmen, choice of quality earthing materials, periodic testing, inspection and maintenance as strategies to improve the earthing condition in the area.
Keywords: Corrosion, Earthing, Electricity, Niger Delta, Protection
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