Machine equipment usually comprises many mechanical elements that can fail because of functional deterioration and friction. For tribo-elements like plane bearings, it is extremely important to diagnose the abnormal conditions and prevent such parts from breakdown caused by wear. However, diagnosing tribo-elements requires expensive diagnostic equipment and expertise. This study aims to propose a cost- and time- effective system that detect the signs of breakdown during equipment operation by using machine learning to identify abnormalities. We conducted wear tests in contaminated oil and used multiple sensors to collect data regarding the friction force, the electrical contact resistance, the acoustic emission (AE) signal, and vibration. An appropriate learning sample was selected using k-fold cross-validation. The electrical contact resistance was found to contribute relatively little to the detection of abnormalities, whereas the friction coefficient contributed greatly. Furthermore, the AE signal and the vibration detected local changes on the sliding surface. Consequently, we found that machine learning can judge whether monitoring data are normal or abnormal.
This paper presents a numerical solution to shape identification problems on internal flow and external flow in unsteady viscous flow fields. In the internal flow problem, shape design problem that controlled the flow velocity distribution in the sub-domains of the unsteady viscous flow field was introduced. The square integration error between the actual flow velocity distribution and the target flow velocity distribution in the specified sub-domains was employed as the objective functional for the shape design. In the external flow problem, drag control problem for an isolated body located in uniform flow was formulated in the domain of unsteady viscous flow fields. The shape gradient of these shape identification problems were derived theoretically using the adjoint method, the Lagrange multiplier method and the formulae of the material derivative. Reshaping was accomplished using the traction method that was proposed as a solution to domain optimization problems. Numerical analysis programs for the shape identification problems were developed based on FreeFem++, and the validity of the proposed method was confirmed by the results of 2D numerical analyses.
This paper presents a discrimination method of Sleep Apnea Syndrome (SAS) and early detection of potential Sleep Apnea Syndrome (Pre-SAS) using sleep breath sound, by which each subject can take the required data for the diagnosis at home only with a voice recorder. Sleep breath sound of around two hours is analyzed statistically for detecting SAS patients. Long silence sections in the sleep breath sound and the biggest sound pressure typically occurred after them are compared for distinguishing Pre-SAS, SAS patients and non-patients. The k-means method is applied for classifying the above sound data. The proposed method drastically reduces the time and effort required for SAS diagnosis compared to the current medical approaches. Experimental results show the effectiveness of the proposed method, by which 100 % accuracy of discrimination is achieved.
High strength steel (HSS) have several advantages such as lightweight and high shock absorption. In sheet metal forming of HSS, twist springback occurs remarkably, which results in the low product quality. In addition, major defects such as wrinkling and tearing easily occur due to the low formability. Blank holder force (BHF) and blank shape have a direct influence on the twist springback, the wrinkling and the tearing. Variable BHF (VBHF) that the BHF varies through the stroke is valid for the twist springback reduction. In this paper, we propose a novel method to evaluate the twist springback, in which both the torsion angle of top of the product surface and the angle of left/light flange are evaluated. Based on the evaluation, a design optimization to determine the VBHF trajectory and blank shape is performed under several design constraints. The numerical simulation is so intensive that a sequential approximate optimization using radial basis function network is adopted to determine the optimal VBHF trajectory and the blank shape. Thorough the numerical simulation, the validity of proposed approach is examined.
Cast stainless steel (CASS) is widely used in primary coolant piping of nuclear power plants because of its high corrosion resistance and high strength. An in-service inspection based on ultrasonic testing (UT) has to be conducted for such weld joints on the basis of JSME Rules on Fitness-for-Service for Nuclear Power Plants. However, it is difficult to detect and estimate flaws in CASS components with high accuracy because ultrasonic waves are scattered and attenuated due to coarse grains, and anisotropic properties by grain orientations lead to ultrasonic beam distortion. In order to better understand the wave propagation behavior in the CASS, numerical simulations become useful and reasonable manners. To achieve this, it is effective to incorporate three-dimensional (3D) grain microstructures into the simulation model. If the microstructures in CASS can be made from a casting simulation, we can predict wave propagation for a more realistic situation. In this study, the cellular automaton using finite element model is introduced to imitate the grain microstructures in the CASS. Then, the constructed structure is fed into the explicit finite element analysis for 3D wave simulation. Consequently, the wave propagation using the numerical simulation show good agreement with measured wave propagation obtained by contact-scanning on the surface of CASS specimens.
