• Smart Structures and Systems
• /
• v.30 no.1
• /
• pp.75-88
• /
• 2022

Engineering structures in operation essentially belong to time-varying or nonlinear structures and the resultant response signals are usually non-stationary. For such time-varying structures, it is of great importance to extract time-dependent dynamic parameters from non-stationary response signals, which benefits structural health monitoring, safety assessment and vibration control. However, various traditional signal processing methods are unable to extract the embedded meaningful information. As a newly developed technique, variational mode decomposition (VMD) shows its superiority on signal decomposition, however, it still suffers two main problems. The foremost problem is that the number of modal components is required to be defined in advance. Another problem needs to be addressed is that VMD cannot effectively separate non-stationary signals composed of closely spaced or overlapped modes. As such, a new method named generalized adaptive variational modal decomposition (GAVMD) is proposed. In this new method, the number of component signals is adaptively estimated by an index of mean frequency, while the generalized demodulation algorithm is introduced to yield a generalized VMD that can decompose mode overlapped signals successfully. After that, synchrosqueezing wavelet transform (SWT) is applied to extract instantaneous frequencies (IFs) of the decomposed mono-component signals. To verify the validity and accuracy of the proposed method, three numerical examples and a steel cable with time-varying tension force are investigated. The results demonstrate that the proposed GAVMD method can decompose the multi-component signal with overlapped modes well and its combination with SWT enables a successful IF extraction of each individual component.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.12
• /
• pp.2341-2347
• /
• 2016

In this paper, we implement monitoring system for grain sorting using a high-speed FPGA and embedded LINUX. The proposed system is designed by base on web server and web-based applications while existing system was designed by base on stand-alone mode.The interface the Web server with high speed hardware of FPGA is designed on the implemented monitoring system. The proposed system has the advantages of multi-tasking on Linux web server and real-time high speed on FPGA also. The control logic of a high speed rate line-scan CCD camera, the method of center of gravity, HSL decoding and the interface on the Web server are implemented in FPGA. The implemented monitoring system has the advantage of being able to control the grain monitoring, system failure and recovery remotely by web application. As a result, we can upgrade the performance of sorting quality compared by existing system.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.37 no.3
• /
• pp.163-171
• /
• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.40 no.4
• /
• pp.343-352
• /
• 2016

A multi-rotor vehicle is an unmanned vehicle consisting of multiple rotors. A multi-rotor vehicle can be categorized as tri-, quad-, hexa-, and octo-rotor depending on the number of the rotors. Multi-rotor vehicles have many advantages due to their agile flight capabilities such as the ability for vertical take-off, landing and hovering. Thus, they can be widely used for various applications including surveillance and monitoring in urban areas. Since multi-rotors are subject to uncertain environments and disturbances, it is required to implement robust attitude stabilization and flight control techniques to compensate for this uncertainty. In this research, an advanced nonlinear control algorithm, i.e. sliding mode control, was implemented. Flight experiments were carried out using an onboard flight control computer and various real-time autonomous attitude adjustments. The feasibility and robustness for flying in uncertain environments were also verified through real-time tests based on disturbances to the multi-rotor vehicle.

• Nuclear Engineering and Technology
• /
• v.52 no.8
• /
• pp.1689-1696
• /
• 2020

In this study, we developed a fiber-optic humidity sensor (FOHS) system for the monitoring and detection of coolant leakage in nuclear power plants. The FOHS system includes an FOHS, a spectrometer, a halogen white-light source, and a Y-coupler. The FOHS is composed of a humidity-sensing material, a metal tube, a multi-mode plastic optical fiber, and a subminiature version A (SMA) fiber-optic connector. The humidity-sensing material is synthesized from a mixture of polyvinylidene fluoride (PVDF) in dimethyl sulfoxide (DMSO) and hydroxyethyl cellulose (HEC) in distilled water. We measured the optical intensity of the light signals reflected from the FOHS placed inside the humidity chamber with relative humidity (RH) variation from 40 to 95%. We found that the optical intensity of the sensing probe increased linearly with the RH. The reversibility and reproducibility of the FOHS were also evaluated.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.229-234
• /
• 2002

Under the hostile influence of the extreme space environmental conditions due to the deep space and direct solar flux, the thermal control in space applications is especially of major importance. There are tight temperature range restrictions for electro-optical elements while on the other hand there are low power consumption requirements due to the limited energy sources on the spacecraft. So, we usually have strong requirement of thermal and power control module in space applications. In this paper, the design concept of a thermal and power control module in the MSC(Multi-Spectral Camera) system which will be a payload on KOMPSATII is described in terms of H/W & S/W. This thermal and power control module, called THTM(Thermal and Telemetry Module) in MSC, resides inside the PMU(Payload Management Unit) which is responsible for the proper management of the MSC payload for controlling and monitoring the temperature insides the EOS(Electro-Optic System) and gathering all the analog telemetry from all the MSC sub-units, etc. Particularly, the designed heater controller has the special mode of "duty cycle" in addition to normal closed loop control mode as usual. THTM controls heaters in open loop according to on/off set time designed through analysis in duty cycle mode in case of all thermistor failure whereas it controls heaters by comparing the thermistor value to temperature based on closed loop in normal mode. And a designed THTM provides a checking and protection method against the failure in thermal control command using the test pulse in command itself.

