This paper proposes an intelligent diagnosis method for a centrifugal pump system with frequency-domain symptom parameters using wavelet Transform, rough sets and fuzzy neural network to detect faults and distinguish fault types at an early stage. The wavelet transform is used to extract fault features to capture the fault information hidden in signals. The diagnosis knowledge for the training of neural network can be acquired by rough sets. A fuzzy neural network called "partially-linearized neural network (PNN)" is proposed, by which the fault types of machinery can be quickly and effectively distinguished on the basis of the possibilities of symptom parameters. The non-dimensional symptom parameters that can reflect the characteristics of signals are also described in frequency-domain. Practical examples of diagnosis for a centrifugal pump system are shown to verify the efficiency of the method.

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Differential pressure transmitter with orifice is widely used in process automation system. Since the most frequent problem they present is blockage in impulse line, online blockage detection method is required. The authors developed an impulse-line blockage detection algorithm, which applied to non-compressible fluids in previous works. The purpose of the paper is to apply the detection algorithm to compressible fluid such as air, which is also used in process automation systems. The experimental result shows that proposed detection algorithm is able to detect blockage before measurement of differential pressure is affected by the blockage. In addition, it is evidenced that the blockage condition when differential pressure is affected by blockage is more slight degree in air line than that in water line.

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The developments of practical application using the smart structure system are desired since recent years in Japan. The improvement of the social recognition for smart structure systems is an important subject, due to the concept of smart structure is not familiar in Japan. This paper addresses the example of the one-link robot arm as a home robot use by adopting the concept of smart structure. The supervisory fault diagnosis method with multiple observers is proposed for the purpose of the loosening detection to the fastened screw for the driving joint and forearm. Numerical simulation indicate the results to verify the effectiveness of the proposed method.

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Small fishing boats meet marine peril associated with engine damage on account of insufficient maintenance and aggressive operation in Japan. This research gains resurgence of dynamical features of a dynamical model under abnormal condition generated small fishing boat engine. Because, it's absolutely essential that comprehension of dynamic characteristics against abnormal condition, of development mechanism abnormal signal based on vibration generated in fishing boat engines. Furthermore, relevance of the dynamical model has been verified by using an actual four cycle glow engine under abnormal conditions in experiment. Dynamically reproduced abnormal conditions in fishing boat engine are a spot flaw on cylinder liner and torque rich condition which is generated, when over load operation acted on small fishing boat engine.

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Delicious taste of puffer meat has been determined by texture and its degree of freshness in Japan. If more exact estimation method of delicious taste is desired, the method associated with nondestructive method is most suitable. The texture of puffer meats is defined as its stiffness associated with mechanical dynamics. This paper experimentally proposes new estimation method on texture of raw puffers meat. Proposed method has been exercised by the measurement about frequency response function based on added vibration to puffer meat. This estimation method is characterized by nondestructive, quantitative, speedy and concise procedure. In this research, determination parameter on texture of puffer meat has been composed by applied non dimensional parameters called area ratio which is obtained from frequency response function of raw puffer meat.

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This paper describes a vibration analysis based on the chaos theory to diagnose rolling bearings. We introduced the largest Lyapunov exponent which is one of the chaotic time series analyses. The largest Lyapunov exponent has several parameters we need to determine. These parameters affect the value of the largest Lyapunov exponent. Therefore it is important to determine the parameters suitable for the diagnosis. We paid attention to the two parameters: radius and time delay, and investigated the influence to the chaotic time series analysis to improve the accuracy of diagnosis.

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In this paper, a method to identify the geometrical shape and the location of the defect embedded in a concrete structure by processing the thermal image of the structural surface acquired by infrared thermography is presented. In the proposed method, the structure is modeled as a homogeneous infinite plate whose boundary condition on the observed surface is known. A layer-by-layer inverse analysis using a regularized interlayer transfer matrix based on 2D Fourier transform is carried out to obtain the sharper image of the defect as well as the depth of the damaged layer. The estimated depth information mapped on the image plane has resulted in a "depth image" which can display the shape of the defects as well as their depth simultaneously. The effectiveness of the proposed technique has been examined both numerically and experimentally.

