Hitoshi Tsunashima

Control and monitoring for railway vehicle dynamics

Over the last twenty to thirty years, railway vehicle dynamics has changed from being an essentially mechanical engineering discipline to one that is increasingly starting to include sensors, electronics and computer processing. This paper surveys the application of these technologies to suspensions and running gear, focused upon the complementary issues of control (which has been reviewed within Vehicle System Dynamics previously) and monitoring (which has not previously been reviewed). The theory, concepts and implementation status are assessed in each case, from which the paper identifies the key trends and concludes with a forward look at what is likely to develop over the next years.

Measurement of brain function of car driver using functional near-infrared spectroscopy (fNIRS)

The aim of this study is to propose a method for analyzing measured signal obtained from functional Near-Infrared Spectroscopy (fNIRS), which is applicable for neuroimaging studies for car drivers. We developed a signal processing method by multiresolution analysis (MRA) based on discrete wavelet transform. Statistical group analysis using Z-score is conducted after the extraction of task-related signal using MRA. Brain activities of subjects with different level of mental calculation are measured by fNIRS and fMRI. Results of mental calculation with nine subjects by using fNIRS and fMRI showed that the proposed methods were effective for the evaluation of brain activities due to the task. Finally, the proposed method is applied for evaluating brain function of car driver with and without adaptive cruise control (ACC) system for demonstrating the effectiveness of the proposed method. The results showed that frontal lobe was less active when the subject drove with ACC.

SELF-POWERED ACTIVE CONTROL APPLIED TO A TRUCK CAB SUSPENSION

Abstract A method of active vibration control using regenerated vibration energy, i.e. self-powered active control, applied to the cab suspension of a heavy duty truck. In the proposed system, an electric generator that is installed in the suspension of the chassis regenerates vibration energy and stores it in the condenser. An actuator in the cab suspension achieves active vibration control using the energy stored in the condenser. Numerical simulations and basic experiments demonstrate better isolation performance of the self-powered active vibration control system than that of a passive and a semi-active control.

Track geometry estimation from car-body vibration

Track maintenance works based on track geometry recordings are essential to enhance the safety and comfort of railway transportation. The track condition monitoring system is mainly used for the choice of area needing track tamping works for the purpose of the good riding comfort. An advantage of car-body acceleration measurement devices is their simple structures, which make it easier to carry out maintenance. However, the car-body acceleration waveform is considerably different from track geometry. This paper demonstrates the possibility to estimate the track geometry of Shinkansen tracks using car-body motions only. In an inverse problem to estimate track irregularity from car-body motions, a Kalman Filter (KF) was applied to solve the problem. Estimation results showed that track irregularity estimation in vertical direction is possible with acceptable accuracy for real use.

Brain-computer interface using near-infrared spectroscopy for rehabilitation

This study proposes a new method for detecting brain activity level for brain-computer interface (BCI) using a near-infrared spectroscopy (NIRS) which is applicable for rehabilitation. NIRS detects the radiated near-infrared rays, and measures relative variations of oxygenated hemoglobin (oxy-Hb) and deoxygenated hemoglobin (deoxy-Hb) based on those absorbencies. The proposed method detects the brain activity level using oxy-Hb and the differential value of oxy-Hb. Results with grasping task show that the proposed method is effective for the detecting of brain activity level.

Vehicle and Road State Estimation Using Interacting Multiple Model Approach

This article describes the estimation algorithm of the vehicle state and the road condition, which is formulated on the basis of the interacting multiple model algorithm. Ten system modes of tire are modeled (considered nonlinearity) according to the road friction. Ten system modes are provided for switching from one mode to another in a probabilistic manner. The mode probabilities and states of vehicle are estimated based on extended Kalman filter (EKF). This algorithm is evaluated in the simulation study. Simulation results show that the algorithm is effective in the state estimation of vehicle and road surface.

