• Title/Summary/Keyword: mechanical signal

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Retrieving the Time History of Displacement from Measured Acceleration Signal

  • Han, Sangbo
    • Journal of Mechanical Science and Technology
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    • v.17 no.2
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    • pp.197-206
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    • 2003
  • It is intended to retrieve the time history of displacement from measured acceleration signal. In this study, the word retrieving means reconstructing the time history of original displacement signal from already measured acceleration signal not just extracting various information using relevant signal processing techniques. Unlike extracting required information from the signal, there are not many options to apply to retrieve the time history of displacement signal, once the acceleration signal is measured and recorded with given sampling rate. There are two methods, in general, to convert measured acceleration signal into displacement signal. One is directly integrating the acceleration signal in time domain. The other is dividing the Fourier transformed acceleration signal by the scale factor of - $\omega$$^2$and taking the inverse Fourier transform of it. It turned out both the methods produced a significant amount of errors depending on the sampling resolution in time and frequency domain when digitizing the acceleration signals. A simple and effective way to convert the time history of acceleration signal into the time history of displacement signal without significant errors is studied here with the analysis on the errors involved in the conversion process.

Analysis of Signal Characteristics of Resistance Scanning-type Flexible Tactile Sensor (저항 스캐닝 방식의 유연 촉각센서 신호 특성분석)

  • Sin, Yu-Yeong;Kim, Seul-Ki;Lee, Ju-Kyoung;Lee, Suk;Lee, Kyung-Chang
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.14 no.5
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    • pp.28-35
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    • 2015
  • This paper introduces a resistance scanning-type flexible tactile sensor for intelligent robots and presents the output characteristics of the sensor via signal processing. The sensor was produced via the lamination method using multi-walled carbon nanotubes (a conductive material), an insulator, and Tango-plus (an elastic material). Analog and digital signal processing boards were produced to analyze the output signal of the sensor. The analog signal processing board was made up of an integrator and an amplifier for signal stability, and the digital signal processing board was made up of an IIR filter for noise removal. Finally, the sensor output for the contact force was confirmed through experiments.

Electrical Impedance Change due to Contamination at the Contact Interface of Connectors for Automobile Crank Shaft Position Sensor

  • Kim, Young-Tae;Sung, In-Ha;Kim, Dae-Eun
    • International Journal of Precision Engineering and Manufacturing
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    • v.5 no.2
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    • pp.46-52
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    • 2004
  • Numerous connectors are used in automobiles for transmission of electrical signals across various electro-mechanical components. The connectors must operate with high reliability in order to minimize failures due to signal degradation. In this work, the effects of contamination at the contact interface of connectors used fur automobile crankshaft position sensor on the impedance change were investigated. An experimental set-up was built to simulate the electrical signal transmitted from the sensor to the engine control unit through a connector. Output from the connector was investigated using connectors contaminated with engine block residues and water droplets. It was found that slight contamination of the connectors could lead to significant signal degradation which can lead to engine failure. Also, the effect of water in the connector altered the signal severely. However, the signal gradually regained the original state as the water evaporated from the interface.

Evaluation of Fracture Behavior of SA-516 Steel Welds Using Acoustic Emission Analysis

  • Na, Eui-Gyun;Ono, Kanji;Lee, Dong-Whan
    • Journal of Mechanical Science and Technology
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    • v.20 no.2
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    • pp.197-204
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    • 2006
  • The purpose of this study is to evaluate the AE characteristics for the basemetal, PWHT (post-weld heat treatment) and weldment specimens of SA-516 steel during fracture testing. Four-point bending and AE tests were conducted simultaneously. AE signals were emitted in the process of plastic deformation. AE signal strength and amplitude of the weldment was the strongest, followed by PWHT specimen and basemetal. More AE signals were emitted from the weldment samples because of the oxides, and discontinuous mechanical properties. AE signal strength and amplitude for the basemetal or PWHT specimen decreased remarkably compared to the weldment because of lower strength. Pre-cracked specimens emitted even lower event counts than the corresponding blunt notched specimens. Dimple fracture from void coalescence mechanism is associated with low-level AE signal strength for the basemetal or PWHT. Tearing mode and dimple formation were shown on the fracture surfaces of the weldment, but only a small fraction produced detectable AE.

Shape estimation of the composite smart structure using strain sensors (변형률 감지기를 이용한 복합재료 지능구조물의 변형형상예측)

  • Yoon, Young-Bok;Cho, Young-Soo;Lee, Dong-Gun;Hwang, Woon-Bong;Ha, Sung-Kyu
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.22 no.1
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    • pp.23-32
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    • 1998
  • A shape estimation is needed to control actively a smart structure. A method is, hence, proposed to predict the deformed shape of the structure subjected to unknown external load using the signal from sensors attached to the structure. The shape estimation is based on the relationship between the deformation of the structure and the signal from the sensors. The matrix containing the relationship between the deformation and signal is obtained using fictitious force or eigenvector of global stiffness matrix. Then the deformed shape can be predicted using the linear matrix and signal from sensors attached to the structure. To verify this method, experiment and FEM were performed and it was shown that the shape estimation method based on the fictitious force predicts deflections well and more accurately than that based on eigenvector.