Natural convective heat transfer from staggered banks of horizontal cylinders to air was investigated experimentally. The experiments were mainly carried out with the banks consisted of five horizontal rows having nine and ten cylinders. The whole cylinders in the bank were heated with identical heat flux and their diameter d, vertical and horizontal gaps Gh, Gv between cylinders were varied as d=8.4, 14.4mm, Gh=10.6-30.6mm and Gv=5.6-30.6mm. The flow induced in the banks was first visualized with smoke and the Nusselt numbers of the whole cylinders in the banks were subsequently measured. The visual results depicted that the smokes issued from the bottom horizontal row of cylinders gather toward the vertical centerline of the bank. With the gathering of the plumes, the Nusselt numbers of the cylinders showed gradual reduction toward downstream. Their Nusselt numbers were next arranged with non-dimensional parameters to obtain heat transfer correlations. The result showed that the Nusselt numbers NuGv based on the vertical gaps Gv between cylinders are correlated well with the parameter [RaGv*(Gv/d)2] for the bottom row, while those for the central cylinders in the second to fifth rows are predicted well with the parameter [RaGv*(Gv/d)(Gh/d)], where RaGv* and (Gv/d), (Gh/d) stand for the modified Rayleigh numbers based on the vertical gaps Gv and the ratios of vertical and horizontal gaps to the cylinder diameter, respectively.
Creep-fatigue damage preferentially exceeds at stress concentration portions in high temperature components such as steam turbine rotors during cyclic start up- shut down operation. Therefore development of an accurate crack initiation life assessment method under creep-fatigue conditions at the stress concentration portions under multiaxial stress states is necessary to maintain reliable operation. In this study, creep-fatigue tests using circular notch bar specimens on a CrMoV forging steel have been conducted to clarify effect of stress conditions on failure life. Three dimensional finite element elastic-plastic creep analyses have been performed. Fatigue lives of the notch specimens are about 10 times shorter than those of plain specimens, and the lives of the notch specimen under the creep-fatigue condition are about 1/5 times of the plain specimen. From observation of notch root of the creep-damage specimens, it suggested that most of the creep-fatigue life was occupied by crack propagation up to 1mm from the notch surface. It was also indicated that triaxial tension stress state occurs around the notch root surface and stresses decrease with distance from the notch root surface by the inelastic analysis. A new creep-fatigue life evaluation procedure of notch specimens, in which concept of a damage evaluation area was introduced, was proposed by considering damage extension and the stress component distribution around the notch root. As a result, creep-fatigue lives of the notch specimens were accurately predicted by coupling of the new procedure and the nonlinear damage accumulation rule.
It is necessary to understand wall heat transfer mechanisms in order to mitigate cooling losses in an internal combustion engine. To investigate the turbulent heat transfer on the engine wall, a heat flux sensor has to have a low noise and multi measurement points on comparable scale of gas turbulence. Therefore, the authors have developed a new heat flux sensor with three measurement points by using MEMS (Micro-Electro-Mechanical Systems) technologies. The MEMS sensor has three thin film RTDs (Resistance Temperature Detector) with the size of 315 μm on a 900 μm diameter circle in rotational symmetry. Measurement tests were conducted in a laboratory engine. The noise of the MEMS sensor was evaluated as 13.8 kW/m2, which is small enough to detect instantaneous heat flux. The instantaneous heat flux had oscillation with the amplitude of a few hundred kW/m2. Since the amplitude of the oscillation was much larger than the noise, it was supposed that the oscillation was a meaningful signal reflecting the disturbance of a velocity or temperature field in the gas phase. By a cross-correlation analysis between the three RTDs, it was found that the instantaneous heat fluxes had a moderate correlation with a certain delay time. That can be interpreted as the traveling of a turbulent vortex structure from one RTD to another RTD with the time. Therefore, it can be expected that the turbulent characteristics will be extracted from the instantaneous heat flux data measured with the three RTDs.