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Structural health monitoring for identification of the impact loading, detection of the structural damage and assessment of the severity of the damage ensures safety operation of the industrial mechanical system. Author's research group demonstrated impact identification capability of time reversal processing by using experimentally measured sensor output signals. A model based impact identification method using experimentally measured sensor signals from nine surface bonded PZT sensors on a rectangular aluminum plate was presented. The time-reversed wave traveled back through the plate and was focused on the region around a point where had been hit by the impact hammer in backward process. In this study, the effect of time duration of the measured sensor signal to the impact identification capability of time reversal processing method is experimentally demonstrated. The illustrative experimental and numerical processes demonstrated the impact identification capability of time reversal processing method. Even if the measured signals were missing the wave front induced by the impact, the signal to noise ratio of the backward process was successfully improved by using the long time duration of the measured sensor signals.

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The objective of this study is the loosening detection of bolted joints without human involvement by applying the concept of structural health monitoring. The smart washer consists of the cantilever available to detect bolt loosening by using flexibility of cantilever and self-sensing/actuation function. The principle of how to detect the loosening of a bolt is the basis that the natural frequency of a smart washer system vary depending on a bolt tightening axial tension. The natural frequency of the smart washer was identified by using 4SID in previous papers. The natural frequency of the smart washer was identified by using the sub-space state space identification method in previous papers. However, 4SID was confirmed unsuitable for the periodic maintenance. This paper is proposed that the smart washer is detected bolt loosening by the supervisory method by using multiple observer. Numerical simulation results for several bolt loosening state for the bolted joint indicate the effectiveness of the proposed loosening detection method.

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A new method to measure the pulse wave velocity in blood vessel was studied because the velocity is one of the important signs to show arteriosclerotic. Assuming one dimensional wave propagation, the wave velocity can be determined by the pressures measured at three different points along the axis. This method is effective even for arbitrary boundary conditions. Fundamental experiments of the wave velocity in silicon rubber tube were executed to certify the new method. Experimental results suggest that the new method might be used to the blood vessel of human body.

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The development of surface stress measurement technology using ultrasonic wave has been in progress. The surface tensile stress of the structure, such as nuclear power plant components, may cause stress corrosion cracking, fatigue cracking, and so on. As the sound velocity is slightly changed by the residual stress, the residual stress value is calculated from the measured sound velocities. Because the stress on the surface is important, the surface acoustic wave such as Rayleigh wave is the best choice as the ultrasonic wave mode. In the following report, the relationship of the stress value and the sound velocity is discussed based on the acoustic-elastic law of Rayleigh wave. Then the stress measurement test was performed. As a result, it is shown that the measured value by the Rayleigh wave method agrees with the measurement value by the strain gauge method within the accuracy of ±20MPa.

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非定常な異常信号の検出において,実信号マザーウェーブレット(Real signal Mother Wavelet:RMW)を用いるウェーブレット瞬時相関は有効であることは実証された.しかし,RMWは理論上連続ウェーブレット変換のみ利用が可能であり,リアルタイムでの異常検出には不利がある.本研究ではこの欠点を克服するために,寄生的離散ウェーブレット変換(Parasitic Discrete Wavelet Transform:PDWT)を提案した.さらに,それを車の異常音源探査へ応用し有効性を確認した.

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This paper describes a preliminary study of an activity monitoring system for a residential house based on Bayesian networks. For the demonstrative purpose, a proof-of-concept system using vibration measurement has been proposed, in which specific physical features of the vibration that may indicate either daily activities of residents or other disturbances such as traffic-induced vibration are extracted from the collected data. Vibration data is classified into two groups based on these features, and the attribution degree was defined based on one-class support vector machines associated with the extracted data classes. A Bayesian Network is designed as the data model that represents the relevance of the data classes to external variables such as time and in/out status. Finally an abnormality index has been proposed and investigated based on the likelihood evaluated on the trained Bayesian network.