Wearable Force Sensor Using 3D-printed Mold and Liquid Metal (삼차원 프린트된 몰드와 액체 금속을 이용한 웨어러블 힘 센서 개발)

  • Kim, Kyuyoung;Choi, Jungrak;Jeong, Yongrok;Kim, Minseong;Kim, Seunghwan;Park, Inkyu
    • Journal of Sensor Science and Technology
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    • v.28 no.3
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    • pp.198-204
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    • 2019
  • In this study, we propose a wearable force sensor using 3D printed mold and liquid metal. Liquid metal, such as Galinstan, is one of the promising functional materials in stretchable electronics known for its intrinsic mechanical and electronic properties. The proposed soft force sensor measures the external force by the resistance change caused by the cross-sectional area change. Fused deposition modeling-based 3D printing is a simple and cost-effective fabrication of resilient elastomers using liquid metal. Using a 3D printed microchannel mold, 3D multichannel Galinstan microchannels were fabricated with a serpentine structure for signal stability because it is important to maintain the sensitivity of the sensor even in various mechanical deformations. We performed various electro-mechanical tests for performance characterization and verified the signal stability while stretching and bending. The proposed sensor exhibited good signal stability under 100% longitudinal strain, and the resistance change ranged within 5% of the initial value. We attached the proposed sensor on the finger joint and evaluated the signal change during various finger movements and the application of external forces.

Monitoring system of physical behavior for dementia patient

  • Tanaka, Motohiro;Murakami, Ryuya;Dong, Rue Shao;Ishimatsu, Takakazu
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1968-1970
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    • 2003
  • In this paper we propose a system to forecast the dangerous behavior of the dementia patients. Basic idea of our approach is to measure the body movements of the dementia patients using the acceleration sensor. Based on the data measured, warning the care-givers about possible dangerous actions like falling down from the bed and slipping down onto the floor to some extent. The signals measured by the acceleration sensor are processed by a one-chip computer. Based on the diagnosis of the one-chip computer , alert signal is generated to the care-giver by a wire-less signal. The sensor is implemented in a compact body . Applicability of the system is now being examined at a nursing home.

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Measurement of the Flying Characteristics of HDD Slider Air Bearing Using AE Signal (AE 신호를 이용한 HDD 슬라이더 공기베어링의 부상상태 측정)

  • Kim, Jae-Jic;Jeong, Tae-Gun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.9
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    • pp.1391-1399
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    • 2001
  • The AE measurement is one of the most convenient methods for detecting contacts between the slider and the disk. The AE method has been widely used in the investigation of the tribology of sliding interfaces due to its convenience. We examined the relationship between the AE signal and the flying height of a slider. We investigated the influence of the disk linear velocity on the AE rms signal by using the AE measurement system. The experiment also gives the relationship between the take-off velocity and the disk surface conditions. To investigate the behavior of the slider further, the variances of the AE signals are analyzed. The experimental results indicate that the increase in the magnitude of the AE rms signal does not necessarily mean the slider/disk contacts.

Adaptive Signal Processing Methods for ECG Signal Analysis using EMG Signal Analysis (근전도 신호를 이용한 심전도 신호의 적응신호처리 방법)

  • Oh, Kwang-Seok;Park, Jun-Sik;Lee, Choon-Young;Lee, Sang-Ryong
    • Proceedings of the IEEK Conference
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    • 2006.06a
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    • pp.889-890
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    • 2006
  • This paper pertains to introducing the design of adaptive filters for the cancellation of muscle noise among several types of noise sources from the ECG signal. We used EMG signals measured along with ECG at the same time to use it as the reference input to the adaptive filter for the experiments. PSD results showed that the statistical characteristics of ECG are closely correlated with those of EMG.

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Classification of Welding Defects in Austenitic Stainless Steel by Neural Pattern Recognition of Ultrasonic Signal (초음파신호의 신경망 형상인식법을 이용한 오스테나이트 스테인레스강의 용접부결함 분류에 관한 연구)

  • Lee, Gang-Yong;Kim, Jun-Seop
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.20 no.4
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    • pp.1309-1319
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    • 1996
  • The research for the classification of the natural defects in welding zone is performd using the neuro-pattern recognition technology. The signal pattern recognition package including the user's defined function is developed to perform the digital signal processing, feature extraction, feature selection and classifier selection, The neural network classifier and the statistical classifiers such as the linear discriminant function classifier and the empirical Bayesian calssifier are compared and discussed. The neuro-pattern recognition technique is applied to the classificaiton of such natural defects as root crack, incomplete penetration, lack of fusion, slag inclusion, porosity, etc. If appropriately learned, the neural network classifier is concluded to be better than the statistical classifiers in the classification of the natural welding defects.