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邵, 毅敏 ; 時任, 朋也 ; 根津, 紀久雄
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application/pdf<br />Journal Article<br />Improving signal to noise ratio is a key problem to detect early faults of machinery under environment noise conditions. An effective method is presented for improving the signal to noise
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ratio by the adaptive neural network. This paper has made a comparison of failure detect-ability between least-mean-square (LMS) algorithm and adaptive neural network under heavy environment noise conditions. Experiment results have shown that using adaptive neural network is an effective means to extract early symptoms of machine fault under heavy environment noises and low rotating speed conditions.
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周, 斌 ; Machacon, H.T.C. ; 志賀, 聖一 ; 譚, 達明 ; 柄澤, 隆夫 ; 小保方, 富夫 ; 中村, 寿雄
概要:
application/pdf<br />Journal Article<br />In this study a neural network prediction method that can be used in predicting engine behavior is proposed. Using data from a series of characteristic experiments, this method eliminates
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the need for complicated mathematical calculations used in prediction models. To test this method exhaust emissions and engine performance data from intake gas composition variation experiments were taken and compared with the predicted data from this network. The method has been tested and found effective in predicting engine exhaust emissions and engine performance. This technique can be a valuable tool in engine research.
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藤沢, 延行 ; 中林, 貴光 ; 池本, 宏一郎 ; 長屋, 幸助
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application/pdf<br />Journal Article<br />The active control of vortex shedding from a circular cylinder by rotary ocillations is studied experimentally using neural networks, which optimizes automatically the control parameters such as
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the phase lag and the feedback coefficient. This optimization procedure is applied to find out an optimum position of reference probe to attenuate the vortex shedding effectively. The attenuation effect of vortex shedding under this control is investigated by measuring the velocity fluctuations in the cylinder wake and the unsteady pressure distributions over the cylinder surface. It is found that the drag and lift forces acting on the cylinder are reduced under the optimum reference control in comparison with the control under other reference positions as well as those of the stationary cylinder.
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李, 連進 ; 長屋, 幸助
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application/pdf<br />Journal Article<br />We present a system for reducing noise from structures using electromagnetic vibration absorbers. Conventional design techniques for vibration absorbers are not appropriate for noise reduction
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absorbers, because higher-mode vibrations exert strong effects on noise. Hence, we first derive an analytical expression for noise power including higher modes, then present a method for obtaining optimal parameters for noise reduction absorbers. In this method, noise power is taken as a function of cost, and the parameters are decided by using a neural network procedure. An improved algorithm of the neural network for obtaining the parameters is given, experimental tests are performed and the theoretical values are compared with the experimental data.
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李, 連進 ; 長屋, 幸助
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application/pdf<br />Journal Article<br />This paper presents a method for optimizing vibration absorbers on a flexible beam by means of a neural network procedure. Analytical results for the response of the beam with multi-absorbers
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have been obtained using a transfer matrix method. To achieve optimal control, a cost function composed of second-order nonlinear forms in terms of the displacement, strain, and frequencies was used. A method of minimizing the function was presented, in which input values, weights and output function were effectively controlled on the basis of the back-propagation procedure of the neural network method. Numerical calculations were carried out for an example problem. It is ascertained that the present method gives a better result than that obtained by the previously published method. The validity of the method and the analytical results was confirmed by experimental tests.
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金森, 康継 ; 根津, 紀久雄
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application/pdf<br />Journal Article<br />In the small-diameter pipe thrust method, the successful operation is dependent on the experience of skilled operators. Because of this, we forecast that we cannot cope with increasing work
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demand in the future. Therefore, improvement of the control system is required. The objectives of this study are to examine the auto steering control method by means of a construction experiment using a model plant and to compare the accuracy of the sequence, the fuzzy, and the neural network-driven fuzzy controls with the manual one.
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長屋, 幸助 ; 鄭, 惟
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application/pdf<br />Journal Article<br />This paper discusses vibration control problems of a cantilever plate with variable width. A moment-type actuator using a moving coil was presented. A mothod for obtaining optimal feedback
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coefficients was proposed on the basis of neural networks. An analytial solution for the response of the plate under the control using the feedback coefficients was obtained. Numerical calculations were carried out for some typical cases. It is clarified that the present method is valid for controlling vibrations of plates.
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小島, 宏行 ; 木村, 仁次郎 ; 小林, 敏雄
概要:
application/pdf<br />Journal Article<br />In this paper, the magnetic levitation neuro-adaptive control method of a body by use of an electromagnet attached to a vertical robot with a prismatic joint is presented, and the usefulness of the
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present control method is confirmed by experiment and numerical simulation. When the gap between the levitated body and the electromagnet hand varies, an adaptive control method to compensate the nonlinear characteristics of the magnetic attracting force is desirable. The magnetic levitation neuro-adaptive control system consists of a PD feedback control loop and an adaptive mechanism based on a neural network. From the experimental results and the numerical simulation results, it is confirmed that the levitated body can be controlled successfully by the present magnetic levitation neuro-adaptive control method.
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小島, 宏行 ; 張, 敏 ; 松浦, 勉 ; 村上, 岩範 ; 植木, 利明
概要:
application/pdf<br />Journal Article<br />This paper describes the position and force neuro-adaptive control of a two-link flexible robot arm. First, the equation of motion of the flexible robot arm consisting of the first rigid link
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and second flexible link is shown. The end of the second flexible link is constrained by a rgid wall. Second, the position and force neuro-adaptive control system is composed of two-layer neural networks and proportional feedback control loops. Furthermore, from the experimental results and the numerically simulated ones, it is confirmed that the control error of position and force with the neuro-adaptive control is markedly smaller than the control error without the neuro-adaptive control.
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