Based on the beginning, propagating and ending mechanism of rotating-stallcell, the relation between the pressure history signal and the pressure distribution along rotorcircumference is proposed. The angular velociti...Based on the beginning, propagating and ending mechanism of rotating-stallcell, the relation between the pressure history signal and the pressure distribution along rotorcircumference is proposed. The angular velocities of rotating-stall cell propagating are computedfrom time series picked by the pressure probes on a cross section. Self-relation calculatingfiltered the random noise of the pressure history data. The exciting load on rotor is computed byintegral of filtered pressure signal along rotor circumference. By Prohl-Myklestad method, dynamicalequations of rotor system are obtained. The dynamical response of rotor system is resolved by usingMatlab system. Further more, the situation of more than one of stall cells is discussed. Two casesrespectively from the natural gas compressor of some fertilizer plant and the CO_2 compressor ofsome nitrogenous fertilizer plant demonstrate that both methods of calculating the load exerted onrotor by pressure fluctuation and resolving the dynamic response of rotor are available and thecharacteristics of frequency spectrum of rotating stall are correct.展开更多
Ⅰ. INTRODUCTION Let us consider the self-regression forecast model of classical n-order Y<sub>t</sub>=A<sub>0</sub>+A<sub>1</sub>Y<sub>t-1</sub>+…+A<sub>n</su...Ⅰ. INTRODUCTION Let us consider the self-regression forecast model of classical n-order Y<sub>t</sub>=A<sub>0</sub>+A<sub>1</sub>Y<sub>t-1</sub>+…+A<sub>n</sub>Y<sub>t-n</sub>+e. （1.1） This note applies fuzzy set theory to the expansion of（1. 1）, i.e.展开更多
The prediction methods for nonlinear dynamic systems which are decided by chaotic time series are mainly studied as well as structures of nonlinear self-related chaotic models and their dimensions. By combining neural...The prediction methods for nonlinear dynamic systems which are decided by chaotic time series are mainly studied as well as structures of nonlinear self-related chaotic models and their dimensions. By combining neural networks and wavelet theories, the structures of wavelet transform neural networks were studied and also a wavelet neural networks learning method was given. Based on wavelet networks, a new method for parameter identification was suggested, which can be used selectively to extract different scales of frequency and time in time series in order to realize prediction of tendencies or details of original time series. Through pre-treatment and comparison of results before and after the treatment, several useful conclusions are reached: High accurate identification can be guaranteed by applying wavelet networks to identify parameters of self-related chaotic models and more valid prediction of the chaotic time series including noise can be achieved accordingly.展开更多
The philosopher Eugene Gendlin argues that a distinctive mode of reasoning, called experiencing, is necessary for working through personally salient problems such as are encountered in psychotherapy. We review support...The philosopher Eugene Gendlin argues that a distinctive mode of reasoning, called experiencing, is necessary for working through personally salient problems such as are encountered in psychotherapy. We review supporting empirical support. It is now possible to consider Gendlin’s ideas from a neurological perspective. Work directed at understanding the neurological underpinnings of consciousness and self-related processing, as well as comparative neuroanatomical work, are all consistent with and elucidated by Gendlin’s experiencing construct. We argue from this data that the human mind is composed of three interacting systems that are unique to or enhanced in humans compared to other primates. Two are dedicated to “hot and cold” cognition. The most important, least well-studied third system is dedicated to mediating between these forms of cognition. We outline how interactions between these systems define different forms of psychopathology and what they suggest about the structure of the human mind.展开更多
基金This project is supported by "Nine five" National Key Project on Basic Research and Applied Research of China (No.PD9521908Z1)Provincial Science and Technology Key Project of Henan (No.20001120323).
文摘Based on the beginning, propagating and ending mechanism of rotating-stallcell, the relation between the pressure history signal and the pressure distribution along rotorcircumference is proposed. The angular velocities of rotating-stall cell propagating are computedfrom time series picked by the pressure probes on a cross section. Self-relation calculatingfiltered the random noise of the pressure history data. The exciting load on rotor is computed byintegral of filtered pressure signal along rotor circumference. By Prohl-Myklestad method, dynamicalequations of rotor system are obtained. The dynamical response of rotor system is resolved by usingMatlab system. Further more, the situation of more than one of stall cells is discussed. Two casesrespectively from the natural gas compressor of some fertilizer plant and the CO_2 compressor ofsome nitrogenous fertilizer plant demonstrate that both methods of calculating the load exerted onrotor by pressure fluctuation and resolving the dynamic response of rotor are available and thecharacteristics of frequency spectrum of rotating stall are correct.
文摘Ⅰ. INTRODUCTION Let us consider the self-regression forecast model of classical n-order Y<sub>t</sub>=A<sub>0</sub>+A<sub>1</sub>Y<sub>t-1</sub>+…+A<sub>n</sub>Y<sub>t-n</sub>+e. （1.1） This note applies fuzzy set theory to the expansion of（1. 1）, i.e.
文摘The prediction methods for nonlinear dynamic systems which are decided by chaotic time series are mainly studied as well as structures of nonlinear self-related chaotic models and their dimensions. By combining neural networks and wavelet theories, the structures of wavelet transform neural networks were studied and also a wavelet neural networks learning method was given. Based on wavelet networks, a new method for parameter identification was suggested, which can be used selectively to extract different scales of frequency and time in time series in order to realize prediction of tendencies or details of original time series. Through pre-treatment and comparison of results before and after the treatment, several useful conclusions are reached: High accurate identification can be guaranteed by applying wavelet networks to identify parameters of self-related chaotic models and more valid prediction of the chaotic time series including noise can be achieved accordingly.
文摘The philosopher Eugene Gendlin argues that a distinctive mode of reasoning, called experiencing, is necessary for working through personally salient problems such as are encountered in psychotherapy. We review supporting empirical support. It is now possible to consider Gendlin’s ideas from a neurological perspective. Work directed at understanding the neurological underpinnings of consciousness and self-related processing, as well as comparative neuroanatomical work, are all consistent with and elucidated by Gendlin’s experiencing construct. We argue from this data that the human mind is composed of three interacting systems that are unique to or enhanced in humans compared to other primates. Two are dedicated to “hot and cold” cognition. The most important, least well-studied third system is dedicated to mediating between these forms of cognition. We outline how interactions between these systems define different forms of psychopathology and what they suggest about the structure of the human mind.
