• Advances in Computational Design
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• 제8권3호
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• pp.255-271
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• 2023

The gear drive of a combat aircraft engine is responsible for power transmission to the different accessories necessary for the engine's operation. Incorrect power transmission can occur due to the presence of failure modes in the gears like bending fatigue, pitting, adhesive wear, scuffing, abrasive wear and polished wear etc. Fault diagnosis of the gear drive is necessary to get an early indication of failure of the gears. The present research is to develop an algorithm using different vibration signal processing techniques on industrial vibration acquisition systems to establish gear fault diagnosis architecture. The signal processing techniques have been used to extract various feature vectors in the development of the fault diagnosis architecture. An open-source dataset of other gear fault conditions is used to validate the developed architecture. The results is a basis for development of artificial intelligence based expert systems for gear fault diagnosis of a combat aircraft engine.

• 한국정밀공학회지
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• 제20권10호
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• pp.89-97
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• 2003

The faults diagnosis of machine tool, which is controlled by CNC(Computer Numerical Control) and PLC(Programmable Logic Controller), is generally based on ladder diagram of PLC because sequential controls for CNC and servo motor are mostly processed in PLC. However, when fault is occurred, a searching of logical relationship for fault reasons is required a lot of diagnosis experiences and times because PLC program has step structure. In this paper, FDS(Fault Diagnosis System) is developed and implemented to machine tool with open architecture controller in order to find the reason of fault fast and correctly. The diagnosed reasons for fault are remote serviced on web through developed RSS(Remote Service System). The operationability and usefulness of developed system are evaluated on specially manufactured machine tool with open architecture CNC. The results of this research can be the model of remote monitoring and fault diagnosis system of machine tool with open architecture CNC.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.121-124
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• 2003

The conventional CNC(Computerized Numerical Controller) of machine tool, which is dependent to CNC maker, was a closed architecture type. Therefore, it is impossible to implement a special user-define function to CNC. But recently, CNC is changed to OAC(Open Architecture Controller) type increasingly and the general function of CNC can be upgrade efficiently. This paper describes web service application for remote monitoring regarding the faults or machine tool with open architecture CNC. The major faults of CNC machine tool can be defined to the operational faults to be charged over 70%. Those faults are unpredictable because of being occurred without any warning. To generalize the fault diagnosis efficiently. two diagnosis models such as SF(Switching Function) and SSF(Step Switching Function) are proposed and the function of fault diagnosis is implemented to internal function of OAC. Also, to service remotely the faults of CNC machine tool. the suitable web environment is proposed and practical function is programmed to evaluate its operation on web.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.7-10
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• 2002

The diagnosis of faults of machine tool, which is controlled by CNC and PLC, is generally based on ladder diagram of PLC. Because sequential controls for CNC and servo motor are mostly processed in PLC. However, when fault is occurred, a searching for logical relation to fault reasons is required a lot of fault experiences and times, because PLC program has step structure. In this paper, FDS(Fault Diagnosis System) is developed and implemented to machine tool with open architecture controller in order to find the reason of fault lastly and correctly. The diagnosed reasons for fault are tele-serviced on web through developed RSS(Remote Service System). The operationability and usefulness of developed system are evaluated on specially manufactured machine tool with open architecture CNC. The results of this research can be the model of remote monitoring and fault diagnosis system of machine tool with open architecture CNC.

• Journal of Mechanical Science and Technology
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• 제19권5호
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• pp.1095-1106
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• 2005

Recently, the conventional controller of machine-tool has been increasingly replaced by the PC-based open architecture controller, which is independent of the CNC vendor and on which it is possible to implement user-defined application programs. This paper proposes CNC­implemented fault diagnosis and web-based remote services for machine-tool with open architecture CNC. The faults of CNC machine-tool are defined as the operational faults occupied by over $70{\%}$ of all faults. The operational faults are unpredictable as they occur without any warning. Two diagnostic models, the switching function and the step switching function, were proposed in order to diagnose faults efficiently. The faults were automatically diagnosed through the fault diagnosis system using the two diagnostic models. A suitable interface environment between CNC and developed application modules was constructed for the internal function of CNC. In addition, a suitable web environment was constructed for remote services. The web service functions, such as remote monitoring and remote control, were implemented, and their operability was tested through the web. The results obtained through this research could be a model of fault diagnosis and remote servicing for machine-tool with open architecture CNC.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.233-238
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• 2000

CNC machine tool is assembled by central processor, PLC(Programmable Logic Controller), and actuator. The sequential control of machine generally controlled by a PLC. The main fault occured at PLC in 3 control parts. In LC faults, operational fault is charged over 70%. This paper describes diagnosis model and data processing for remote monitoring and diagnosis system in machine tools with open architecture controller. Two diagnostic models based on the ladder diagram. Logical Diagnosis Model(LDM), Sequential Diagnosis Model(SDM), are proposed. Data processing structure is proposed ST(Structured Text) based on IEC1131-3. The faults from CNC are received message form open architecture controller and faults from PLC are gathered by sequential data.. To do this, CNC and PLC's logical and sequential data is constructed database.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.37-41
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• 2002

This study has been focused on the development of an open architecture CNC system and integration of core application technology for machine tool such as a remote monitoring/diagnosis system, NURBS interpolation, and cutting process simulation. To do this, we have developed a comprehensive CNC software including the basic HMI, screen editor, ASF, and visual builder. As a control hardware system for machine tool, the universal I/O module and CNC main unit have been developed. Then the remote monitoring/diagnosis system and NURBS interpolation have been implemented in the CNC software. The cutting simulation software will be used for enhancing the productivity of machine tools. Through a simulator and test bed, the whole technology has been verified.

• Smart Structures and Systems
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• 제31권1호
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• pp.79-88
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• 2023

As the number of deteriorated buildings increases, the importance of safety diagnosis, maintenance, and the repair of buildings also increases. Traditionally, building condition assessments are performed by one person or one company and various inspections are needed. This entails a subjective judgment by the inspector, resulting in different assessment results, poor objectivity and a lack of reliability. Therefore, this study proposed a method to bring about accurate grading results of building conditions. The limitations of visual inspection and condition assessment processes previously conducted were identified by reviewing existing studies. Building defect data was collected using the reverse-engineered three-dimensional (3D) model. The accuracy of the results was verified by comparing them with the actual evaluation results. The results show a 50% time-saving to the same area with an accuracy of approximately 90%. Consequently, defect data with high objectivity and reliability were acquired by measuring the length, area, and width. In addition, the proposed method can improve the efficiency of the building diagnosis process.

• 건축사
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• 통권549호
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• pp.36-55
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• 2015

• International Journal of Internet, Broadcasting and Communication
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• 제15권2호
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• pp.133-143
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• 2023

In this study, we propose a big data set of strawberry pests collected directly for diagnosis model learning and an automatic pest diagnosis model architecture based on deep learning. First, a big data set related to strawberry pests, which did not exist anywhere before, was directly collected from the web. A total of more than 12,000 image data was directly collected and classified, and this data was used to train a deep learning model. Second, the deep-learning-based automatic pest diagnosis module is a module that classifies what kind of pest or disease corresponds to when a user inputs a desired picture. In particular, we propose a model architecture that can optimally classify pests based on a convolutional neural network among deep learning models. Through this, farmers can easily identify diseases and pests without professional knowledge, and can respond quickly accordingly.