• 음성과학
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• 제12권3호
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• pp.19-33
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• 2005

Tremor is a main factor of parkinsonism. Voice tremor may be the first, later or the only symptom of a neurological disease and its frequency, amplitude, and regularity may differ among the diseases of different neural subsystems. Differential diagnosis between idiopathic Parkinson's disease (IPD) and multiple system atrophy (MSA) has been difficult. This study included three groups: (1) 6 IPD patients; (2) 6 MSA patients; and (3) 20 ageand sex-matched normal controls. The MDVP (Multidimensional Voice Program) was used to analyze the sustained /a/phonation. The results were as follows: (1) frequency perturbation parameters (jitter, sPPQ, Vf0) and FTRI of tremor parameter of two patient groups were statistically different from those of the controls (p < .01); (2) measures were higher in short-term and long-term f0 and amplitude perturbation in MSA than IPD; (3) however, any acoustic parameters between IPD and MSA were not statistically different; except for the rate of frequency tremor, 4$\sim$5 Hz in IPD, 5$\sim$11 Hz in MSA and (4) the pattern of regularity for voice tremor through histogram indicated that amplitude of IPD was irregular while both f0 and amplitude of MSA were irregular. In conclusion, F0, rate of frequency tremor, and pattern of f0 regularity may be predictors for differential diagnosis. These findings might signify that voice tremor of parkinsonism was resulted from modulation of f0.

• Asian Pacific Journal of Cancer Prevention
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• 제15권3호
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• pp.1269-1274
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• 2014

Breast tubular adenomas are rare benign breast tumors and detailed descriptions of their sonographic appearance are necessary for differential diagnosis from fibroadenomas or breast cancers. This study investigated twenty-one histology-proved tubular adenomas in 17 patients and also included 48 fibroadenomas in 35 patients as a control group. There was no significant difference between the two groups with clinical presentation, which was age, tumor location, tumor number (p>0.05). Statistic analysis showed three significant factors in the differential diagnosis of tubular adenomas and fibroadenomas, including macro-lobulation (p=0.01), "tiny branch like" patterns (p=0.001) and vascularity (p=0.02). Other ultrasonographic features such as echogenicity, border, uniformity of echotexture, posterior acoustic enhancement, lateral wall shadowing were of no clinical significance (p>0.05). Calcifications were seen in three tubular adenomas which were different from those of carcinomas. Although tubular adenomas have some typical characteristics on sonography, surgery and core needle biopsy are still needed for complex cases to exclude progress to malignancy.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 하계학술대회 논문집 Vol.3 No.2
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• pp.894-899
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• 2002

In this papers, we proposed the new method in order to diagnosis partial discharge type of transformers. For wavelet transform, Daubechies filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion, skewness, kurtosis) about high frequency current signal per 3-electrode type (needle-plane electrode, IEC electrode and Void electrode.). Also. these coefficients are used to identify Signal of internal partial discharge in transformer. As a result. from compare of high frequency current signal amplitude and average value. we are obtained results of IEC electrode> Void electrode> Needle-Plane electrode. otherwise. In case of skewness and kurtosis, we are obtained results of Void electrode> IEC electrode > Needle-Plane electrode. As Improved method in order to diagnosis partial discharge type of transformers, we use neural network.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.231-235
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• 2001

Insulation aging diagnosis system provides early warning regarding electrical equipment defect. Early warning is very important in that it can avoid great losses resulting from unexpected shutdown of the production line. Since relations of insulation aging and partial discharge dynamics are non-linear, it is very difficult to provide early warning in an electrical equipment. In this paper, we propose the design method of insulation aging diagnosis system that use a magnetic wave and acoustic signal to diagnoses an electrical equipment. Proposed system measures the partial discharge on-line from DAS(Data Acquisition System) and acquires 2D Patterns from analyzing it. For fettering the noise contained in sensor signals we used ICA algorithms. Using this data design of the neuro-fuzzy model that diagnoses an electrical equipment is investigated. Validity of the new method is asserted by numerical simulation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.993-998
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• 1997

The advanced technology of micro-machining is starting to penetrate our lives. This technology, with which it is possible to make micro-structures by means of processing on the order of nm (micrometer = 1/1,000 mm) or less, is realizing machines that were only part of our wildest imagination. However, the fact is that many issues remain in the quest for a variety of applications. With the advent of computing technologies, information technologies, and telecommunications technologies, we foresee the need for new approaches in design, process, and the use of materials, technologies, and people in a globalized manufacturing enterprise. A new thinking paradigm is needed to focus on quality of service on the products we design and manufacture. Factories in different regions need to be co-ordinated through use of the state-of-the-art information on productivity, diagnostics, and service evaluation of manufacturing systems could be shared among different locations and partners. In this research, We develope the internet based Diagnosis system for micro machining and evaluate its characteristics by using mechatronic sensor like Dynamometer, acoustic emission, Acceleration sensor, micro phone, vision, infra-red thermometer.

