• IEMEK Journal of Embedded Systems and Applications
• /
• v.14 no.6
• /
• pp.287-294
• /
• 2019

With the automation of production lines in the manufacturing industry, the importance of real-time fault diagnosis of facility is increasing. In this paper, we propose a fault diagnosis algorithm of LM (Linear Motion)-guide based on deep learning using vibration signals. Generally, in order to guarantee the performance of the deep learning, it is necessary to have a sufficient amount of data, but in a manufacturing industry, it is often difficult to obtain enough data due to physical and time constraints. To solve this problem, we propose a convolutional neural networks (CNN) model based on transfer learning. In addition, the spectrogram image is input to the CNN to reflect the frequency characteristic of the vibration signals with time. The performance of fault diagnosis according to various load condition and transfer learning method was compared and evaluated by experiments. The results showed that the proposed algorithm exhibited an excellent performance.

• Journal of Korea Multimedia Society
• /
• v.20 no.2
• /
• pp.134-143
• /
• 2017

Machine fault diagnosis recovers all the studies that aim to detect automatically faults or damages on machines. Generally, it is very difficult to diagnose a machine fault by conventional methods based on mathematical models because of the complexity of the real world systems and the obvious existence of nonlinear factors. This study develops an automatic machine fault diagnosis system that uses pattern recognition techniques such as principal component analysis (PCA) and artificial neural networks (ANN). The sounds emitted by the operating machine, a drill in this case, are obtained and analyzed for the different operating conditions. The specific machine conditions considered in this research are the undamaged drill and the defected drill with wear. Principal component analysis is first used to reduce the dimensionality of the original sound data. The first principal components are then used as the inputs of a neural network based classifier to separate normal and defected drill sound data. The results show that the proposed PCA-ANN method can be used for the sounds based automated diagnosis system.

• Proceedings of the KOSOMBE Conference
• /
• v.1995 no.05
• /
• pp.173-178
• /
• 1995

This paper relates the occidental constitutional theory to the oriental one, concluding their origins to be similar, and demonstrates a new method of constitutional diagnosis by O-Ring Measurement System Of Muscular Meridians and Laser Constitutional Diagnosis. It establishes Laser Constitutional Diagnosis(L.C.D) using laser beams according to the principles of acupuncture and Sa-Sang constitutional physiology under the effect of spatial morphological energy of geometric isomers. Finally, hypothetical theory of L.C.D. was experimented by the O-Ring Measurement Systems of Muscular Meridians(O-R MSMM). O-R MSMM has been specially devised to improve the manual O-Ring Test prevailing to distinguish energetic response by muscle tonicity. Statistically, it has been proved that the constitutional diagnosis with O-R MSMM was highly effective and objective in the clinical experiences.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.64 no.1
• /
• pp.29-34
• /
• 2015

DC bus electrolytic capacitors are used in variety of equipments as smoothing element of the power converters because it has high capacitance for its size and low price. It is responsible for frequent breakdowns of many static converters and inverter drive systems. Therefore it is important to diagnosis monitoring the condition of an electrolytic capacitor in real-time to predict the failure of power converter. In this paper, the on-line remote diagnosis monitoring system for DC BUS electrolytic capacitors of power converter using low-cost type Zigbee communication modules is developed. To estimate the health status of the capacitor, the equivalent series resistor(ESR) of the component has to be determined. The capacitor ESR is estimated by using RMS computation using AC coupling method of DC link ripple voltage/current. The Zigbee communication-based experimental results show that the proposed remote DC capacitor diagnosis monitoring system can be applied to DC/DC converter and UPS successfully.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.4
• /
• pp.518-523
• /
• 2008

In this paper, we present the development of an intelligent diagnosis system for detecting faults of the transmission line. Based on the TFDR (Time-Frequency Domain Reflectometry), the fault detecting performs to measure the location of fault line. We analyze the reflected signal which is sent from the wire detecting system and classify the fault type of the wires by using intelligent diagnosis system. In order to analyze effectively, we construct the intelligent diagnosis system which is based on the fuzzy-bayesian algorithm. Finally, we provide the simulation results which are performed at transmission line to evaluate the feasibility and generality of the proposed method in this paper.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.25 no.8
• /
• pp.30-38
• /
• 2011

