• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.6
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• pp.873-878
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• 2002

Stator current spectrum by the fast Fourier transform (FFT) of current signals has been widely used for fault detection in induction motors. In this paper, we propose efficient rotor fault detection of Induction motors using stator current spectrum monitoring. The proposed method utilizes the mean absolute difference (MAD) between a Predetermined reference vector and a feature vector extracted from the stator current spectrum. Our proposed approach requires a smaller amount of computations when compared to fault detection algorithms based on neural networks, since it uses simple MAD criterion to detect rotor faults related broken rotor bars. Experimental results show that our proposed method can successively detect the rotor fault of the induction motor.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.90-93
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• 2014

In this paper, we have developed a new fault detection method based on vibration signal for rotor machinery. Generally, many methods related to detection of rotor fault exist and more advanced methods are continuously developing past several years. However, there are some problems with existing methods. Oftentimes, the accuracy of fault detection is affected by vibration signal change due to change of operating environment since the diagnostic model for rotor machinery is built by the data obtained from the system. To settle a this problems, we build a rotor diagnostic model by using feature residual based on vibration signal. To prove the algorithm's performance, a comparison between proposed method and the most used method on the rotor machinery was conducted. The experimental results demonstrate that the new approach can enhance and keeps the accuracy of fault detection exactly although the algorithm was applied to various systems.

• 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.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.827-838
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• 2023

Centrifugal pump is a key part of nuclear power plant systems, and its health status is critical to the safety and reliability of nuclear power plants. Therefore, fault diagnosis is required for centrifugal pump. Traditional fault diagnosis methods have difficulty extracting fault features from nonlinear and non-stationary signals, resulting in low diagnostic accuracy. In this paper, a new fault diagnosis method is proposed based on the improved particle swarm optimization (IPSO) algorithm-based variational modal decomposition (VMD) and relevance vector machine (RVM). Firstly, a simulation test bench for rotor faults is built, in which vibration displacement signals of the rotor are also collected by eddy current sensors. Then, the improved particle swarm algorithm is used to optimize the VMD to achieve adaptive decomposition of vibration displacement signals. Meanwhile, a screening criterion based on the minimum Kullback-Leibler (K-L) divergence value is established to extract the primary intrinsic modal function (IMF) component. Eventually, the factors are obtained from the primary IMF component to form a fault feature vector, and fault patterns are recognized using the RVM model. The results show that the extraction of the fault information and fault diagnosis classification have been improved, and the average accuracy could reach 97.87%.

• Journal of Power Electronics
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• v.5 no.1
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• pp.62-66
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• 2005

A simple fault correction method for rotor position detection of a brushless DC(BLDC) motor with trapezoidal back EMF(electromotive force) using a Hall effect latch unit is presented. The reason why the Hall effect latch unit does not operate properly during the startup of a BLDC motor is thoroughly explained. To solve this problem, a simple code change method and its hardware implementation issues are proposed and discussed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.2
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• pp.136-144
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• 1999

This paper deals with the fault detection problem in uncertain linear multivariable systems and its application. A robust fault detection method presented by Kim et a. (1998) for MIMO (Multi Input/Multi Output) systems has been adopted and applied to the twin rotor MIMO experimental setup using industrial DSP. The system identification problem is formulated for the twin rotor MIMO system and its parameters are estimated using experimental data. Based on the estimated parameters, some fault detection simulations are performed using the robust fault detection method, which shows that the preformance is satisfied.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.29-37
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• 2016

Fast and accurate fault diagnosis of the position sensor is of great significance to ensure the reliability as well as sensor fault tolerant operation of the Switched Reluctance Wind Generator (SRWG). This paper presents a fault diagnostic scheme for a SRWG based on the residual between the estimated rotor position and the actual output of the position sensor. Extreme Learning Machine (ELM), which could build a nonlinear mapping among flux linkage, current and rotor position, is utilized to design an assembled estimator for the rotor position detection. The data for building the ELM based assembled position estimator is derived from the magnetization curves which are obtained from Finite Element Analysis (FEA) of an SRWG with the structure of 8 stator poles and 6 rotor poles. The effectiveness and accuracy of the proposed fault diagnosis method are verified by simulation at various operating conditions. The results provide a feasible theoretical and technical basis for the effective condition monitoring and predictive maintenance of SRWG.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.232-239
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• 2008

The position sensors used in a magnetic bearing system are desirable to provide some degree of fault-tolerance as the rotor position is necessary for the feedback control to overcome the open-loop instability. In this paper, we propose an inductive position sensor that can cope with a partial fault in the sensor. The sensor has multiple poles which can be combined to sense the in-plane motion of the rotor. When a high-frequency voltage signal drives each pole of the sensor, the resulting current in the sensor coil contains information regarding the rotor position. The signal processing circuit of the sensor extracts this position information. In this paper, we used the magnetic circuit model of the sensor that shows the analytical relationship between the sensor output and the rotor motion. The multi-polar structure of the sensor makes it possible to introduce redundancy which can be exploited for fault-tolerant operation. The proposed sensor is applied to a magnetically levitated turbo-molecular vacuum pump. Experimental results validate the fault-tolerance algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.1
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• pp.132-137
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• 2006

The second part of paper related rotor failure is to evaluate that the axial magnetic flux measurement could be used as a tool of the condition monitoring system for the induction motor and to develope the diagnostic algorithm for the various fault in the electric motors. The magnetic leakage flux signal is captured by the flux coil located at the end of motor without the disturbance of the operation. And the signal is analyzed both time and frequency domain to detect the failure of the motor. Specific signature can be described in tin and frequency domain for each fault of the motor. The experimental test found that the rotor failures - broken rotor bar, broken end ing and rotor eccentricity, could be detected from the spectrum with high resolution. The method of detecting the rotor fault was found by analysing the specific frequency and the sideband of the rotor bar pass frequency from axial leakage flux spectrum. In addition the optimal flux coil and measuring equipment for the axial leakage flux measurement was verified and the diagnostic method for the detection of the rotor related failure was developed.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.54-63
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• 2016

A novel attitude tacking control method using Time Delay Control (TDC) scheme is developed to provide robust controllability of a rigid hexacopter in case of single or multiple rotor faults. When the TDC scheme is developed, the rotor faults such as the abrupt and/or incipient rotor faults are considered as model uncertainties. The kinematics, modeling of rigid dynamics of hexacopter, and design of stability and controllability augmentation system (SCAS) are addressed rigorously in this paper. In order to compare the developed control scheme to a conventional control method, a nonlinear numerical simulation has been performed and the attitude tracking performance has been compared between the two methods considering the single and multiple rotor faults cases. The developed control scheme shows superior stability and robust controllability of a hexacopter that is subjected to one or multiple rotor faults and external disturbance, i.e., wind shear, gust, and turbulence.