Wiangtong, Theerayod

Preferred name

Alternative Name

Wiangtong, T.

Main Affiliation

School of Engineering

theerayod.wi@kmitl.ac.th

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The Experiment of Partial Discharge testing for Low Voltage Motor
(2025-01-01)
Sawangsri, Jaturaphat
;
Wiangtong, Theerayod
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Pathanrat, Khomsan
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Ruangwong, Khomsan
;
Jeenmuang, Siwakorn
Low-voltage (LV) motors are widely used and highly popular in industrial settings due to their critical role in production processes. Any malfunction or failure of an LV motor can lead to production downtime, resulting in reduced output and potential revenue loss. Therefore, it is essential to conduct diagnostic assessments that evaluate the reliability of the insulation system in LV motors. Partial Discharge (PD) testing is recognized as a highly effective and reliable method for assessing the condition of motor insulation. This paper presents PD testing on LV motors to investigate the behavior of partial discharges using multiple analysis techniques. Additionally, an acoustic camera is integrated into the testing process to accurately identify the discharge locations.
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A heuristic approach for scheduling in heterogeneous distributed embedded systems
(2020-02-01)
Prongnuch, Sethakarn
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Sitjongsataporn, Suchada
;
Wiangtong, Theerayod
This paper presents a heuristic approach for workflow scheduling in heterogeneous distributed embedded system (HDES). A genetic algorithm (GA) and ant colony optimization (ACO) modified with the greedy algorithm introduced to the system contains multiple heterogeneous embedded machines (HEMs) working as a cluster. Users can remotely access and utilize their computational power. The communications on different types of buses are taken into account to find an optimal solution. New meta-heuristic information based on forwarding dependency is proposed to build probability for ACO to generate task priorities. Besides, a greedy algorithm for machine allocation is incorporated to complete task scheduling. Experiments based on random task graphs running in the HEM cluster demonstrate the effectiveness of the modified greedy ant colony optimization algorithm which outperforms the others by 33% more result quality.
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Stochastic behaviour analysis of adaptive averaging step-size sign normalised hammerstein spline adaptive filtering
(2021-01-01)
Wiangtong, Theerayod
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Prongnuch, Sethakarn
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Sitjongsataporn, Suchada
We introduce a sign algorithm based on the normalised least mean square with Hammerstein adaptive filtering using adaptive averaging step-size mechanism, which is derived by the minimised absolute a posteriori squared error. To improve the performance by reducing computational complexity, we suggest an adaptive averaging using energy of errors to update step-size variant. The analysis of convergence behaviour and mean square performance are derived. Experimental results reveal that the proposed algorithm can perform better than the least mean square approach based on the Hammerstein model of adaptive filtering.
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An Adaptive inverse Square-root Affine Projection Sign Algorithm based on QR-Decomposition
(2020-10-14)
Sitjongsataporn, Suchada
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Prongnuch, Sethakarn
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Wiangtong, Theerayod
In this paper, we present an adaptive averaging step-size inverse square-root affine projection sign algorithm. Based on the QR-decomposition method, we derive the modified inverse autocorrelation matrix in order to reduce the complexity of inverse matrix, which a criterion is based on the proposed algorithm with the sign error. Adaptive averaging step-size mechanism is used for the fast adaptation. Convergence analysis in form of a posteriori error is presented. Simulation results show that the proposed algorithm can obtain clearly the better performance compared with the conventional affine projection algorithm.
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Exploitation of IoTs for PMU in Tethered Drone
(2021-04-01)
Wiangtong, Theerayod
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Pookaiyaudom, Panavy
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Sirisuk, Phaophak
This paper presents the implementation of IoT (Internet of Things) for monitoring and control in the tethered drone PMU (Power Management Unit) system. Traditionally, power source of a drone is from battery which causes the tradeoff between weight and flight time. To overcome this limitation, stationary tethered drones consume energy from a ground energy source thru light weighted power cords. Tethered drones' benefits are ideally suited for military uses such as border security and surveillance system, where day-night surveillance capabilities are crucial to monitoring perimeters. It can also be used for tactical communication, fast-deployed relay stations. Since a long operation time, monitoring and control power onboard becomes necessary. Using extra cords for communication will increase the airborne weight. This paper presents the exploitation of wireless IoT system for the tethered drone PMU system. It consists of the PMU-ground constantly delivering 4000W power to PMU-air for BLDC motors also various payloads. With additional IoT including Raspberry Pi, NodeMCUs and sensors, users at ground station can monitor voltage and current values in real-time, also can control MOSFET switches connected with loads onboard via PMU touch screen monitor or smart devices.
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Simplified Set-Membership Affine Projection Least Mean Fourth Algorithm
(2022-01-01)
Sitjongsataporn, Suchada
;
Prongnuch, Sethakarn
;
Wiangtong, Theerayod
