• Journal of Information Processing Systems
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• v.18 no.6
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• pp.822-829
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• 2022

According to existing study into the remote fault diagnosis procedure, the current diagnostic approach has an imperfect decision model, which only supports communication in a close distance. An Internet of Things (IoT)-based remote fault diagnostic approach for wind power equipment is created to address this issue and expand the communication distance of fault diagnosis. Specifically, a decision model for active power coordination is built with the mechanical energy storage of power generation equipment with a remote diagnosis mode set by decision tree algorithms. These models help calculate the failure frequency of bearings in power generation equipment, summarize the characteristics of failure types and detect the operation status of wind power equipment through IoT. In addition, they can also generate the point inspection data and evaluate the equipment status. The findings demonstrate that the average communication distances of the designed remote diagnosis method and the other two remote diagnosis methods are 587.46 m, 435.61 m, and 454.32 m, respectively, indicating its application value.

• Proceedings of the KIEE Conference
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• 2001.07c
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• pp.1664-1666
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• 2001

This paper presents the development of electromagnetic wave detecting equipment for diagnosis of enclosed switchboard. High voltage power equipments are very important equipment of the key industries and the private enterprise. Power line accidents are national plans because of those set off casualties lose of power equipments and communication networks. Therefore the necessity of the development of detecting for power equipment diagnosis is demand for prevention of high voltage equipment accidents. This paper is the development of electromagnetic wave detecting equipment for diagnosis of high voltage equipment. This paper establishes the diagnosis method for high voltage power equipments, that secures original technique and possesses detecting technique for electromagnetic wave. By the study we developed electromagnetic wave detector, and we applied this equipment application tests at the place constructed high voltage equipments.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.05c
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• pp.178-181
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• 2001

This paper presents the development of electromagnetic wave detecting equipment for diagnosis of enclosed switchboard. High voltage power equipments are very important equipment of the key industries and the private enterprise. Power line accidents are national plans because of those set off casualties lose of power equipments and communication networks. Therefore the necessity of the development of detecting for power equipment diagnosis is demand for prevention of high voltage equipment accidents. This paper is the development of electromagnetic wave detecting equipment for diagnosis of high voltage equipment. This paper establishes the diagnosis method for high voltage power equipments, that secures original technique and possesses detecting technique for electromagnetic wave. By the study we developed electromagnetic wave detector, and we applied this equipment application tests at the place constructed high voltage equipments.

• Proceedings of the KIEE Conference
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• 2000.11b
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• pp.318-320
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• 2000

This paper presents the develop-ment of electromagnetic wave detecting equipment for diagnosis of enclosed switchboard. High voltage power equipments are very important equipment of the key industries and the private enterprise power line accidents are national plans because of those set off casualties lose of power equipments and communication networks. Therefore the necessity of the development of detecting for power equipment diagnosis is demand for prevention of high voltage equipment accidents. This paper is the development of electromagnetic wave detecting equipment for diagnosis of high voltage equipment. This paper establishes the diagnosis method for high voltage power equipments, that secures original technique and possesses detecting technique for electromagnetic wave. By the study we developed electromagnetic wave detector and we applied this equipment application tests at the place constructed high voltage equipments.

• Tribology and Lubricants
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• v.38 no.4
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• pp.143-151
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• 2022

This study analyzes patents related to oil diagnosis of construction equipment. Oil diagnosis is extremely important for maintaining construction equipment properly. Through the evaluation of existing patents, a patent strategy for the future construction equipment market is presented. The related patents are classified and selected in several steps. Finally, 16 valid patents are selected and analyzed in detail. In the classification process, patents are classified by country, year, and company. A market analysis shows that the top 10 companies have a market share of more than 50. In addition to patents related to the oil analysis of construction equipment, patents related to automobile oil analysis and development of oil sensors are investigated to identify the contents of patents in other fields that can be applied to oil diagnosis technology for construction equipment. Moreover, not only the contents of research articles of two Korean construction companies, but also the research trends in the literature in this field are used in the analysis. The related patents of the two Korean companies are few. Companies with a high market share, including Caterpillar, hold many patents, and patents for diagnosis algorithms using such technologies as artificial intelligence and artificial neural networks, along with oil sensor-based condition monitoring technology, are gradually expanding.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.252-261
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• 2014