• The Journal of Korean Physical Therapy
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• 제22권4호
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• pp.83-89
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• 2010

Purpose: The goal of this study was to investigate the feasibility for the early diagnosis of inflammatory arthritis by the reconstruction of three-dimensional photoacoustic imaging with a tissue phantom. Methods: Q-switched Nd:YAG laser (l = 532 nm) was applied to a tissue phantom to generate photoacoustic waves, and the acquired photoacoustic signals at different positions around the sample were used to recombine the distribution of the optical absorption and the images were subsequently generated through a reconstruction algorithm. Results: From the acquired photoacoustic signals, the surface andinner core of the phantom was clearly distinguished. Furthermore, the back-projection algorithm was able to reconstruct two-dimensional and three-dimensional photoacoustic images that contained the optical absorption property information of the tissue phantom. Conclusion: The results indicate that the photoacoustic imaging technique has many advantages such as high optical contrast and high acoustic resolution. The acquired images can be used for the early diagnosis of inflammatory arthritis by the structural information obtained from the region of interest.

• 말소리와 음성과학
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• 제4권4호
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• pp.95-107
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• 2012

As BTX-A, which has been known to be the most effective treatment for ADSD, is not effective in treating vocal tremors, voice assessment must be employed to perform differential diagnosis of SD and vocal tremor in an accurate fashion. In this study, the characteristics of vocal changes after botulinum toxin injection were compared by analyzing the voice characteristics resulting from the presence of vocal tremors using objective analysis devices, with the aim of helping to provide prognoses and to determine remedial effects in clinical cases comprising patients with adductor spasmodic dysphonia accompanied by voice tremors. Respiratory function tests, aerodynamic analysis, electroglottography (EGG), acoustic analysis, auditory perception tests, and K-VHI had been conducted at intervals of four, eight, and twelve weeks before and after injection, targeting a group of 17 ADSD female patients (a ADSD group of four with vocal tremor and a ADSD group of 13 without voice tremor). For average FVC and FEV1, the T group showed statistically significant low averages compared with the NT group, whereas the T group showed statistically significant high average ATRI compared with the NT group. In addition, the T group showed a statistically significant Fatr, lower than that of the NT group. For the ADSD group of patients with voice tremor, their vocal tremor remained unchanged despite noticeable decrease in wringing voices. In other words, as the vocal tremor and wringing voices are two distinctive features, there is a need for the two features to be targeted separately for differential diagnosis.

• 한국소음진동공학회논문집
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• 제24권7호
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• pp.555-561
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• 2014

Acoustic Emission technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the bearing problems and wavelet transform is a powerful method to detect faults occurred on rotating machinery. However, exact method for AE signal is not developed yet for the rotating machinery diagnosis. Therefore, in this paper two methods which are processed by Hilbert transform and DET for feature extraction. In addition, we evaluate the classification performance with varying the parameter from 2 to 15 for feature selection DET, 0.01 to 1.0 for the RBF kernel function of SVR, and the proposed algorithm achieved 94 % classification of averaged accuracy with the parameter of the RBF 0.08, 12 feature selection.

• Nuclear Engineering and Technology
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• 제53권1호
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• 대한후두음성언어의학회지
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• 제23권1호
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• pp.48-51
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• 2012

Background and Objectives : Vocal fold cyst is generally treated by surgical resection, it has a difference with vocal fold polyp, treated by conservative management first. Decrease in mucosal waves is known as main diagnostic criteria of vocal fold cyst. Sometimes there is a difficulty for diffrential diagnosis between cyst and polyp only by endoscopic examination. The purpose of the study is to identify the objective features of vocal cyst and polyp on the basis of voice analysis for the proper differential diagnosis, especially at high pitched phonation. Materials and Method : The voice analysis was done in 15 focal fold cyst patients and 42 vocal fold polyp. Parameters of perceptual assessment, acoustic and aerodynamic measure, and voice range profile were compared between two groups. Results : Vocal fold cyst patients showed significantly reduced MPT by acoustic and aerodynamic analysis, narrowed frequency-range and low maximun frequency by voice range profile analysis compared with vocal fold polyp patient. Maximun frequency 381 Hz is established for cut off value, differential diagnosis between cyst and polyp (ROC analysis, sensitivity 60%, specificity 68%). Conclusion : Voice analysis is helpful for differential diagnosis between vocal fold cyst and polyp, especially there is a difficulty for distinguish cyst from polyp at clinical situation by endoscopic examination. The result of decreased maximum frequncy at vocal fold cyst supports incomplete high-pitched phonation and falsetto regester at vocal fold cyst patients due to decreased mucosal wave, compared with vocal fold polyp patients.