bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of Real-Time Driver's Health Detection System by Using Smart Handle
Authors: LIU Hao , LEE Jae-Cheon , KIM Yoon Nyun , HEO Yun Seok
Published: March 2024

The number of vehicle accidents due to driver's drowsiness continues to increase. Therefore, prompt and effective detection for driver's health during driving is crucial to improvement of traffic safety. A set of real-time healthdetection system built-in a smart handle for driver is proposed in the research. By monitoring driver’s biological signals, including respiration, hand gripping force, photoplethysmogram (PPG), and electrocardiogram (ECG), driver's health condition (drowsiness) is able to be detected via the developed algorithm. Meanwhile the driver's state of arrhythmia can be diagnosed too. The test results indicate that the developed real-time driver’s health detection  system can effectively monitor not only the state of vigilance but also the state of arrhythmia of a driver.
Data-Driven Prognostics for Major Piping in Nuclear Power Plants
Authors: Kim Gibeom , Kim Hyeonmin , Chang Yoon-Suk , Jung Seungho , Heo Gyunyoung
Published: March 2024

As operation period of Nuclear Power Plants (NPPs) is getting longer, necessity of reflecting ageing effect is increasing. Especially, when it comes to the piping in NPPs such as reactor coolant system piping or steam generatortubes, it is vulnerable to stress corrosion crack (SCC) or wear due to the fluid with high temperature, high pressure and radiation. Accidents related to such cases have been reported. Since ruptures of the piping can result in severe accidents, it is important to predict and prevent them in advance. Current NPPs ageing management is performed with the physical model based on generic experimental data, which cannot properly consider each NPPs’ different operation environment or history. Prognostics using plant specific data can compensate this limit of ageing management using the physical model. Recently, as usable data of NPPs is increasing with the development of instrumentation technology, applicability of prognostics for NPPs has been increased. Therefore, this paper suggests some prognostics methods such as GPM (General Path Model), MCMC (Markov Chain Monte Carlo) and Particle filter that can consider ageing degradation for the major piping in NPPs. It is expected that prognostics results can be used in Probabilistic Safety Assessment (PSA) considering current or future ageing degradation.
A Study on the Characteristic of Stator Winding Degradation Process and Its Life Estimation of Induction Motors
Authors: Nguyen Viethung , Wang Danwei , Seshadrinath Jeevanand , Ukil Abhisek , Jaiswal Vinay , Verma Nishant , Vaiyapuri Viswanathan , Nadarajan Sivakumar
Published: March 2024

This paper presents an analysis on the characteristics of the stator winding degradation process. A diagnostic and prognostic parameter, which is derived using the sequence component approach, is proposed. It is estimated using only the measurements of voltages and currents, which are easily obtained, and hence, the method can be implemented in real-time applications. A test is designed for generating stator winding inter-turn fault and accelerating it.  The characteristic of the degradation process based on the prognostic parameter is discussed. The collected data is modeled and the remaining useful life (RUL) is estimated.
Optimization of Creep Rupture Life Prediction for A231 T91 Alloy Steel Using Kriging Surrogate Model
Authors: Huh Y.-H. , Lee H. , Park C. , Bae S. , Kim N.H
Published: March 2024

Creep rupture life prediction for the A231 T91 alloy steel has been optimized using the Kriging surrogate model. Creep rupture data published by NIMS data sheet was used in this optimization, and isothermal creep rupture life-stress and TTP(Time-Temperature Parameter)-stress curves were optimized with Kriging model. The creep rupture data having the rupture life of less than 10,000 hours was interpolated with the K海ing surrogate model and theKriging extrapolation to the creep life of 100,000 hours was verified by comparing with experimental data. It was found that the Kriging model could fit to the data within 3% of relative error. Furthermore, the Kriging surrogate model was compared to Wilshire, Manson-Brown, Manson-Haferd, and MCX models. It can be found that the creep rupture stress extrapolated to 100,000 hours by Kriging surrogate showed a relatively good accuracy and uncertainty of 4% - 16%.
Running State Evaluation Method of Turbine Bearing Based on Feature Vector
Authors: Zhang Hao , Yun Xianghe , Dang Pengfei , Han Qingkai
Published: March 2024

Due to the high modal coupling of the cooling turbine bearing in environment control system, it is very difficult to extract the vibration signal feature and construct the recognition model on different feature.Arunning state evaluation method of the turbine bearing is proposed based on the feature vector with limited testing data in this paper. Firstly, aiming at some failure modes in several typical faults of turbine bearing, three time domain feature  parameters and seven frequency domain feature parameters are chosen to construct feature vector for discrimination. Then, the feature vectors of different fault testing data are dimensional reduced based on the principal component analysis method. Based on above, the support vector machine (SVM) model of the turbine bearing running state is proposed for monitoring and predicting the occurrence and development of typical turbine bearing failure modes. Experimental results suggest that the bearing running state evaluation method proposed in this paper can improve the prediction accuracy effectively.
Analysis of Big Data Streams to obtain Braking Reliability Information for Train Protection systems
Authors: Pfaff Raphael
Published: March 2024

