• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.4
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• pp.271-276
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• 2021

Arc fault detector based on multilevel DWT with analysis of high-frequency noise components over 100 kHz is proposed in this study to improve the performance in detecting serial arcs and distinguishing them from inverter noise in PV systems. PV inverters generally operate at a frequency range of 20-50 kHz for switching operation and maximum power tracking control, and the effect of these frequency components on the signal for arc detection leads to negative arc detection. High-speed ADC and multilevel DWT are used in this study to analyze frequency components above 100 kHz. Such high frequency components are less influenced by inverter noise and utilized to detect as well as separate DC series arc from inverter noise. Arc detectors identify the input current of PV inverters using a Rogowski coil. The sensed signal is filtered, amplified, and used in 800kSPS ADC and DWT analysis and arc occurrence determination in DSP. An arc detection simulation facility in UL1699B was constructed and AFD tests the proposed detector were conducted to verify the performance of arc detection and performance of distinction of the negative arc. The satisfactory performance of the arc detector meets the standard of arc detection and extinguishing time of UL1699B with an arc detection time of approximately 0.11 seconds.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• International Journal of Reliability and Applications
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• v.2 no.3
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• pp.147-160
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• 2001

The reliability of computer software is of prime importance for all developers of software. The complicated nature of detecting and removing faults from software has led to a plethora of models for reliability growth. One of the most basic of these is the Jelinski Moranda model, where it is assumed that there are N faults in the software, and that in testing, bugs (or faults) are encountered (and removed when defected) according to a stochastic process at a rate which at a given point in time is proportional to the number of bugs remaining in the system. In this research, we consider the possibility that imperfect repair may occur in any attempt to remove a detected bug in the Jelinski Moranda model. We let p represent the probability that a fault which is discovered or detected is actually perfectly repaired. The possibility that the probability p may differ before and after release of the software is also considered. The distribution of both the number of bugs detected and perfectly repaired in a given time period is studied. Cost models for the development and release of software are investigated, and the impact of the parameter p on the optimal release time minimizing expected costs is assessed.

• Journal of Power Electronics
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• v.15 no.3
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• pp.806-818
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• 2015

Based on the inherent relationship between dc-bus voltage and grid feeding active power, two dc-bus voltage regulators with different references are adopted for a grid-connected PV inverter operating in both normal grid voltage mode and low grid voltage mode. In the proposed scheme, an additional dc-bus voltage regulator paralleled with maximum power point tracking controller is used to guarantee the reliability of the low voltage ride-through (LVRT) of the inverter. Unlike conventional LVRT strategies, the proposed strategy does not require detecting grid voltage sag fault in terms of realizing LVRT. Moreover, the developed method does not have switching operations. The proposed technique can also enhance the stability of a power system in case of varying environmental conditions during a low grid voltage period. The operation principle of the presented LVRT control strategy is presented in detail, together with the design guidelines for the key parameters. Finally, a 3 kW prototype is built to validate the feasibility of the proposed LVRT strategy.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
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• 2002.05a
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• pp.387-396
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• 2002

Batch processes are a significant class of processes in the process industry and play an important role in the production of high quality speciality materials. Examples include the production of semiconductors, chemicals, pharmaceuticals, and biochemicals. With on-line sensors connected to most batch processes, massive amounts of data are being collected routinely during the batch on easily measured process variables such as temperatures, pressures, and flowrates. In this paper, multivariate SPC charts for on-line monitoring of the progress of new batches are developed which utilize the information in the on-line measurements in real-time. We propose the formation of statistical model which describes the normal operation of a batch at each time interval during the batch operation. An on-line monitoring scheme based on the proposed method can handle both cross-correlation among process variables at any one time and auto-correlation over time. And the control limits for the monitoring charts are established from sound statistical framework unlike previous researches which use the external reference distribution. The proposed charts perform real-time, on-line monitoring to ensure that the batch is progressing in a manner that will lead to a high-quality product or to detect and indicate faults that can be corrected prior to completion of the batch. This approach is capable of tracking the progress of new batch runs, identifying the time periods in which the fault occurred and detecting underlying cause.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.10
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• pp.530-538
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• 2004

