• Journal of Applied Reliability
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• v.14 no.4
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• pp.230-235
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• 2014

The failure modes of pneumatic directional control valves include leakage, wear of the spool seal, and sticking of the spool. Among them, the main failure mode of the valve is leakage. The leakage is caused by the wear of the spool seal. However, due to the characteristics of the seal material, the leakage rate is fluctuated a lot rather than constantly increased over time. If life analysis is performed using the first time data of leakage failure, predicted life cycles can be different from the real life cycles. This paper predicts life cycles of the pilot pneumatic directional control valve based on the three point moving average which considers the average of the fluctuating leakage rate.

• IE interfaces
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• v.25 no.4
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• pp.422-430
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• 2012

In this article, we introduced the estimation method by 'Safety Integrity Level'(SIL) for the criterion of safety assurance and performed a case study on a flame scanner. SIL requires probabilistic evaluation of each set of equipment used to reduce risk in a safety related system. FMEDA(Failure Modes, Effects and Diagnostic Analysis) method is widely used to evaluate the safety levels and provides information on the failure rates and failure mode distributions necessary to calculate a diagnostic coverage factor for a part or a component. Basically, two parameters resulting from FMEDA are used for SIL classification of the device : SFF(Safe Failure Fraction) and PFD(Probability of Failure on Demand). In this case study, it is concluded that the flame scanner is designed to fulfill the condition of SIL 3 in the aspect of SFF and PFD.

• 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 Advanced Navigation Technology
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• v.28 no.2
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• pp.216-224
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• 2024

This paper presents a method for analyzing the reliability of hardware electronic equipment, taking into account failures caused by radiation. Traditional reliability analysis primarily focuses on the wear out failure rate and often neglects the impact of radiation failure rates. We calculate the wear out failure rate through physics of failure analysis, while the radiation failure rate is semi-empirically estimated using the Verilog Fault Injection tool. Our approach aims to ensure reliability early in the development process, potentially reducing development time and costs by identifying circuit vulnerabilities in advance. As an illustrative example, we conducted a reliability analysis on the ISCAS85 circuit. Our results demonstrate the effectiveness of our method compared to traditional reliability analysis tools. This thorough analysis is crucial for ensuring the reliability of FPGAs in environments with high radiation exposure, such as in aviation and space applications.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.11
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• pp.94-101
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• 2020

In the age of industry 4.0, artificial intelligence is being widely used to realize machinery condition monitoring. Due to their excellent performance and the ability to handle large volumes of data, machine learning techniques have been applied to realize the fault diagnosis of different equipment. In this study, we performed the failure mode effect analysis (FMEA) of an aluminum electrolytic capacitor by using deep learning and big data. Several tests were performed to identify the main failure mode of the aluminum electrolytic capacitor, and it was noted that the capacitance reduced significantly over time due to overheating. To reflect the capacitance degradation behavior over time, we employed the Vanilla long short-term memory (LSTM) neural network architecture. The LSTM neural network has been demonstrated to achieve excellent long-term predictions. The prediction results and metrics of the LSTM and Vanilla LSTM models were examined and compared. The Vanilla LSTM outperformed the conventional LSTM in terms of the computational resources and time required to predict the capacitance degradation.

• Journal of the Earthquake Engineering Society of Korea
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• v.13 no.2
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• pp.47-58
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• 2009

In this study, a seismic fragility analysis was performed for substation systems in Korea. To evaluate the seismic fragility function of the substation systems, a fragility analysis of the individual equipment and facilities of the substation systems was first performed, and then all systems were considered in the fragility analysis of the substation systems using a fault-tree method. For this research, the status of the substation systems in Korea was investigated for the classification of the substation systems. Following the classification of the substation systems, target equipment was selected based on previous damage records in earthquake hazards. The substation systems were classified as 765kV, 345kV, and 154kV systems. Transformer and bushing were chosen as target equipment. The failure modes and criteria for transformer and bushing were decided, and fragility analysis performed. Finally, the fragility functions of substation system were evaluated using the fault tree method according to damage status.

