scholarly journals Real-Time Inverse Estimation of Ocean Wave Spectra from Vessel-Motion Sensors Using Adaptive Kalman Filter

2019 ◽  
Vol 9 (14) ◽  
pp. 2797 ◽  
Author(s):  
HanSung Kim ◽  
HeonYong Kang ◽  
Moo-Hyun Kim
Keyword(s):  
Kalman Filter ◽  
Real Time ◽  
High Frequency ◽  
Practical Importance ◽  
Ocean Wave ◽  
Sensor Data ◽  
Wave Spectra ◽  
Inverse Estimation ◽  
High Frequency Waves ◽  
Vessel Motion

The real-time inverse estimation of the ocean wave spectrum and elevation from a vessel-motion sensor is of significant practical importance, but it is still in the developing stage. The Kalman-filter method has the advantages of real-time estimation, cost reduction, and easy installation than other methods. Reasonable estimation of high-frequency waves is important in view of covering various sea states. However, if the vessel is less responsive for high-frequency waves, amplified noise may occur and cause overestimation problem there. In this paper, a configuration of Kalman filter with applying the principle of Wiener filter is proposed to suppress those over-estimations. Over-estimation is significantly reduced at high frequencies when the method is applied, and reliable real-time wave spectra and elevations can be obtained. The simulated sensor data was used, but the proposed algorithm has been proved to perform well for various sea states and different vessels. In addition, the proposed Kalman-filter technique is robust when it is applied to time-varying sea states.

scholarly journals Wind Speed and Direction Estimation from Wave Spectra using Deep Learning

2021 ◽  
Author(s):  
Haoyu Jiang
Keyword(s):  
Wind Speed ◽  
High Frequency ◽  
Deep Neural Networks ◽  
Fourier Coefficients ◽  
Ocean Wave ◽  
Wave Spectra ◽  
Strongly Coupled ◽  
Wave Measurements ◽  
Short Period ◽  
Wind Measurements

Abstract. High-frequency parts of ocean wave spectra are strongly coupled to the local wind. Measurements of ocean wave spectra can be used to estimate sea surface winds. In this study, two deep neural networks (DNNs) were used to estimate the wind speed and direction from the first five Fourier coefficients from buoys. The DNNs were trained by wind and wave measurements from more than 100 meteorological buoys during 2014–2018. It is found that the wave measurements can best represent the wind information ~1 h ago, because the wave spectra contain wind information a short period before. The overall root-mean-square error (RMSE) of estimated wind speed is ~1.1 m/s, and the RMSE of wind direction is ~14° when wind speed is 7~25 m/s. This model can not only be used for the wind estimation for compact wave buoys but also for the quality control of wind and wave measurements from meteorological buoys.

scholarly journals Development of Liquid Capacity Measuring Algorithm Based on Data Integration from Multiple Sensors

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Kiwoong Park ◽  
Si-Kyoung Lee ◽  
Hyeon Cheol Kim
Keyword(s):  
Kalman Filter ◽  
Data Integration ◽  
Real Time ◽  
Rotation Angle ◽  
Sensor Data ◽  
Multiple Sensors ◽  
Complementary Filter ◽  
Level Sensor

This research proposes an algorithm using a process of integrating data from multiple sensors to measure the liquid capacity in real time regardless of the position of the liquid tank. The algorithm for measuring the capacity was created with a complementary filter using a Kalman filter in order to revise the level sensor data and IMU sensor data. The measuring precision of the proposed algorithm was assessed through repetitive experiments by varying the liquid capacity and the rotation angle of the liquid tank. The measurements of the capacity within the liquid tank were precise, even when the liquid tank was rotated. Using the proposed algorithm, one can obtain highly precise measurements, and it is affordable since an existing level sensor is used.

Research of a New Method to Predict Ocean Wave Spectra

2014 ◽  
Vol 565 ◽  
pp. 238-242
Author(s):  
Xin Yu Zhang ◽  
Bo Zhou ◽  
Ai Guo Shi ◽  
Meng Liu
Keyword(s):  
Neural Network ◽  
Remote Sensing ◽  
Random Process ◽  
Real Time ◽  
Wavelet Decomposition ◽  
Ocean Wave ◽  
New Method ◽  
Wave Spectra ◽  
Traditional Methods ◽  
X Band

A new method to predict wave spectra is presented in this paper, which is based on X-band radar. Traditional methods to research ocean wave are usually based on the hypothesis that ocean wave is a stationary random process, which is proved to be not right. X-band radar is a remote sensing, ship borne equipment, which can measure wave information in real time conveniently. And the wave spectra measured by this equipment can represent non-stationary of ocean wave. In this paper wavelet decomposition and neural network is combined to predict wave spectra thus the trend how the ocean wave develop can be reflected. The experiment results show that this method is relatively credible.

scholarly journals Development of an Autonomous Endoscopically Implantable Submucosal Microdevice Capable of Neurostimulation in the Gastrointestinal Tract

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
J. Hajer ◽  
M. Novák
Keyword(s):  
Diabetes Mellitus ◽  
Animal Model ◽  
Gastrointestinal Tract ◽  
Real Time ◽  
High Frequency ◽  
Implantable Device ◽  
The Body ◽  
Sensor Data ◽  
Live Animal ◽  
Common Diseases

Gastric dysmotility can be a sign of common diseases such as longstanding diabetes mellitus. It is known that the application of high-frequency low-energetic stimulation can help to effectively moderate and alleviate the symptoms of gastric dysmotility. The goal of our research was the development of a miniature, endoscopically implantable device to a submucosal pocket. The implantable device is a fully customized electronics package which was specifically designed for the purpose of experiments in the submucosa. The device was endoscopically inserted into the submucosal pocket of a pig stomach and partially severed pig side in order to adequately simulate a live animal model. The experiment confirmed that the designed device can be implanted into the submucosa and is capable of the measurement of sensor data and the transmission of this data wirelessly in real time to a computer outside of the body. After proving that the device can be implanted submucosally and transmit data, further experiments can now be performed, primarily with an electrogastrography (EGG) instrument and implantable device with tissue stimulation capability.

Evolution of high frequency waves in shoaling and breaking wave spectra

2019 ◽  
Vol 31 (8) ◽  
pp. 087102
Author(s):  
Samira Ardani ◽  
James M. Kaihatu
Keyword(s):  
High Frequency ◽  
Breaking Wave ◽  
Wave Spectra ◽  
High Frequency Waves
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