Yoichiro Iwasaki

Investigation of electric discharge sound in atmospheric pressure plasma using optical wave microphone

Abstract The light diffraction technique, which we call the “Optical Wave Microphone (OWM)” technique, is an effective sensing method to detect the sound and is flexible for practical uses as it involves only a simple optical lens system. This technique is also very useful to detect the sound wave without disturbing the sound field. Moreover, OWM can be used for sound field visualization by computerized tomography (CT) because the ultrasmall modulation by the sound field is integrated along the laser beam path. The characteristics of the coplanar DBD (Dielectric Barrier Discharge) operated in air is investigated. Applied voltage, current and the electrical discharge sound of coplanar DBD are measured, and examined the relationship between the micro discharge and the acoustic properties. We expect that understanding of acoustic properties gives more details of electric discharges. These are the first experiments to verify the feasibility of the OWM-CT method for the visualization of the sound field of DBD discharge.

Robust vehicle detection even in poor visibility conditions using infrared thermal images and its application to road traffic flow monitoring

We propose an algorithm for detecting vehicle positions and their movements by using thermal images obtained through an infrared thermography camera. The infrared thermography camera offers high contrast images even in poor visibility conditions like snow and thick fog. The proposed algorithm specifies the area of moving vehicles based on the standard deviations of pixel values along the time direction of spatio-temporal images. It also specifies vehicle positions by applying the pattern recognition algorithm which uses Haar-like features per frame of the images. Moreover, to increase the accuracy of vehicle detection, correction procedures for misrecognition of vehicles are employed. The results of our experiments at three different temperatures show that the information about both vehicle positions and their movements can be obtained by combining those two kinds of detection, and the vehicle detection accuracy is 96.2%. Moreover, the proposed algorithm detects the vehicles robustly in the 222 continuous frames taken in poor visibility conditions like snow and thick fog. As an application of the algorithm, we also propose a method for estimating traffic flow conditions based on the results obtained by the algorithm. By using the method for estimating traffic flow conditions, automatic traffic flow monitoring can be achieved.

Investigation of electric discharge sound in atmospheric pressure plasma

Abstract The characteristics of the Coplanar DBD (Dielectric Barrier Discharge) operated in air, argon or helium are investigated. Applied voltage, current and the electrical discharge sound of Coplanar DBD discharge are measured, and examined the fundamental relationship between the micro discharge and the acoustic properties. We expect that the understanding of acoustic properties gives more details of electric discharges and also develops new applications in the field of medical diagnostics, environment system, etc. We apply the new method to examine the electric discharge sound using Fraunhofer diffraction effect of visible laser beam. This new system is called the optical wave microphone by us and is very useful for the detection of sound wave without disturbing the sound field. The Fast Fourier Transform (FFT) is applied to discriminate the acoustic sound of the Coplanar DBD discharge and the dominant frequency components.

Vehicle Detection Even in Poor Visibility Conditions Using Infrared Thermal Images and Its Application to Road Traffic Flow Monitoring

We propose an algorithm for detecting vehicle positions and their movements by using thermal images obtained through an infrared thermography camera. The proposed algorithm specifies the area of moving vehicles based on the variations of pixel values, i.e. the standard deviations of pixel values along the time direction of spatio-temporal images. It also specifies vehicle positions by applying the pattern recognition algorithm which uses Haar-like features per frame of the images. Moreover, to increase the accuracy of vehicle detection, correction procedures for misrecognition of vehicles are employed. The results of our experiments show that the information about both vehicle positions and their movements can be obtained by combining those two kinds of detection, and the vehicle detection accuracy is 96.3 %. As an application of the algorithm, we also propose a method for estimating traffic flow conditions based on the results obtained by the algorithm. By use of the method for estimating traffic flow conditions, automatic traffic flow monitoring can be achieved. In addition, there is a possibility that traffic accidents, vehicle troubles, and illegal parking can be detected with the proposed method. By using the traffic information obtained from the proposed method, we also expect to realize an optimized traffic signal control around the clock even in changeable weather.

