• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.5
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• pp.423-430
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• 2009

Recently as the inactive response characteristics of the existing RCD used on low voltage power distribution system, so control of overload and electric short circuit faults, major causes of electrical fires, are not enough. Therefore, this paper confirms the unreliability of the existing RCD by electrical fault simulator and proposes a EFDPD by using semiconductor switching devices and a high precision current sensor (namely, reed switch) for the prevention of electrical disasters in low voltage power distribution system caused by overload or electric short circuit faults. The sensitive reed switch in the proposed EFDPD exactly detects the increased magnetic flux with the overload or the short current caused by a number of electrical faults, and the following, the self circuit breaker in EFDPD rapidly cuts off the system. The proposed EFDPD confirms the excellent characteristics in response velocity and accuracy in comparison with the conventional circuit breaker through various operation performance analysis. The proposed EFDPD can also prevent electrical disasters, like as electrical fires, which resulted from the malfunction and inactive response characteristics of the existing RCD.

• Fire Science and Engineering
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• v.23 no.3
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• pp.40-47
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• 2009

Nowadays the diversity and large-capacity of electric appliances are strong effect on electrical fires augment in an alarming way. But, as the inactive response characteristics of the existing RCD (Residual Current protective Device) used on low voltage power distribution system, so control of overload and electric short circuit faults, major causes of electrical fires, are not enough. Therefore, this paper is confirmed the unreliability of the existing RCD by electrical fault simulator and is proposed a Electrical Fire Disaster Prevention Device (EFDPD) by using a high precision current sensor (namely, reed switch) for the prevention of electrical disasters in low voltage power distribution system caused by overload or electric short circuit faults. The sensitive reed switch in the proposed EFDPD exactly detects the increased magnetic flux with the overload or the short current caused by a number of electrical faults, and the following, the EFDPD has double protection function which operates self circuit breaker or rapidly cuts off the existing RCD. The proposed EFDPD is confirmed the excellent characteristics in response velocity and accuracy in comparison with the conventional circuit breaker through various operation performance analysis. The proposed EFDPD can also prevent electrical disaster, like as electrical fires, which resulted from the malfunction and inactive response characteristics of the existing RCD.

• Korean Chemical Engineering Research
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• v.46 no.2
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• pp.233-247
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• 2008

Process monitoring technology is able to detect the faults and the process changes which occur in a process unpredictably, which makes it possible to find the reasons of the faults and get rid of them, resulting in a stable process operation, high-quality product. Statistical process monitoring method based on data set has a main merit to be a tool which can easily supervise a process with the statistics and can be used in the analysis of process data if a high quality of data is given. Because a real process has the inherent characteristics of nonlinearity, non-Gaussianity, multiple operation modes, sensor faults and process changes, however, the conventional multivariate statistical process monitoring method results in inefficient results, the degradation of the supervision performances, or often unreliable monitoring results. Because the conventional methods are not easy to properly supervise the process due to their disadvantages, several advanced monitoring methods are developed recently. This review introduces the theories and application results of several remarkable monitoring methods, which are a nonlinear monitoring with kernel principle component analysis (KPCA), an adaptive model for process change, a mixture model for multiple operation modes and a sensor fault detection and reconstruction, in order to tackle the weak points of the conventional methods.

• Journal of Korean Society of Transportation
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• v.13 no.4
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• pp.133-151
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• 1995

The collective of highly reliable traffic data is necessary for traffic signal control. This study is to test application of RTMS sensor to traffic signal control. In order to find out the possibility of its application th traffic signal control, 5 types of experiments were performed. The major findings are as follows ; -The detection are a has been changing according to degree and gain. -At the results of experiments for interference are a measure, Degree 60 is stable condition. -At the results of reliability test for volume and speed. the error rate decreases as speed increases and that of Zone 1 is lower than that of Zone 3. -Two modes are set up for reliability test of traffic volume. It founds that the detection reliability of the stopped vehicles are higher than that of the passing vehicles at sidefire-intersection mode. It founds that the results are vice-versa at sidefire-highway mode. Conclusively, this sensor cannot directly apply to colection of traffic data for traffic signal control. However, this sensor can be substituted for a loop detector which is used popularly for signal control, and freeway traffic control if above faults are made up.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.899-904
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• 2011