A simplified forms of adaptive set-membership affine projection based on least mean fourth algorithm is proposed. Least mean fourth (LMF) algorithm is defined by taking the fourth power of error to against the non-Gaussian environment. A set-membership adaptive filtering is described firstly. Then, an affine projection algorithm is based on LMF algorithm. A simplified set-membership affine projection algorithm based on LMF is introduced. Adaptive threshold parameter and learning rate are presented for improvement of convergence rate. Numerical simulations show that the proposed algorithm can provide significantly to the conventional affine projection algorithm.
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Diffusion Affine Projection Sign Algorithm based on QR-Decomposition
(2021-03-10)
Sitjongsataporn, Suchada
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Prongnuch, Sethakarn
;
Wiangtong, Theerayod
In this paper, an Adapt-Then-Combine diffusion strategy on affine projection sign algorithm is presented. Based on the QR-decomposition method, the modified inverse autocorrelation matrix is shortly brief to decrease the computational complexity. The Adapt-Then-Combine diffusion strategy is applied on the low complexity of sign algorithm version of inverse square-root affine projection algorithm including with the adaptation and combination steps. By applying an idea of diffusion adaptation algorithm, we derive a diffused version of an affine projection sign algorithm based on QR-Decomposition, denoted as DiQR-APSA. Experimental results show that the proposed DiQR-APSA can achieve the good performance in comparison with the standard affine projection sign algorithm.
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Effect of Rapping Frequency and Intensity in Electrostatic Precipitator Efficiency
(2023-01-01)
Banthoengjai, Thanpilin
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Wiangtong, Theerayod
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Pattanadech, Norasage
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Pannil, Pittaya
Electrostatic precipitator (ESP) is one of air pollution control equipment which widely use in biomass power plant. There is a rapping system in ESP use for removing ash from collecting plate (CP) and discharge electrode (DE). Rapping frequency and intensity of rappers effect the efficiency of ESP because they relate to dust quantity in ESP. Dust layer at CP, which has $108\ \Omega\mathrm{m}$ of resistivity, can cause back corona. Back corona can cause spark in dust layer. To prevent back corona, ESP should operate at lower voltage. Therefore, ESP efficiency is also lower. A chance of ash accumulation is depended on ion charged in dust particle. Rapping cause re-entrainment of dust particle which is uncharged. Re-entrainment dust particle increase uncharged dust in charging area. Therefore, charging process require more ion to charge more dust particle but generating more ion can cause spark over in ESP. There is the appropriate rapping frequency and intensity of rapping due to ESP condition. To study the effect of rapping system in ESP, the experiment was set in 9 cases. The rapping system in the experiment was set as different round trip time (RTT), which determine the rapping frequency, and lifting distance, which determine the intensity. There are 3 different RTT, 2, 3, and 4 minutes, and 3 lifting distance, 8, 10, and 12 inches. Total suspended particulate (TSP) was measured by EPA Method 5 and analyzed by Isokinetic and Gravimetric method to compare the efficiency of ESP in each case. Changing in rapping frequency and intensity of rapping system affect TSP. In case which lifting distance is 8 and 10 inches, TSP tend to decrease when rapping frequency was decreased, means higher efficiency of ESP. On the other hand, TSP tend to increase when rapping frequency was decreased in case of lifting distance is 12 inches. The lowest TSP was the case with 4 minutes RTT and 8 inches lifting distance. From the experiment, there is an appropriate value of rapping frequency and intensity of rapping system. Setting rapping system improve ESP efficiency.
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Adaptive Orthogonal Gradient Algorithm Based on Fair Cost Function
(2024-01-01)
Sitjongsataporn, Suchada
;
Wiangtong, Theerayod
This paper presents an adaptive orthogonal gradient algorithm with the unconstrained Fair cost function. An adaptive orthogonal gradient-based algorithm is investigated with the help of orthogonal projection mechanism to update the approximate tap-weight vector for the convergence enhancement. Fair cost function is preferable with a smooth points that is able to detect the statistical characteristics of error. Objective of this work is to present an adaptive orthogonal gradient algorithm using Fair cost function (OGA-Fair) to enhance the performance. Simulation results show that proposed adaptive OGA-Fair algorithm can perform with the fast convergence rate and robustness better than the existing method.
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Set-Membership Orthogonal Gradient Adaptive Algorithm on Least Mean Fourth Criterion
(2024-01-01)
Sitjongsataporn, Suchada
;
Wiangtong, Theerayod
;
Pookaiyaudom, Panavy
In this paper, we introduce a set-membership mechanism on the orthogonal gradient adaptive (OGA) algorithm based on least mean fourth (LMF) algorithm. In accordance with the fast convergence, the OG A-based scheme is conducted based on LMF algorithm that is described with the fourth power of the estimated error. The organisation of proposed algorithm composes with a brief of set-membership adaptive filtering and taking an advantage of OGA algorithm based on LMF algorithm. In order to make a smooth, an adaptive learning rate of algorithm and threshold value are furnished for convergence rate performance. There are some experimental simulations from proposed algorithm that show the mean square error trends can converge remarkably to the existing algorithm for system identification.

Wiangtong, Theerayod

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