• Journal of Electrical Engineering and Technology
• /
• v.9 no.1
• /
• pp.37-44
• /
• 2014

This paper proposes a new diagnosis algorithm to detect broken rotor bars (BRBs) faults in induction motors. The proposed algorithm is composed of a frequency signal dimension order (FSDO) estimator and a fault decision module. The FSDO estimator finds a number of fault-related frequencies in the stator current signature. In the fault decision module, the fault diagnostic index from the FSDO estimator is used depending on the load conditions of the induction motors. Experimental results obtained in a 75 kW three-phase squirrel-cage induction motor show that the proposed diagnosis algorithm is capable of detecting BRB faults with an accuracy that is superior to a zoom multiple signal classification (ZMUSIC) and a zoom estimation of signal parameters via rotational invariance techniques (ZESPRIT).

• 한국신재생에너지학회:학술대회논문집
• /
• 2011.11a
• /
• pp.139.1-139.1
• /
• 2011

Electric vehicle use independent electricity of high voltage. if isolation of electricity is destructed, devices and people are considerably damaged. Therefore, detection of ground fault is necessary for electric vehicle. As the existing detection method of ground fault can not detect ground fault when isolation of both positive side and negative side of electricity is destructed, and change of voltage of electricity. This paper proposed detection method for ground fault of both two sides of electricity and change of voltage. The proposed method is verified by analysis of equivalent circuit.

• International Journal of Aeronautical and Space Sciences
• /
• v.7 no.1
• /
• pp.73-83
• /
• 2006

In this paper, a redundancy management system for aircraft is studied, and fault detection and isolation algorithms of inertial sensor system are proposed. Contrary to the conventional aircraft systems, UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional fault detection and isolation (FDI) method cannot isolate multiple faults in a triple redundancy system. In this paper, two FDI techniques are proposed. First, hardware based FDI technique is proposed, which combines a parity equation approach with a wavelet based technique. Second, analytic FDI technique based on the Kalman filter is proposed, which is a model-based FDI method utilizing the threshold value and the confirmation time. To provide the reference value for detecting the fault, residuals are calculated using the extended Kalman filter. To verify the effectiveness of the proposed FDI methods, numerical simulations are performed.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.98.3-98
• /
• 2001

The research for detecting of insulating deterioration in transformer has been studied from long ago. Analysis method of combustible gas, which is included in insulating oil, has been widely used in detection of transformer pre-fault detection due to the effectiveness of its method. Recently the fault effect of the large transformer is very critical in a power system, therefore the on-line monitoring and diagnostic system is needed. In addition, the more accurate method of detecting a Partial Discharge (PD) location should be developed. For preventive maintenance against discharge failures, it is important not only to detect the discharges, but also to accurately estimate their positions. However ...

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2002.05a
• /
• pp.453-459
• /
• 2002

In this paper. the correlation among vibration. wear and temperature are experimentally investigated when rubbing is caused by static and dynamic forces. Each measurement reflects the characteristics of the system and is useful in detecting and diagnosing the current status of rotating machinery. For experiment, the rotor system with lubricating equipment such as trochoid pump, oil tank and wear detecting sensor is implemented to simulate the rubbing condition. Experimental results show that significant change in wear quantity can be notified when vibration signal is changed by rubbing. The results can be applied to system monitoring and fault diagnosis in rotating machinery.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1829-1846
• /
• 2021

Transient faults occur in computation units of a processor, which can cause control flow errors (CFEs) and compromise system reliability. The software-based methods perform illegal control flow detection by inserting redundant instructions and monitoring signature. However, the existing methods not only have drawbacks in terms of performance overhead, but also lack of configurability. We propose a configurable approach CCFCA for detecting CFEs. The configurability of CCFCA is implemented by analyzing the criticality of each region and tuning the detecting granularity. For critical regions, program blocks are divided according to space-time overhead and reliability constraints, so that protection intensity can be configured flexibly. For other regions, signature detection algorithms are only used in the first basic block and last basic block. This helps to improve the fault-tolerant efficiency of the CCFCA. At the same time, CCFCA also has the function of solving confusion and instruction self-detection. Our experimental results show that CCFCA incurs only 10.61% performance overhead on average for several C benchmark program and the average undetected error rate is only 9.29%. CCFCA has high error coverage and low overhead compared with similar algorithms. This helps to meet different cost requirements and reliability requirements.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2007.11a
• /
• pp.1401-1409
• /
• 2007

This paper presents a detecting technique for the improvement in quality by appling the various vibrational characteristics theory. The object of this study is to objectively point out faulty gear by developing the program which can be used to analyze and predict the vibrational characteristics caused by gear wear, deformation and nick of auto-transmission. The fault detection methods by vibrational signal analysis of gear have been progressed in the various fields of industry. These methods have the advantage of being easy to attach the accelerometer without discontinuance of the structure. But not all the methods are efficient for finding early faults. So in the thesis, we completed development of the inspection system of vibration by appling the most efficient detecting methods and verified the system's reliability through experiments.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.12 no.4
• /
• pp.21-27
• /
• 1975

In this paper, a procedure for deriving of multiple fault detection test sets is presented for fan-out reconvergent combinational logic networks. A fan-out network is decomposed into a set of fan-out free subnetworks by breaking the internal fan-out points, and the minimal detecting test sets for each subnetwork are found separately. And then, the compatible tests amonng each test set are combined maximally into composite tests to generate primary input binary vectors. The technique for generating minimal test experiments which cover all the possible faults is illustrated in detail by examples.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.18 no.1
• /
• pp.47-56
• /
• 2008

This paper presents a detecting technique for the improvement in quality by appling the various vibrational characteristics theory. The object of this study is to objectively point out faulty gear by developing the program which can be used to analyze and predict the vibrational characteristics caused by gear wear, deformation and nick of auto-transmission. The fault detection methods by vibrational signal analysis of gear have been progressed in the various fields of industry. These methods have the advantage of being easy to attach the accelerometer without discontinuance of the structure. But not all the methods are efficient for finding early faults. So in the thesis, we completed development of the inspection system of vibration by appling the most efficient detecting methods and verified the system's reliability through experiments.

• 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.