• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.801-807
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• 2024

Linear motion robots are devices that perform functions such as transferring parts or positioning devices, and require high precision. In companies that develop linear robot application systems, human workers are in charge of quality control and fault diagnosis of linear robots, and the result and accuracy of a fault diagnosis varies depending on the skill level of the person in charge. Recently, there have been many attempts to utilize artificial intelligence to diagnose faults in industrial devices. In this paper, we present a system that automatically diagnoses linear rail and ball screw misalignment of a linear robot using transfer learning. In industrial systems, it is difficult to obtain a lot of learning data, and this causes a data imbalance problem. In this case, a transfer learning model configured by retraining an established model is widely used. The information obtained by using an acceleration sensor and torque sensor was used, and its usefulness was evaluated for each case. After converting the signal obtained from the sensor into a spectrogram image, the type of abnormality was diagnosed using an image recognition artificial intelligence classifier. It is expected that the proposed method can be used not only for linear robots but also for diagnosing other industrial robots.

• Transactions of the Korean hydrogen and new energy society
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• v.30 no.6
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• pp.556-566
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• 2019

Recently, as the supply of residential polymer electrolyte membrane fuel cells (PEMFCs) increases, the durability and lifetime of the PEMFC system are becoming important. The related studies have been mainly focused on the durability and lifetime of materials while the research on the durability and maintenance of the system level is insufficient. In this paper, a model-based fault detection method is developed considering an air supply system that is dominant to the system performance and efficiency. A commercial 1 kW residential fuel cell system is built, and experiments are conducted under various operation loads and states (normal, 6 faults). From the experimental data, nominal models and residuals are generated. With the residual pattern obtained from real-time data, the detection and classification of various faults can be possible. The technical importance of this paper is to minimize extra sensor installation by using the empirical model rather than a complex mathematical model, and to decrease the number of models by using the applicable model at three loads. Finally, the model-based fault detection method for the air supply system of a PEMFC is established and is expected to be applicable to other subsystems.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.806-818
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• 2009

Since the invention of the integrated circuit (IC) in 1950s, semiconductor technology has undergone dramatic development up to these days. A complete semiconductor is manufactured through a diversity of processes. For better semiconductor productivity, fault detection and classification (FDC) has been rigorously studied for finding faults even before the processes are completed. For FDC, various kinds of sensors are attached in many semiconductor manufacturing devices, and sensor values are collected in a periodic manner. The collection of sensor values consists of sequences of real numbers, and hence is regarded as a kind of time-series data. In this paper, we propose an algorithm for detecting and clustering faults in semiconductor processes. The proposed algorithm is a modification of the existing anomaly detection algorithm dealing with symbolically-represented time-series. The contributions of this paper are: (1) showing that a modification of the existing anomaly detection algorithm dealing with general time-series could be used for semiconductor process data and (2) presenting experimental results for improving correctness of fault detection and clustering. As a result of our experiment, the proposed algorithm caused neither false positive nor false negative.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.11a
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• pp.155-159
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• 2002

Wire ropes are used in a myriad of various industrial applications such as elevator, mine hoist, construction machinery, lift, and suspension bridge. Especially, wire rope of crane is important component to container transfer. If it happens wire rope failures in operating, it may lead to safety accident, economic power loss by productivity decline, competitive power decline of container terminal and so on. To solve this problem, we developed wire rope fault detecting system as a portable instrument, and this system is consisted of 3 parts that fault detecting part using hall sensor, permanent magnets and analog unit, and digital signal processing part using data acquisition card, monitoring part using wavelet transform, denoising method. In this paper, a wire rope is scanned by this system after makes several broken parts on the surface of wire rope artificially. All detected signal has external noise or disturbance according to circumstances. So, we applied to discrete wavelet transform to extract a signal from noisy data that was used filter. In practical applications of denoising, it is shown that wavelet pursue it with little information loss and smooth signal display. It is verified that the detecting system by denoising has good efficiency for inspecting faults of wire ropes in service. As a result, by developing this system, container terminal could reduce expense because of extension of wire ropes exchange period and could competitive power. Also, this system is possible to apply in several fields like that elevator, lift and so on.

