• Journal of Interdisciplinary Genomics
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• 제4권1호
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• pp.11-14
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• 2022

Primary ciliary dyskinesia (PCD) is a genetic disorder that affects approximately 1 in 15,000-30,000 people, with the majority of patients inheriting the disorder via autosomal recessive inheritance. PCD is characterized by abnormal ciliary ultrastructure and/or function, which results in impaired mucociliary clearance and recurrent respiratory infections. Despite the presence of symptoms from birth, many patients with PCD remain undiagnosed until adulthood. Many advances in the diagnosis of PCD have occurred in recent years, including nasal nitric oxide assays, ciliary motility tests, and genetic sequencing. Early diagnosis and symptom management may reduce morbidity and mortality from PCD improving the patient's quality of life.

• 전기학회논문지
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• 제64권6호
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• pp.912-921
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• 2015

In this paper, we introduce fuzzy inference-based real-time deterioration diagnosis system with the aid of infrared thermal imaging camera. In the proposed system, the infrared thermal imaging camera monitors diagnostic field in real time and then checks state of deterioration at the same time. Temperature and variation of temperature obtained from the infrared thermal imaging camera variation are used as input variables. In addition to perform more efficient diagnosis, fuzzy inference algorithm is applied to the proposed system, and fuzzy rule is defined by If-then form and is expressed as lookup-table. While triangular membership function is used to estimate fuzzy set of input variables, that of output variable has singleton membership function. At last, state of deterioration in the present is determined based on output obtained through defuzzification. Experimental data acquired from deterioration generator and electric machinery are used in order to evaluate performance of the proposed system. And simulator is realized in order to confirm real-time state of diagnostic field

• 한국전자통신학회논문지
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• 제11권1호
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• pp.59-64
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• 2016

본 논문에서는 주택의 전기화재 방지를 위해 아크고장전류로부터 아크 진단 기능을 가지는 지능형 분전반이 개발된다. 지능형 분전반의 주 제어장치는 단상전력관리를 지원하는 단상 전력관리 장치와 아크전류로부터 아크 고장을 진단하기 위한 아크 진단 장치로 구성된다. 본 논문에서는 단상 전력관리 장치와 아크진단장치의 시작품이 설계, 제작되며, 전기화재의 원인을 분전반으로부터 원격 서버 시스템에 전송하기 위해서 주제어장치와 아크 고장 진단 장치와의 연동기능이 개발된다.

• Journal of Electrical Engineering and Technology
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• 제13권1호
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• pp.89-96
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• 2018

When a fault occurs in a power system, the existing analytic models for the power system fault diagnosis could generate multiple solutions under the condition of one or more protective relays (PRs) and/or circuit breakers (CBs) malfunctioning, and/or an alarm or alarms of these PRs and/or CBs failing. Therefore, this paper presents an improved analytic model addressing the above problem. It takes into account the interaction between the uncertainty involved with PR operation and CB tripping and the uncertainty of the alarm reception, which makes the analytic model more reasonable. In addition, the existing analytic models apply the penalty function method to deal with constraints, which is influenced by the artificial setting of the penalty factor. In order to avoid the penalty factor's effects, this paper transforms constraints into an objective function, and then puts forward an improved immune clonal multi-objective optimization algorithm to solve the optimal solution. Finally, the cases of the power system fault diagnosis are served for demonstrating the feasibility and efficiency of the proposed model and method.

• 제어로봇시스템학회논문지
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• 제5권4호
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• pp.427-436
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• 1999

This paper describes an ECG signal labeling algorithm based on fuzzy clustering, which is very useful to the automated ECG diagnosis. The existing labeling methods compares the crosscorrelations of each wave form using IF-THEN binary logic, which tends to recognize the same wave forms such as different things when the wave forms have a little morphological variation. To prevent this error, we have proposed as ECG signal labeling algorithm using fuzzy clustering. The center and the membership function of a cluster is calculated by a cluster validity function. The dominant cluster type is determined by RR interval, and the representative beat of each cluster is determined by MF (Membership Function). The problem of IF-THEN binary logic is solved by FCM (Fuzzy C-Means). The MF and the result of FCM can be effectively used in the automated fuzzy inference -ECG diagnosis.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1994년도 추계학술대회 논문집
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• pp.670-675
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• 1994

