• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1231-1234
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• 2003

A sensor working in outdoor may generate some faulty signal owing to dust and high temperature. This paper describes an intelligent sensor system and controller which has a reconstruction mechanism for faulty signal. The faulty signals are dievided into two types as linear distortion and non linear distortion, respectively. The linear distorted signal is due to dust, and non linear distorted signal is due to physical breakdown of sensor or high temperature. These distorted signal have been reconstructed by the proposed method based on polynomial regression method and principal component analysis approach.. The proposed method has been applied to sun tracking system working in outdoor. For a robust and precision control of sun tracker, a fuzzy controller was also proposed. The fuzzy controller controls the tracker by using the collected sensor signal. The tolerance of the position control is within 1.5 degree. To show the validity of the developed system, some experiments in the field were illustrated.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.10
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• pp.965-975
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• 2005

In the case of the fault in stator windings of a high voltage motor. it facilitates certain destructive characteristics in insulations. This will result in a decreased reliability in power supplies and will prevent the generation of electricity, which will result in huge economic losses. This study simulates motor windings using normal windings and four faulty windings for an actual fault in stator winding of a high voltage motor. The partial discharge signals produced in each faulty winding were measured using an 80 PF epoxy/mica coupler sensor. In order to quantified signal waves its a way of feature extraction for each faulty signal, the signal wave of winding was quantified to measure the degree of skewness shape and kurtosis, which are both types of statistical parameters, using a discrete wavelet transformation method for each faulty type. Wave types present different types lot each faulty type, and the skewness and kurtosis also present different quantified values. The result of feature extraction was used as a preprocessing stage to identify a certain fault in stater windings. It is evident that the type of faulty signals can be classified from the test results using faulty signals that were randomly selected from the signal, which was not applied in the training after the training and learning period, by applying it to a back-propagation algorithm due to the supervising and learning method in a neural network in order to classify the faulty type. This becomes an important basis for studying diagnosis methods using the classification of faulty signals with a feature extraction algorithm, which can diagnose the fault of stator windings in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.311-314
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• 2003

This paper describes a virtual instrument system with faulty sensor reconstruction mechanism based on personal computer. This system consists of sensor control board using 16bit RISC machine, error signal reconstruction algorithm based on principal component analysis and auto tunned GUI interface according to the attached sensors. USB module is used for fast communication between PC and sensor controller. To show the veridity of the proposed system, the proposed system was applied to the developed sun tracker with 8 solar sensors.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1999-2005
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• 2005

Collaboration in wireless sensor networks must be fault-tolerant due to the harsh environmental conditions in which such networks can be deployed. This paper focuses on finding signal processing algorithms for collaborative target detection based on the generalized approach to signal processing in the presence of noise that are efficient in terms of communication cost, precision, accuracy, and number of faulty sensors tolerable in the wireless sensor network. Two algorithms, namely, value fusion and decision fusion constructed according to the generalized approach to signal processing in the presence of noise, are identified first. When comparing their performance and communication overhead, decision fusion is found to become superior to value fusion as the ratio of faulty sensors to fault free sensors increases. The use of the generalized approach to signal processing in the presence of noise under designing value and decision fusion algorithms in wireless sensor networks allows us to obtain the same performance, but at low values of signal energy, as under the employment of universally adopted signal processing algorithms widely used in practice.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.3
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• pp.113-120
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• 2018

In this study, we proposed a monitoring system for identifying and handling faulty sensing stream data on manufacturing equipments where low-cost sensors can be safely used. Low cost sensors will lessen the cost of implementing distributed monitoring system, but suffer from sensor noises and inaccurate sensed data. Therefore, a distributed monitoring system with low cost sensors should identify faulty signal data as either of sensor fault or machine fault, and filter out faulty signals from sensing fault. To this end, we adopted a fourier transform based diagnostic approach mixed with a weighed moving averaging method, in order to identify faulty signals. We measured how effective our approach is and found out our approach can filter out one-third faulty signals from our experimental environment. In addition, we attached wireless communication modules to reduce sensor and network installation cost. To handle massive sensor data efficiently, we employed unstructured data format with NoSQL based database.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.321-328
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• 1998

