KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 10 of 31

Some of the metrics are blocked by your
consent settings
Two-Quadrant Current-Mode Logarithmic and Anti-logarithmic Amplifiers with Temperature Compensation
(2025-09-01)
Pukkalanun, Tattaya
;
Roongmuanpha, Natchanai
;
Tangsrirat, Worapong
;
Suesut, Taweepol
This paper proposes circuit topologies for realizing two-quadrant current-mode logarithmic and anti logarithmic amplifier configurations with temperature compensation. The design approach employs the translinear approach to generate the output currents that directly correspond to the absolute values of the logarithmic and anti logarithmic functions. The proposed circuits can operate at a low-level supply voltage of 2V with both input and output current signals. A detailed examination of the non-ideal circuit performance has also been considered. To validate their functionality and illustrate their superior thermal stability, the developed circuits have been simulated. All simulations were conducted via PSPICE for a real bipolar transistor model of the HFA3096 technology.
Some of the metrics are blocked by your
consent settings
Automatic Fish Classification Using Lanczos Resampling and Deep Learning
(2025-09-01)
Kuswantori, Ari
;
Suesut, Taweepol
;
Suthanupaphwut, Worapanya
;
Tangsrirat, Worapong
;
Nunak, Navaphattra
The development of automation in the fish industry, a vital sector of the food industry, is a highly relevant and essential topic. This development is essential for boosting output and mitigating the risk of future food shortages brought on by the world’s population expansion. Automatic fish classification using computer vision has been widely developed in fish industry automation, and a lot of research on that topic has been published. However, while some research has produced promising results using complex methods, others have applied simpler approaches with less satisfactory outcomes. This study suggests a straightforward but efficient technique for differentiating between fish species by concentrating on their main characteristics, such as body form and scale patterns. To effectively support these image capturing properties, the Lanczos re-sampling technique is used in this study. Additionally, our basic deep learning model can correctly learn and identify fish species thanks to a fish picture categorization engine created using Google Teachable Machine. Utilizing the Fish-Pak dataset, a popular fish picture dataset frequently used in studies on fish species classification, the suggested approach successfully overcomes the difficulty and attains a high accuracy rate of 97.16%.
Some of the metrics are blocked by your
consent settings
Monitoring of Food Fouling in A Plate Heat Exchanger Using Heat Flux Sensor
(2025-01-01)
Nunak, Navaphattra
;
Suthanupaphwut, Worapanya
;
Suesut, Taweepol
This article aims to describe the effect of fluid flow rate on soymilk fouling in a flat plate heat exchanger at a surface temperature of 95 °C using a foil heat flux sensor. The experiment was conducted in the pilot-scale fouling test rig for 6 hours each run. Five product flow rates of 1.5, 3.0, 4.5, 6.0, and 7.5 1/min were studied. The results showed that a heat flux sensor could be used to real-time monitor the changes of soymilk fouling deposits formed on the heated surface. Fouling curves of soymilk at flow rates of 3.0 and 4.5 1/min exhibited a falling rate pattern, while at flow rate of 1.5 showed an asymptotic pattern. It was found that the thickness of fouling decreased with increasing product flow rate in the range of 1.5 - 4.5 1/min. At higher flow rates, only a slightly thin film of fouling layer was observed.
Some of the metrics are blocked by your
consent settings
Optimal Design and Installation of Solar Rooftop for Thai government building
(2025-01-01)
Chaishome, Jedsada
;
Nunak, Navaphattra
;
Suesut, Taweepol
This research presents an approach for installing grid-connected solar cells on the rooftops of a prototype building in Thailand to offset electricity consumption, aligning with TOU electricity pricing. It includes design methods, energy-saving calculations, and illustrates the savings from solar cell installation over a one-year period, without accounting for solar cell deterioration or system loss charges. The study compares the concept of installing solar cells on the rooftop based on the building's electricity usage characteristics, distinguishing between installing solar cells across the entire rooftop area and according to the building's electricity usage behavior during daytime and working days, ensuring minimal electricity remains while still being sufficient for use. Furthermore, it calculates the comparison before and after installation to provide information for rooftop installation on the prototype building. The research results indicate that installing solar cells across the entire rooftop area can save electricity costs up to 550,000 THB per year.
Some of the metrics are blocked by your
consent settings
Estimating the Power Losses in Induction Motor using Temperature Monitoring
(2025-01-01)
Suesut, Taweepol
;
Nunak, Teerawat
;
Nunak, Navaphattra
;
Chaishome, Jedsada
The paper proposes the estimation of power losses in electrical machines using a measurement technique based on the temperature of the electrical machine and the heat transfer equation. To demonstrate this concept, the heat diffusivity of the induction motor can be illustrated through thermal images. This research addresses the impact of supply voltage unbalance on power loss in induction motors. The system comprises A contact temperature measuring circuit utilizing the IC LM 35DZ as a temperature sensor and signal converter, paired with a computer equipped with a National Instruments PCI 6014 data acquisition card. The experiment was conducted by adjusting the phase unbalance to 10%, 20%, and 50% to observe temperature changes. This allows for a direct temperature in the induction motor. The primary advantage of this method is that the machines do not need to stop or be removed from their operational process to measure their losses during preliminary maintenance.