In this study, we focused on premixed charge compression ignition (PCCI) combustion with dual fuel of carbon monoxide (CO) and diesel fuel. The effects of CO as fuel on PCCI combustion characteristics were investigated based on engine tests and numerical simulations. As a result, it was found that the combustion became mild and combustion phase was retarded with increasing amount of CO supply. The results suggest that the combustion phase can be controlled by optimizing amount of CO supply, and moreover that the operating regions of PCCI combustion will be extended. In addition, it became clear that the supply of CO on PCCI combustion could be an alternative method for introducing large amount of EGR and lowering the compression ratio. On the other hand, the supply of CO led to an increase in unburnt CO emission and a deterioration in thermal efficiency. The numerical simulation results showed that it is effective to simultaneously increase the effective compression ratio and the EGR ratio in order to overcome these disadvantages without increasing NOx emission. Therefore, there is a possibility that PCCI combustion with dual fuel of CO and diesel fuel will possibly achieve high thermal efficiency.
In recent years, the electrical wiring works of automobiles and home electronics have become highly complicated, and a spot welding is being used as the interconnecting joining method. The high-conductivity materials such as copper and aluminum need a huge current for a short time in the welding. Therefore, tungsten and molybdenum materials having high melting point and high heat resistance are currently being used for the electrode. In this research, the welding operations were carried out repeatedly up to 3,000 cycles using two kinds of tungsten electrodes with two different microstructures (unrecrystallized and recrystallized), where the temperature of the boundary between the electrode and the work metal (tough pitch copper) at the initial cycle of welding was maintained constant with different forces applied onto the work metal. The influences of the electrode microstructure and the applied pressure on cracking behavior on the electrode surface were examined, and then the durability and lifespan of the electrode were discussed. As the results, the total crack length, the maximum crack width and the crack depth of the unrecrystallized tungsten electrode were all smaller than those of the recrystallized tungsten electrode. The total crack length increased with increasing welding cycles and applied force. The cracking was considered to be caused by a late shrinking of heat area during the cooling and an expansion of the outer part, and the crack progressed along the grain boundaries. From the point of view of the cracking of the electrode surface, it became clearly that the unrecrystallized tungsten material had high durability and would be able to reduce the exchange of the electrode. Therefore, the unrecrystallized tungsten electrode was considered to be effective in expansion of the lifespan of electrode in the spot welding of copper materials.
Safety is a crucial issue in rehabilitation assist suits. We have proposed and developed a rehabilitation assist suit equipped with a velocity-based mechanical safety device (VBMSD). The assist suit assists a patient's knee joint. The VBMSD switches off the assist suit's motor if it detects an unexpected high joint angular velocity. The VBMSD works even when the assist suit's computer breaks down, because it consists of only passive mechanical components without controllers, actuators, or batteries. However, the VBMSD may resonate with a walking cycle (0-1Hz) in a gait exercise because it has a bar, a rotary damper, and two tension springs, that is, it is a mass-spring-damper system. In this paper, we check whether the VBMSD resonates with the walking cycle by using the frequency response analysis of the VBMSD. Firstly, we review the assist suit equipped with the VBMSD. Secondly, we analyze the VBMSD and examine whether it resonates with the walking cycle. Finally, we present experimental results to verify the effectiveness of the VBMSD.
