• Journal of the Korea Computer Industry Society
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• v.2 no.6
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• pp.817-826
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• 2001

In this paper, the method of processing a blurred noisy signal has been researched. The conventional method of processing signal has faults which are slow-convergence speed and long time-consuming process at the singular point and in the ill condition. There is the process, the Gauss-Seidel's method to remove these faults, but it takes too much time because it processes signal repeatedly. For overcoming the faults, this paper shows a signal process method which takes shorter than the Tikhnov-Miller's by comparing the Tikhnov-Miller's with proposed algorithm and accelerating convergence speed at the singular point in the ill condition. In this paper, the conventional process method and proposed optimal algorithm were used to get a standard image (256 ＊ 256 ＊ 8bits),and then the results are simulated and compared each other in order to examine the variance of MSE ( Mean-Square Error ) by the acceleration parameter in the proposed two dimensional signal procedures. The result of the signal process and the processing time was measured at all change of acceleration parameter in order to verify the effectiveness of the proposed algorithm.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.12 no.5
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• pp.157-162
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• 2013

To analyze the dynamic acceleration characteristics, it is necessary to identify the acceleration model using some methods that can represent the dynamic properties well. In this sense, fractal methods were used for the verification of characteristics of an acceleration signal. To estimate and analyze the geometry of acceleration signal, a fractal interpolation and its analysis was introduced in this paper. The chaotic nature of acceleration signal was considered in fractal modeling. In this study the fractal signal modeling has brought a focus within the scope of the fractal interpolation and fractal dimension. And a new idea of fractal dimension has been introduced and discussed considering the damping ratio and amplitude for its dynamic properties of the signal. The fractal dimension of acceleration with respect to the scaling factor using fixed data points of 1000 points was calculated and discussed. The acceleration behaviors of this results show some different characteristics. And this fractal analysis can be applied to other signal analysis of several machining such as pendulum type grinding and milling which has many dynamic properties in the signal.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.17-20
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• 2000

In a digital communication system, the transmission channel may introduce error into the digital signal being transmitted. It would be useful if a process could be devised so that the error could be removed in order to recover the transmitted digital signal. We design a corrective filter that is inverse filter, which will generate an output signal identical to the input signal. in order for two systems connected in cascade to produce an output which is identical to the input signal, the over-all unit sample response of the cascade connection must be a unit sample function.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.196-200
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• 2000

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used fur on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.136-139
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• 2000

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used for on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

• 전자공학회논문지 IE
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• v.47 no.4
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• pp.18-27
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• 2010

This paper is designed the efficient Data Acquisition System for an vibration of rotatory machines. The Data Acquisition System is consist of the analog logic having signal filer and amplifier, and digital logic with ADC, DSP, FPGA and FIFO memory. The vibration signal of rotatory machines acquired from sensors is controlled by the FPGA device through the analog logic and is saved to FIFO memory being converted analog to digital signal. The digital signal process is performed by the DSP using the vibration data in FIFO memory. The vibration factor of the rotatory machinery analysis and diagnosis is defined the RMS, Peak to Peak, average, GAP, FFT of vibration data and digital filtering by DSP, and is need to follow as being happened the event of vibration and make an application to an warning system. It takes time to process the several analysis step of all vibration data and the event follow, also special event. It should be continuously performed the data acquisition and the process, however during processing the input signal the DSP can not be performed to the acquisited data after then, also it will be lose the data at several channel. Therefore it is that the system uses efficiently the DSP and FPGA devices for reducing the data lose, it design to process a part of the signal data to FPGA from DSP in order to minimize the process time, and a process to parallel process system, as a result of design system it propose to method of faster process and more efficient data acquisition system by using DSP and FPGA than signal DSP system.

• 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.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.262-267
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• 2003

At process of production according to development of accumulation degree of semi-conductor element, because functional mistake examination time required increases, is becoming big obstacle factor in cost-cutting. Studied pattern generator that generate pattern and address that is bundle enemy to process these controversial point effectively.

• 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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.1
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• pp.7-14
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• 2010

AE(acoustic emission) sensor has been used for a state monitoring and observation during a ultra-precision machining because AE signal, which has high frequency range, is sensitive enough. In case of ceramic fabrication, a monitoring of machining state is important because of its hard and brittle nature. A machining characteristic of ceramic is susceptibly different in accordance with variable machining conditions. In this study, Yttria($Y_2O_3$) ceramic was fabricated using the ultra-precision lapping process with in-process electrolytic dressing(IED) method. And the surface machining characteristic and AE sensor signal were compared and analyzed.