• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.37-38
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• 2009

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.78-83
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• 2019

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1233-1241
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• 2019

The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.

• Journal of Power Electronics
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• v.9 no.2
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• pp.224-231
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• 2009

The induction motor rotor fault diagnosis system using current signals, which are measured using an axis-transformation method, is presented in this paper. In inverter-fed motor drives, unlike line-driven motor drives, the stator currents are rich in harmonics; therefore fault diagnosis using stator current is not trivial. The current signals for rotor fault diagnosis need precise and high resolution information, which means the diagnosis system demands additional hardware such as a low pass filter, high resolution ADC, and encoder, etc. The proposed axis-transformation method with encoder and without encoder is expected to contribute to a low cost fault diagnosis system in inverter-fed motor drives without the need for any additional hardware. In order to confirm the validity of the developed algorithms, various experiments for rotor faults are tested and the line current spectrum of each faulty situation using Park transformation is compared with the results obtained from fast Fourier transforms.

• Journal of Sasang Constitutional Medicine
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• v.22 no.4
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• pp.20-29
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• 2010

1. Objectives Our goal is to observe the feasibility of constitution discrimination from computing quantitative roughness index from dynamic friction coefficients and their gradients with the measurement device of skin friction with 3-Axis load cell sensor. 2. Methods In the traditional Korean medicine, skin diagnosis is one of the examination methods to discriminate Sasang constitution since it was known that Tae-eumin has rough skin, and Soyangin has smooth one. It is based on the skin roughness on the back of one's hand for the discrimination. The measurement device of skin friction with 3-axis load cell sensor has been developed in order to provide quantitative skin roughness through dynamic friction coefficients. The effective interval of the coefficients is obtained from the automatic sampling algorithm to use their curvature and slope. Then, Fisher's discriminant function of them makes the discrimination. 3. Results The success rate of extracting the effective interval was about 90% and the discriminant accuracy between Tae-eumin and Soyangin was 70% and 68% for men and women, respectively. The entire methods showed the possibility to distinguish between Tae-eumin and Soyangin by using stochastic properties of roughness index, which can make the entire system to include the measurement, the computation of the roughness index and the discrimination of constitution automatical. 4. Conclusions The measurement device, the automatic sampling algorithm of dynamic friction coefficients and the constitution discrimination algorithm were developed, respectively, and their combination can become the serial and automatic procedure for quantitative and objective skin diagnosis, which mimics the movement of the Oriental medical doctors' skin diagnosis. It can be applied to healthcare as well as the diagnosis of constitution in a u-Health system soon.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.57-63
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• 2022

This study describes a system that monitors the tool and cutting state of automatic beveling operation in real time. As a signal for cutting state monitoring, a motor current detected from the spindle drive system of the automatic beveling machine is used to monitor abnormal state. Because automatic beveling is processed using a face milling cutter, the cutting force mechanism is the same as the milling process. The predicted cutting torque is obtained using a cutting force model based on specific cutting resistance. Then, the predicted cutting torque is converted into the spindle motor current value, and cutting state stability is diagnosed by comparing it with the motor current value detected during beveling operation. The experimental results show that the spindle motor current can detect abnormal cutting state such as overload and tool wear during beveling operation, and can diagnose the cutting stability using the proposed equip-current line diagram.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.6
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• pp.643-653
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• 2020

The concrete lining inspection by inspector after traffic control poses various problems such as congestion caused by traffic control and social loss costs resulting from it, and risks of traffic accidents and safety accidents for inspectors et al. To solve the problems, the concrete lining inspection has been carried out using automatic inspection equipment and image analysis that can be objectively and quantitatively investigated in overseas. In this study, to solve the problems of concrete lining inspection by inspector and to review improvement plan for inspection, inspection was carried out using automatic inspection equipment for ◯◯ tunnel that precision safety diagnosis has been conducted in 2019. Analysis was carried out for both inspection results. Automatic inspection equipment investigated defects in concrete lining such as cracks more accurately than precision safety diagnosis.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.582-584
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• 1999

Generator has synchronized with power Network after build-up output voltage. In order to prevent a current surge when synchronizing, the conditions such as identical no-load voltages identical no-load frequencies and identical phase positions must be met between generator voltage and network voltage. Hydro-Pump generators or Gas-turbine generators, Co-generation Generators that serve peak load of network are synchronized many times. So, Automatic Synchronizing Circuits are very important service. This report apply Diagnosis methods the Automatic Synchronizing Circuits(Device) by developing simulator.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.482-491
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• 2005

In this paper, we proposed the microcalcification detection algorithm which is based on wavelet transform and automatic thresholding method in the X-ray mammographic images. Digital X-ray imaging system is essential equipment in the field diagnosis and is widely used in the various fields such as chest, fracture of a bone, and dental correction. Especially, digital X-ray mammographic imaging is known as the most important method to diagnose the breast cancer, many researches to develop the imaging system are processing in country. In this paper, we proposed a microcalcifications detection algorithm necessary in the early phase of breast cancer diagnosis and showed that a algorithm could effectively detect microcalfication and could aid diagnosis-radiologist.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.6 no.1
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• pp.40-51
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• 2006

Purpose: A personal computer-based system was developed for automated metabolic profiling of organic aciduria and aminoacidopathy by gas chromatography-mass spectrometry and data interpretation for the diagnosis of metabolic disorders Methods: For automatic data profiling and interpretation, we compiled retention time, two target ions and their intensity ratio for 77 organic acids and 13 amino acids metabolites. Metabolites above the cut-off values were flagged as abnormal compounds. The data interpretation was a based on combination of flagged metabolites. Diagnostic or index metabolites were categorized into three groups, "and", "or" and "NO" compiled for each disorder to improve the specificity of the diagnosis. Groups "and" and "or" comprised essential and optional compounds, respectively, to reach a specific diagnosis. Group "NO" comprised metabolites that must be absent to make a definite diagnosis. We tested this system by analyzing patients with confirmed Propionic aciduria and others. Results: In all cases, the diagnostic metabolites were identified and correct diagnosis was founded to be made among the possible disease suggested by the system. Conclusion: The study showed that the developed method could be the method of choices in rapid, sensitive and simultaneous screening for organic aciduria and amino acidopathy with this simplified automated system.