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Implementation of International Safety Standard EN ISO 13849 into Machinery of Tyre Industry
(2017-01-01)
Wongpiriyayothar, N.
;
Chitwong, S.
This paper presents application of international safety standard in risk assessment and risk reduction following by machinery directive. Many industries using machinery for manufacturing products have tendency to take risk from poor-quality of machinery design which may not be produced according to international safety standard. This can lead dangerous situation to machine user. The new standard EN ISO 13849-1 [1] which replaced the old standard EN 954-1 [2] definitely in December 2011 made machine designer not be familiar with the new concept and feel confused due to most of concerned parameters shown in term of statistic value that there are difficulty in interpretation and understanding. In the present, there is still lack of examples of implementation this standard into machinery of specific industry, especially in tyre industry. Therefore the objective of this paper is made for implementation this safety standard into machinery of tyre industry in order to build a safe situation for machine user.
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SIL Verification of Safety Instrumented System for Block Valve System in Gas Pipeline by Using Markov Model Methodology
(2017-01-01)
Kongtong, P.
;
Chitwong, S.
This paper presents about methods for evaluation of safety integrity level (SIL) which is significant to reduce risk of failure of block valve in gas pipeline system by using Markov Model method which refer to International standard IEC 61508/61511. The reason of using Markov Model method is that it takes less time and more flexible than other methods to determine SIL. This method uses a qualitative approach showing Average Probability of Failure (PFDavg) rate data and repairing time from model to implement in further process.
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Implementation of self-tuning fuzzy PI controller on DCS for flow control system
(2015-01-01)
Assawathanatorn, K.
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Anuntahirunrat, K.
;
Chitwong, S.
In case of changing a communication between field instruments and controller from analog signal into digital signal or of changing a model of plant, performance of controller is degraded because of the fixed controller parameters such as PID controller. To solve this problem, a self-tuning PID controller is proposed. One of a popular self-tuning method is self-tuning fuzzy. Many researchers have been presented the self-tuning fuzzy PID controller. In this paper, we present implementing of self-tuning fuzzy PI controller for flow control system. Both fuzzy and PI controller is implemented on distributed control system (DCS) as controller at which communication between field instruments and distributed control system is via both the analog input and output modules as analog signal in range of 4-20mA and digital signal as Profibus PA. The PI controller parameters, proportional gain and integral time, from auto-tuning method is used to control plant, flow control system, by using analog signal at which result shows that flow process variable reaches to flow set point. The same PI controller parameters is applied for PROFIBUS PA at which results shows that flow process variable oscillates because of effect of delay-time taken place from communication between field instruments and distributed control system.
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Developing harmonic power analyzer based on IEEE 1459-2010 Standard
(2012-01-01)
Wattanayingcharoen, P.
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Detchrat, A.
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Chitwong, S.
This paper describes the developing harmonic power analyzer based on IEEE 1459-2010. This instrument use the power definitions present in IEEE standard, the instrument use ARM Cortex-M3 high performance 32bits microcontroller to calculate electric power from isolated current and voltage transducers, and compare the experimental results with commercial instrument.
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Contrast enhancement for mimimum mean brightness error from histogram partitioning
(2009-12-01)
Phanthuna, N.
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Cheevasuvit, F.
;
Chitwong, S.
This paper presents the image enhancing using a mean separated histogram equalization method. To provide the minimum mean brightness error after the histogram modification. It separates the input image's histogram into n (n=1,2,3,⋯) groups based on input mean before equalizing them independently. The image initially is separated class by calculated threshold level and each class is histogram equalized to entire image, and gets lowest AMBE (AMBE: Absolute Mean Brightness Error). The result found that AMBE gradually reduces when the separation is increased. Therefore, the error threshold is assigned in order to automatically dividing the original histogram for obtaining the desired AMBE. This process will be applied to remote sensing data by treating each region of histogram independently. Also Tenengrad is employed in order to verify the contrast performance. The image performance is considered higher if its Tenengrad value is larger.
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A fast intensity-hue-saturation fusion approach via principal component analysis for ikonos imagery
(2008-12-01)
Minhayenud, S.
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Chitwong, S.
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Cheevasuvit, F.
To enhance spatial information of low resolution multi-spectral (RGB) image, the intensity-hue-saturation (IHS) approach is perfectly used to fuse the low resolution RGB image and the high resolution panchromatic (Pan) image by replacing intensity component with the high-resolution Pan image. Disadvantage of the mentioned approach is that color of a fused image is changed because the saturation component is changed or spectral of the low resolution RGB image and the high resolution Pan image is different, that is, spectral information of the fused RGB image is distorted. This problem is important for applying the fused image for classification. To solve this problem, in this paper, we employ the principal component analysis (PCA) transformation to extract information from the low resolution RGB image. In procedure of fusion method, the first principal component is used to adjust brightness of the high resolution Pan image. The intensity component from IHS transformation is replaced by the adjusted brightness high-resolution Pan image. The experimental results by using IKONOS imagery show that the proposed approach is better performance than the original IHS methods by improving spectral distortion and still correlating to the Pan image.
