• Proceedings of the KIEE Conference
• /
• 2002.07d
• /
• pp.2222-2224
• /
• 2002

Induction motors are critical components of many industrial machines and are frequently integrated in commercial equipment. The heavy economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method are used for induction motor fault diagnosis. This method analyzes the motors supply current. since this diagnoses faults of the motor. The diagnostic algorithm is based on the artificial neural network, and the diagnosis system is programmed by using LabVIEW and MATLAB.

• Journal of Electrical Engineering and Technology
• /
• v.5 no.1
• /
• pp.140-145
• /
• 2010

The monitoring and the diagnosis of the faults in induction motors starting from the stator current are very interesting, since it is an accessible and measurable quantity. The spectral analysis of the stator current makes it possible to highlight the characteristic frequencies of the faults but in a wide frequency range depending on half the sampling frequency, making it very difficult to monitor on-line the faults. In order to facilitate the use of the relevant frequencies of machine faults we proposed the extraction of the frequency components using two methods, namely, the amplitude and the instantaneous frequency. The theoretical bases of these methods were presented and the results were validated on a test bench with an induction motor of 5.5 kw.

• Proceedings of the KIEE Conference
• /
• 2001.07d
• /
• pp.2172-2174
• /
• 2001

Induction motors are a critical component of many industrial machines and are frequently integrated in commercial equipment. The many economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method is used for induction motor fault diagnosis. This method analyzes the motor's supply current, since this diagnoses the motor's condition. The diagnostic system is constructed by using LabVIEW of National Instruments.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.65.1-65
• /
• 2001

Induction motors are a critical component of many industrial machines and are frequently integrated in commercial equipment. The many economical losses and the deterioration of system reliability might be caused by the failure of induction motors in industrial field. Based on the reliability and cost competitiveness of driving system motors, the faults detection and diagnosis of system is considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis MCSA method are emphasized. In this paper, MCSA method is used for induction motor fault diagnosis. This method analyzes the motor´s supply current, since this diagnoses the motor´s condition. The diagnostic system is constructed by using LabVIEW of National Instruments.

• Corrosion Science and Technology
• /
• v.7 no.4
• /
• pp.197-200
• /
• 2008

In this paper, physical scale modeling was employed to identify the configurations of ICCP system and the electric field signatures. Computational boundary element modeling technique has been used to simulate the performance of the CP system and to predict the associated electric fields signatures. The optimization methods combined with the computer models and physical scale modeling will be presented here, which enable the optimum system design to be achieved both in terms of the location and current output of the anode but also in the location of reference electrodes for impressed current cathodic protection(ICCP) systems. The combined methodology was utilized to determine optimal placement of ICCP components (anodes and reference electrodes) and to evaluate performance of ICCP system for the 2%, 10% and 14% wetted hull coatings loss. The objective is to design the system to minimise the electric field while at the same time provide adequate protection for the ship. The results show that experimental scale modeling and computational modeling techniques can be used in concert to design an optimum ICCP system and to provide information for quickly analysis of the system and its surrounding environment.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1439-1444
• /
• 2005

Induction motors are the most commonly used electrical drives because they are rugged, mechanically simple, adaptable to widely different operating conditions, and simple to control. The most common faults in squirrel-cage induction motors are bearing, stator and rotor faults. Surveys conducted by the IEEE and EPRI show that the most common fault in induction motor is bearing failure (${\sim}$40% of failure). Thence, this paper addresses experimental results for diagnosing faults with different rolling element bearing damage via motor current spectral analysis. Rolling element bearings generally consist of two rings, an inner and outer, between which a set of balls or rollers rotate in raceways. We set the experimental test bed to detect the rolling-element bearing misalignment of 3 type induction motors with normal condition bearing system, shaft deflection system by external force and a hole drilled through the outer race of the shaft end bearing of the four pole test motor. This paper takes the initial step of investigating the efficacy of current monitoring for bearing fault detection by incipient bearing failure. The failure modes are reviewed and the characteristics of bearing frequency associated with the physical construction of the bearings are defined. The effects on the stator current spectrum are described and related frequencies are also determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. We utilized the FFT, Wavelet analysis and averaging signal pattern by inner product tool to analyze stator current components. The test results clearly illustrate that the stator signature can be used to identify the presence of a bearing fault.

