on a testing system for ship motions and waves in full scale

• Main Authors: liu shao-wei, 劉紹偉
• Other Authors: chiu forng-chen
• Format: Others
• Language: zh-TW
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/09595494806179659365

碩士 === 國立臺灣大學 === 工程科學與海洋工程學系 === 91 === ABSTRACT In this research , we constructed a new full-scale testing and analysis system for ship motions and waves estimation . The paper contains five important points . First , we integrated the hardware and software into a system. Second , a set of conversion formulations of five degrees of motions from the kinematics of rigid bodies was performed. A data acquisition and analysis program was designed in LABVIEW application software , thirdly. The motions simulated by a wood plank was analyzed by the system in the laboratary. Finally , we apply the system to evaluate the motion of a planning craft in the seaway . The instrument (PC-Based DAQ system) consists of the following components : transducers ( 7 accelerators , a dual inclinemeter ) , signal conditioning hardware (DAQP-BRIDGE module) , plug in DAQ boards and application software (LABVIEW) can be designed to control acquisition and data processing. The data measured directly are compared with those converted from the formula calculations for confirming the consistency of the system . We derive the responses of roll , pitch , heave , sway and yaw motions . After obtainig the motion responses , we can analyze the time histories of motions by means of the Fast Fourier Transform , and acquire the response variance(m0) , the variance of response velocity(m2) and the variance of response acceleration(m4) .We test the system for a ship in a seaway at the same period of time , in the same sea area , and analyze the response of motions to confirm its consistency and effectiveness. The response spectral moments of motions are not only a index for assessing the seakeeping of a ship but also the important data sources that can be used to estimate ocean wave characteristics such as the significant height、the significant period and the main direction of waves by using a Neural Network Classifier based on its statistical learning and pattern recongnition.