• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4774-4796
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• 2018

Wireless sensor networks are composed of a large number of inexpensive and tiny sensors used in different areas including military, industry, agriculture, space, and environment. Fault tolerance, which is considered a challenging task in these networks, is defined as the ability of the system to offer an appropriate level of functionality in the event of failures. The present study proposed an intelligent throughput descent and distributed energy-efficient mechanism in order to improve fault tolerance of the system against soft and permanent faults. This mechanism includes determining the intelligent neighborhood radius threshold, the intelligent neighborhood nodes number threshold, customizing the base paper algorithm for distributed systems, redefining the base paper scenarios for failure detection procedure to predict network behavior when running into soft and permanent faults, and some cases have been described for handling failure exception procedures. The experimental results from simulation indicate that the proposed mechanism was able to improve network throughput, fault detection accuracy, reliability, and network lifetime with respect to the base paper.

• Proceedings of the KSR Conference
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• 2000.05a
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• pp.330-335
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• 2000

Faults detection and containment requirements are typically allocated from a top-level specification as a percentage of total faults detection and containment, weighted by failure rate. This faults detection and containments are called as a fault coverage. The fault coverage requirements are typically allocated identically to all units in the system, without regard to complexity, cost of implementation or failure rate for each units. In this paper a simple methodology and mathematical model to support the allocation of system fault coverage rates to lower-level units by considering the inherent differences in reliability is presented. The models are formed as a form of constrained optimization. The objectives and constraints are modeled as a linear form and this problems are solved by linear programming. It is identified by simulation that the proposed solving methods for these problems are effective to such requirement allocating.

• Corrosion Science and Technology
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• v.18 no.6
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• pp.277-284
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• 2019

External corrosion control of buried pipe can be achieved by the combination of barrier coating and cathodic protection. Coating damage and deterioration can be induced by many reasons; damage during handling and laying, enhanced failure at low temperatures, failure during commissioning and operation, disbanding due to inadequate surface cleaning, rock penetration during installation and service etc. This work focused on the effect of survey conditions on the reliability of coating flaw detection of buried pipes. The effects of applied voltage and anode location on the detection reliability of coating flaw of buried pipe in soil with the resistivity of ca. 25.8 kΩ·cm were discussed. Higher applied voltage increased the detection reliability, regardless of buried depth, but deeper burial depth reduced the reliability. The location of the anode has influenced on the detection reliability. This behaviour may be induced by the variation of current distribution by the applied voltage and buried depth. From the relationship between the applied voltage and reliability, the needed detection potential to get a desire detection reliability can be calculated to get 100% detection reliability using the derived equation.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.143-146
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• 2005

The software reliability growth depends on the testing time because the failure rate varies whether it is long or not. On the other hand, it might be difficult to reduce failure rate for most of the cases are not available for debugging during operational phase, hence, there are some literatures to study that the failure rate is uniform throughout the operational time. The failure rate reduces and the reliability grows with time regardless of debugging. As a result, the products reliability varies with the time duration of these products in point of customer view. The reason of this is that it accumulates the products experience, studies the exact operational method, and then finds and takes action against the fault circumstances. I propose the simple model to represent this status in this paper.

• Journal of the Korean Society of Safety
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• v.20 no.3 s.71
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• pp.1-8
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• 2005

The industrial induction motor is widely used in the rotating electrical machine for the transmission of power. It is very reliable equipment, but it could lead to the loss of production and lift when failure occurs. Therefore, the failure data is acquired and analyzed by attaching an exclusive instrument to existing induction motor. However, these instruments could lead to side effects, increasing the production costs, because they are very expensive. The purpose of this study is the development of an induction motor bearing failure diagnosis system constructed using LabVIEW which can be supplied the kernelled function, process monitoring and current signature analysis. In addition, the availability and reasonability of the constructed system was examined for an induction motor with failure defects in outer raceway and ball bearing. From the results, it shows that failure diagnosis system constructed is useful for real-time monitoring with detection of bearing defects over the web.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.306-311
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• 2016

