• 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.

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.109-117
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• 2008

In this study, a method predicting the displacement responseof structures from the measured dynamic strain signal is proposed by using a mode decomposition technique. Dynamic loadings including wind and seismic loadings could be exerted to the bridge. In order to examine the bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. Because it may be not easy for the displacement response to be acquired directly on site, an indirect method to predict the displacement response is needed. Thus, as an alternative for predicting the displacement response indirectly, the conversion of the measured strain signal into the displacement response is suggested, while the measured strain signal can be obtained using fiber optic Bragg-grating (FBG) sensors. To overcome such a problem, a mode decomposition technique was used in this study. The measured strain signal is decomposed into each modal component by using the empirical mode decomposition(EMD) as one of mode decomposition techniques. Then, the decomposed strain signals on each modal component are transformed into the modal displacement components. And the corresponding mode shapes can be also estimated by using the proper orthogonal decomposition(POD) from the measured strain signal. Thus, total displacement response could be predicted from combining the modal displacement components.

• Imaging Science in Dentistry
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• v.31 no.2
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• pp.93-99
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• 2001

Purpose: To analyze the possible association between magnetic resonance imaging signal intensity of temporomandibular joint disk and posterior attachment, and the type and extent of disk displacement, disk configuration, effusion and clinical signs in patients with internal derangement. Materials and Methods: Magnetic resonance images of the 132 temporomandibular joints of 66 patients with temporomandibular joint displacement were analyzed. The clinical findings were obtained by retrospective review of the patients' records. The type and extent of disk displacement, disk configuration and effusion were evaluated on the proton density MR images. The signal intensity from the anterior band, posterior band and posterior attachment were measured on MR images. The associations between the type and extent of disk displacement, disk configuration, effusion and clinical signs and the MR signal intensity of disk and posterior attachment were statistically analyzed by student's t-test. Results: Of 132 joints, 87 (65.9%) showed anterior disk displacement with reduction (ADR) and 45 (34.1%) showed anterior disk displacement without reduction (ADnR). The signals from posterior attachments were lower in joints with ADnR than those of ADR (p<0.05). The results showed statistically significant (p<0.05) association between the type and extent of disk displacement and disk configuration, and decreased signal intensity of posterior attachment. There were no statistical associations between pain, noise and limited mouth opening, and signal intensity of disk and posterior attachment. Conclusions: The average signal from posterior attachment was lower in joints with ADnR than that of ADR. The type and extent of disk displacement and disk configuration appeared to be correlated with the signal intensity from posterior attachment.

• Journal of Welding and Joining
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• v.13 no.4
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• pp.65-74
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• 1995

The weld seam tracking sensor is indispensable to improve the flexibility of automatic arc welding systems. Among the position sensing methods available, a laser displacement sensor is one of the most prevailing methods. In this study, a laser displacement sensor was examined on detecting the weld seam of lap joints in sheet metal arc welding. The output signal of the laser displacement sensor may ontain severe fluctuation from the effect of arc light, spatters, fume, etc. So a variety of signal processing methods was applied to smooth the output signal of the sensor. And then the weld joint was determined by using the central difference method. It was revealed that the quadratic mean method plays an important role in detecting the weld seam during welding especially.

• Journal of Drive and Control
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• v.12 no.3
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• pp.44-51
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• 2015

In this study, a metering cylinder was constructed, and the velocity obtained from the linear velocity transducer (LVT) of the cylinder piston was used to evaluate the dynamic performance of an electro-hydraulic servovalve. Frequency response experiments involving the spool displacement and piston velocity (LVT signal) were conducted with different input signal amplitudes, hydraulic pipe diameters, and supply pressures. The spool displacement signal accurately reflected the performance of the servovalve. Meanwhile, the -3 dB bandwidth frequency of the LVT signal was similar to the spool displacement signal, except for a small-amplitude input signal, and the $-90^{\circ}$ phase lag bandwidth frequency showed some differences.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.6
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• pp.476-482
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• 2014

