• Journal of Ocean Engineering and Technology
• /
• v.35 no.4
• /
• pp.266-272
• /
• 2021

Mooring systems are among the most important elements employed to control the motion of floating offshore structures on the sea. Considering the use of polymer material, a new method is proposed to address the creep characteristics rather than the method of using a tension load cell for measuring the tension of the mooring line. This study uses a synthetic mooring rope made from a polymer material, which usually consists of three parts: center, eye, and splice, and which makes a joint for two successive ropes. We integrate the optical sensor into the synthetic mooring ropes to measure the rope tension. The different structure of the mooring line in the longitudinal direction can be used to measure the loads with the entire mooring configuration in series, which can be defined as SMART (Smart Mooring and Riser Truncation) mooring. To determine the characteristics of the basic SMART mooring, a SMART mooring with a diameter of 3 mm made of three different polymer materials is observed to change the wavelength that responds as the length changes. By performing the longitudinal tension experiment using three different SMART moorings, it was confirmed that there were linear wavelength changes in the response characteristics of the 3-mm-diameter SMART moorings. A 54-mm-diameter SMART mooring is produced to measure the response of longitudinal tension on the center, eye, and splice of the mooring, and a longitudinal tension of 100 t in step-by-step applied for the Maintained Test and Fatigue Cycle Test is conducted. By performing a longitudinal tension experiment, wavelength changes were detected in the center, eye, and splice position of the SMART moorings. The results obtained from each part of the installed sensors indicated a different strain measurement depending on the position of the SMART moorings. The variation of the strain measurement with the position was more than twice the result of the difference measurement, while the applied external load increased step-by-step. It appears that there is a correlation with an externally generated longitudinal tensional force depending on the cross-sectional area of each part of the SMART mooring.

• Journal of Advanced Navigation Technology
• /
• v.26 no.2
• /
• pp.78-84
• /
• 2022

In this paper, we propose a closed-form based 3D localization method in the presence of multiple signal sources. General localization methods such as TDOA, AOA, and FDOA can estimate a location when a single signal source exists. When there are multiple unknown signal sources, there is a limit in estimating the location. The proposed method calculates a cross-correlation vector of signals received by sensors having an array antenna, and estimates TDOA and AOA values from the cross-correlation values. Then, the coordinate transformation is performed using the position of the reference sensor. Then, the coordinate rotation is performed using the estimated AOA value for the transformed coordinates, and then the three-dimensional position of each emitter is estimated. The proposed method verifies its performance through computer simulation.

• Journal of Platform Technology
• /
• v.9 no.4
• /
• pp.79-89
• /
• 2021

In this paper, the fine dust (PM10) and ultrafine dust (PM2.5) measurement platforms are designed to be mobile and fixed using oneM2M, the international standard for IoT. The fine dust measurement platform is composed and designed with a fine dust measurement device, agent, oneM2M platform, oneM2M IPE, and monitoring system. The main difference between mobile and fixed is that the mobile uses the MQTT protocol for interconnection between devices and services without blind spots based on LTE connection, and the fixed uses the LoRaWAN protocol with low power and wide communication range. Not only fine dust, but also temperature, humidity, atmospheric pressure, volatile organic compounds (VOC), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and noise data related to daily life were collected. The collected sensor values were managed using the common API provided by oneM2M through the agent and oneM2M IPE, and it was designed into four resource types: AE and container. Six functions of operability, flexibility, convenience, safety, reusability, and scalability were analyzed through the fine dust measurement platform design.

• Nuclear Engineering and Technology
• /
• v.54 no.7
• /
• pp.2614-2624
• /
• 2022

Monte Carlo simulations were used to model a portable Neutron backscattering (NBT) sensor suitable for detecting plastic anti-personnel mines (APMs) buried in dry and moist soils. The model consists of a 100 MBq ²⁵²Cf source encapsulated in a neutron reflector/shield assembly and centered between two ³He detectors. Multi-parameter optimization was performed to investigate the efficiency of Be/Zr(BH₄)₄ and Be/Be(BH₄)₂ assemblies in terms of increasing the signal-to-background (S/B) ratio and reducing the total dose equivalent rate. The MCNP results showed that 2 cm Be/3 cm Zr(BH₄)₄ and 2 cm Be/3 cm Be(BH₄)₂ are the optimal configurations. However, due to portability requirements and abundance of Be, the ²⁵²Cf-2 cm Be/3 cm Be(BH₄)₂ NBT model was selected to scan the center of APM buried 3 cm deep in dry and moist soils. The selected NBT model has positively identified the APM with a S/B ratio of 886 for dry soils of 1 wt% hydrogen content and with S/B ratios of 615, 398, 86, and 12 for the moist soils containing 4, 6, 10, and 14 wt% hydrogen, respectively. The total dose equivalent rate reached 0.0031 mSv/h, suggesting a work load of 8 h/day for 806 days within the permissible annual dose limit of 20 mSv.

• The Journal of the Acoustical Society of Korea
• /
• v.41 no.4
• /
• pp.419-425
• /
• 2022

This paper aims to evaluate the acoustic detection performance for the deployment of the source and receiver positions of a bi-static sonar. In contrast with a mono-static sonar, a bi-static sonar has a large amount of computation and complexity for deployment. Therefore, in this study, we propose an assessment method that reduces the amount of computation while considering the variability of the ocean environment as a method to apply to the placement of the source and receiver of a bi-static sonar. First, we assume the representative ocean environment in the shallow and deep water. The signal excess is calculated with the source to receiver ranges and sensor depths. And the result is compared with the proposed assessment method of acoustic detection performance.

