• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.1 s.24
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• pp.89-98
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• 2006

This paper describes signal attenuation characteristics as splicing the output on LVDT for stability and reliability of switching mechanism, which is developed to use common signal between FLCC and EDFLCC, on T-50 aircraft. The method of test is classified a Pspice simulation and an actual hardware evaluation. The difference of error margin for two methods is 10times, the latter higher. The result in this experiment shows that the signal attenuation as splicing the output on LVDT doesn't affect and the static error margin is 53% for develope the EDFLCC.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.499-502
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• 2014

This paper presents a comparison study between simulation and experiment for fault diagnostics of a spur gear. In simulation, fault diagnostics using transmission error (TE) was performed and concluded to be valid. In a real experiment, however, it is not as easy to detect faults of gears using TE as in simulation. In this paper, after seeding the various faults like tooth crack of different length, tooth breakage and spalling in test rig, TE was calculated. Then, several signal processing techniques were performed to overcome the limitations of an experiment in detecting the fault signals of TE. After signal processing, we could detect the various faults of spur gears and different amplitude of TE sparks from cracks of different length. Then we discussed the difference between simulation and experment.

• 전기의세계
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• v.19 no.6
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• pp.1-7
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• 1970

In this paper, to determine process dynamic characteristics, the correlation method for measuring the impulse response of process using a pseudo-random binary signal as the test signal instead of white noise was studied. The error caused by using the signal of Mesquence signal generator which was built up by the authors was analysed. Experments were performed on the 1st and 2nd order lag systems and the results were in good coincidence with theoretical values. It is expected that applying these results, it may be possible to develop a continuous measuring method adaptable to modern control systems.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.423-426
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• 2003

Adaptive algorithm used in Acoustic Echo Canceller (AEC) needs fast convergence algorithm when reference signal is colored speech signal. Set-Membership Affine Projection (SMAP) algorithm is derived from the constraint, which is the minimum value adaptive filter coefficient error. In this paper, we test the characteristic about noise of the SMAP algorithm and proposed modified version of SMAP algorithm fur using at AEC. As the projection order increase, the convergence characteristic of the SMAP algorithm is improved where no noise space. But if the noise uncorrelated with input signal exists, the AEC shows bad performance. In this paper, we propose normalized version of adaptive constants using estimated error signal for robust to noise and show the good performance through AEC simulation.

• ETRI Journal
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• v.17 no.1
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• pp.11-22
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• 1995

This paper proposes a modified error function to improve the error back-propagation (EBP) algorithm for multi-Layer perceptrons (MLPs) which suffers from slow learning speed. It can also suppress over-specialization for training patterns that occurs in an algorithm based on a cross-entropy cost function which markedly reduces learning time. In the similar way as the cross-entropy function, our new function accelerates the learning speed of the EBP algorithm by allowing the output node of the MLP to generate a strong error signal when the output node is far from the desired value. Moreover, it prevents the overspecialization of learning for training patterns by letting the output node, whose value is close to the desired value, generate a weak error signal. In a simulation study to classify handwritten digits in the CEDAR [1] database, the proposed method attained 100% correct classification for the training patterns after only 50 sweeps of learning, while the original EBP attained only 98.8% after 500 sweeps. Also, our method shows mean-squared error of 0.627 for the test patterns, which is superior to the error 0.667 in the cross-entropy method. These results demonstrate that our new method excels others in learning speed as well as in generalization.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.5
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• pp.713-718
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• 2016

Predicting precise specifications of differential mixed-signal circuits is a difficult problem, because analytically derived correlation between process variations and conventional specifications exhibits the limited prediction accuracy due to the phase unbalance, for most self-tests. This paper proposes an efficient prediction technique to provide accurate specifications of differential mixed-signal circuits in a system-on-chip (SoC) based on a nonlinear statistical nonlinear regression technique. A spectrally pure sinusoidal signal is applied to a differential DUT, and its output is fed into another differential DUT through a weighting circuitry in the loopback configuration. The weighting circuitry, which is employed from the previous work [3], efficiently produces different weights on the harmonics of the loopback responses, i.e., the signatures. The correlation models, which map the signatures to the conventional specifications, are built based on the statistical nonlinear regression technique, in order to predict accurate nonlinearities of individual DUTs. In production testing, once the efficient signatures are measured, and plugged into the obtained correlation models, the harmonic coefficients of DUTs are readily identified. This work provides a practical test solution to overcome the serious test issue of differential mixed-signal circuits; the low accuracy of analytically derived model is much lower by the errors from the unbalance. Hardware measurement results showed less than 1.0 dB of the prediction error, validating that this approach can be used as production test.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.623-629
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• 2002

The spectrum of impulse response signal from an impulse hammer testing is widely used to obtain frequency response function(FRF) of the structure. However the FRFs obtained from impact hammer testing have not only leakage errors but also finite record length errors when the record length for the signal processing is not sufficiently long. The errors cannot be removed with the conventional signal analyzer which treats the signals as if they are always steady and periodic. Since the response signals generated by the impact hammer are transient and have damping, they are undoubtedly non-periodic. It is inevitable that the signals be acquired for limited recording time, which causes the finite record length error and the leakage error. In this paper, the errors in the frequency response function of multi degree of freedom system are formulated theoretically. And the method to remove these errors is also suggested. This method is based on the optimization technique. A numerical example of 3-dof model shows the validity of the proposed method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.10
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• pp.792-798
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• 2002

The spectrum of impulse response signal from an impulse hammer testing is widely used to obtain frequency response function (FRF) of the structure. However the FRFs obtained from impact hammer testing have not only leakage errors but also finite record length errors when the record length for the signal processing is not sufficiently long. The errors cannot be removed with the conventional signal analyzer which treats the signals as if they are always steady and periodic. Since the response signals generated by the impact hammer are transient and have damping, they are undoubtedly non-periodic. It is inevitable that the signals be acquired for limited recording time, which causes the finite record length error and the leakage error. In this paper, the errors in the frequency response function of multi degree of freedom system are formulated theoretically. And the method to remove these errors is also suggested. This method is based on the optimization technique. A numerical example of 3-dof model shows the validity of the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.125-129
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• 2004

For the diagnosis of compressor abnormal condition in air-conditioner, AE signal which is derived from wear condition, compressed air and assembly error is analyzed experimentally. The burst and continuous type AE signal occurred by metal contact and compressed air and AE raw signal of compressors were directly acquired in production line. After extracting samples according to waveforms, Early Life Test(ELT) is conducted and classified to normal and abnormal waveform. The efficient parameters of waveform pattern are investigated in time and frequency domain and the diagnosis algorithm of air-conditioner by Neural Network estimation is suggested.

• Journal of KSNVE
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• v.6 no.5
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• pp.679-684
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• 1996

The Instrumental Variable Method(IVM), modified from least square algorithm, is applied to parameter identification of a noise contaminated bearing test rig. The signal to noise ratio included in Frequency Response Function(FRF) can cause significant errors in parameter identification. Therefore, among several candidates of parameter identification method, results of the applied IVM were compared with noise-contaminated least square method. This study shows that the noise-contaminated least square method can have indonsistent accuracy depending on the degree of noise level, while the IVM has robuster performance to signal to noise ratio than least square method.