• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 추계학술대회 논문집
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• pp.394-399
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• 2012

최근 MEMS 센서는 기계상태감시에 있어서 전력소모, 크기, 비용, 이동성, 응용 등에 있어서 각광을 받고 있다. 특히, MEMS 센서는 스마트센서와 통합가능하고, 대량생산이 가능하여 가격이 저렴하다는 장점이 있다. 이와 관련한 기계상태감시를 위한 많은 실험적 연구가 수행되고 있다. 이 논문은 MEMS 센서들을 3 가지 인공지능 분류기 성능평가를 위한 비교연구에 대해 설명하고 있다. 회전기계에 MEMS 가속도와 전류센서들을 부착하여 데이터를 취득했고, 특징추출과 파라미터 최적화를 위해 Cross validation 기법을 사용하였다. MEMS 센서를 이용한 결함분류기 적용은 적합하다고 판단된다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2000년도 추계학술대회논문집
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• pp.796-801
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• 2000

The monitoring and diagnostics of the rotating machinery have been received considerable attention for many years. The objectives are to classify the machinery condition and to find out the cause of abnormal condition. This paper describes a signal classification method for diagnosing the rotating machinery using the artificial neural network and the wavelet transform. In order to extract salient features, the wavelet transform are used from primary noise signals. Since the wavelet transform decomposes raw time-waveform signals into two respective parts in the time space and frequency domain, more and better features can be obtained easier than time-waveform analysis. In the training phase for classification, self-organizing feature map(SOFM) and learning vector quantization(LVQ) are applied, and the accuracies of them are compared with each other. This paper is focused on the development of an advanced signal classifier to automatise the vibration signal pattern recognition. This method is verified by small reciprocating compressors, for refrigerator and normal and abnormal conditions are classified with high flexibility and reliability.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1026-1034
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• 2021

Tire wear and defect are important factors for safe driving condition. These defects are generally inspected by some specialized experts or very expensive equipments such as stereo depth camera and depth gauge. In this paper, we propose tire safety vision inspector based on deep neural network (DNN). The status of tire wear is categorized into three: 'safety', 'warning', and 'danger' based on depth of tire tread. We propose an attention mechanism for emphasizing the feature of tread area. The attention-based feature is concatenated to output feature maps of the last convolution layer of ResNet-101 to extract more robust feature. Through experiments, the proposed tire wear classification model improves 1.8% of accuracy compared to the existing ResNet-101 model. For detecting the tire defections, the developed tire defect detection model shows up-to 91% of accuracy using the Mask R-CNN model. From these results, we can see that the suggested models are useful for checking on the safety condition of working tire in real environment.

• 대한한의학원전학회지
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• 제23권1호
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• pp.163-186
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• 2010

Objective and Background : Attempt to express knowledge by IT is the current of the times, knowledge of the oriental medicine have to meet the needs of the times. It takes 'classification system of the oriental medicine terms' and 'system of the predicate' for explaining the relation between concepts to express knowledge by IT technique. Researches for 'classification system of the oriental medicine terms' are in progress already, researches for 'system of the predicate' are insufficient. Subject of study : We proceeded to study of the predicate in Idongwon(李東垣)'s "Biwiron(脾胃論)" has clear theory system and considerable influence upon knowledge of the oriental medicine for studying 'system of the predicate' which expresses knowledge of the oriental medicine in early stage. Method : Acquire Chinese play a predicate part in "Biwiron(脾胃論)", translate the Chinese to answer the context, group the similar predicate, decide representative predicate of group. And attempt to make classification system of the representative predicate with Term management system based on SQL Server 2005. Results and Considerations : I classify the predicate which predicate diagnosis, treatment, symptoms and knowledge of the oriental medicine into existence, condition, cognition and will. This classification seems to be useful to explain factors which have an effect on demonstration and treatment.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.403-413
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• 2022

Classification and analysis are improved factors for the realtime automation system. In the field of agriculture, the cultivation of different paddy crop depends on the atmosphere and the soil nature. We need to analyze the moisture level in the area to predict the type of paddy that can be cultivated. For this process, Ensemble Modulation Pattern system and Block Probability Neural Network based classification models are used to analyze the moisture and temperature of land area. The dataset consists of the collections of moisture and temperature at various data samples for a land. The Ensemble Modulation Pattern based feature analysis method, the extract of the moisture and temperature in various day patterns are analyzed and framed as the pattern for given dataset. Then from that, an improved neural network architecture based on the block probability analysis are used to classify the data pattern to predict the class of paddy crop according to the features of dataset. From that classification result, the measurement of data represents the type of paddy according to the weather condition and other features. This type of classification model assists where to plant the crop and also prevents the damage to crop due to the excess of water or excess of temperature. The result analysis presents the comparison result of proposed work with the other state-of-art methods of data classification.