A Robust Method for Detecting Vehicle Positions and Their Movements Even in Bad Weather Using Infrared Thermal Images

We propose a method for detecting vehicle positions and their movements by using thermal images obtained through an infrared thermography camera. Our method specifies the area of moving vehicles based on the variations of pixel values, i.e. the standard deviations of pixel values along the time direction of spatio-temporal images. It also specifies vehicle positions by applying the pattern recognition algorithm which uses Haar-like features per frame of the images. The results of our experiments show that the information about both vehicle positions and their movements can be obtained by combining those two kinds of detection. Our method has the advantage of distinguishing between smooth traffic flows and heavy ones. In addition, there is a possibility that traffic accidents, vehicle troubles, and illegal parking can be detected with our method. We also expect to realize a robust automatic monitoring for road traffic around the clock even in changeable weather with our method of using thermal images.

Visualization of sound field using Optical Wave Microphone coupled with computerized tomography

The novel method, which we call the “Optical Wave Microphone (OWM)” technique, is based on a Fraunhofer diffraction effect between sound wave and laser beam. The light diffraction technique is an effective sensing method to detect the sound and is flexible for practical uses as it involves only a simple optical lens system. In this work, fibered OWM which is improved in signal-noise ratio of the conventional OWM, was developed. This new method can realize high accuracy measurement of slight density change of atmosphere. Moreover, fibered OWM can be applied for sound field visualization by computerized tomography (CT) because the ultra-small modulation by the sound field is integrated along the laser beam path.

Pulsed neodymium-doped yttrium aluminum garnet laser heating of multiwalled carbon nanotube film

A multiwalled carbon nanotube (MWCNT) film surface was irradiated with a single pulse from a neodymium-doped yttrium aluminum garnet (Nd:YAG) laser. When an MWCNT film is irradiated with a pulsed Nd:YAG laser of 23.7 mJ/cm2, the calculated maximum surface temperature becomes 304 °C. The surface temperature increases from 595 to 2968 °C with an increase in laser power from 59.4 to 469 mJ/cm2. The MWCNT film is examined by increasing the intensity of the two characteristic Raman shifts ID (defect-induced mode: D-band) and IG (graphite-induced mode: G-band) to clarify the effect of pulsed Nd:YAG laser heating. Moreover, a new original image analytical method is developed to characterize CNTs from scanning electron microscopy (SEM) images. This method is useful for measuring the diameter of as-grown CNTs and those after annealing with a pulsed Nd:YAG laser. The number of detected diameters between 40 and 60 nm increases with an increase in laser energy density from 181 to 268 mJ/cm2.

Thermal treatment of carbon nanotubes film by a pulsed Nd: YAG laser irradiation

Multi-walled carbon nanotubes (MWCNTs) film have been analyzed by Raman spectroscopy to clarify the effect of a pulsed Nd: YAG laser heating. The MWCNTs film surface was flashed with the fundamental harmonic (λ=1064 nm) or the second harmonic (λ=532 nm) of a single pulse of Nd: YAG laser in the air. The dynamics of pulsed nanosecond laser heating process was simulated by the solution of the one-dimensional heat conduction equation. Raman spectroscopy of MWCNTs films before and after irradiation were measured. The intensity of the two characteristic Raman shifts ID (defect-mode) and IG (graphite-mode) was measured by the Raman spectroscopy. The maximum surface temperature was calculated and compared with the IG/ID ratio of MWCNTs film. The heating process by a pulsed Nd: YAG laser was further examined in the context of atmosphere (oxygen, ozone, nitrogen or partial vacuum).

An Automatic Measurement Algorithm for the Diameters of Carbon Nanotubes by Using Image Processing

We propose an automatic measurement algorithm for the diameters of carbon nanotubes (CNTs) electron microscopy images by using image processing. In the algorithm, Otsu’s method (discriminant analysis method) was employed to determine automatically the threshold for image binarization. Proposed algorithm provides the numerous values of diameters detected by horizontal and vertical scans for the binary images. The diameter measurements using developed program were carried out for the multi-walled CNTs (MWNTs) taken by a scanning electron microscopy (SEM).