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Contrast enhancement of satellite image based on adaptive unsharp masking using wavelet transform
(2006-12-01)
Chitwong, S.
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Phahonyothing, S.
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Nilas, P.
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Cheevasuvit, F.
This paper concerns with a method for unsharp masking for contrast enhancement of satellite image. We employ the nature of wavelet transform that separates the original image into low and high frequency sub-band images as low and high pass filter. Particularly, a number of high frequency sub-band images consist of horizontal, vertical, and diagonal coefficients that contain detail of information. Taking inverse wavelet transform of each sub-band image separately except low frequency one, we have each of high frequency information in horizontal, vertical, and diagonal image. All of them are scaled by the scaling factor in each one separately. Adaptive algorithm is implemented to results the suitable scaling factor to obtain the enhanced image corresponding with the given criterion based on variance of each area smooth and detail area. Experimental results show that our method performs well to high enhance in detail area and low in smooth area.
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Tracking notch filter for electrocardiograph measurement
(2006-01-01)
Witthayapradit, S.
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Chitwong, S.
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Tumthong, S.
This paper presents a tracking notch filter with opened-loop architecture for elimination of electric field frequency which can also interfere into ECG waveform. For measuring ECG waveform having the isolated instrumentation amplifier, at here, the quality factor (Q) of this filter is assigned about 8 and the attenuation of frequency noise is around of-35 dB and the gain of amplifier is of 1000. The frequency from frequency noise detector is multiplied by the frequency synthesizer. The clock signal from the frequency synthesizer is used for the switched capacitor network The performance of the proposed filter is tested with ECG waveform included frequency noise of 50Hz , 55Hz and 60Hz and also with measuring in Lead I of bipolar lead included noise signal of 50Hz for both cases, that is, before and after through the notch filter circuit in the time and frequency domain. The measured results have been successfully tested. In this paper, the discrete and passive devices are used for the designed circuit.
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Speckle noise reduction using adaptive singular value decomposition in logarithmic domain
(2005-12-01)
Chitwong, S.
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Thongsila, A.
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Intajag, S.
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Nilas, P.
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Cheevasuvit, F.
This paper presents applying the singular value decomposition to reduce speckle noise. Generally, it is used to filter the additive Gaussian noise with zero mean and any variance. Since speckle noise is in multiplicative model, to transform multiplicative model into additive model, we then employ logarithmic transformation. In this paper, speckle noise is generally modeled as Gamma distribution function corresponding with speckle noise of synthetic aperture radar (SAR) imagery applied. All singular value decomposition based filtering processing is in logarithmic domain. Threshold value to determine the effective rank and orders of matrix are adapted as homogeneity analysis. The orders of matrix are consisted of 16 by 16, 8 by 8 and 4 by 4. Normally, the results of the singular value decomposition based filtering after that the filtered matrix is transformed into spatial domain by exponential function is in block-fashion, then blocking effect is occurred. To smooth, the filtered matrix is performed as average filtering by using a number of pixels of 4 by 4 pixels around center of one. Experiments are tested using both simulated image and real image. Signal to noise ratio and equivalent number of looks are employed to evaluate the performance of our method. Our results are good enough when compared with the recent results at which such method is more complex. © 2005 by the American Society for Photogrammetry and Remote Sensing.
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Local area histogram equalization based multispectral image enhancement from clustering using competitive hopfield neural network
(2003-10-01)
Chitwong, S.
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Boonmee, T.
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Cheevasuvit, F.
One of important issues for enhancing image based on local area histogram equalization (LHE) is a clustering or segmenting technique. That is, the more the accuracy of separating image into specified classes is needed, the better the performance of enhancement is. As mentioned objective, in this paper, the competitive Hopfield neural network (CHNN) is then proposed for clustering to the LHE based image enhancement. By using simulated image, standard image and mutispectral image from Landsat 7 satellite, experimental results are shown in both accuracy of clustering and variance of the enhanced image. The criteria for a good enhancement algorithm is that it can give high variance in detail area, low variance in smooth and edge areas. Also comparing the variance of the enhanced image by both LHE and global area histogram equalization (GHE) methods shows that one from LHE outperforms. In addition, the enlarged image from small area is shown clearly by visualization. All results compare with the conventional methods such as fuzzy c-means (FCM).

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