Measurement of Brain Function Using Near-Infrared Spectroscopy (NIRS)

Near-infrared spectroscopy (NIRS) has gained attention in recent years (Hoshi et al., 2001; Tamura, 2003). This non-invasive technique uses near-infrared light to evaluate increases or decreases in oxygenated hemoglobin or deoxygenated hemoglobin in tissues below the body surface. NIRS can detect the hemodynamics of the brain in real time while the subject is moving. Brain activity can therefore be measured in various environments. Recent research has used NIRS to measure brain activity in a train driver (Kojima et al., 2005, 2006). NIRS has also been used to evaluate the mental activity of an individual driving a car in a driving simulator (Shimizu et al., 2009). Various arguments have focused on interpretation of signals obtained from NIRS, and no uniform signal-processing method has yet been established. Averaging and baseline correction are conventional signal-processing methods used for the NIRS signal. These methods require block design, an experimental technique that involves repeating the same stimuli (tasks) and resting multiple times in order to detect brain activation during a task. However, brain activation has been noted to gradually decline when a subject repeats the same task multiple times (Takahashi et al., 2006). Fourier analysis, which is frequently used for signal analysis, transforms information in the time domain into the frequency domain through the Fourier transform. However, time information is lost in the course of the transform. As the NIRS signal fluctuates, timefrequency analysis is suitable for the NIRS signal. The wavelet transform is an efficient method for time-frequency analysis (Mallat, 1998). This approach adapts the window width in time and frequency so that the window width in frequency becomes smaller when the window width in time is large, or the window width in frequency becomes larger when the window width in time is small. Multi-resolution analysis (MRA) (Mallat, 1989) decomposes the signal into different scales of resolution. MRA with an orthonormal wavelet base effectively facilitates complete decomposition and reconstruction of the signal without losing original information from the signal. Oxygenated hemoglobin and deoxygenated hemoglobin as measured in NIRS are relative values from the beginning of measurement and vary between subjects and parts of the brain. Simple averaging of the NIRS signal thus should not be applied for statistical analysis. To solve this problem, we propose the Z-scored NIRS signal.

Applications of Double-Wayland Algorithm to Detect Anomalous Signals

The Wayland algorithm has been improved in order to evaluate the degree of visible determinism for dynamics that generate a time series in a simple and accurate manner. Additionally, the Double-Wayland algorithm that we proposed can detect phase transitions among multi-states and non-stationarity in the dynamics. We are applying the Double-Wayland algorithm to detect anomalous signals in railways, stock prices, stabilometry and electrograms recorded by using mapping catheters. In this study, we reported the manner in which these anomalous signals can be detected; however, due to space limitations, we have not reported this data for applications in the field of medicine.

Static and Dynamic Performance of Permanent Magnet Suspension for Maglev Transport Vehicle

SUMMARY The design and performance of a mechanical air gap controller for a maglev transport vehicle are described. The basic requirement for a functional design of the controller is derived first and its effectiveness is shown by experiments. After the construction of dynamic vehicle models dynamic characteristics of the maglev vehicle are introduced and the stability criteria for magnetic levitation are derived. The effect of a dead zone in the mechanical air gap controller and nonlinear characteristics of the magnets, which are expected to exert a large influence on vehicle levitation performance, are investigated by simulations. The simulation results show that a low control lever ratio causes sudden deterioration of the levitation performance if there exists a dead zone in the controller, and a suitable control lever ratio which is unaffected by the dead zone is proposed. Finally, field test results with an actual maglev transport vehicle are shown and the dynamic levitation performance of the vehicl...

Condition monitoring of railway vehicle suspension using adaptive multiple model approach

This paper demonstrates the possibility to detect suspension failures of railway vehicles using a multiple-model approach from on-board measurement data. The railway vehicle model used includes the lateral and yaw motions of the wheelsets and bogie, and the lateral motion of the vehicle body, with sensors measuring the lateral acceleration and yaw rate of the bogie, and lateral acceleration of the body. The detection algorithm is formulated based on the Interacting Multiple-Model (IMM) algorithm adding a method updating estimation model. The IMM method has been applied for detecting faults in vehicle suspension systems in a simulation study. The mode probabilities and states of vehicle suspension systems are estimated based on a Kalman filter (KF). This algorithm is evaluated in simulation examples. Simulation results indicate that the algorithm effectively detects on-board faults of railway vehicle suspension systems in realistic situation.