Due to the long braking distance of railway systems and the high velocities achieved, railway operation needs to rely on train control systems. At the foundation of these systems are models to predict the motion of the trains, including their anticipated braking curve. Depending on the infrastructure manager, these braking curves need to be achieved with a given safety, which is typically in the rare event region of probabilities.In current settings, it is typical to develop these so called braking curves either by physical modelling of the train followed by a Monte Carlo simulation or following a heuristic approach, mostly based on the high level of safety over the past centuries. However, higher developed train protection and control systems, such as the European Rail Traffic Management System (ERTMS) or the Russian KLUB-U System together with current efforts towards quantitative risk analysis, e.g. the European Common Safety Methods, require a more formal approach to communicate the braking curve of a train between rolling stock and infrastructure. An a priori determined set of braking curves is feasible for trains running in fixed or a limited number of formations, such as multiple unit trains, however in the freight railway system due to its vast amount of different vehicles and possible train setups, the determination of the braking curves is prohibitive. In this work, a procedure is proposed to obtain the variation in braking force from accelerometer data onboard the vehicles. In order to allow for the large amount of data to be  expected, the procedure is formalised in MapReduce form. The variation of the braking force from the expected value determined in this way can then be forwarded to a Monte Carlo Analysis using importance sampling methodologies to allow for an online calculation of braking curves based on the safety requirements communicated by the infrastructure manager. It is expected that such a procedure yields shorter braking curves than the safety factors currently proposed, leading to higher commercial speeds and thus higher infrastructure usage.
Validation of Remaining Useful Life Prediction of Li-Ion Battery Based on the Voltage drop
Authors: Yun Yuri , Kim Seokgoo , Jung Kyusung , Choi Joo-Ho
Published: March 2024

Batteries, which are used for the energy storage and power distribution, tend to degrade, and their capacity declines with repeated charging and discharging cycles. The battery is considered to fail when it reaches 80% of its initialcapacity. In general, the battery state under operation can be characterized by identifying the state of health (SOH) and state of life (SOL), which refer the capacity degradation and remaining useful life respectively. Recently, authors have found that the SOH can be indirectly estimated based on the observation that the slope of voltage curve under charging is proportional to the capacity degradation. In the study, only the full charge and discharge cycles under room temperature were conducted with Li-ion battery, which is not the case in reality. In this study, more research is conducted to find out more reliable and robust measurement of the capacity and voltage drop that may be independent of the degradation conditions. Several tests are made under various C-rates, charging stabilization time and surrounding temperatures. Once succeeded, the regression model is established between the capacity and voltage drop, that is used in the estimation of the SOH. Adaptive Particle filtering (APF) framework is then applied during the battery usage to estimate the SOH and predict the RUL in the form of a probability distribution. In the APF, the recursive state transition and measurement functions are given by the empirical degradation model and the regression model, respectively. The APF performs the two functions at the same time which are the anomaly detection and prognostics. Experiments are conducted for a Li-ion battery by repeating full charge discharge cycles, in which a fault is imbedded to change the degradation pattern at a certain moment of thecycle to illustrate the technique.
A phenomenological force model of Li-ion battery packs for enhanced performance and health management
Authors: Oh Ki-Yong , Epureanu Bogdan I.
Published: March 2024

A 1-D phenomenological force model of a Li-ion battery pack is proposed to enhance the control performance of Li-ion battery cells in pack conditions for efficient performance and health management. The force model accounts for multiple swelling sources under the operational environment of electric vehicles to predict swelling-induced forces in pack conditions, i.e. mechanically constrained. The proposed force model not only incorporates structural nonlinearities due to Li-ion intercalation swelling, but also separates the overall range of states of charge into three ranges to account for phase transitions. Moreover, an approach to study cell-to-cell variations in pack conditions is proposed with serial and parallel combinations of linear and nonlinear stiffness, which account for battery cells and other components in the battery pack. The model is shown not only to accurately estimate the reaction force caused by swelling as a function of the state of charge, battery temperature and environmental temperature, but also to account for cell-to-cell variations due to temperature variations, SOC differences, and local degradation in a wide range of operational conditions of electric vehicles. Considering that the force model of Li-ion battery packs can account for many possible situations in actual operation, the proposed approach and model offer potential utility for the enhancement of current battery management systems and power management strategies.
Research on the Degradation Model of the Clamping Device Based on CAE Simulation and Data-driven
Authors: Li Yu , Rui Kang , Bin Zhang , Yansong Wang
Published: March 2024