Yhis paper describes a fault diagnosis simulation of the Real-Time Multiple Fault Dignosis System (RTMFDS) for forcasting faults in a system and deciding current machine state from signal information. Comparing with other diagnosis system for single fault,the system developed deals with multiple fault diagnosis,comprising two main parts. One is a remotesignal generating and transimission terminal and the other is a host system for fault diagnosis. Signal generator generate the random fault signal and the image information, and send this information to host. Host consists of various modules and agents such as Signal Processing Module(SPM) for sinal preprocessing, Performence Monotoring Module(PMM) for subsystem performance monitoring, Trigger Module(TM) for multi-triggering subsystem fault diagnosis, Subsystem Fault Diagnosis Agent(SFDA) for receiving trigger signal, formulating subsystem fault D\ulcornerB and initiating diagnosis, Fault Diagnosis Module(FDM) for simulating component fault with Hierarchical Artificial Neural Network (HANN), numerical models and Hofield network,Result Agent(RA) for receiving simulation result and sending to Treatment solver and Graphic Agent(GA). Each agent represents a separate process in UNIX operating system, information exchange and cooperation between agents was doen by IPC(Inter Process Communication : message queue, semaphore, signal, pipe). Numerical models are used to deseribe structure, function and behavior of total system, subsystems and their components. Hierarchical data structure for diagnosing the fault system is implemented by HANN. Signal generation and transmittion was performed on PC. As a host, SUN workstation with X-Windows(Motif)is used for graphic representation.

• 대한물리의학회지
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• 제2권1호
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• pp.65-72
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• 2007

Purpose : The purpose of this study is a research on the evaluation about shoulder joint function. Methods : It's based on the reference books. Result : Shoulder joint has the biggest ROM in human body, and it is a joint that stability and mobility are required at the same time sport art. Especially, function of shoulder joint than other what item players of more important overhead item correct diagnosis and evaluation for shoulder joint injury require. Measurement equipment for shoulder joint is helping a lot of incorrect diagnosis and analysis about shoulder joint function of overhead players through a lot of developments. Conclusion : I think a lot of helps torture in motor ability elevation of players and player protection as analysis by special quality in item of overhead players.

• 한국소음진동공학회논문집
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• 제14권12호
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• pp.1233-1240
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• 2004

Condition monitoring and fault diagnosis of machines are gaining importance in the industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. By comparing the nitration signals of a machine running in normal and faulty conditions, detection of faults like mass unbalance, shaft misalignment and bearing defects is possible. This paper presents a novel approach for applying the fault diagnosis of rotating machinery. To detect multiple faults in rotating machinery, a feature selection method and support vector machine (SVM) based multi-class classifier are constructed and used in the faults diagnosis. The results in experiments prove that fault types can be diagnosed by the above method.

• 한국소음진동공학회논문집
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• 제24권9호
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• pp.675-681
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• 2014

This paper proposes a fault diagnosis system for an induction motor. This system uses empirical mode decomposition(EMD) to extract fault signatures and multi-layer perceptron(MLP) neural network to facilitate an accurate fault diagnosis. EMD can not only decompose a signal adaptively but also provide intrinsic mode functions(IMFs) containing natural oscillatory modes of the signal. However, every IMF does not represent fault signature, an IMF selection algorithm based on harmonics and their energy of each IMF is proposed. The selected IMFs are utilized for fault classification using MLP and this system shows approximately 98 % diagnosis accuracy for the fault vibration signal of the induction motor.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.326-327
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• 2007

We investigated whether the CT images of hepatic lesions could be analyzed by computer-aided diagnosis (CAD) tool. We retrospectively reanalyzed 14 liver CT images (10 hepatocellular cancers and 4 benign liver lesions; patients who presented with hepatic masses). The hepatic lesions on CT were segmented by rectangular ROI technique and the morphologic features were extracted and quantitated using fractal texture analysis. The contrast enhancement of hepatic lesions was also quantified and added to the differential diagnosis. The best discriminating function combining the textural features and the values of contrast enhancement of the lesions was created using linear discriminant analysis. Textural feature analysis showed moderate accuracy in the differential diagnosis of hepatic lesions, but statistically insignificant. Combining textural analysis and contrast enhancement value resulted in improved diagnostic accuracy, but further studies are needed.