A controller and sensor fault tolerant system jot a steam generator is designed with fuzzy logic. A structure of the : proposed fault tolerant redundant system is composed of a supervisor and two fuzzy weighting modulators. A supervisor alternatively checks a controlled and a sensor induced performances to identify Which Part, a controller or a sensor, is faulty. In order to analyze controller induced performance both an error and a charge in error of the system output an chosen as fuzzy variables. The fuzzy logic jot a sensor induced performance uses two variables : a deviation between two sensor outputs and its frequency, Fuzzy weighting modulator generates an output signal compensated for faulty input signal. Simulations show that the : proposed fault tolerant control scheme jot a steam generator regulates welt water level by suppressing fault effect of either controllers or sensors. Therefore through duplicating sensors and controllers with the proposed fault tolerant scheme, both a reliability of a steam generator control and sensor system and that of a power plant increase even mote.

• Journal of Power System Engineering
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• v.14 no.2
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• pp.40-47
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• 2010

This paper proposes a fault detection system to detect the strip rupture in six-high stand Cold Rolling Mills based on transient current signal of an electrical motor. For this work, signal smoothing technique is used to highlight precise feature between normal and fault condition. Subtracting the smoothed signal from the original signal gives the residuals that contains the information related to the normal or faulty condition. Using residual signal, discrete wavelet transform is performed and acquire the signal presenting fault feature well. Also, feature extraction and classification are executed by using PCA, KPCA and SVM. The actual data is acquired from POSCO for validating the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2530-2547
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• 2015

In the recent years, femtocell technology has received a considerable attention due to the ability to provide an efficient indoor wireless coverage as well as enhanced capacity. However, under the spectrum sharing between femtocell user equipment (FUEs) and the owner of spectrum macrocell user equipment (MUEs), both may experience higher uplink interference to each other. This paper proposes a novel distributed power control algorithm for the interference management in two-tier femtocell networks. Due to the assignment of licensed radio frequency to the outdoor macrocell users, the access priority of MUEs should be higher than FUEs. In addition, the quality of service (QoS) of MUEs that is expressed in the target signal-to-interference-plus-noise ratio (SINR) must always be achieved. On the other hand, we consider an efficient QoS provisioning cost function for the low-tier FUEs. The proposed algorithm requires only local information and converges even in cases where the frontiers of available power serve the target SINRs impossible. The advantage of the algorithm is the ability to implement in a distributed manner. Simulation results show that the proposed algorithm based on our cost function provides effective resource allocation and substantial power saving as compared to the traditional algorithms.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.25-32
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• 2010

The paper proposes a hierarchical fault detection method for the high voltage equipment using a microphone array which detects the location of fault and the thermal imaging and CCD cameras which verifies the fault and stores the image, respectively. There are partial arc discharges on the faulty insulators, which generates a specific pattern of sound. Detecting the signal using the microphone array, the location of the faulty insulator can be estimated. The 6th band-pass filter was applied to remove noise signal from wind or external influence. When the mobile robot carries the thermal and CCD cameras to the possible place of the fault insulator, the fault insulators or power transmission wires can be detected by the thermal images, which are caused by the aging or natural erosion. Finally, the CCD camera captures the image of the fault insulator for the record. The detection scheme of fault location using the microphone array and the thermal images have been proved to be effective through the real experiments. As a result of this research, it becomes possible to use a mobile robot with the integrated sensors to detect the fault insulators instead of a human being.

• Journal of Power Electronics
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• v.6 no.1
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• pp.8-17
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• 2006

In this paper, we propose a fault-tolerant control system for the position control and vibration suppression of a flexible arm robot. The proposed control system has a strain gauge sensor signal observer based on a reaction force observer and detects a fault by monitoring an estimated error. In order to improve the estimation accuracy, the plant parameters included in the sensor signal observer are updated by using the strain gauge sensor signal in normal time through the adaptive law. After fault detection, the proposed control system exchanges the faulty sensor signal for the estimated one and switches to a fault mode controller so as to maintain the stability and the control performance. We confirmed the effectiveness of the proposed control system through several experiments.