We have constructed a design method for body structures consist of standardized components which connects pipes, spacers and joints in a previous study. As a practical application example, we have designed detailed shape of spacers and joints of rear frame. In order to evaluate stiffness and displacement under four experiments such as torsion and bending, we have constructed the three-dimensional CAE models. In the CAE models, we have assumed the CFRP's Young's modulus was low considering the manufacturing process. Furthermore, we have made it possible to simulate adhesive behavior by simple modeling instead of adopting the adhesive model called CZM (Cohesive Zone Model) with high model creation cost. As a result, in the initial CAE model, mean square error of displacement at the representative points was from 18.4% to 35.4%. In the improved CAE model, we obtained a model that allows the displacement error to be within 8%.
We discuss a new obstacle avoidance technique for a UAV (Unmanned Aerial Vehicle) using PSO (Particle Swarm Optimization) called optimization imitated animal foraging. In this method, the avoidance orbit is generated by the response by step change of the target position in the left and right direction and the response by the step change of the target speed in the forward direction. The magnitude of the change of the two target values is determined by the PSO based on the unique evaluation function. The evaluation function is a function consisting of collision risk based on the closest distance to the obstacle, energy based on magnitude of step change of the target value to be applied, and avoidance time based on speed change in the forward direction. Here, the calculation of the closest approach distance is obtained by performing a simulation based on the mathematical model expressing the flight trajectory of the obstacle and the own vehicle each time the evaluation function calculation of the repetitive calculation in the optimization calculation of the PSO is performed. We confirmed that this technique is effective by the numerical simulation.
In this paper, a new formulation for computing ΔJ using the three-dimensional equivalent domain integral method for finite deformation elastic-plastic problem is presented. It is known that J-integral represents the energy release rate per unit crack extension and is useful for the fracture mechanics analysis of elastic-plastic materials. However, J-integral is only valid under the proportional loading condition in elastic-plastic problem. As a method applicable to the cyclic loading problem, ΔJ was proposed and shown that it is valid for evaluating low-cycle fatigue. ΔJ was initially proposed in experimental studies. Later, a contour integral approach for the evaluation of ΔJ was proposed and many numerical analyses have been conducted by engineers and researchers. However, path-independence of ΔJ was shown under the many assumptions and therefore is valid only for limited problems. In addition, the contour integral for ΔJ evaluation was proposed with assuming small deformation formulation, and it was not clear how it could be extended to the finite deformation problem. In this paper, we present a new formulation for the computation of ΔJ using the three-dimensional equivalent domain integral method. This formulation is based on the three-dimensional J-integral formulation for arbitrary load history and finite deformation that was proposed by the authors. It is shown in this paper that proposed ΔJ evaluation method for finite deformation elastic-plastic problems holds the path-independent property in small/finite deformation under any load histories. Finally, small and finite deformation cyclic elastic-plastic analyses using the finite element method are presented. They show that the present method always holds the path-independent property and can be applied to cyclic elastic-plastic fracture problems.
An experimental study is performed on a two-dimensional offset jet with a dielectric barrier discharge plasma actuator (PA) as a flow control device that introduces a periodic disturbance to the system. The offset jet is produced by a flow of air emitted from the end of a long parallel channel, and the offset ratio H/h (H: step height, h: channel height) is 1.0. The plasma actuator is installed on the lower wall of the jet exit, and is operated using burst-modulated or continuous waveforms. The Reynolds number based on the mean velocity and the hydraulic diameter of the inlet channel is 2.0 × 103, and the flow at the channel exit is laminar. The wall static pressure and the heat transfer coefficient of the offset plate are measured, and the pressure loss and average Nusselt number are processed. The flow field is examined by flow visualization using a high-speed camera, and the velocity profiles are measured using a particle image velocimetry system. The results show that the reattachment length decreases and the Nusselt number in the recirculation region increases with the induced flow due to the PA. These effects are remarkable at a burst frequency of 100 Hz, which matches the acceptance frequency of the dividing shear layer. At a duty ratio of D = 50 %, due to the existence of a periodic large vortex structure, the reduction of the reattachment length is similar and the Nusselt number is higher compared to those obtained for continuous operation (D = 100 %).