The paper is based on PHM oriented design and modeling of durability testing for clamping devices. The testing scheme is made out through the Computer Aided Engineering (CAE) simulation result and the degradation model is studied by Data-driven according to the test data. Based on the analysis of main failure mode and mechanism, it is concluded that the reason of clamping device cracking is fatigue which caused by the cycle force. The durability test is conducted by CAE simulation analysis, and the strain data of the device have been collected by the NI data acquisition equipment. Based on the collected data, Data-driven method is used to model the high-cycle fatigue degradation caused by the cycle force. And with the comparison among different regression models, we selected the appropriate one which will provide theoretical support for PHM management of similar machines. In applications, by updating this model with actual degradation data of the target device, can monitor the health state and predict the remaining service life of the target device. So that the actively predictive maintenance can be done and the failure can be avoided.
Research Status of Prognostics and Health Management in Nuclear Field
Authors: Kim Hyeonmin , Hur Seop , Heo Gyunyoung , Kim Jung-Taek
Published: March 2024

Recently, the concerns of Nuclear Power Plants (NPPs) safety and reliability have increasing because of Fukushima disaster and NPPs increasing operating years. Operational experience has shown that greater situational awareness of the state of safety-critical nuclear plant System, Structure, and Components (SSCs) is necessary, particularly as they age due to exposure to harsh service conditions. While replacement of a subset of components is possible, and may even be economically attractive, it may be economically prohibitive to replace several of the lager components, including the reactor pressure vessel and primary piping. Thus, characterization, management, and mitigation of aging-related degradation in these critical passive components become important to maintain safety margins. In order to deal with these problem above mentioned, thus, it is necessary to develop Prognostics and health Management (PHM) technology. The key technology in PHM is to detect degradation and anomalies and to determine Remaining Useful Life (RUL) and Probability of Failure (POF) of SSCs. The prognostics results can be used to manage the evolving health and condition of nuclear plant SSCs. The prognostics information is used in a Probabilistic Safety Assessment (PSA) model to assess the risk significance of the degradation and the corresponding reduced safety margin. In this paper, the review of the state of the art in PHM for nuclear industry was summarized. In addition, the prognostics application in case of Nuclear filed and technical gap for NPPs weredescribed.
Prediction of system reliability using failure types of components based on Weibull lifetime distribution
Authors: Ko Hee Yang , Sung Si-Il , Kim Yong Soo
Published: March 2024

Nowadays, products are complicated and standards of reliability are higher than ever before. In contrast, the time available for developing products has gradually decreased. In this context, assessment of the system reliability of products is an active field of study. In this paper, an experimental design was used to investigate the effect of the failure type of components on the whole system’s failure type. For this, a general procedure for estimating system reliability based on the Weibull distribution was adopted.
A PSA framework for an Interim Dry Storage Facility Subjected to an Aircraft Crash
Authors: Lee Sanghoon , Amomani Belal , Jang Dong Chan , Kang Hyun-Gook
Published: March 2024

An overview of a risk evaluation framework for an aircraft crash into an interim spent fuel storage facility using a probabilistic safety assessment is presented. Damages evaluation of a detailed generic cask model in a simplifiedbuilding structure under aircraft impact is discussed through a numerical structural analysis and an analytical fragility assessment. Sequences of the impact scenario are shown in a developed event tree, with uncertainties considered in the impact analysis and failure probabilities calculated. Risks are estimated for three specification levels of cask and storage facility structures to evaluate the influence of parameters relevant to design safety. The proposed assessment procedure includes the determination of loading parameters and reference impact scenario, structural response analyses of facility walls, cask containment, and fuel assemblies, and a radiological consequence analysis with dose-risk estimation. The risk results for the proposed scenario in this study are expected to be small relative to design basis accidents for best-estimated, conservative values. The importance of this framework is seen in the flexibility to evaluate facility capability to withstand aircraft impact and the expectation of potential realistic risks; the framework also provides insight into epistemic uncertainty in the available data, and into the sensitivity of design parameters for structural health management of interim dry storage facility.
Sound Energy Harvester with Frequency Tunable Acoustic Metamaterial Cavity
Authors: Song Kyungjun , Kim Jae Eun , Kim Jedo , Sun Kyung Ho
Published: March 2024

We demonstrate a new type of acoustic harvester by utilizing an acoustic metamaterial cavity designed by double coiledup space like structures. In the case of double coiled-up metamaterials, high refractive index (n) miniaturizes the device at the subwavelength scale and high impedance (z) leads to efficient sound amplification rate inside the cavity, respectively. These miniaturized cavities enable to enhance the energy-convergence rate of acoustic harvester. When the resonant frequency of acoustic cavity coincides with the 1st natural frequency of the piezoelectric harvester, the amplification of sound pressure with 16dB sound pressure level gain leads to efficient acoustic mechanical-electrical conversion rate. Compared to acoustic harvesting method with only piezoelectric devices, experimental results illustrate that the proposed techniques exhibit six-time higher voltage output.
Development of experimental metal sphere-mass map of reactor vessel scale models
Authors: Han Soon-Woo , Lee Seong-Il , Lee Jeong-Han , Park Jin-Ho
Published: March 2024

