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Author: search.filters.author.Khummongkol, RojaneeHas files: No

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    2D-CNN Based Classification on Water Leakage Identification in Automatic Pump
    (2026-01-01)
    Satthamsakul, Sutham
    ;
    Rattanakun, Kritsana
    ;
    Khummongkol, Rojanee
    ;
    Tangsrirat, Worapong
    This study proposes an approach for classification of unusual in automatic water pump systems, especially on a water leakage, one of the key issues that can significantly affect system efficiency and cause serious damage. The method utilizes motor current signals, which are transformed into 2D spectrograms using the Short-Time Fourier Transform (STFT). These spectrograms are then classified by a 2D Convolutional Neural Network (2D-CNN) Designed to determine between usual and unusual operating conditions with high accuracy. Experimental results indicate that the model can effectively detect unusual and leakage events when trained with appropriate parameters, such as a learning rate of 0.001 and 60 training epochs. This model serves as an efficient tool for preventing system failures and reducing maintenance costs in automatic water pump systems.
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    Contamination Measurement Techniques in Hydraulic Fluid Based on Hall Effect Sensor
    (2024-01-01)
    Satthamsakul, Sutham
    ;
    Khummongkol, Rojanee
    This paper proposed two methods to examine metal particles in fluid using Hall Effect Sensor under the condition of nondestructive testing based on two conditions: test of particles in oil samples, and test of particles in industrial machinery simulation. Hall Effect Sensor was a low-cost device had ability to detect magnetic fields in objects, so this work applied Hall Probe to measure the density of metal in liquid. Hereby, hydraulic liquid was selected to examine because it was one of the most use in industrial machines. By using the sensor, two types of experiment were designed: test of oil sample, and test of simulation process, where the results showed that Hall Effect Sensor had ability to measure particles in both two types of experiment. For oil sample test, the sensor was able to detect metallic powder when the number of contaminants were greater than or equal to 10 milligrams (equivalented to NAS 15 standard). On the other hand, to measure particle in simulation process, magnetic field were generated in two ways, i.e. use of electromagnet, and use of permanent magnet. For using electromagnet as magnetic field source, the result showed that temperature had an influence on metal particle evaluation. Therefore, to get the most accurate value, system's temperature had to employed in calculation process. While, the result of using permanent magnet to generate magnetic field showed that the relationship between output voltage and amount of metal particles were probably in linear form. To apply this method in industrial applications could be an inexpensive way to help officer in detecting metal particle in oil which was able to extend service time of hydraulic liquid properly.