Inspections and diagnoses of corona discharge are important in order to prevent electrical faults of external insulation in power systems. This paper studies a measurement of ultra-violet rays(UV) strength of corona discharges on insulators using a UV sensor with an optic lens. The data has been compared with the images of a UV camera. The UV sensor estimated that DC voltage needed to be set at 700V for accurate data analysis of the properties of UV detected during corona discharge. UV was generated at 60kV when the corona discharge occurred. UV strength and images of UV increased at a high voltage. The image area of the UV using a UV camera and the detection of UV using a UV sensor have shown, that the polymer insulator mounted on a live part must be checked when the applied voltage on the good polymer insulator is greater than 37.5% of its breakdown voltage.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.116.1-116
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• 2001

In the near future, drive-by-wire systems will replace mechanical systems of vehicles. Since there would be no mechanical redundancy in the x-by-wire subsystem, it needs to improve the reliability of the system using fault diagnosis of sensors and actuators. This paper proposes a Kalman filter based fault diagnosis method for the vehicle with the drive-by-wire system, which includes steer-by-wire, brake-by-wire and throttle-by-wire systems. We will show that the proposed method is successful in fault detection and isolation for single sensor/actuator faults of the vehicle system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.2
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• pp.35-44
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• 1994

In this paper, an observer for linear discrete systems with unknown inputs is presented. The suggested observer can estimate the system state vector and the unknown inputs simultaneously. As an extension of the observer, a new fault diagnosis observer for linear discrete systems with structured uncertainty is presented. The fault diagnosis observer can detect and identify the actuator and the sensor faults as well. The stability conditionsand the design methods of the each observers are presented and the usability of the observers is shown via numerical examples.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.185-195
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• 2018

As machines have been automated in the field of industries in recent years, it is a paramount importance to manage and maintain the automation machines. When a fault occurs in sensors attached to the machine, the machine may malfunction and further, a huge damage will be caused in the process line. To prevent the situation, the fault of sensors should be monitored, diagnosed and classified in a proper way. In the paper, we propose a sensor fault detection scheme based on SVM and CNN to detect and classify typical sensor errors such as erratic, drift, hard-over, spike, and stuck faults. Time-domain statistical features are utilized for the learning and testing in the proposed scheme, and the genetic algorithm is utilized to select the subset of optimal features. To classify multiple sensor faults, a multi-layer SVM is utilized, and ensemble technique is used for CNN. As a result, the SVM that utilizes a subset of features selected by the genetic algorithm provides better performance than the SVM that utilizes all the features. However, the performance of CNN is superior to that of the SVM.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.75-79
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• 2010

Wireless sensor networks (WSN) are widely used in many applications. WSN acquires the data of surrounding environments with sensors attached to each node. It is important to design sensor networks that can communicate energy-efficiently as well as to get sensor readings with high accuracy. In this paper, we propose a novel routing scheme that assures high accuracy and significantly reduces data transmission costs in WSN with faults. First, we organize a number of network topologies randomly for routing sensor readings to the base station. Because every sensor node is connected each other with a single path, redundant transmissions are not incurred. It can reduce unnecessary transmissions and guarantee final sensor readings with high accuracy. To show the superiority of our scheme, we compare it with an existing multi-path routing scheme. In the result, our scheme has similar accuracy as the existing scheme and reduces unnecessary data transmissions by about 70% over the existing technique.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2335-2339
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• 2003

To prevent the critical situation due to the fault in the aircraft sensor system, the fault tolerant system with triple or quadruple redundancy can be made. However, if the faults are occurred in two or more than sensors simultaneously, the conventional fault detection process, such as cross-channel monitoring, may give the wrong fault alarm. For this case, we can detect the fault by estimating the state vector based on the system dynamics model, which is nonlinear for aircraft. In this paper, we propose the unscented Kalman filter to estimate the nonlinear state vector. This filter utilizes the so-called unscented transformation of sigma points featured the statistical characteristics of the random variable. For verification, we perform the simulations for F-16 aircraft with accelerometers, gyros, GPS and air data system.