• Wind and Structures
• /
• v.37 no.6
• /
• pp.445-460
• /
• 2023

Accurate estimation of modal parameters (i.e., natural frequency, damping ratio) of tall buildings is of great importance to their structural design, structural health monitoring, vibration control, and state assessment. Based on the combination of variational mode decomposition, smoothed discrete energy separation algorithm-1, and Half-cycle energy operator (VMD-SH), this paper presents a method for structural modal parameter estimation. The variational mode decomposition is proved to be effective and reliable for decomposing the mixed-signal with low frequencies and damping ratios, and the validity of both smoothed discrete energy separation algorithm-1 and Half-cycle energy operator in the modal identification of a single modal system is verified. By incorporating these techniques, the VMD-SH method is able to accurately identify and extract the various modes present in a signal, providing improved insights into its underlying structure and behavior. Subsequently, a numerical study of a four-story frame structure is conducted using the Newmark-β method, and it is found that the relative errors of natural frequency and damping ratio estimated by the presented method are much smaller than those by traditional methods, validating the effectiveness and accuracy of the combined method for the modal identification of the multi-modal system. Furthermore, the presented method is employed to estimate modal parameters of a full-scale tall building utilizing acceleration responses. The identified results verify the applicability and accuracy of the presented VMD-SH method in field measurements. The study demonstrates the effectiveness and robustness of the proposed VMD-SH method in accurately estimating modal parameters of tall buildings from acceleration response data.

• Structural Engineering and Mechanics
• /
• v.37 no.6
• /
• pp.671-684
• /
• 2011

Deciding on an optimal sensor placement (OSP) is a common problem encountered in many engineering applications and is also a critical issue in the construction and implementation of an effective structural health monitoring (SHM) system. The present study focuses with techniques for selecting optimal sensor locations in a sensor network designed to monitor the health condition of Dalian World Trade Building which is the tallest in the northeast of China. Since the number of degree-of-freedom (DOF) of the building structure is too large, multi-modes should be selected to describe the dynamic behavior of a structural system with sufficient accuracy to allow its health state to be determined effectively. However, it's difficult to accurately distinguish the translational and rotational modes for the flexible structures with closely spaced modes by the modal participation mass ratios. In this paper, a new method of the OSP that computing the mode shape matrix in the weak axis of structure by the simplified multi-DOF system was presented based on the equivalent rigidity parameter identification method. The initial sensor assignment was obtained by the QR-factorization of the structural mode shape matrix. Taking the maximum off-diagonal element of the modal assurance criterion (MAC) matrix as a target function, one more sensor was added each time until the maximum off-diagonal element of the MAC reaches the threshold. Considering the economic factors, the final plan of sensor placement was determined. The numerical example demonstrated the feasibility and effectiveness of the proposed scheme.

• Smart Structures and Systems
• /
• v.14 no.1
• /
• pp.39-54
• /
• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.34-34
• /
• 2023

The Chah-Nimeh reservoirs, which are a sort of natural lakes located in the border of Iran and Afghanistan, are the main drinking and agricultural water resources of Sistan arid region. Considering the occurrence of intense seasonal wind, locally known as levar wind, this study aims to explore the possibility to provide a TSM (Total Suspended Matter) monitoring model of Chah-Nimeh reservoirs using multi-temporal satellite images and in-situ wind speed data. The results show that a strong correlation between TSM concentration and wind speed are present. The developed empirical model indicated high performance in retrieving spatiotemporal distribution of the TSM concentration with R²=0.98 and RMSE=0.92g/m³. Following this observation, we also consider a machine learning-based model to predicts the average TSM using only wind speed. We connect our in-situ wind speed data to the TSM data generated from the inversion of multi-temporal satellite imagery to train a neural network based mode l(Wind2TSM-Net). Examining Wind2TSM-Net model indicates this model can retrieve the TSM accurately utilizing only wind speed (R²=0.88 and RMSE=1.97g/m³). Moreover, this results of this study show tha the TSM concentration can be estimated using only in situ wind speed data independent of the satellite images. Specifically, such model can supply a temporally persistent means of monitoring TSM that is not limited by the temporal resolution of imagery or the cloud cover problem in the optical remote sensing.