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In order to improve energy saving and reduction of operational cost by introducing distributed energy supply systems, control performance assessment during operation is indispensable. Thus, this paper assesses control performance of a heat recovery process in a gas engine cogeneration system, which is a typical distributed energy supply system, through numerical analyses. First, the influence of the control performance of the jacket cooling water temperature for stable operation of the gas engine on efficient heat recovery is examined. Then, the influence of environmental condition including ambient temperature and supply water temperature, and load condition such as supply water flow rate on efficient heat recovery is also evaluated. These numerical analyses show that the control performance of the jacket cooling water temperature is very sensitive to efficient heat recovery, while environmental and load conditions hardly have an influence on it.

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The on-line performance monitoring of a heat exchange process using water and steam, which is one of the key components of distributed energy supply systems, has been developed on the basis of a theoretical model. By using a steady-state model of the heat exchanger, this performance monitoring first estimates output process variables and heat exchange performance of the heat exchanger in response to the variation in measured input process variables. These estimated values are then compared with the measured ones for the on-line performance monitoring. Its effectiveness under transient state has been confirmed by the numerical analysis. The results confirm the sufficiency of the estimation accuracy of the output process variables and heat exchange performance under transient state and the detection capability of the deterioration of the heat exchange performance in a short period.

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Amount supporting a engine isolates a vibration caused by a engine. Crackes in a mount by aged deterioration decreses a spring constant of mount, isolation ability and causes noise. We must check a mount if a mount does its function normally. In this paper, we assumed a mount as linear spring and identified its spring constant by solving a inverse problem. To regulate a inverse problem, a singular value decomposition technique was applied. We related a location of exciting force and damaged mount on the identification ability.

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The identification of external force acting on a machine or a structure is important for the diagnosis. One of the force identification methods is based on the frequency response function. The method is very useful although it requires the information of location of force acting. In this study, an identification method is proposed for the case of unknown excitation points. The method is firstly the external forces, whose amount is same as the one of sensors, are assumed at every candidate location, and the amplitudes of forces are identified. Then the exact location of external force is determined by the classification of all identified results. The method is numerically checked and it was shown that the method was useful using the data with noise. Moreover the experimental results showed that the method was feasible when the location and amplitude are separately identified.

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Estimation of instantaneous damping and frequencies by the wavelet transform is based on the ridge identification and the phase extraction in the time-frequency map. Time-varying parameters due to nonlinearities are also estimated by this technique. However, the process of the ridge identification is complicated, and the most suitable mother wavelet to yield a time-frequency map for an efficient identification can not be determinately chosen. There are some problems in easiness to operate the technique. In this paper, we propose the segmental use of the harmonic wavelet. The segmental harmonic wavelet is implemented in combination with the Fourier transfer, which is utilized to set bounds to frequency range. It shows significantly good results compared with the simple application of the Hilbert transform. The time-varying parameters pertaining to nonlinearities are successfully estimated by the proposed method.

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This paper concerns an algorithm for modal identification of large-scale structures by distributed sensor networks that have localized and decentralized computation capability. The sensor network assumed in the paper is to have a hierarchical structure consisting of a host, master nodes having relatively high computation capability with a communication channel between the center node, slave nodes detected and administrated ad hoc by the nearest master node. The modal parameters to be identified are classified in local and global ones, then the dependency relations between the parameters and the sensor measurements are modeled by a Bayesian network. An algorithm to calculate the posterior of the modal parameters by Bayesian inference algorithms is presented. The proposed approach would be advantageous in a large scale sensor network with hundreds of nodes because the raw data will transmitted only between the slave nodes and their master node.

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We have been developing a method of material and structure component tests under high heat flux conditions by using a high power diode-laser as a heat source. The new system consists of the diode-laser and a couple of galvanometer scanner mirrors, and it is expected that, by controlling the scanning pattern of mirrors, the arbitrary heating conditions can be given. In this report, we examined the distributions of heat flux for non-uniform heating tests applying both scanning lines interval and laser power control methods by comparing temperature distributions to numerical calculation. Moreover, we tried to apply the method to evaluate more precise heat flux distribution profile by using PMMA ablation.

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本報では、開放循環式冷却水系の多管式熱交換器に生じたガルバニック腐食の事例とその対策について説明する。さらに、実プラント試験結果から炭素鋼のガルバニック腐食に及ぼすカソードとアノードとの面積比の影響について解明した。また、ラボ試験結果から炭素鋼のガルバニック腐食に及ぼすインヒビターの影響について解明した。

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