This paper proposes a new intelligent diagnosis equipment for the partial discharge, which keeps deteriorating the insulating materials inside electric machineries, ultimately leading to electrical breakdown. In order to simulate experimentally the partial discharge inside the electric machinery, the tip-to-plate, the sphere-to-plate, the sphere-to-sphere and the plate-to-plate electrodes are used respectively, of which the gaps are 1[mm], 3[mm] or 5[mm] and the applied voltages are 3[kV], 5[kV] or 7[kV]. Ceramic coupler sensor and FIR digital filter are used to measure the partial discharge and the artificial neural network is used for the deterioration diagnosis of the electric machinery. The microprocessor of PD diagnosis equipment is DSP (TMS320C6713) with FPGA (Cyclone II). The results of the real-time and on-line experiments performed with the developed equipment are also explained.

• The Journal of the Society of Korean Medicine Diagnostics
• /
• v.13 no.1
• /
• pp.72-80
• /
• 2009

Objective: We performed this study to check relationship of Cold-Heat attribute analyzed quantitatively by questionnaire with acoustic analysis index. Method : We checked a questionnaire composed of 15 items about the contents of Cold-Heat and asked 83 subjects to answer in the form Likert-like 7-points score. And then, we extracted Cold-Heat attribute from heat score, cold score, heat index and cold index. we measured the acoustic analysis indexes of cardinal vowels by Dr. speech program. Afterward, the data were analyzed by correlation analysis. Results : All cardinal vowels is positive correlated with cold score, heat score and cold index. NNE of vowel /a/ is negative correlated with cold index. Shimmer and F0 tremor of vowel /e/ is negative correlated with cold index. Jitter of vower /u/ is positive correlated with Cold score.

• The Journal of the Korea Contents Association
• /
• v.17 no.9
• /
• pp.466-475
• /
• 2017

Various factors in daily life cause stress, which could stem from trivial or major events. Stress is not appeared at any time but is appeared over the lifetime. Therefore, it is necessary to conduct studies to identify ways to manage stress. In the present study, we developed an iris analysis-based system to diagnose and manage stress. By analyzing its correlation with the degree of stress measured using the iris diagnosis and a questionnaire, the user's degree of stress quantitates. The system proposed in this study can be used to measure the degree of stress experienced by the user, which can be an effective method for the early diagnosis and prevention of stress-related diseases.

• Journal of Chest Surgery
• /
• v.33 no.2
• /
• pp.179-182
• /
• 2000

Background: A pleural effusion is not a disease entity but a clincial sign of systemic or pleural disease. Although the diagnosis of pleural effusion can often be done by toracentesis and pleural needle biopsy the yeild of positive diagnosis is low.

• Journal of Society of Preventive Korean Medicine
• /
• v.26 no.2
• /
• pp.25-35
• /
• 2022

Objectives : This study aims to analyze the patents filed in the clinical diagnosis sector where technologies have been actively developed since the advent of the 4th industrial revolution. Methods : The analysis has been conducted in two ways - the period from 2016 to 2021 and the time points before and after COVID-19 - by visualizing based on the word cloud method. Results : Over two thirds of patents has been filed in the A61B sector (71.8%) and cure, sensor, self diagnosis, control, and breakdown have been observed in the period above. During the overall period (2016~2021), 'ultrasound'(7.5%), 'image'(5.1%), 'skin'(4.0%), 'treatment'(3.4%), and 'artificial intelligence(2.5%)' were the frequently patent applications technologies. In addition, 'ultrasound'(6.2%), 'image'(5.5%), 'skin'(4.0%), 'treatment' (3.7%), and 'portable'(1.7%) appeared most frequently before COVID-19 whereas 'ultrasound(5.5%)', 'artificial intelligence(4.2%)', 'diagnostic device'(1.9%), 'dimentia'(1.6%), and 'diagnostic kit'(1.4%) emerged the most after COVID-19. Conclusion : This study is meaningful in that it showed the technological development trend in the digital diagnosis sector and it was found that the Korean medicine field should contribute to this field more actively in the future.