This study introduces a deep learning engine designed for the non-destructive automatic detection of defects within weld beads. A 1D waveform ultrasound signal was collected using an A-scan pulser receiver to gather defect signals from inside the weld bead. We established 5,108 training datasets and 500 test datasets for five pass/fail labels in this study. We developed a multi-branch deep fusion network (MBDFN) model that independently trains 1D-CNN for local pattern learning within a sequence and 2D-CNN for spatial feature extraction and then combines them in an ensemble method, achieving a classification accuracy of 92.2%. The resulting deep learning engine has potential applications in automatic welding robots or welding inspection systems, allowing for rapid determination of internal defects without compromising the integrity of the finished product.

We propose an advanced quadrature sampling method for a fiber grating sensor interrogation. A Mach-Zehnder interferometer output is sampled at internal triggers which are generated at the zero-crossing points of a double-pass Mach-Zehnder interferometer output. Due to the phase relationship, the internal trigger signals assure a 90^deg phase difference between the sampled signals even in the presence of environmental disturbances. Also, no parameter adjustment is required when the frequency and/or shape of the phase modulation signal changes, which makes it a very practical technique for fiber grating sensor demodulation. From the preliminary experiments, we could obtain a measurement resolution of ~8 pm.

우주기술과 응용(Journal of Space Technology and Applications; J. Space Technol. Appl. 이하 JSTA )은 한국의 우주과학 및 우주 응용 분야에서 가장 권위 있는 학술단체인 한국우주과학회에서 Journal of Astronomy and Space Sciences 와 더불어 발행되고 있는 공식적인 정기 간행물이다. JSTA 는 2021년 5월 창간호를 시작으로 연 4회 분기별로 발간되고 있으며, JSTA 의 논문과 기고문 은 한국어 또는 영어로 게재 가능하며, 각 논문과 기고문에는 고유의 DOI가 부여된다. JSTA 에 게재 되는 모든 논문과 기고문은 Open Access 정책에 따라 JSTA 홈페이지(https://www.jstna.org)를 통해 누구나 전문을 무료로 열람할 수 있다.

In this paper, we present a sensing device with the optical temperature sensors-based quad receiver (Quad-RX) module and a security module. In addition, in order to prevent cyberattacks on critical national infrastructures and key facilities, we implemented symmetric-key and secure hash algorithm-based hardware security modules in the key elements of the sensing device. A preliminary test was conducted prior to a field trial to verify the performance of the developed sensing device. The accuracy and stability of the sensing device were then verified for 1 month in a field test at facilities for energy storage systems and photovoltaic converters in sewage treatment plants.

This study proposes a liquid-crystal-based active wavelength filter for phase-sensitive optical time domain reflectometry to mitigate the amplified spontaneous emission (ASE) noise and accurately match the passband with the light source. The validity of the proposed system was verified using comparative experiments with conventional passive optical filters. The experiment showed an increase in signal-to-noise ratio (SNR) of up to 2.21 dB compared with passive filters. Additionally, the proposed system can effectively eliminate ASE noise, resulting in an SNR of 12.99 dB.

This study presents a beam divergence optimization strategy to minimize rain-induced signal attenuation in free-space optical communication (FSOC) systems. FSOC technology holds considerable potential for providing high-data-transmission speeds and reliability in the communication era beyond 5G and 6G. However, it is highly vulnerable to extreme atmospheric conditions, such as rainfalls. The impact of beam divergence adjustment on FSOC system performance at varying rainfall rates was experimentally analyzed at a transmission distance of 100 m. Additionally, communication performance was evaluated based on simulations at various beam divergence angles and transmission distance scenarios. Furthermore, an adaptive beam divergence control algorithm based on reinforcement learning is proposed to enhance link stability by optimizing beam divergence in response to real-time weather changes. The experimental results and simulation analyses highlight the need for a balance between the optimization of the beam divergence angle to the mitigation of signal attenuation, ensuring the performance of the pointing, acquisition, and tracking system. The findings provide valuable insights for enabling stable communication under extreme weather conditions and contribute to the durability and scalability of next-generation wireless communication networks.