Software reliability in the software development process is an important issue. Infinite failure NHPP software reliability models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, reliability software cost model considering logarithmic and exponential fault detection rate based on observations from the process of software product testing was studied. Adding new fault probability using the Goel-Okumoto model that is widely used in the field of reliability problems presented. When correcting or modifying the software, finite failure non-homogeneous Poisson process model. For analysis of software reliability model considering the time-dependent fault detection rate, the parameters estimation using maximum likelihood estimation of inter-failure time data was made. The logarithmic and exponential fault detection model is also efficient in terms of reliability because it (the coefficient of determination is 80% or more) in the field of the conventional model can be used as an alternative could be confirmed. From this paper, the software developers have to consider life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.5
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• pp.449-455
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• 2015

Built-In-Test(hereafter: BIT) is necessary functionality for aircraft flight safety and it requires a high failure detection capacity of more than 95 % in the case of avionics equipment. The BIT coverage analysis is needed to make sure that BIT meets its fault diagnosis capability. FMECA is used a lot of for the BIT coverage analysis. However, in this paper, the BIT coverage analysis based on electronic components is introduced to minimize the analytical error. Further, by applying the failure mode of the electronic components and excluding electronic components that do not affect flight safety, the BIT coverage analysis can be more accurate. Finally, BIT demo was performed and it was confirmed that the performance of the actual BIT matches the analysis of BIT performance.

• Journal of the Korean Society of Safety
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• v.30 no.5
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• pp.108-113
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• 2015

Plastic injection moulding machine is widely used for many industrial field. It is classified into mandatory safety certification machinery in Industrial Safety and Health Act because of its high hazard. In order to prevent industrial accidents by plastic injection moulding machine, it is necessary for designer to identify hazardous factors and assess the failure modes to mitigate them. This study tabulates the failure modes of main parts of plastic injection moulding machine and how their failure has affect on the machine being considered. Failure Mode & Effect Analysis(FMEA) method has been used to assess the hazard on plastic injection moulding machine. Risk and risk priority number(RPN) has been calculated in order to estimate the hazard of failures using severity, probability and detection. Accidents caused by plastic injection moulding machine is compared with the RPN which was estimated by main regions such as injection unit, clamping unit, hydraulic and system units to find out the most dangerous region. As the results, the order of RPN is injection unit, clamping unit, hydraulic unit and system units. Barrel is the most dangerous part in the plastic injection moulding machine.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.199-210
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• 2008

Acoustic emission(AE)/Microseimsic(MS) activities are low-energy seismic events associated with a sudden inelastic deformation such as the sudden movement of existing fractures, the generation of new fractures or the propagation of fractures. These events rapidly increase before major failure and happen within a given rock volume and radiate detectable seismic waves. The main difference between AE and MS signals is that the seismic motion frequencies of AE signals are higher than those of MS signals. As the failure of geotechnical structures usually happens as a high velocity and small displacement, it is not easy to determine the precursor and initiation stress level of failure in displacement detection method. To overcome this problem, AE/MS techniques for detection of structure failure and damage have recently adopt in civil engineering. In this study, AE/MS monitoring system, which consist of sensor, data acquisition and operation program, is constructed with domestic technology. To verify and optimize the developed system, we are now carrying out the field application at an underground research laboratory and the developed AE/MS monitoring will be used in detecting of seismic events with various scales.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.123-131
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• 2020

There have been a lot of studies in the past for the method of predicting the failure of a machine, and recently, a lot of researches and applications have been generated to diagnose the physical condition of the machine and the parts and to calculate the remaining life through various methods. Survival models are also used to predict plant failures based on past anomaly cycles. In particular, special machine that reflect the fluid flow and process characteristics of chemical plants are connected to hundreds or thousands of sensors, so there are not many factors that need to be considered, such as process and material data as well as application of derivative variables. In this paper, the data were preprocessed through time series anomaly detection based on unsupervised learning to predict the abnormalities of these special machine. Next, clustering results reflecting clustering-based data characteristics were applied to produce additional variables, and a learning data set was created based on the history of past facility abnormalities. Finally, the prediction methodology based on the supervised learning algorithm was applied, and the model update was confirmed to improve the accuracy of the prediction of facility failure. Through this, it is expected to improve the efficiency of facility operation by flexibly replacing the maintenance time and parts supply and demand by predicting abnormalities of machine and extracting key factors.