We describe a method for improving recognition of lying postures using a measured signal intensity of respiration and heartbeat. We have proposed a measurement method of lying posture, respiration, and heartbeat using a Smart Rubber sensor, a rubber-based flexible tactile sensor sheet developed by us. We can obtain respiration and heartbeat by means of using the time series data of the body pressure measured at the suitable location determined by lying posture in this measurement method. Therefore, a recognition rate of lying postures and a measured signal intensity of respiration and heartbeat have positive correlation. In the experiments, we show that recognition of lying postures is improved by means of using a measured signal intensity of respiration and heartbeat.
This paper provides a hybrid simulation (HS) system for pantograph/catenary systems based upon the dynamically substructured system (DSS) method. HS consists of a physical pantograph, an actuator to excite the pantograph head and a real-time simulator for the catenary model. The real-time simulator calculates the displacement of the contact wire using the contact force between the pantograph head and the actuator. Since the actuator is driven by the calculated displacement of the contact wire at the contact point of pantograph and contact wire, HS provides a pseudo dynamical testing method for pantograph/catenary systems. In this paper a multi degree-of-freedom (MDOF) catenary model is adopted, in order to realise wave propagation of the vertical displacement along the wires. To compensate for the dynamic characteristics of the actuator, the DSS method is adopted, which uses both state feedback and output feedback control. A key finding in this work is that the DSS-based HS system is more accurate than the commonly-used inverse transfer function method. Furthermore, in order to realise real-time simulation of the MDOF catenary model, this study uses a modal analysis technique to reduce the dimension of the catenary model. Additionally, the long catenary model is reduced to a 4-span model, and, by copying the state of the wires and contact point, long distance travelling of the pantograph is realised. The proposed method has been validated by simulated HS testing and by HS testing using an actual pantograph at the Railway Technical Research Institute.
Hardness representation in VR is one of the important problems to create virtual touch feeling as if the feeling is caused by real touch. In this study, we are attempting to improve the hardness representation method by combining the pseudo-haptics and tactile stimuli, which was presented in our previous research. In the current study, we investigated the ability of both of these methods to express tactile hardness stimulation: in Experiment A hardness was generated solely by visual stimulation using CG; and in Experiment B hardness was generated solely by the dot-matrix display. Based on the results of Experiments A and B, in Experiment C we conducted psychophysical experiments on the ability to express tactile hardness by combining the effects of pseudo-haptics and the tactile stimuli. In Experiment C, we were able to express six levels of distinguishable hardness, while only four and two levels were observed in Experiments A and B, respectively. In addition, the relationship between hardness evaluation and the six levels shows high linearity with R2 = 0.98.
Bioethanol is a well-known oil-alternate fuel for automobiles as a carbon neutral fuel adapted to environmental problems. Furthermore, ethanol water solution is thought to be effective to the depletion of problems of fossil fuel resources. Continuous combustion is achieved in a wide range of air ratios using low concentration ethanol water solution in previous research. This study aims to examine the influences on spray combustion characteristics by using a swirl burner. The images of flame structure for ethanol water solution was visualized for various air ratio and water contents by using a glass tube. The exhaust gases (CO, NOx, O2) and exhaust gas temperature are measured in a combustion chamber and exhaust pipe by using N type thermocouples. The main conclusions are as follows: 1) The brightness and length of flame for ethanol water solution at low ethanol concentration (E45) decreases compared to the other ethanol water concentrations (E60, E80 E95). 2) The exhaust temperature decreases with decreasing the air ratio at any ethanol concentration under constant ethanol flow rate conditions. 3) The CO emission decreases with increasing the air ratio at the low ethanol concentration (E45). 4) The NOx emission decreases with decreasing the ethanol concentration at any air ratios. 5) Fuel flow rate has a small influence for NOx emission under high air ratios at any ethanol water concentration.