The stress analysis of the pipeline is required in any kind of plant for its safe operation. For this, the displacement vibration data measured at many locations of the pipeline should be provided. In reality, the installation of the non-contact type displacement sensors such as laser displacement sensors or eddy current type proximity sensors in a narrow and confined region in the vicinity of the pipeline is almost impracticable. In this work, the general purpose piezo-ceramic accelerometers were attached on the measuring points on the pipeline and the acceleration vibration signal was acquired. The measured acceleration signal was low pass filtered and then downsampled. The resulting acceleration signal was transformed into both the time-domain and frequency-domain displacement signal utilizing the fast Fourier transform techniques. All the procedures are presented in detail. It is demonstrated that the measurement of the pipeline acceleration by using contact type accelerometers can be made for the purpose of providing the required displacement data for the stress analysis of the pipeline.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.9
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• pp.60-67
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• 2007

A signal conditioning circuit for capacitive displacement sensors was developed using a high frequency modulation/demodulation method, and its performance was evaluated. Since capacitive displacement sensors can achieve high resolution and linearity, they have been widely used as precision sensors within the range of several hundred micrometers. However, they inherently have a limitation in low frequency range and some nonlinearity characteristics and so a specially designed signal conditioning circuit is needed to handle these properties. The developed signal processing circuit consists of three parts: linearization, modulation/demodulation, and nonlinearity compensation. Each part was constructed discretely using several IC chips and passive elements. An evaluation system for precision displacement sensors was developed using a laser interferometer, a precision stage, and a PID position controller. The signal processing circuit was tested using the evaluation system in the respect of resolution, repeatability, linearity, and so on. From the experimental results, we know that a highly linear voltage output can be obtained successfully, which is proportional to displacement and the nonlinearity of output is less than 0.02% of full range. However, in the future, further investigation is required to reduce noise level and phase delay due to a low-pass filter. The evaluation system also can be applied effectively to calibration and evaluation of precision sensors and stages.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4A
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• pp.507-515
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• 2008

In this study, a method predicting the displacement response of structures from the measured dynamic strain signal is proposed by using mode decomposition technique. Evaluation of bridge stability is normally focused on the bridge completed. However, dynamic loadings including wind and seismic loadings could be exerted to the bridge under construction. In order to examine the bridge stability against these dynamic loadings, the prediction of displacement response is very important to evaluate bridge stability. Because it may be not easy for the displacement response to be acquired directly on site, an indirect method to predict the displacement response is needed. Thus, as an alternative for predicting the displacement response indirectly, the conversion of the measured strain signal into the displacement response is suggested, while the measured strain signal can be obtained using fiber optic Bragg-grating (FBG) sensors. As previous studies on the prediction of displacement response by using the FBG sensors, the static displacement has been mainly predicted. For predicting the dynamic displacement, it has been known that the measured strain signal includes higher modes and then the predicted dynamic displacement can be inherently contaminated by broad-band noises. To overcome such problem, a mode decomposition technique was used. Mode decomposition technique estimates the displacement response of each mode with mode shape estimated to use POD from strain signal and with the measured strain signal decomposed into mode by EMD. This is a method estimating the total displacement response combined with the each displacement response about the major mode of the structure. In order to examine the mode decomposition technique suggested in this study model experiment was performed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.675-680
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• 2008

This paper proposes a way to measure the displacement of a multi-point by using a pattern recognition from video signal. Generally in measuring displacement, gab sensor, which is a displacement sensor, is used. However, it is difficult to measure displacement by using a common sensor in places where it is unsuitable to attach a sensor, such as high-temperature areas or radioactive places. In this kind of places, non-contact methods should be used to measure displacement and in this study, images of CCD camera were used. When displacement is measure by using camera images, it is possible to measure displacement with a non-contact method. It is simple to install and multi-point displacement measuring device so that it is advantageous to solve problems of spatial constraints.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.12
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• pp.1256-1261
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• 2008

This paper proposes a way to measure the displacement of a multi-point by using a pattern recognition from video signal. Generally in measuring displacement, gab sensor, which is a displacement sensor, is used. However, it is difficult to measure displacement by using a common sensor in places where it is unsuitable to attach a sensor, such as high-temperature areas or radioactive places. In this kind of places, non-contact methods should be used to measure displacement and in this study, images of CCD camera were used. When multi-point is measure by using a pattern recognition, it is possible to measure displacement with a non-contact method. It is simple to install and multi-point displacement measuring device so that it is advantageous to solve problems of spatial constraints.