• Journal of the Korean Society for Nondestructive Testing
• /
• v.33 no.1
• /
• pp.20-25
• /
• 2013

Ultrasonic methods are widely used to degradation assessment. Remaining-life cycle of metal can be estimated by ultrasonic parameters because ultrasonic velocity and attenuation are affected by change of material properties with accumulated fatigue in the metal. Therefore, in this study, we will estimate overall change of material properties by 2D C-scan image. Fatigued aluminum alloy 6061-T6 samples from 0 to 85% were prepared for evaluating fatigue life cycle. Also, degraded image of materials using attenuation is proposed to estimate degree of material degradation for determining degraded area of fatigued samples. Finally, we will predicts process pf degradation with measured attenuation of fatigued aluminum alloy 6061-T6 samples.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.59-61
• /
• 2021

The electric propulsion development is underway to minimize pollutants and greenhous gas emissions during the operation of ships / offshore installation vessels. The importance of the use and efficient management of batteries, which is an ESS system in ships / offshore installation vessels, is increasing. Generally, in ESS where battery is applied, cell balancing and life span are monitored in real time by BMS. Ships / offshore installation vessel are equipped with several ESS rooms, and ESS rooms with ESS systems of the same specification are being constructed due to the recent demand for electric propulsion development. In this paper, we propose an algorithm to additionally predict and diagnose battery pack and cell balancing failures by comparing BMS data for each rooms. The proposed algorithm compares the BMS data of each ESS Room according to the environmental change of the ship / offshore installation vessels, measures accurate status information, and reliably monitors it to prevent accidents in advance.

• Journal of Technology Innovation
• /
• v.26 no.3
• /
• pp.37-68
• /
• 2018

Since the 20th century, automobiles, which are the most common means of transportation, have been evolving as the use of electronic control devices and automotive semiconductors increases dramatically. Automotive semiconductors are a key component in automotive electronic control devices and are used to provide stability, efficiency of fuel use, and stability of operation to consumers. For example, automotive semiconductors include engines control, technologies for managing electric motors, transmission control units, hybrid vehicle control, start/stop systems, electronic motor control, automotive radar and LIDAR, smart head lamps, head-up displays, lane keeping systems. As such, semiconductors are being applied to almost all electronic control devices that make up an automobile, and they are creating more effects than simply combining mechanical devices. Since automotive semiconductors have a high data rate basically, a microprocessor unit is being used instead of a micro control unit. For example, semiconductors based on ARM processors are being used in telematics, audio/video multi-medias and navigation. Automotive semiconductors require characteristics such as high reliability, durability and long-term supply, considering the period of use of the automobile for more than 10 years. The reliability of automotive semiconductors is directly linked to the safety of automobiles. The semiconductor industry uses JEDEC and AEC standards to evaluate the reliability of automotive semiconductors. In addition, the life expectancy of the product is estimated at the early stage of development and at the early stage of mass production by using the reliability test method and results that are presented as standard in the automobile industry. However, there are limitations in predicting the failure rate caused by various parameters such as customer's various conditions of use and usage time. To overcome these limitations, much research has been done in academia and industry. Among them, researches using data mining techniques have been carried out in many semiconductor fields, but application and research on automotive semiconductors have not yet been studied. In this regard, this study investigates the relationship between data generated during semiconductor assembly and package test process by using data mining technique, and uses data mining technique suitable for predicting potential failure rate using customer bad data.

• KIPS Transactions on Computer and Communication Systems
• /
• v.9 no.4
• /
• pp.77-82
• /
• 2020

Wireless sensor networks (WSNs) suffer from not only a short lifetime due to limited energy but also an energy imbalance between nodes close to the sink and others. In order to fundamentally solve the short lifetime, recent studies utilize the environmental energy such as solar power. Additionally, WSNs using mobile sinks are being studied to address the energy imbalance problem. This paper proposes an improved CTP (Collection Tree Protocol) scheme which uses these two approaches simultaneously. Basically, it is based on a CTP scheme which is a very popular data collection strategy designed for the typical battery-based WSNs with a fixed sink. Therefore, we tailored it for solar-powered WSNs with a mobile sink. Performance verification confirms that our scheme reduces the number of blackout nodes significantly compared to the typical CTP, thus increases the amount of data collected by the sink.

• Convergence Security Journal
• /
• v.12 no.6
• /
• pp.85-92
• /
• 2012

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, we proposed a control mechanism based on NHPP using mean value function of log Poission, log-linear and Parto distribution.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.34 no.6
• /
• pp.763-769
• /
• 2010

In recent times, there has been considerable interest in HIPS (High Impact Polystyrene) materials for their use in construction of office equipments, home electronics, housing for electronics appliances, packing containers, etc. However, these materials suffer from problems caused by fatigue fracture. Further, their strength is substantially affected by environmental conditions. Therefore, in this study, the effect of temperature was analyzed by performing a tensile test and a fatigue test. It was observed that the yield strength, the ultimate strength, and the fatigue life decreased relatively with an increase in temperature. Further, an S-N curve can be predicted by using the results of the tensile test and a micro-Vickers hardness test.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.5
• /
• pp.345-353
• /
• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do parameter inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision to market software, the conditional failure rate is an important variables. In this case, finite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of polynomial hazard function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.05a
• /
• pp.904-907
• /
• 2013

Demand Controller is a control device that if current electric power consumption seems to exceed the targeted amount of electric power, block the connected load devices. When this ON/OFF way is applied to electric power management of electric furnace, start and stop operation of inverter and an electric heater which supplying electric power is being performed repeatedly. This has a problem of life-shortening of inverter and an electric heater by electrical damage. In addition, when electric power supplying is blocked, attemperation is not allowed until return to normal operation condition. In this paper, we develop power management system for electric furnace using the electric furnace remote controller. This system provides the automatic control for approved electric power to electric furnace organically and prevent electric damage of inverter and an electric heater through continuous electric power supply within the targeted amount of electric power.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.6
• /
• pp.483-490
• /
• 2015

There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do likelihood inference for software reliability models based on finite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The infinite failure model are used in a wide variety of practical situations. Their use in characterization problems, detection of outlier, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many study. Statistical process control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper, proposed a control mechanism based on NHPP using mean value function of Musa-Okumo and Power law type property.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.882-885
• /
• 2010

In view of the severe energy constraint in sensor networks, it is important to use the error control scheme of the energy efficiently. In this paper, we presented FEC (Forward Error Correcting) codes in terms of their power consumption. One method of FEC is RS (Reed-Solomon) coding, which uses block codes. RS codes work by adding extra redundancy to the data. The encoded data can be stored or transmitted. It could have errors introduced, when the encoded data is recovered. The added redundancy allows a decoder to detect which parts of the received data is corrupted, and corrects them. The number of errors which are able to be corrected by RS code can determine by added redundancy. We could predict the lifetime of RS codes which transmitted at 32 byte a 1 minutes. RS(15, 13), RS(31, 27), RS(63, 57), RS(127,115), and RS(255,239) can keep the days of 138, 132, 126, 111, and 103 respectively.