Sound speed is one of the most important thermodynamic properties for developing a fuel injection system and it is often used to validate the equation of state. There are a few measurement data of sound speed in DME, however the measurement range of pressure and temperature was limited. The critical temperature of DME is lower than that of diesel fuel and close to the injection condition. At the critical point, the isothermal bulk modulus theoretically drops to 0. Thus, the isothermal bulk modulus and sound speed are expected to show a complex behavior around the critical point. In this study, sound speed in DME over a wide range of pressures and temperatures, from 1 MPa to 80 MPa, 298 K to 413 K including the critical point, was measured, and the isothermal bulk modulus of DME was estimated from the measured sound speed. The sound speed increased with increasing pressure or decreasing temperature. Around the critical point, the sound speed drastically dropped with approaching the critical point. Measurement results of the sound speed in this study were in good agreement with the estimated values from the equation of state proposed by Wu. The isothermal bulk modulus of DME was extremely low around the critical point. It is indicated that the performance of the injection pump of DME significantly decreases near the critical point.
This paper describes the results of a combination of EGR and supercharging applied to a diesel dual fuel (DDF) engine using natural gas (CNG) introduced from an intake pipe. The oxygen concentration in the intake charge were varied from 21% (without EGR) to 17% (26% EGR) with a cooled EGR technique. The boost pressures were set at two conditions, 100 kPa (naturally aspirated operation) and 120 kPa (supercharged operation) with a Roots blower supercharger driven by an inverter controlled motor. The influence of combining EGR and supercharging on the engine performance, combustion characteristics, and emissions were investigated with coconut oil methyl ester (CME) and gas oil under ordinary diesel and DDF operation modes. The results showed that the trade-off relation between the NOx and smoke emissions under the DDF operation combined with EGR and supercharging improved remarkably while also maintaining a relatively high brake thermal efficiency. Regardless of the engine operation mode, both the brake thermal efficiency and smoke emissions with the CME with supercharging improved more than with gas oil operation over the tested EGR regions.
Effects of underwater shock waves driven by imploding detonation on marine microorganisms have been experimentally studied. The detonation tube was initially changed with a stoichiometric C3H8-O2 mixture, while a test section was filled with water containing marine microorganisms. An initial pressure of the mixture was varied from 100 to 200 kPa. The experimental results show that mortality rate over 80 % is obtained for the maximum pressure more than 150 MPa or the shock energy more than 100 kJ/m2. Double treatment by the underwater shock waves gives mortality rate of almost 100 % even for the low initial pressure of 100 kPa. Around the maximum pressure of 100 MPa, mortality rate is found to increase with the maximum pressure decrease rate.
It is important to manage inventory adequately at a retail stores or wholesales. For this reason, we propose an inventory management method based on model predictive control. Model predictive control is an optimal operation method of dynamical systems and the process of stocks is able to be seen as a dynamical system. Therefore, by using model predictive control, there is a possibility that orders can manage their items properly for various evaluation criteria, such as reducing order cost and equalizing the order quantity. In order to achieve order's purpose, we need to improve a long-term prediction accuracy. Consequently, we also propose a stochastic demand forecast model based on a state space model and use a particle filter that one of non-liner and non-Gaussian filters for this model so as to make accurate demand forecasts. In our proposed model, we consider changes in demand due to price changes, such as changes in consumption tax rate, and adopt an idea from Prospect Theory in behavioral economics. In general, it is difficult to identify parameters in the state space model. For this purpose, we use a self-organizing state space model to solve this problem. In the self-organizing state space model, parameters are included in the state vector and they are estimated simultaneously online. We demonstrate that a proper inventory control is achieved by our proposed method using actual sales data of canned beer at a real retail store and show its effectiveness by comparing the conventional method.
In surface temperature measurement by thermocouple, measurement error was quantitatively investigated when the temperature measuring junction was adhered to the surface and a part of the lead wire was placed on the isothermal surface. First, heat paths of a thermocouple were modeled by thermal-resistance-network. Unknown parameters related to the contact between the thermocouple and the surface were estimated based on the measured data. The error ratio calculated by the thermal-resistance-network model agreed well to the experimental data both quantitatively and qualitatively, which indicates the validity of this model. Then, an analytic solution was derived with only main heat paths of the thermal-resistance-network. As a result, it was confirmed that even with only main heat paths, a reasonable error-ratio corresponding to the measurement can be obtained. Using the analytic solution, the error-ratio was calculated against various parameters, such as type and diameter of metal wire, gap between the junction and the surface, thermal conductivity of adhesive, lead-length placed on the isothermal surface, and so forth. Based on the analytic results, the effective method was presented to reduce the measurement error.