Loose parts in coolant systems of a nuclear power plant (NPP) can damage structural integrity of the systems and loose part signals monitoring systems (LPMS) are installed in most of NPPs. LPMS detect impact signal of a loose part and generate alarm if amplitude of the signal is over preset level. If impact signal detected, mass estimation of the loose part must be carried out in order to see the effect of the part impact on structural integrity. A metal sphere-mass map, which shows relations between amplitude and center frequency of impact signals according to mass, is essential in mass evaluation of a loose part and the map built for US NPPs has been used so far. For the purpose of precise impact analysis suitable for Korean NPPs, this work discusses the development of a mass map of Korean Standard Nuclear Power Plant (KSNP) based on experimental data for scale models of a KSNP reactor vessel as tests for real NPP vessels under operation is actually impossible. Impact tests were carried out for scale models by using metal sphere with various mass and velocity. Amplitudes and center frequencies of impact signals were investigated based on time-frequency analysis and the mass map for each models were constructed based on the results. Blind tests were additionally implemented with metal sphere with unknown mass and velocity and verified feasibility of the proposed metal sphere mass map.
Development of a Mechanical Characterization Technique for Microand Nanoscale Polymer Thin-films
Authors: Kim Yun Young
Published: March 2024

A measurement technique for the mechanical characterization of micro- and nanoscale polymer thin-films was introduced in the present study. An experimental setup was established using an ultrasonic pulser that actuates a microcantilever so that material properties such as the Young’s modulus and shear modulus can be determined by detecting the resonant frequency shift upon coating of a thin-film to be evaluated using a laser interferometer. The present research proposes an evaluation method for the robust design of organic electronics and energy devices.
A Preliminary Study for Aircraft Engine Health Management based on Multi-Scale Kalman Filters
Authors: Kim Seokgoo , Yoon Yuri , Kim Heeseong , Choi Joo-Ho
Published: March 2024

Aircraft engine is directly associated with flight safety. Its unpredicted failures lead to catastrophic accident and downtime. To prevent these problems, prediction of the accurate remaining useful life of engine is essential. With the rapid development of sensor technology, engine health condition can be monitored with multiple sensors. Therefore, it is important to develop suitable methodologies of integrating various data to improve the accuracy of remaining useful life. This paper attempts to establish fusion methods after examining the existing model based and data driven methods used for the remaining useful life estimation of gas turbine engine. The developed methods are evaluated using the simulated data set C-MAPSS, which includes the parameters associated with degradation in the fan, compressor and turbine during a series of flights.
Development of Scanning Free-Space Measurement setup and its application to structural imaging.
Authors: Ahmed Hasan , Hyun Jongmin , Lee Jung-Ryul , Lee Won-Jun
Published: March 2024

This paper proposes a scanning free-space measurement (SFSM) setup for the evaluation of microwave absorption properties of a structure. The system works by illuminating the specimen with microwave signals of varying frequencies and measuring the power of reflected microwaves. Thereflected power is then divided by the emitted power in order to convert the measurements to the standard parameter known as S11. The system comprises of a vector network analyzer (VNA) to measure S11 parameter, focused horn antenna attached to the VNA for transmitting/receivingmicrowave signals, a dual-axis automated translation stage for raster scanning of the specimen and a standard personal computer. A graphical user interface (GUI) running on the computer manages the configuration and synchronization of the VNA and the stage system, S11 reception from VNA and compilation of results for display to the user. The GUI is created in C++ using Qt framework and Qt Widgets for Technical applications (QWT). It is designed with a minimalistic approach to promote usability and adaptability masking the intricacies of actual system operation.
Computer vision-based stress estimation of concrete structures
Authors: Kim Eun-Jin , Gwon Seongwoo , Cho Soojin , Sim Sung-Han
Published: March 2024

Losing tension forces of tendons is a critical issue in preand post-tensioned structures. The decreasing tension force can be considered as an initial step of structural damage, as it can further cause concrete cracks, reduced load carrying capacity, and even structural instability. Indeed, it is aserious threat to structural soundness while difficult to identify. Several approaches for estimating current tension forces have been developed, including ultrasonic wavebased methods, vibration-based methods, and impedance of the piezoelectric material. Although these methods in theliterature have made certain progress in this field, practical use is still limited. Instead of measuring the tension force, this study presents a method that can directly measures the static stress level of concrete by combining the stress relaxation method (SRM) and digital image correlation (DIC). By drilling a small hole, a part of the current static stress can be released, inducing stress field change around the hole. DIC can identify the deformation due to the stress field change using two images taken before and after drilling the hold. This deformation is subsequently compared to one that is calculated using finite element model to finally estimate the current static stress level in concrete. The proposed strategy is validated using concrete specimen loaded by the universal testing machine.
Line Laser Scanning Thermography System for Paint Thickness Estimation
Authors: Hwang Soonkyu , Park Jiho , An Yun-Kyu , Sohn Hoon
Published: March 2024

