For seismic design of structure and machinery, it is important to reproduce input earthquake motions that are likely to occur at a target site. Among the various methods used for generating artificial earthquake motio...For seismic design of structure and machinery, it is important to reproduce input earthquake motions that are likely to occur at a target site. Among the various methods used for generating artificial earthquake motions, the Synthesis Method of Trigonometric Function is used widely. In this method, artificial waves are reproduced by superimposing sine waves and then adding information about amplitude and phase in the frequency domain. In the Japanese architectural design code, the amplitude is standardized as the target response spectrum, and the phase can be defined by random numbers or by the phase of one observed wave. However, a random phase is distinctly different from the phase of an actual earthquake. Further, the phase of one observed wave is confined to the phase characteristic of the artificial wave of only one specific earthquake motion. In this paper, the authors introduce a new convenient method to reproduce artificial waves that not only satisfy the standardized spectrum property but also have the time-frequency characteristics of multiple observed waves. The authors show the feature of the artificial waves, discuss the merits of the method by comparing with existing methods, and report the tendencies of the non-liuear response by using simple model.展开更多
In this paper, it presents a project of a fuzzy controller and a neural estimator to control a coordinate table powered by three-phase induction motor, aiming to implement an intelligent milling system. The position/s...In this paper, it presents a project of a fuzzy controller and a neural estimator to control a coordinate table powered by three-phase induction motor, aiming to implement an intelligent milling system. The position/speed control is performed using vector techniques of three-phase induction machines. The estimation of the motor electromagnetic torque is used for setting the feedrate of the table. The speed control is developed using TS （Takagi-Sugeno） fuzzy logic model and electromagnetic torque estimation using neural network type LMS （least mean square） algorithm. The induction motor is powered by a frequency inverter driven by a DSP （digital signal processor）. Control strategies are implemented in DSP. Simulation results are presented for evaluating the performance of the system.展开更多
文摘For seismic design of structure and machinery, it is important to reproduce input earthquake motions that are likely to occur at a target site. Among the various methods used for generating artificial earthquake motions, the Synthesis Method of Trigonometric Function is used widely. In this method, artificial waves are reproduced by superimposing sine waves and then adding information about amplitude and phase in the frequency domain. In the Japanese architectural design code, the amplitude is standardized as the target response spectrum, and the phase can be defined by random numbers or by the phase of one observed wave. However, a random phase is distinctly different from the phase of an actual earthquake. Further, the phase of one observed wave is confined to the phase characteristic of the artificial wave of only one specific earthquake motion. In this paper, the authors introduce a new convenient method to reproduce artificial waves that not only satisfy the standardized spectrum property but also have the time-frequency characteristics of multiple observed waves. The authors show the feature of the artificial waves, discuss the merits of the method by comparing with existing methods, and report the tendencies of the non-liuear response by using simple model.
文摘In this paper, it presents a project of a fuzzy controller and a neural estimator to control a coordinate table powered by three-phase induction motor, aiming to implement an intelligent milling system. The position/speed control is performed using vector techniques of three-phase induction machines. The estimation of the motor electromagnetic torque is used for setting the feedrate of the table. The speed control is developed using TS （Takagi-Sugeno） fuzzy logic model and electromagnetic torque estimation using neural network type LMS （least mean square） algorithm. The induction motor is powered by a frequency inverter driven by a DSP （digital signal processor）. Control strategies are implemented in DSP. Simulation results are presented for evaluating the performance of the system.