A electromagnetic waves are used for sensing in insulation diagnosis at electric machine or equipment. When it a method, waves are transformed into the FFT(Fast Fourier Transform); a kind of the process for data transformation. In a general way, a scientist use frequncy band 30[㎒]～l[㎓] to applied field. If we are measured high frequency band, we will need to a high capacity hardware. Also a antenna has a fault on atmospheric phenomena, outside environment and the like. In this paper We proposed new method for detecting electric equipment faulty state using only electric voltage which is generally measured in the electric and electronic field. It is called the Partition-FFT The analytic method is this first divide measured voltage waves into equal parts, second each deal with give effect to the FFT, finally each results deal with a graphic method and gather graphic. We are compare Partition-FFT with discharge form by tracking tester. As the result it demonstrated that the Partition-FFT is applicable.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.5
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• pp.68-74
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• 2001

This paper describes the new algorithm method for detecting abnormal causes within power transformers. Generally, the gas analysis has been proved the most confident method of many transformer diagnostics. The proposed algorithm is adapted to the international codes of IEC, Dornenburg, Gas Pattern including the DEPCO´s gas analysis method for the improvement of diagnostic efficiency. Specially, this algorithm is programmed by the tool of Element Expert developed Neuron DATA Inc. in USA. Also, it was confirmed that the developed algorithm is proved the confidence by the use of real data in fault power transformers.

• Journal of Mechanical Science and Technology
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• v.18 no.9
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• pp.1537-1548
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• 2004

This paper presents a novel diagnostic technique for monitoring the system conditions and detecting failure modes and precursors based on wavelet-packet analysis of external noise/vibration measurements. The capability is based on extracting relevant features of noise/vibration data that best discriminate systems with different noise/vibration signatures by analyzing external measurements of noise/vibration in the time-frequency domain. By virtue of their localized nature both in time and frequency, the identified features help to reveal faults at the level of components in a mechanical system in addition to the existence of certain faults. A prima-facie case is made via application of the proposed approach to fault detection in scroll and rotary compressors, although the methods and algorithms are very general in nature. The proposed technique has successfully identified the existence of specific faults in the scroll and rotary compressors. In addition, its capability of tracking the severity of specific faults in the rotary compressors indicates that the technique has a potential to be used as a prognostic tool.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.271-287
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• 2013

We propose a new multipath-based reliable routing protocol on MANETs, Multipath-based Reliable routing protocol with Fast-Recovery of failures (MRFR). For reliable message transmission, MRFR tries to find the most reliable path between a source and a destination considering the end-to-end packet reception reliability of the routes. The established path consists of a primary path that is used to transmit messages, and the secondary paths that are used to recover the path when detecting failures on the primary path. After establishing the path, the source transmits messages through the primary path. If a node detects a link failure during message transmission, it can recover the path locally by switching from the primary to the secondary path. By allowing the intermediate nodes to locally recover the route failure, the proposed protocol can handle the dynamic topological change of the MANETs efficiently. The simulation result using the QualNet simulator shows that the MRFR protocol performs better than other protocols in terms of the end-to-end message delivery ratio and fault-tolerance capability.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.5
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• pp.97-103
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• 2002

The assessment of the condition of a transformer winding which is suspected of having suffered short circuit damage can be difficult. Conventional test such as winding resistance, magnetic current or insulation resistance will only detect damage if a permanent electrical fault exists. Visual inspection of windings necessitates the removal of oil and in many cases only a very small proportion of the winding can be seen. We describe the characteristic of LVI test system and methods to detect the deformation of windings in the power transformers. As the front rise time of recurrent-surge generator pulse less than 1000 ㎱ and the peak value of pulse is about 500 V, we have the good results of detecting winding deformation in the LVI test of transformers.