• 품질경영학회지
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• 제51권1호
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• pp.119-129
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• 2023

Purpose: This study proposes a classification model for implementing condition-based maintenance (CBM) by monitoring the real-time status of a machine using acceleration sensor data collected from a vehicle. Methods: The classification model's performance was improved by applying Fourier transform to convert the acceleration sensor data from the time domain to the frequency domain. Additionally, the Generative Adversarial Network (GAN) algorithm was used to augment images and further enhance the classification model's performance. Results: Experimental results demonstrate that the GAN algorithm can effectively serve as an image augmentation technique to enhance the performance of the classification model. Consequently, the proposed approach yielded a significant improvement in the classification model's accuracy. Conclusion: While this study focused on the effectiveness of the GAN algorithm as an image augmentation method, further research is necessary to compare its performance with other image augmentation techniques. Additionally, it is essential to consider the potential for performance degradation due to class imbalance and conduct follow-up studies to address this issue.

• 터널과지하공간
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• 제13권5호
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• pp.353-361
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• 2003

터널 조사계획 혹은 공사중, RMR 및 Q분류법에 따라 암반분류를 수행하는데 있어 지하수조건에 대한 평가는 가능한 조건들의 제약 때문에 경험적 방법에 의존하고 있다. 절리 수압 및 지하수 유입량 측정, 수리전도도 모델 산정, 3차원 수치해석 및 해석해 방법을 사용한 대전 LNG Pilot Cavern의 결과를 바탕으로, 지하수 조건 평가에 관한 합리적인 접근 방법을 비교 검토하였다. 그 결과, Raymer(2001) 이론해 방법이 예비 조사단계에서 유용한 도구로 활용될 수 있음을 검증하였다.

• 품질경영학회지
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• 제17권2호
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• pp.64-69
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• 1989

This paper aims at analyzing the process capability and at determining an optimal condition by experimental designs using the 2-way classification with repitition in order to maintain lower Nacl content and to refine both of a very small quantity of fatty acid and various magnetic ions in the glycerin to use ion exchange resin treatment process. An optimal condition of each level combination in both of passing temperature of cation exchange resin($A_1$, $A_2$, $A_3$) and of anion exchange resin($B_1$, $B_2$, $B_3$) is $A_3B_3$. The process capability index is improved from 0.63 to 1.40 and is interpreted as a desirable state. This analysis of process capability by experimental designs will contribute to improving productivity and quality of products.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.60-64
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• 2001

In this paper, a new learning methodology for Kernel Methods is suggested that results in a sparse representation of kernel space from the training patterns for classification problems. Among the traditional algorithms of linear discriminant function(perceptron, relaxation, LMS(least mean squared), pseudoinverse), this paper shows that the relaxation procedure can obtain the maximum margin separating hyperplane of linearly separable pattern classification problem as SVM(Support Vector Machine) classifier does. The original relaxation method gives only the necessary condition of SV patterns. We suggest the sufficient condition to identify the SV patterns in the learning epochs. Experiment results show the new methods have the higher or equivalent performance compared to the conventional approach.

• 동력기계공학회지
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• 제14권2호
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• pp.40-47
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• 2010

This paper proposes a fault detection system to detect the strip rupture in six-high stand Cold Rolling Mills based on transient current signal of an electrical motor. For this work, signal smoothing technique is used to highlight precise feature between normal and fault condition. Subtracting the smoothed signal from the original signal gives the residuals that contains the information related to the normal or faulty condition. Using residual signal, discrete wavelet transform is performed and acquire the signal presenting fault feature well. Also, feature extraction and classification are executed by using PCA, KPCA and SVM. The actual data is acquired from POSCO for validating the proposed method.