• Journal of Sensor Science and Technology
• /
• v.31 no.1
• /
• pp.51-56
• /
• 2022

In this study an efficient method for detecting and monitoring engine misfiring, focusing on minute speed changes in the crankshaft is proposed., Its validity is verified using various misfiring cases. Typically, the crankshaft speed fluctuates around the normal value depending on the engine misfiring status. Even a minute speed change in the crankshaft can be estimated by measuring the rotation time of each tooth of the 118-tooth flywheel attached to the crankshaft with a 2-MHz timer. Therefore, a speed pattern for an in-line six-cylinder engine consists of 236 tooth rotation speeds corresponding to the two rotations of the crankshaft, in which all the cylinders complete four-stroke cycle. FFT analysis can reduce the number of components of a speed pattern from 236 to just four major components: - fundamental frequency_(f), 2f, 3f, 6f., - This makes the comparison of the misfiring cases simpler and faster. In the experiment, five engine status cases (one normal firing and, four misfiring cases) were simulated. While the 6f component was the largest for the normal case, the f component increased as misfiring occurred one, two apart, and two consecutive times. The 3D FFT pattern comprising the ratio of f, 2f, and 3f, 6f showed that the distance between the misfiring and normal states was larger

• Journal of Platform Technology
• /
• v.9 no.4
• /
• pp.42-50
• /
• 2021

Recently, the need to introduce smart farms is increasing in order to solve the problems of intensifying competition such as a decrease in rural population due to aging, a decrease in production, and the inflow of foreign agricultural products, and accordingly, the need for education is increasing. This paper is a study on the implementation of an Android-based IoT smart farm for education so that it can be used in a real environment by reducing the farm's smart farm system. To confirm that Android-based education can be applied in a real environment using the IoT smart farm for education, experiments were performed in automatic mode and manual mode using Bluetooth, Wi-Fi, and server/client communication methods. In the automatic mode, the current status can be checked in real time by receiving all data, and in the manual mode, commands are transmitted in real time using the received sensor data and remote control is performed. As a result of the experiment, it was possible to understand the characteristics of each communication method, and it was confirmed that remote monitoring and remote control of the smart farm using the Android App was possible.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.4
• /
• pp.1-11
• /
• 2021

Recently, the importance of preventive maintenance has been emerging since failures in a complex system are automatically detected due to the development of artificial intelligence techniques and sensor technology. Therefore, prognostic and health management (PHM) is being actively studied, and prediction of the remaining useful life (RUL) of the system is being one of the most important tasks. A lot of researches has been conducted to predict the RUL. Deep learning models have been developed to improve prediction performance, but studies on identifying the importance of features are not carried out. It is very meaningful to extract and interpret features that affect failures while improving the predictive accuracy of RUL is important. In this paper, a total of six popular deep learning models were employed to predict the RUL, and identified important variables for each model through SHAP (Shapley Additive explanations) that one of the explainable artificial intelligence (XAI). Moreover, the fluctuations and trends of prediction performance according to the number of variables were identified. This paper can suggest the possibility of explainability of various deep learning models, and the application of XAI can be demonstrated. Also, through this proposed method, it is expected that the possibility of utilizing SHAP as a feature selection method.

• Nuclear Engineering and Technology
• /
• v.53 no.4
• /
• pp.1189-1198
• /
• 2021

When performing remote tasks using robots in nuclear power plants, a 3D shape measurement system is advantageous in improving the efficiency of remote operations by easily identifying the current state of the target object for example, size, shape, and distance information. Nuclear power plants have high-radiation and underwater environments therefore the electronic parts that comprise 3D shape measurement systems are prone to degradation and thus cannot be used for a long period of time. Also, given the refraction caused by a medium change in the underwater environment, optical design constraints and calibration methods for them are required. The present study proposed a method for developing an underwater 3D shape measurement system with improved radiation tolerance, which is composed of commercial electric parts and a stereo camera while being capable of easily and readily correcting underwater refraction. In an effort to improve its radiation tolerance, the number of parts that are exposed to a radiation environment was minimized to include only necessary components, such as a line beam laser, a motor to rotate the line beam laser, and a stereo camera. Given that a signal processing circuit and control circuit of the camera is susceptible to radiation, an image sensor and lens of the camera were separated from its main body to improve radiation tolerance. The prototype developed in the present study was made of commercial electric parts, and thus it was possible to improve the overall radiation tolerance at a relatively low cost. Also, it was easy to manufacture because there are few constraints for optical design.

• Journal of Convergence for Information Technology
• /
• v.11 no.5
• /
• pp.1-8
• /
• 2021

In this paper, we propose the construction of an IOT that monitors foresters' physical abnormalities in real time, performs emergency measures, and provides alarms for natural disasters or heatstroke such as a nearby forest fire or landslide. Nodes provided to foresters include 6-axis sensors, temperature sensors, GPS, and LoRa, and transmit the measured data to the network server through the gateway using LoRa communication. The network server uses 6-axis sensor data to determine whether or not a forester has any signs of abnormal body, and performs emergency measures by tracking GPS location. After analyzing the temperature data, it provides an alarm when there is a possibility of heat stroke or when a forest fire or landslide occurs in the vicinity. In this paper, it was confirmed that the real-time detection of physical abnormalities of foresters and the establishment of disaster early warning IOT is possible by analyzing the data obtained by constructing a node and a gateway and constructing a network server.