Some microorganisms swim in the fluid by rotating their helical flagella rigidly, and many studies have been focused on the mechanics of their swimming in purely viscous Newtonian fluid such as water. Recently, attention has been paid to the effects of viscoelasticity on the swimming of microorganisms, since many microorganisms commonly swim in viscoelastic fluid environments such as mucus gels and biofilms. In this study, we focused on the effect of viscoelastic Mach numbers M = V/c, where V is the speed of an object through a fluid and c is the speed of shear waves in the fluid, to which not much attention has been paid in the literature. We examined experimentally the effect of viscoelastic Mach numbers on the propulsive forces of a rotating model helical flagellum in subcritical (M < 1) and supercritical (M > 1) conditions. Helical flagellum models with different pitches and helical diameters were used for this study. The models were rotated in some viscoelastic fluids with different damping characteristics of the shear waves (such as wormlike micelle solutions and polymer solutions). In the fluid with lower damping characteristics, the force measurement results show that the rotating speed dependence changes significantly at the speed whose Mach number (defined as the ratio of helical wave speed to shear wave speed) is unity. It is also found that the propulsive forces are the function of only the tangential velocity along the helix when the tangential velocity is relatively high. The velocity fields obtained by a particle image velocimetry show that the flow patterns around a model helix changes between subcritical and supercritical conditions and the damping characteristics of the shear waves in the fluid play an important role in the flows generated around the model helix. These results suggest the importance of considering viscoelastic Mach numbers and damping characteristics of shear waves in the fluid.
Nowadays, a monitoring technology has attracted attention in the factory automation fields regarding IoT (Internet of Things). However, it is difficult to monitor the process information from a round tool during rotating operation in machine tools. We therefore develop a novel tool holder equipped with a wireless communication function to monitor tool temperature and vibration. In the present report, we attempt to measure the inner temperature in drill tool and investigate the influence of feed rate and cutting speed on it. Moreover, we attempt to measure the tool vibrations in the rotational and radial direction in countersinking process. As a result, we demonstrated that the developed method with a wireless system is effective to estimate the tool temperature in drilling processes and the tool vibration in countersinking processes.
Words are communication media to share a concept in a community. A word involving ambiguity represents multiple concepts depending on a context. Such ambiguity causes misunderstanding between people having different contexts. On the other hands, a community uses words to obtain responses and/or evaluations from target population, such as customers and participants. The word ambiguity causes misunderstanding between a community and a target population due to different contexts. A community dealing with multiple languages (e.g. multinationals) has a difficulty in translation if there are no words in a second language, all meanings of which do not correspond to all meanings of a word one wishes to translate. To deal with above issues caused by word ambiguity, I propose a multilingual semantic networks(MLSN) framework in this paper. The MLSN is a graph where multiple languages words, as nodes, are semantically linked through concepts, as another type nodes. I implemented MLSN in a graph database with datasets of WordNet in three languages: English, Japanese, and French. With MLSN, I conducted two analysis. In the first analysis, I investigate the meanings of ambiguous words such as “design” and Japanese word “Kansei”, and their semantic relations with relevant words in other languages. I found that there are no words corresponding to all meanings of those words in second languages. For the word “Kansei”, I illustrate semantic relations with words such as “emotion”, “affect”, “feeling”, “impression”, and “intuition” which are often used to define “Kansei”. In the second analysis, I discuss how MLSN supports to select and translate a set of words used as evaluation descriptors. I analyze 10 positive emotion words from well-established Geneva Emotion Wheel and their translation in French and Japanese. I demonstrate how MLSN automatically find translation mismatches and semantic independence between emotion descriptors.