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Performance of Hammerstein Spline Adaptive Filtering Based on Fair Cost Function for Denoising Electrocardiogram Signals
(2025-12-01)
Sitjongsataporn, Suchada
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Wiangtong, Theerayod
This paper proposes a simplified adaptive filtering approach using a Hammerstein function and the spline interpolation based on a Fair cost function for denoising electrocardiogram (ECG) signals. The use of linear filters in real-world applications has many limitations. Adaptive nonlinear filtering is a key development in tackling the challenge of discovering the specific characteristics of biomimetic systems for each person in order to eliminate unwanted signals. A biomimetic system refers to a system that mimics certain biological processes or characteristics of the human body, in this case, the individual features of a person’s cardiac signals (ECG). Here, the adaptive nonlinear filter is designed to cope with ECG variations and remove unwanted noise more effectively. The objective of this paper is to explore an individual biomedical filter based on adaptive nonlinear filtering for denoising the corrupted ECG signal. The Hammerstein spline adaptive filter (HSAF) architecture consists of two structural blocks: a nonlinear block connected to a linear one. In order to make a smooth convergence, the Fair cost function is introduced for convergence enhancement. The affine projection algorithm (APA) based on the Fair cost function is used to denoise the contaminated ECG signals, and also provides fast convergence. The MIT-BIH 12-lead database is used as the source of ECG biomedical signals contaminated by random noises modelled by Cauchy distribution. Experimental results show that the estimation error of the proposed HSAF–APA–Fair algorithm, based on the Fair cost function, can be reduced when compared with the conventional least mean square-based algorithm for denoising ECG signals.
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A Low-cost Autonomous Lawn Mower with AI-Based Obstacle Avoidance and GPS Guidance System
(2025-07-01)
Kosri, Thanapon
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Seekhamharn, Tossawat
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Phoonsrichaiyasit, Phasawut
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Khungpo, Poowadon
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Sirisuk, Phaophak
This paper presents a cost-effective robotic system capable of manual control via RF remote and autonomous navigation using GPS-based information. The system employs artificial intelligence to dynamically classify and avoid non-grass obstacles, ensuring safe operation in real environments. The prototype integrates affordable hardware including Arduino board, sensors, actuators and Raspberry Pi with lightweight algorithms to balance performance and cost. Experimental validation confirms its ability to follow predefined paths with ±1.5 meters deviation in open area and 90% obstacle avoidance success rate. With a total hardware cost under $200, this prototype highlights feasibility for larger-scale implementation.
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Multitask Diffusion Adaptive Tuning Affine Projection Algorithm for Distributed Model
(2025-01-01)
Sitjongsataporn, Suchada
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Wiangtong, Theerayod
This paper presents combine-then-adapt diffusion model on affine projection adaptive algorithm with adaptive tuning mechanism. An adaptive affine projection algorithm is suggested in the distributed network. Diffusion strategy involves with the combination stage and adaptation stage. By adding the extra-stage in the combination stage, the combination between nodes and inside nodes are built with the global cost function for multitask model to eliminate unknown data. As dealt with fast convergence, the adaptive tuning parameters are assigned in terms of step-size value. Experimental results reveal that this proposed algorithm is able to contribute the approving results for system identifications.
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Implementation of Bang-Bang Charge Control for an LLC Resonant Converter for Battery Charger
(2025-01-01)
Potjanatkomol, Natkamol
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Polmai, Sompob
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Wiangtong, Theerayod
This paper presents the design of a 2-kW full-bridge LLC resonant converter for battery charger operating in a range of DC input voltages of 380-420 V and output voltage of 60 V. The bang-bang charge control technique, whose controller adjusts the threshold voltage of the bang-bang comparators, is adopted for controlling the converter switching frequency. This control method provides fast single-pole control-to-output transfer function resulting in simplicity of controller design. In this paper the design procedure of LLC converter resonant circuit is presented and a prototype is built. The discrete-time PI compensator for constant voltage (CV) and constant current (CC) control is implemented using STM32 microcontroller. The simulation and experimental results show satisfactory control characteristics.