• Journal of the Korean Society for Railway
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• v.12 no.4
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• pp.535-541
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• 2009

The reliability of control system composed of electronic parts has been studied by DoD since 1960, and has been undertaken mainly by Europe for railways. Especially in Korea, a study on reliability of signalling equipment has been taken since 2000, requiring reliability test for effective maintenance of old type signalling equipment which no longer has information on its past reliability. This study evaluates the reliability test in units of parts for old type signalling equipment; for instance, failure rate in units of parts, or failure data during operation; which was utilized without its consistent reliability monitoring and analysis data for over 20 years. Also, reliability change at this point in time has been estimated by using residual life span function, and a model which can evaluate the possibility of extended operation through stress acceleration test has been developed. This model will be utilized to establish future maintenance policy for train operating company's operation on old type signalling equipment.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.2
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• pp.95-109
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• 2023

In the 4th industrial revolution, changes in the technological paradigm have had a direct impact on the maintenance system of ships. The 2-stroke low speed engine system integrates with the core equipment required for propulsive power. The Condition Based Management (CBM) is defined as a technology that predictive maintenance methods in existing calender-based or running time based maintenance systems by monitoring the condition of machinery and diagnosis/prognosis failures. In this study, we have established a framework for CBM technology development on our own, and are engaged in engineering-based failure analysis, data development and management, data feature analysis and pre-processing, and verified the reliability of failure mode DB using LSTM algorithms. We developed various simulated failure mode scenarios for 2-stroke low speed engine and researched to produce data on onshore basis test_beds. The analysis and pre-processing of normal and abnormal status data acquired through failure mode simulation experiment used various Exploratory Data Analysis (EDA) techniques to feature extract not only data on the performance and efficiency of 2-stroke low speed engine but also key feature data using multivariate statistical analysis. In addition, by developing an LSTM classification algorithm, we tried to verify the reliability of various failure mode data with time-series characteristics.

• Journal of Applied Reliability
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• v.16 no.3
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• pp.224-230
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• 2016

Purpose: Military maintenance involves corrective and preventive actions carried out to keep a system in or restore it to a predetermined condition. This research develops an optimal maintenance cycle for aviation oil testing equipment with acceptable reliability level and minimum maintenance cost. Methods: The optimal maintenance policy in this research aims to satisfy the desired reliability level at the lowest cost. We assume that the failure process of equipment follows the power law non-homogeneous Poisson process model and the maintenance system is a minimal repair policy. Estimation and other statistical procedures (trend test and goodness of fit test) are given for this model. Results: With time varying failure rate, we developed reliability-based maintenance cost optimization model. This model will reduce the ownership cost through adopting a proactive reliability focused maintenance system. Conclusion: Based on the analysis, it is recommended to increase the current maintenance cycle by three times which is 0.5 year to 1.5 years. Because of the system's built-in self-checking features, it is not expected to have any problems of preventative maintenance cycle.

• Journal of the Korean Society for Railway
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• v.9 no.6 s.37
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• pp.732-738
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• 2006

This research provides a scheme for Highly Accelerated Stress Test that is necessary to demonstrate reliability prediction of Korean Rapid Transit Railway Train Control System sub-equipment, which is calculated by a relevant standard for failure rate prediction of electronic products. Although determining failure information generated in the process of trial running by statistic analysis is widely accepted as a measure of confirmation for reliability prediction, this research suggests the modeling for System Life Test determined by accelerating stress factors as a measure of confirmation for reliability prediction of sub-equipment unit that is generated ahead of a trial running in System Life Cycle. Consequently, the research demonstrates sub-equipment unit reliability test, which is based on the model derived from Accelerated Stress Test, according to accuracy level and the number of samples, and conducts an official experiment by making out a reliability test procedure sheet based on test time as well.