In this study, a novel paint-thickness visualizing (PTV) system is proposed using a line laser thermography and image processing algorithms for the paint thickness estimation. The prior paint-thickness techniques have a high accuracy for estimating paint-thickness on steel structures, but thetechnical hurdles exist for using real structures such as contact type and single point inspection. The proposed PTV system offers advantage of non-contact and non-invasive paint-thickness inspection over the existing techniques. Once the proposed PTV system generates thermal waves on thesteel structure surface using line laser beam scanning, the corresponding thermal responses are measured using an infrared (IR) camera. According to the paint thickness, the thermal wave reflecting phenomena alters at the layer between paint and steel structure and the newly proposed image processing algorithm quantifies the amount of the altered thermal wave reflection with visualizing the paintthickness distribution. The performance of the proposed PTV system was verified through lab scale tests with painted steel structure. Six types of paints which are used for a real steelbox girder bridges were used for the verification and 40 μm of the paint thickness difference was successfully visualized.
Improvement of MFL Sensing based Damage Detection and Quantification for Steel Bar NDE
Authors: Kim Ju-Won , Park Jihwan , Lee Donghwan , Cha Gichun , Park Seunghee
Published: March 2024

A magnetic flux leakage (MFL) method was applied to detect damage for inspecting the steel bar. A multi-channel MFL sensor head was fabricated using Hall sensors and permanent magnets. The MFL sensor head scanned the damaged specimen that have 5 levels of depth to measure the magnetic flux density. A signal processing process including the enveloping process based on Hilbert transform was performed to clarify the flux leakage signal. The enveloped signals were then analyzed for objective damage detection by comparing with the threshold value. For improvement of quantitative analysis, new damage indexes that utilize the relationship between the enveloped MFL signal and the threshold value were additionally proposed. By using the proposed damage indexes and the general damage index for the MFL method, the detected MFL signals were quantified and analyzed according to the size of damage increase.
Probabilistic forecasting method for concrete creep prognosis under model-form uncertainty
Authors: Jin Seung-Seop , Cha Sang-Lyul , Jung Hyung-Jo
Published: March 2024

Time-dependent deformation of structural concrete may cause cracks and has much to do with durability performance of structural concrete. Therefore, it is important to make a reliable prognosis for the time-dependent deformation. Creep is one of the time-dependent deformations under sustained strains generated by permanent loads. In order to predict the creep behavior, several model codes are available from different professional societies: ACI, fib 2010, KCI and so on. Consequently, modelform uncertainty (or model selection) inevitably arises from the competing prediction models. In this situation, classical statistical method may be used to select a best model with a measure of the relative quality of the prediction models given the measurement. In this study, we propose a practical method to improve the creep prediction by combining predictions from competing prediction models. The premise of the proposed method is to use and share the information of individual models rather than using a single model. The combined prediction is estimated by taking a weighted linear combination of the individual prediction models (probabilistic forecasting). A set of weights are determined by maximizing the likelihood between combined prediction and measurement. The performance of the proposed method was evaluated using a creep test. The classical statistical method was also performed to compare with the proposed method.
Monitoring of tensile force of PSC girder by measuring iron loss variation using EM sensors
Authors: Kim Junkyeong , Park Minsoo , Tareen Najeep , Yu Byoung-Joon , Park Seunghee
Published: March 2024

The actual tensile force of pre-stressed (PS) tendons of a prestressed concrete (PSC) girder is one of the important factors for evaluating the performance of PSC girder bridges. To measure the tensile force of the PS tendon, this study proposed an iron loss variation based tensile force estimation method using embedded EM sensors. The iron loss of PS tendons are changed according to the applied tensile force. To measure the iron loss of PS tendon of PSC girder, the EM sensor should be embedded in the PSC girder because the PS tendons were located in inside of PSC girder. To verify the proposed method, the experimental tests were performed. The EM sensors were embedded into PSC girder specimen and the iron loss changes due to the variations of tensile forces were measured using EM sensors. According to the measurement results, the proposed method can be a one of the solution to monitor the tensile force of PS tendons.
Fault Detection of Gearboxes in an Industrial Robot under Various Operating Conditions
Authors: Park Jungho , Kim Yunhan , Ha Jong M. , Youn Byeng D. , Park Jin-Gyun
Published: March 2024

In recent years, industrial robots have been widely used for manufacturing automation. The unexpected failures of the robots could bring about a significant amount of downtime loss due to suspension of the production lines. Fault detection and diagnosis for an industrial robot become one of the backbone technologies in the Industry 4.0. However, the industrial robots operate under variable speeds and loads. This makes fault detection for the industrial robot more challenging. Moreover, signals generated from one arm joint affect those from other joints mutually due to the multiple degree-of-freedom (DOF) motions of the robots. In this paper, we develop a fault detection method for a gearbox, which is one of the most critical components of an industrial robot. Both control and acceleration signals are used for the fault detection. Health data that represent a health state of the robot system are defined as the failure mechanisms of the gears are understood. The effectiveness of the proposed health data is demonstrated using a 6-DOF industrial robot with normal and faulty cases under various operating conditions in terms of rotating speed, rotating directions, number of DOF, different postures of robot arms, and loading condition.
RPM Independent Fault Diagnosis of Rolling Element Bearing
Authors: Kim Su J. , Kim Keunsu , Hwang Taewan , Jeon Byungjoo , Youn Byeng D.
Published: March 2024