A Bayesian network (BN) based fault diagnosis framework for semiconductor etching equipment is presented. Suggested framework contains data preprocessing, data synchronization, time series modeling, and BN inference, and the established BNs show the cause and effect relationship in the equipment module level. Statistically significant state variable identification (SVID) data of etch equipment are preselected using principal component analysis (PCA) and derivative dynamic time warping (DDTW) is employed for data synchronization. Elman's recurrent neural networks (ERNNs) for individual SVID parameters are constructed, and the predicted errors of ERNNs are then used for assigning prior conditional probability in BN inference of the fault diagnosis. For the demonstration of the proposed methodology, 300 mm etch equipment model is reconstructed in subsystem levels, and several fault diagnosis scenarios are considered. BNs for the equipment fault diagnosis consists of three layers of nodes, such as root cause (RC), module (M), and data parameter (DP), and the constructed BN illustrates how the observed fault is related with possible root causes. Four out of five different types of fault scenarios are successfully diagnosed with the proposed inference methodology.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.115-131
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• 1998

Customer service process is one of the most important processes in today's competitive business environment. Among the various activities of customer service process, equipment malfunction diagnosis activity should be performed fast and accurately. When a customer calls the service center and reports the observed symptoms, he/she describes them in layman's terms. Therefore, the customer-reported symptoms have not been considered helpful information for service representatives. However, in order to perform diagnosis activity fast and accurately, we need to make use of the customer-reported symptoms actively. In this research, we developed three systems called R-EMD (Rule-based Equipment Malfunction Diagnostic system), C-EMD (Case-based Equipment Malfunction Diagnostic system) and R&C-EMD (Rule & Case-based Equipment Malfunction Diagnostic system), each of which diagnoses equipment malfunctions using the customer-reported symptoms. R&C-EMD is a hybrid system that utilizes both rule-based and case-based technologies. The diagnosis rules used in R&C-EMD and R-EMD were not acquired from service manuals or interviews with service representatives. Rater, we extracted them directly from the past diagnosis cases based on symptoms' frequencies. By this way, we were able to overcome the knowledge acquisition bottleneck. Using the real 100 malfunction diagnosis cases, we evaluated the performances of R&C-EMC, R-EMD and C-EMD in terms of speed and accuracy. In diagnosis time, R&C-EMD took longer than R-EMD and shorter than C-EMD. However, R&C-EMC was the best in accuracy.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1380-1381
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• 2008

By applying the digital sub-station, the change of various protect and measuring equipments has been applying. This paper is analyzed that the development of GIS partial discharge condition monitoring equipment is suited to the electricity IT technology and digital sub-station. It's constitution apply to be able to suit the data to high rank for GIS partial discharge condition monitoring equipment that is suited digital sub-station and Watch-dog module that be able to monitor the inner communication of the GIS partial discharge equipment. And then it also be able to apply of GIS partial discharge equipment when digital sub-station is applied.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2004.05a
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• pp.502-505
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• 2004

The purpose of this experiment is to modify diagnosis criterion of isothermal relaxation current(IRC) measurement equipment which is using for distribution cable diagnosis. We're using this system for several years in the field instead of DC leakage current measurement and lots of cables were replaced. But we have to investigate on the reliability of this equipment for our cables because we didn't carried out condition assessment of extracted cables after field diagnosis by this equipment. It is important thing for cable maintenance. If the replacement criterion is improper we can not prevent failures or will waste budget on account of replacement of the sound cables. In this papar we selected field installed cables and injected silicone fluid to the cables for insulation rehabilitation. In order to prove reliability of the diagnosis equipment we compared diagnosis results and AC breakdown strength according to operating time after silicone treatment. This is the results of the field test for 1 year.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.5
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• pp.258-263
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• 2004

The purpose of this experiment is to modify diagnosis criterion of isothermal relaxation current(IRC) measurement equipment which is using for distribution cable diagnosis. We're using this system for several years in the field instead of DC leakage current measurement and lots of cables were replaced. But we have to investigate on the reliability of this equipment for our cables because we didn't carried out condition assessment of extracted cables after field diagnosis by this equipment. It is important thing for cable maintenance. If the replacement criterion is improper we can not prevent failures or will waste budget on account of replacement of the sound cables. In this paper we selected field installed cables and injected silicone fluid to the cables for insulation rehabilitation. In order to prove reliability of the diagnosis equipment we compared diagnosis results and AC breakdown strength according to operating time after silicone treatment. This is the results of the field test for 1 year.