• Journal of Sensor Science and Technology
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• v.10 no.1
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• pp.33-41
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• 2001

Wire ropes have been widely used in industrial applications, wherever heavy weight should be carried safely or mechanical energy should be transmitted fast. Especially, wire rope failures in operating elevator may lead to extensive property damage and serious injury to nearby personnel. Hence, it is very important to inspect wire rope periodically. Failure defection of wire rope requires fundamental knowledge of wire rope construction, rope behavior, properties of fault, sensing and signal processing method. In this research, the development of a new fault detecting system incorporating Hall-effect sensors to detect flaws such as abrasion, broken wire, corrosion and deformation for aged wire ropes in elevator, is described. For using a detector as a portable instrument, several performances for implementing sensing part with Hall-effect sensor, analog signal processing unit and programs are described. Experiments and field testing results for the implemented detecting system are also given. As a result, it is verified that the detecting system has good efficiency for inspecting faults of aged wire ropes in service.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.3
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• pp.175-189
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• 2023

Fault detection and diagnosis (FDI) algorithms are actively being researched for ensuring the integrity and reliability of environment perception sensors in autonomous vehicles. In this paper, a fault detection algorithm based on a multi-sensor perception system composed of radar, camera, and lidar is proposed to guarantee the safety of an autonomous vehicle's perception system. The algorithm utilizes reference generation filters and residual generation filters based on finite impulse response (FIR) filter estimates. By analyzing the residuals generated from the filtered sensor observations and the estimated state errors of individual objects, the algorithm detects faults in the environment perception sensors. The proposed algorithm was evaluated by comparing its performance with a Kalman filter-based algorithm through numerical simulations in a virtual environment. This research could help to ensure the safety and reliability of autonomous vehicles and to enhance the integrity of their environment perception sensors.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.287-292
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• 2012

In this study, Multi-Channel Magnetic Flux Leakage(MFL) sensor - based inspection system was applied to monitor the condition of cables. This inspection system measures magnetic flux to detect the local faults(LF) of steel cable. To verify the feasibility of the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to determine the locations of the flaws and the level of damage. Measured signals from the damaged specimen were compared with thresholds set for objective decision making. In addition, the magnetic flux density values measured from every channel were summed to focus on the detection of axial location. And, sum of flux density were displayed with threshold. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.2
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• pp.173-183
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• 1996

In this paper, a new structure that can do fault detection and location of digial logic circuits more efficiently using current testing techniques is proposed. In the conventional method, observation point for steady state power supply current was only one, but in the proposed method more fault classes are divided for fault detection and location through the ovservation of steady state power supply current at two points. Also, it is shown that this structure can be easily applied in detection of stuck-open fault which is not easy to do testing with conventional current testing techniques. In the presented mehtod, an extra trasnistor is used, and current path is made compulsorily in the CMOS circuits in which no current path can be established in steady state, then it can be known that stuck-open tault is in the MOS transistor on the considering current path, if this path disappears due to stuck-open fault. The validity and the effectiveness is shwon, thorugh the SPICE simulation of circuits with fault and the current path search experiment using current path search program based on transistor short model wirtten in C language on SUN sparc workstation.

• Progress in Superconductivity
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• v.6 no.2
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• pp.108-112
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• 2005

We investigated temperature behavior of superconducting fault current limiters (SFCLs) during quenches. Knowledge on temperature behavior during quenches is important to the design of SFCLs, because the temperature of SFCLs is related to their stability. SFCLs were fabricated by patterning $Au/YBa_2Cu_3O_7$ thin films grown on sapphire substrates into meander lines by photolithography. A gold film grown on the back side of the substrate was patterned into a meander line, and used as a temperature sensor. The front meander line was subjected to simulated AC fault currents, and the back line to DC current. They were immersed in liquid nitrogen during the experiment for effective cooling. Overall, temperature at the back side of SFCLs was close to that at the front side. It was closer at the beginning of faults, and at lower applied voltages. Temperature distribution at the back side was even except at the edge, as at the front side. These results tell that the whole SFCL was heated to similar degree during quenches, and that effective cooling of SFCLs at the back side is as important to the stability of SFCLs as at the front side. The results could be explained with the concept of heat transfer within the film.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2196-2201
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• 2007

Materials used at microwave are usually used as a dielectric with a manufacturing purpose of printed circuit boards, etc. Complex permittivity of them can be measured from attenuation constant or propagation constant of a transmission line using a microstrip line with bulk type. But as the technique recently which can manufacture to have complex permittivity and permeability demanded using nonferrous metals for powder-type grows up, we need sensors and methods which can measure characteristics of powder-type materials. So far measuring methods of permittivity and permeability with waveguide or coaxial cable are used but they have faults which have a complex measurement method and are difficult to simultaneously measure permittivity and permeability. In this paper, a simultaneous measuring method of permittivity and permeability with 2-port coaxial cable and a new proposed calculation. The proposed 2-port coaxial cable is designed to be easy to insert materials and to have a wideband. We measure permittivity and permeability of magnetic powder(Ni-Fe-Mo, Ni-Fe) which reveal its characteristic at $0.3{\sim}1.3GHz$ to identify the proposed sensor.