Rolling element bearings are the most widely used and the most frequently broken mechanical components in rotating electrical machines. Therefore, many studies of diagnose the bearing health conditions have been conducted. To apply the diagnosis technology in the actual industrial field, there are two problems. For one thing, as the system operates at various rotational speeds, the behavior of the features change which indicate the health of the bearings making hard to diagnose. For the other thing, as the failure criteria is different for each system, bearing sometimes does not replaced even under localized fault. Continuous operation in such a condition propagates the defect up to distributed fault changing health feature. Thus, in this paper, we investigate the bearing diagnosis of localized and distributed faults under different rotational speeds. A deep grooveball bearing was used for this study and three health condition cases were considered, normal case, localized fault case, and distributed fault case. Experimental data under different rotational speed were acquired from the laboratory-level bearing life test-bed. The acquired data were only the vibration signals, which were gathered using an accelerometer sensor. Then, a number of signal features for bearing fault diagnosis were extracted after preprocessing. We proposed a new feature, which base on residual energy density of defect frequency, and then compared with the traditional time and frequency domain diagnosis feature including root mean square (RMS), Kurtosis, fundamental defect frequency, and so on. Finally, our new feature was selected to best features that could better diagnose bearing fault levels irrelevant to rotational speeds.
Feature extraction for gear diagnostics based on EEMD in different crack size
Authors: HAM Suck-Joo , PARK Sung-Ho , CHOI Joo-Ho
Published: March 2024

In these days, diagnostics techniques enabling the condition based maintenance are being paid great attention in many industry fields to achieve increased reliability of the system as well as the reduction of operating cost. The techniques are particularly useful to the system that costs atremendous amount for the maintenance or leads to the catastrophic results when failure occurs. In such systems, the gearbox is usually employed to deliver the power under extreme loading conditions which are expensive to maintain and replace when failure occurs. Among the many gear faults, crack is the most critical in the sense that it grows suddenly to the tooth breakage, resulting in the whole system loss. To diagnose tooth cracks, many authors have conducted studies using gear vibration signals. Choi and Li estimated gear tooth transverse crack size using vibration signals by fusing selected gear condition indices [1]. G.R proposed vibration signature to estimate fault size [2]. This study classifies features of fault signal in different crack size using TE. In the previous study [4], authors have conducted a fault classification study of spall and crack, in which a pair of gears are operated in a testbed, faults are imbedded to the gear, and features are extracted based on the Ensemble Empirical Mode Decomposition (EEMD) technique using the transmission error (TE) signals [3-4]. Types of the fault are then identified based on the finite element analysis (FEA) of the faulted gears. In this study, further progress is made with the goal to evaluate the severity of the crack faults from the signal. To this end, gears with different crack size are prepared. The FEAs are conducted and compared with the measured signals, from which the critical size is identified that requires maintenance action. Since the measured crack signals include various noise and uncertainties, study on the statisticalsignificance is also made to check whether the signal can be large enough to detect the fault. Once successful, the technique can be applied to estimate not only the size of the crack fault but also its severity against the critical level, using the measured TE signals of the gears in operation.
Design of Cyber-Physical Systems Architecture for Prognostics and Health Management of High-speed Railway Transportation Systems
Authors: Zhang Zhiqiang , Liu Zongchang , Xu Guanji , Jin Wenjing , Lee Jay
Published: March 2024

The high-speed railway (HSR) transportation system in China has been growing rapidly during the past decade. In 2016, the total length of HSR in China has reached to 22,000 kilometers, and there are over 2,000 pairs of high speed trains operating daily. With the advancement of design and manufacturing technologies, the reliability and construction costs have been improved significantly. However, there is still great need for reduction of their operation and maintenance costs. With such incentive, a pilot project has been launched in CRRC to develop a prognostics and health management system for rolling stock to transform the maintenance paradigm from preventive to predictive maintenance. Considering the high task variety and big data environment in HSR real-time monitoring system, a cyber-physical system (CPS) architecture is proposed as the framework for its PHM system. This paper reviews the needs of predictive maintenance for the HSR system, and then present a concept design of the CPS-enabled smart operation and maintenance system.
Selective Isolation of Heterogenic Circulating Tumor Cells(CTCs) using Magnetic Gradient based Microfluidic System
Authors: Kwak Bongseop , Lee Jaehun , Lee Jeonghun
Published: March 2024

