Induction Heating Machine (IHM) is a crucial device in the jewelry industry, utilizing electromagnetic fields to generate heat and join precious metals. This research focuses on developing a Dual Coil Induction Heating Machine (Dual Coil IHM) to enhance production efficiency and reduce costs in jewelry factories using Electromagnetic Analysis (EMA) through Ansys Maxwell software. The research process began with testing a single-coil IHM under real operating conditions and using EMA to analyze the generated magnetic flux density (B). Subsequently, dual-coil configurations in Parallel and Series arrangements were designed and compared. The experimental results revealed that the series dual coil produced a higher magnetic flux and allowed for optimizing current (I), frequency (f), number of coil turns (N), and coil spacing (d) for better manufacturing performance. The findings indicate that the series dual-coil IHM can double production capacity compared to the conventional single-coil model. Furthermore, EMA technology minimizes physical testing, reduces errors, and enhances precision in designing industrial machinery for the jewelry manufacturing sector.
1.ข้อจำกัดของเครื่องทำความร้อนแบบเหนี่ยวนำขดลวดเดี่ยว 2.ความต้องการเพิ่มประสิทธิภาพการผลิตและลดต้นทุน 3.การประยุกต์ใช้เทคโนโลยีการจำลองทางแม่เหล็กไฟฟ้า (EMA) 4.แนวโน้มการเติบโตของอุตสาหกรรมเครื่องประดับในประเทศไทย 5.การพัฒนาองค์ความรู้ด้านเทคโนโลยีการผลิต
วิทยาลัยอุตสาหกรรมการบินนานาชาติ
The capture of a target spacecraft by a chaser is an on-orbit docking operation that requires an accurate, reliable, and robust object recognition algorithm. Vision-based guided spacecraft relative motion during close-proximity maneuvers has been consecutively applied using dynamic modeling as a spacecraft on-orbit service system. This research constructs a vision-based pose estimation model that performs image processing via a deep convolutional neural network. The pose estimation model was constructed by repurposing a modified pretrained GoogLeNet model with the available Unreal Engine 4 rendered dataset of the Soyuz spacecraft. In the implementation, the convolutional neural network learns from the data samples to create correlations between the images and the spacecraft’s six degrees-of-freedom parameters. The experiment has compared an exponential-based loss function and a weighted Euclidean-based loss function. Using the weighted Euclidean-based loss function, the implemented pose estimation model achieved moderately high performance with a position accuracy of 92.53 percent and an error of 1.2 m. The in-attitude prediction accuracy can reach 87.93 percent, and the errors in the three Euler angles do not exceed 7.6 degrees. This research can contribute to spacecraft detection and tracking problems. Although the finished vision-based model is specific to the environment of synthetic dataset, the model could be trained further to address actual docking operations in the future.
คณะสถาปัตยกรรม ศิลปะและการออกแบบ
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วิทยาลัยนวัตกรรมการผลิตขั้นสูง
Ultrasonic cleaning tank is a machine that many factories widely used to clean objects. At one factory, a problem occurred in the cleaning process, resulting in the factory not being able to clean objects, but cracks also appeared on some objects. It was anticipated that these were caused by uneven acoustics pressure distribution which resulted in unsuitable cavitation This directly affected cleaning performance within the tank. In order to improve the tank's efficacy, in this research, we use Harmonic Response Analysis in ANSYS simulate simulate the occurrence of acoustic pressure in the tank to find the appropriate conditions of factors affected the intensity and the distribution pattern of acoustic pressure in ultrasonic tank, including the position of object, power, ultrasonic frequency and a suitable type and placing position of the transducer for the tank. Reliability of the simulate results was validate by the actual result from the foil corrosion test and the ultrasonic power probe. We found that objects receive different pattern of corrosion at each location. When temperature increasing the intensity of cavitation was increased. When we increase the ultrasonic frequency, acoustic pressure that is evenly dispersed throughout the tank.