• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.4
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• pp.287-293
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• 2002

The unexpected failure of the induction motor makes the downtime of production, and the cost of the process cessation enormous. To reduce the downtime and increase the reliability of the motor, the vibration measurements for the fault detection have been used previously. Recently motor current signature analysis(MCSA) has been adapted for the fault detection and diagnosis of the motors. MCSA provides a powerful analysis tool for detecting the presence of mechanical and electrical faults in both the motor and driven equipment. In this paper, the fault severity of the rotor bar has been derived in terms of the resistance change which is calculated from the equivalent circuit model. Results show that the fault of the rotor can be easily detected and the measured value of the resistance change is verified by the detected fault from on-site tests using MCSA for the induction motors in an iron foundry.

• The Transactions of the Korea Information Processing Society
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• v.2 no.6
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• pp.969-973
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• 1995

In this paper, a new parallel Multiplier array is proposed to reduce the multiplication time by modifying CAS(carry select adder) cell structure used in the conventional parallel multiplier array. It is named MCSA(modified CSA) that assignes the addend and augend to the inputs of CSA faster than Ci(carry input). Also the designed DCSA (doubled inverted input CSA) is appended after the last product term for the carry propagation adder. The proposed scheme is designed with MCSA and DCSA, and simulated. It is verified that the circuit size is increased about 13% compared with the conventional multiplier array with CSA cell but the operation time is reduced about 52%.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1876-1877
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• 2011

In this paper, a winding fault diagnosis method base on MCSA(Motor Current Signature Analysis) for BLDC motor is proposed. This method is programmed by LabVIEW for winding fault diagnosis. For winding fault diagnosis, two types of winding fault(shorted turn at one pole, shorted turn at two pole in same phase) are put intentionally in on phase. The motor current is collected by hole sensor, and transformed by the Park's transform, and then the Park's Vector Pattern are obtained, Usually this pattern is formed an ellipse, so a proper threshold value of distortion ratio(the ratio of the shortest axis and longest axis of ellipse) is suggested for winding faults diagnosis.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.645-648
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• 2003

Induction motors are a critical component of industrial processes. Sudden failures of such machines can cause the heavy economical losses and the deterioration of system reliability. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and the diagnosis of system are 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 analyses the motor's supply current. since this diagnoses faults of the motor. The diagnostic algorithm is based on the principal component analysis(PCA), and the diagnosis system is programmed by using LabVIEW and MATLAB.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.6 no.1
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• pp.1-11
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• 2000

In optimum design of packaging container for bulk materials, minimum board area, compression performance and distribution efficiency must be considered. In this study, mathematical models for minimum board area (RMA), compression strength (CS) and maximum compression strength per unit board area (MCSA) of container as algorithm for optimum design of packaging conatiner for bulk materials were developed as follows : RMA=f(V,D), ${\alpha}_{RMA}=f(V,D)$, MCSA=f(V,D), and ${\alpha}_{MCSA}=f(V,D)$. In order to develop these models, compression test according to various dimensions of container and response surface analysis for minimum board area, compression strength, and maximum compression strength per unit board area of container were carried out. In developed models, volume and depth of container were principal independent variables. Through the verified results for these models, optimum design of packaging container on the design conditions and limit conditions was possible. These models might be used in developing optimum design software of packaging container for bulk materials.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.305-307
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• 2006

기존에 사용되어 온 진동데이터를 이용한 유도전동기 고장진단 기법은 유도전동기의 전기적 결함을 파악하기 어렵고 특정 고장의 경우 유사한 진동주파수를 포함하고 있어 정확한 고장진단이 어렵다. 본 논문에서는 유도전동기 고장진단 시스템을 구현하기 위해 기존의 진동데이터 분석에 전류 분석기법 중의 하나인 MCSA(Motor Current Signature Analysis)기법을 추가하여 유도전동기 예지보전시스템의 신뢰성을 향상시켰다. 구현된 시스템의 신뢰성을 검증하기 위해 유도전동기의 고장진단을 위한 실험환경을 구축하고 진동데이터만을 이용하여 얻어진 고장진단 결과와 전류데이터 분석을 병행하여 얻어진 고장진단 결과를 비교 분석하였다.

• Proceedings of the KIEE Conference
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• 2001.04a
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• pp.19-21
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• 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.

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

• Proceedings of the KSR Conference
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• 2003.10c
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• pp.529-534
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• 2003

Within industry induction motors have a broad application area to drive pumps, fans, elevators and electric trains. Sudden failures of such machines can cause the heavy economical losses and the deterioration of system reliability. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and the diagnosis of system are 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 motor's supply current, since this diagnoses faults of the motor. The diagnostic algorithm is based on the principal component analysis(PCA), and the diagnosis system is programmed by using LabVIEW and MATLAB.

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