Circulating tumor cells(CTCs) is one of key marker of cancer metastasis in human body. Despite of the importance to diagnose the cancer metastasis by CTCs, still it is formidable challenge to use in the clinical purpose because of the rarity and the heterogeneity of CTCs in the cancerpatient’s peripheral blood sample. To solve those addressed limitations, we have developed magnetic force gradient based microfluidic system for isolating the total number of CTCs in the sample and characterizing the state of CTCs simultaneously with respect to the epithelial cell adhesionmolecule (EpCAM) expression level. We have synthesized magnetic nanoparticles (MNPs) using hydrothermal method and functionalized anti-EpCAM on their surface for the specific binding with EpCAM on the tumor cell membrane. The microfluidic system designed to isolate and classify the CTCs by isolating at the different location in the chip using magnetic force differences depending on the EpCAM expression level. We observed 95.7% of EpCAM positive and 79.3% of EpCAM negative CTCs isolated in the microfluidic system. At the same time, the 71.3% of isolated EpCAM positive CTCs were isolated at the first half area whereas the 76.9% of EpCAM negative CTCs were collected at the latter half area.
The Lethargy Coefficient Estimation of the Probabilistic Fatigue Life Model Using the Markov Chain Monte Carlo
Authors: Doh Jaehyeok , Lee Jongsoo
Published: March 2024

Recently, the researchers of prognostics and health management (PHM) have been developed to the field of engineering. In this study, probabilistic fatigue life which based on Zhurkov model is suggested using stochastically and statistically estimated lethargy coefficient. The fatigue life model was derived using Zhurkov life model and it was deterministically validated with the reference of fatigue life data. For this process, firstly, lethargy coefficient which is relative to the failure of materials has to be obtained with rupture time and stress from quasi-static tensile test. These experiments are performed using HS40R steel. However, lethargy coefficient has uncertainties due to inherent uncertainty and the variation of material properties in the experiments. Bayesian approach was employed for estimating the lethargy coefficient of the fatigue life model using Markov Chain Monte Carlo (MCMC) sampling method and considering its uncertainties. Once the samples are obtained, one can proceed to the posterior predictive inference on the fatigue life. This life model is reasonable through comparing with experimental fatigue life data. As a result, predicted fatigue life was observed that it was significantly decreased in accordance with increasing stress conditions relatively. This life model is reasonable through comparing with experimental fatigue life data.
Fatigue and Durability Based Analysis and Design of Lower Control Arm with Composite Materials
Authors: Jang Jaeik , Song Chang Yong , Lee Jongsoo , Lim Juhee
Published: March 2024

In order to satisfy the fuel efficiency regulation and CO2 emissions regulation, researches to reduce the weight of automobile body as well as its components have been actively carried out recently. Fatigue analysis is also becoming more important in terms of securing safety as fracture occurs even under lower than the yield stress, even if there is sufficient margin in the strength. In particular, lower control arm is a component that affects the steering safety and ride comfort in suspension system, it is essential to examine whether it satisfies the safety depending on durability. In this paper, we conducted the fatigue and durability based analysis of lower control arm with carbon fiber reinforced plastics, which is a representative composite material. For this, stress and stiffness analysis under given load conditions are performed through finite element analysis, and we verify whether it satisfies the load and stiffness conditions or not. And also, the inertia relief method for finite element analysis is utilized to simulate thestatic load conditions. Based on these results, the fatigue life was predicted by the stress-life method. We also applied the Smith-Watson-Topper index to account for the average stress effect.
A Yield-Reliability Relation Modeling Approach based on Random Effects Degradation Models
Authors: Yuan Tao , Zhu Xiaoyan , Kuo Yue
Published: March 2024

This paper presents a unified modeling framework for yield and reliability in micro-/nano-electronics manufacturing via spatiotemporal modeling of defects. The spatial modeling and temporal modeling of defects refer to modeling of the spatial distribution of defects in manufacturing processes and modeling of the growth of defects with time when devices are subject to stresses, respectively. The defect growth process is characterized by the random-effect degradation modeling method. The presented modeling framework will allow us to use abundantly available process control data to predict the device reliability.
State and non-state actors’ contribution to economic stability or instability of State-Owned Entities: a case study of South African Airways
Authors: Motswaledi Thabang
Published: March 2024

The state and non-state actors have always influenced the issues arising in society, particularly concerning state-owned entities (SOEs), economic stability, and instability. From having an influence within their national borders to the international scale, these actors are very pivotal agents that often seek to bring justice and better ordinary individuals' lives. Non-state actors such as multinational corporations and civil society organizations are some of those on the frontlines of fighting for economic emancipation, especially in less developed states. Yet, this is not always the case; in some instances, they can be noted as villains who would bring about the injustices themselves. Although their influence cuts across many sectors of society, the paper sought to discuss the contribution of these two actors, the state and the non-state actor, to the economic stability and/or instability of state-owned entities. From this premise, the paper adopted a qualitative method and case study approach for South African Airways (SAA) to understand the contribution of state and non-state entities to the financial stability or instability of SAA. Thus, the findings suggest that SOEs are affected by various direct and indirect interventions by both state and non-state actors, especially in their economic ambitions, which provide stability or instability in the entity. Hence, the paper concludes that the economic stability or instability of SOEs such as SAA is largely affected by the intervention of both state and non-state actors.
COMPREHENDING THE ENVIRONMENTAL PRODUCTION AND ATTRIBUTES OF NITROUS OXIDES (N2O) IN THE NORTH-EASTERN MAHARASHTRIAN CLIMATIC CONTEXT
Authors: Phirke Niteen V.
Published: March 2024