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The Experiment of Partial Discharge testing for Low Voltage Motor
(2025-01-01)
Sawangsri, Jaturaphat
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Wiangtong, Theerayod
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Pathanrat, Khomsan
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Ruangwong, Khomsan
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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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Performance analysis of cascade spline adaptive filtering based on normalized orthogonal gradient adaptive algorithm
(2024-12-01)
Wiangtong, Theerayod
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Sitjongsataporn, Suchada
In this paper, the cascade architecture of spline adaptive filtering (CSAF) for nonlinear systems is presented with the normalized version of orthogonal gradient adaptive (NOGA) algorithm. Spline adaptive filtering comprises a sandwich of the first linear adaptive filtering (LAF) and nonlinear adaptive look-up table. In this cascading architecture, SAF is connected to the second LAF. NOGA is considered as the fast convergence applied by stochastic gradient-based approach. Convergence properties of the proposed NOGA-CSAF algorithm in terms of instantaneous errors can be derived by using Taylor series expansion. Experimental results demonstrate the effectiveness of proposed NOGA-CSAF algorithm using the mean square error scheme. It clearly outperforms the traditional least mean square algorithm on CSAF model in the nonlinear identification system.
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Adaptive Orthogonal Gradient Algorithm Based on Fair Cost Function
(2024-01-01)
Sitjongsataporn, Suchada
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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
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Wiangtong, Theerayod
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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.
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Dielectric Response Analysis Characteristic of Service-Aged XLPE Cables
(2024-01-01)
Thongkong, Patchara
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Promphanich, Wiboon
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Udomluksananon, Patt
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Jeenmuang, Siwakorn
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Wiangtong, Theerayod
The main insulation used in plastic underground cables is cross-linked polyethylene (XLPE). The XLPE underground cable which has been utilized in service for a long time, has experienced various stresses, or so-called TEAM stresses. Consequently, the XLPE insulation will be degraded over time and lead to insulation properties degradation. This paper represents the dielectric response analysis technique for characterizing the insulation condition of the service-aged XLPE medium voltage underground cable. The dielectric response analysis was performed on the 22 kV XLPE underground cables that have been in service for more than 10 years and were directly buried. The dielectric response analysis measurement consists of a combination of polarization and depolarization current (PDC) measurement in the time-domain and frequency-domain spectroscopy (FDS) measurement. After that, test results were analyzed to evaluate the insulation condition and compare it to the new 22 kV underground cable. The analyzed dielectric response analysis test results will be reported in this paper.
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Diffusion recursive least squares algorithm based on triangular decomposition
(2023-10-01)
Prongnuch, Sethakarn
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Sitjongsataporn, Suchada
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Wiangtong, Theerayod
In this paper, diffusion strategies used by QR-decomposition based on recursive least squares algorithm (DQR-RLS) and the sign version of DQR-RLS algorithm (DQR-sRLS) are introduced for distributed networks. In terms of the QR-decomposition method and Cholesky factorization, a modified Kalman vector is given adaptively with the help of unitary rotation that can decrease the complexity from inverse autocorrelation matrix to vector. According to the diffusion strategies, combine-then-adapt (CTA) and adapt-then-combine (ATC) based on DQR-RLS and DQR-sRLS algorithms are proposed with the combination and adaptation steps. To minimize the cost function, diffused versions of CTA-DQR-RLS, ATC-DQR-RLS, CTA-DQR-sRLS and ATC-DiQR-sRLS algorithms are compared. Simulation results depict that the proposed DQR-RLS-based and DQR-sRLS-based algorithms can clearly achieve the better performance than the standard combine-then-adapt-diffusion RLS (CTA-DRLS) and ATC-DRLS mechanisms.

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