Some of the metrics are blocked by your
consent settings
Simple and Effective Techniques for Automatic Fish Species Classification Using Image Processing and Deep Learning
(2025-01-01)
Kuswantori, Ari
;
Nunak, Navaphattra
;
Suthanupaphwut, Worapanya
;
Schleining, Gerhard
;
Tangsrirat, Worapong
The advancement of automation in the fish industry, a critical segment of the food sector, has become increasingly relevant in light of the growing global population and the impacts of climate change and global warming. Enhancing productivity through automation is essential to mitigate the looming threat of food scarcity. In this context, automatic fish classification using computer vision has garnered significant attention, with various studies exploring both complex and simple approaches. While complex methods have shown promising results, simpler approaches often fall short in performance. This study proposes a simple yet effective method that highlights key distinguishing features of fish—namely, body shape and scale patterns—for species classification. The Lanczos resampling technique is employed to crop, resize, and focus on the features, enabling a lightweight deep learning model to effectively learn and classify fish species. With the right conceptual framework, appropriate feature extraction techniques, and an efficient deep learning architecture, the proposed method addresses the classification challenge in a straightforward yet effective manner. Experimental evaluations using the Fish-Pak dataset, comprising six aquaculture fish species, and the KMITL Fish dataset, containing eight species, demonstrate the effectiveness of the method, achieving accuracy rates of 97.16% and 98.59%, respectively.
Some of the metrics are blocked by your
consent settings
Inspection of Heat Seal Packing Bag Integrity Using Thermal Images With YOLO Algorithm
(2025-01-01)
Chaishome, Jedsada
;
Khannakum, Wirat
;
Nunak, Navaphattra
;
Suesut, Taweepol
This paper presents an inspection of heat seal packing bag integrity using thermal imaging with a deep learning technique. The performance was evaluated by comparing the object detection rates obtained from the YOLOv4-Tiny Algorithm and the Convolutional Neural Network (CNN) technique. Two sets of completely sealed and failure-sealed packaging bags were prepared for the training (100 bags) and testing (100 bags) of the models. Some sample bags containing tomato sauce inserted between the seals represent a failure-sealed condition. The integrity of the heat seal packaging bag was analyzed by examining the differences in color shade patterns of the thermal images. As a result, the YOLOv4-Tiny model achieved a detection accuracy of 98.80%, significantly outperforming the CNN technique, which detected only 78.40%, while using the same dataset; additionally, the time required for detection and training was faster.
Some of the metrics are blocked by your
consent settings
A Fast and Simple Machine Vision Framework for Approximating the Volume of Axi-Symmetric Objects Using Shadow Ray Casting
(2024-01-01)
Sukprasertchai, Siwakorn
;
Suesut, Taweepol
;
Nunak, Navaphattra
The volume measurement using machine vision system is contactless techniques that play an important role in industries now a day. Basically, three-dimensional reconstruction is required to determine a depth using a special lighting system or multiple cameras. This increases the complexity of the measurement system. A fast and simple machine vision framework called RayVol for estimating the volume of axisymmetric objects in near real-time using a single camera and simple illumination is presented. The RayVol framework employs a shadow casting method to reconstruct the 3D shape of the object by tracing rays from the object’s shadow pixels to the light source location. The result of this technique shows a significant accuracy improvement from the area-projection method. A virtual slice representing the cross-section of an object is reconstructed using a cubic spline approximation from baseline points derived from the boundary pixels of the object image and a shadow casting method. The volume estimation was calculated by restricted integration using the Riemann sum estimation algorithm, and the closed area of the virtual slices was calculated using the shoestring algorithm. Mangoes were used as a case study of the RayVol framework. The volume estimation provides the correlation coefficient of 0.9849 between the developed system and the water replacement method.
Some of the metrics are blocked by your
consent settings
Effects of heat transfer surface temperature on liquid egg yolk fouling
(2024-01-01)
Sritham, Eakasit
;
Nunak, Navaphattra
;
Suthanupaphwut, Worapanya
;
Somlitsopak, Badin
;
Chaishome, Jedsada
This study was aimed at investigating the effects of different surface temperatures (60-80°C) on the formation of egg yolk deposits on heat transfer surface. Experimental data from the fouling period were fitted with zero- and first-order reaction models and the reaction kinetics of fouling was obtained using the Arrhenius equation. Egg yolk fouling curves exhibited an asymptotic pattern showing only fouling and post-fouling periods. The fouling resistance at transition point increased with the increasing surface temperature. The zero-order reaction model was well describing the reaction rate of egg yolk fouling. The obtained activation energy of 85.47 kJ/mol was less than that for thermal denaturation of egg yolk proteins. The fouling process of egg yolk was mainly controlled by the deposition reaction.
Some of the metrics are blocked by your
consent settings
The Influence of Measuring Location on Volume Estimation by Shadow Casting Method
(2024-01-01)
Suesut, Taweepol
;
Sukprasertchai, Siwakorn
Non-contact inspection has dominated various industries for many years, particularly in the field of food and agricultural processes. Volume estimation can be achieved by volumetric imagery or 3D reconstruction. The casting of shadows or shape by shading is an active technique that can be utilized to generate volumetric imagery. By evaluating the length of shadows, the object height data can be achieved, and the transformation of image coordinates to world coordinates is facilitated by means of homography transformation. The width, length, and height of object edges along the entirety of its length are employed to reconstruct virtual slices. The integration of these virtual slices enables the estimation of the object's volume. This research studied the variation of the measuring locations, three different diameters spherical balls 38mm, 50mm, and 80mm are used as test materials. The percentage of errors in volume obtained from all sections by shadow casting were compared to computation volume of sphere formula is approximately -1.6 %, -1.13 %, and - 6.60%, respectively, depending on the size of the object. Furthermore, a visualization-based analysis is presented which has no significant difference. From this studied, it can be concluded that this method is valuable in estimating the volume of axially symmetrical objects.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results