Alterations in the regional climate, a major problem for the livelihood of the human and non-human inhabitants of the
north eastern Maharashtra; has been reviewed, studied and trouble-shot to achieve sustainability and remove
vulnerability in the region to preserve the biodiversity, culture and environment. The increase in climatic temperature and rainfall pattern has been
correlated with the emission of atmospheric trace gases that bestow the green house effect on the region. Among the major contributors, N O were 2
found to be added with net emission much higher than needed and thus, increasing the implications of green house effect over the region,
contributing to global warming. Besides, the contribution from industrialisation, vehicular pollution, deforestation, microbial contribution of
green house gases is enormous in the existing conditions due conventional and inappropriate methods of waste management, agriculture,
industrialisation and overall human activities.
ASSOCIATION OF MATERNAL & CORD BLOOD TSH WITH FETAL DISTRESS & APGAR SCORE OF NEWBORN
Authors: Parihar Priyanka , Ranawat Aditi , Meena Kusumlata , Mishra Sandhya
Published: March 2024

Introduction- Thyroid disorder affects 2.3–3.8% of expectant mothers. The commonest thyroid disorder in pregnancy is
maternal hypothyroidism. Cord blood TSH is a recognized method of screening for hypothyroidism at birth. The
"APGAR SCORE" was used to measure fetal discomfort in newborns. The purpose of this study was to examine the impact of maternal and cord
blood TSH levels on fetal discomfort. The study was conducted on 100 postpartum females fullling th Material and method- e inclusion criteria
and their neonates enrolled in Zanana Hospital attached to S.M.S. Hospital, Jaipur. After obtaining their informed written consent, detailed
history was taken and blood sample was drawn,Cord Blood samples were also taken .Newborns APGAR scoring was routinally done. TSH was
analysed and data was evaluated statistiacally. There is a signicant positive correlation between Result and discussion- maternal TSH and cord
blood TSH levels.In our study there is signicant negative correlation between APGAR score with maternal TSH and cord blood TSH. The Cord
Blood TSH was lower in neonates with fetal distress or needing advanced resuscitation after birth than neonates receiving routine care and the
difference was statistically non-signicant p>0.05). Therefore, in all children with neurological sy Conclusion- mptoms who were exposed to
severe hypoxia or had low Apgar scores, we recommend a thorough evaluation of thyroid function.
UNRAVELING THE STIGMA PREJUDICE AND DISCRIMINATION SURROUNDING MENTAL ILLNESS
Authors: Ranjan Ashutosh , Shrivastava Janak Kumari
Published: March 2024

Background: Various therapeutic approaches have been devised and rigorously evaluated to effectively alleviate the
symptoms and decits associated with several mental disorders. Regrettably, individuals aficted with these disorders
sometimes fail to seek assistance or opt not to participate fully in the existing programmes. Mental illness stigma hinders individuals from
seeking care and impairs the efcacy of the service system. Most nations in the world place less emphasis on mental health and mental illnesses
than they do on physical health. Due to a deciency of knowledge and comprehension in our society, about 50% of individuals aficted with
mental illnesses are not provided with treatment for their disorders. The objective of the present r Objective: esearch was to highlight the
demographic factors as well as the awareness and society about mental illnesses among the people of rural and urban areas. The current Method:
investigation is carried out on a sample of persons residing in both urban and rural regions of Bhagalpur district, Bihar. A total of 200 people from
Teken were included in the study's sample: 100 were from rural and 100 were from urban regions. A deliberate sampling approach was
employed. The sample of respondents was made up of people aged 21 to 30. Population Data and Hybridization Magnitude the Community
Attitudes towards the Mentally Ill (CAMI) scale, developed by Taylor, S., & Dear Michael J. in 1981, comprises four subscales. Each subscale
contains 10 items used to assess the scale's effectiveness. Each item was to be scored on a 5-point scale by the participants. To examine Result:
the inuence of demographic characteristics like age on resilience, chi square and p-value were computed on the responses to the measures
employed in this study using SPSS-18. The present study found that most persons had enough information but unfavourable attitudes regarding
mental illness. A study found a moderate positive link between people' knowledge and attitude towards mental illness (P < 0.001). Higher
knowledge scores were associated with better attitudes among rural adults. Studies indicated that m Conclusion: ental disease attitudes improve
with information. Association analysis showed that only married status was associated with mental illness knowledge, however no research
supported this. This study also demonstrated that religion and education affect mental disease attitudes.