• Smart Structures and Systems
• /
• v.29 no.6
• /
• pp.785-790
• /
• 2022

Condition monitoring of permanent magnet synchronous motors (PMSMs) and detecting faults such as eccentricity and demagnetization are essential for ensuring system reliability. Motor current signal analysis is the most commonly used precursor for detecting faults in the PMSM drive system. However, the current signature responds sensitively to the load and temperature of the motor, thereby making it difficult to monitor faults in real- applications. Therefore, in this study, a condition monitoring methodology that detects motor faults, including their classification with standstill conditions, is proposed. The objective is to detect and classify faults of PMSMs by using programmable inverter without additional sensors and systems for detection. Both DC and AC were applied through the d-axis of a three-phase motor, and the change in incremental inductance was investigated to detect and classify faults. Simulation with finite element analysis and experiments were performed on PMSMs in healthy conditions as well as with eccentricity and demagnetization faults. Based on the results obtained from experiments, the proposed method was confirmed to detect and classify types of faults, including their severity.

• Journal of Power Electronics
• /
• v.11 no.2
• /
• pp.163-172
• /
• 2011

Oxidation models of a rotor bar and end ring segment in an induction motor are presented to simulate the behavior of an induction machine working with oxidized rotor parts which are modeled as rotor faults in progress. The leakage inductance and resistance of the rotor parts arc different from normal values because of the oxidation process. The impedance variations modify the current density and magnetic flux which pass through the oxidized parts. Consequently, it causes the rotor asymmetry which induces abnormal harmonics in the stator current spectra of the faulty machine. The leakage inductances of the oxidation models are derived by the Ampere's law. Using the proposed oxidation models, the rotor bar and end ring faults in progress can be modeled and simulated with the motor current signature analysis (MCSA). In addition, the oxidation process of the rotor bar and end ring segment can motivate the rotor asymmetry, which is induced by electromagnetic imbalances, and it is one of the major motor faults. Results of simulations and experiments are compared to each other to verify the accuracy of the proposed models. Experiments are achieved using 3.7 kW, 3-phase, and squirrel cage induction motors with a motor drive inverter.

• Journal of Ginseng Research
• /
• v.43 no.4
• /
• pp.666-675
• /
• 2019

Background: Korean Red Ginseng (KRG) has been widely used as an herbal medicine to normalize and strengthen body functions. Although many researchers have focused on the biological effects of KRG, more studies on the action mechanism of red ginseng are still needed. Previously, we investigated the proteomic changes of the rat spleen while searching for molecular signatures and the action mechanism of KRG. The proteomic analysis revealed that differentially expressed proteins (DEPs) were involved in the increased immune response and phagocytosis. The aim of this study was to evaluate the biological activities of KRG, especially the immune-enhancing response of KRG. Methods: Rats were divided into 4 groups: 0 (control group), 500, 1000, and 2000 mg/kg administration of KRG powder for 6 weeks, respectively. Isobaric tags for relative and absolute quantitation was performed with Q-Exactive LC-MS/MS to compare associated proteins between the groups. The putative DEPs were identified by a current UniProt rat protein database search and by the Gene Ontology annotations. Results: The DEPs appear to increase the innate and acquired immunity as well as immune cell movement. These results suggest that KRG can stimulate immune responses. This analysis refined our targets of interest to include the potential functions of KRG. Furthermore, we validated the potential molecular targets of the functions, representatively LCN2, CRAMP, and HLA-DQB1, by Western blotting. Conclusion: These results may provide molecular signature candidates to elucidate the mechanisms of the immune response by KRG. Here, we demonstrate a strategy of tissue proteomics for the discovery of the molecular function of KRG.

• International Journal of Advanced Culture Technology
• /
• v.9 no.4
• /
• pp.288-294
• /
• 2021

There are various ways to be infected with malicious code due to the increase in Internet use, such as the web, affiliate programs, P2P, illegal software, DNS alteration of routers, word processor vulnerabilities, spam mail, and storage media. In addition, malicious codes are produced more easily than before through automatic generation programs due to evasion technology according to the advancement of production technology. In the past, the propagation speed of malicious code was slow, the infection route was limited, and the propagation technology had a simple structure, so there was enough time to study countermeasures. However, current malicious codes have become very intelligent by absorbing technologies such as concealment technology and self-transformation, causing problems such as distributed denial of service attacks (DDoS), spam sending and personal information theft. The existing malware detection technique, which is a signature detection technique, cannot respond when it encounters a malicious code whose attack pattern has been changed or a new type of malicious code. In addition, it is difficult to perform static analysis on malicious code to which code obfuscation, encryption, and packing techniques are applied to make malicious code analysis difficult. Therefore, in this paper, a method to detect malicious code through dynamic analysis and static analysis using Trojan-type Downloader/Dropper malicious code was showed, and suggested to malicious code detection and countermeasures.