• Vacuum Magazine
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• v.2 no.1
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• pp.31-34
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• 2015

This article introduces fundamentals of self-diagnosis and predictive (or preventive) maintenance technologies for dry vacuum pumps. The state variables of dry pumps are addressed, such as the pump and motor body temperatures, consumption currents of main and booster pumps, mechanical vibration, and exhaust pressure, etc. The adaptive parametric models of the state variables of the dry pump are exploited to provide dramatic reduction of data size and computation time for self-diagnosis. Two indicators, the Hotelling's $T^2$ and the sum of squares residuals (Q), are illustrated to be quite effective and successful in diagnosing dry pumps used in the semiconductor processes.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.10
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• pp.931-940
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• 2017

This paper describes a predictive fault diagnosis algorithm for autonomous vehicles based on a kinematic model that uses a sliding mode observer. To ensure the safety of autonomous vehicles, reliable information about the environment and vehicle dynamic states is required. A predictive algorithm that can interactively diagnose longitudinal environment and vehicle acceleration information is proposed in this paper to evaluate the reliability of sensors. To design the diagnosis algorithm, a longitudinal kinematic model is used based on a sliding mode observer. The reliability of the fault diagnosis algorithm can be ensured because the sliding mode observer utilized can reconstruct the relative acceleration despite faulty signals in the longitudinal environment information. Actual data based performance evaluations are conducted with various fault conditions for a reasonable performance evaluation of the predictive fault diagnosis algorithm presented in this paper. The evaluation results show that the proposed diagnosis algorithm can reasonably diagnose the faults in the longitudinal environment and acceleration information for all fault conditions.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.143-147
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• 2005

Monitoring and diagnosis of the operating machines are very important for safety operation and maintenance in the industrial fields. These machines are most rotating machines and the diagnosis of the machines has been researched for long time. We can easily see the faulted signal of the rotating machines from the changes of the signals in frequency. The Linear Predictive Coding(LPC) is introduced for signal analysis in frequency domain. In this paper, we propose fault detection and diagnosis method using the Linear Predictive Coding(LPC) and residual signal energy. We applied our method to the induction motors depending on various status of faulted condition and could obtain good results.

• Clinical and Experimental Emergency Medicine
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• v.5 no.4
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• pp.264-271
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• 2018

Objective For patients with acute myocardial infarction (AMI), symptoms assessed by emergency medical services (EMS) providers have a critical role in prehospital treatment decisions. The purpose of this study was to evaluate the diagnostic accuracy of EMS provider-assessed cardiac symptoms of AMI. Methods Patients transported by EMS to 4 study hospitals from 2008 to 2012 were included. Using EMS and administrative emergency department databases, patients were stratified according to the presence of EMS-assessed cardiac symptoms and emergency department diagnosis of AMI. Cardiac symptoms were defined as chest pain, dyspnea, palpitations, and syncope. Disproportionate stratified sampling was used, and medical records of sampled patients were reviewed to identify an actual diagnosis of AMI. Using inverse probability weighting, verification bias-corrected diagnostic performance was estimated. Results Overall, 92,353 patients were enrolled in the study. Of these, 13,971 (15.1%) complained of cardiac symptoms to EMS providers. A total of 775 patients were sampled for hospital record review. The sensitivity, specificity, positive predictive value, and negative predictive value of EMS provider-assessed cardiac symptoms for the final diagnosis of AMI was 73.3% (95% confidence interval [CI], 70.8 to 75.7), 85.3% (95% CI, 85.3 to 85.4), 3.9% (95% CI, 3.6 to 4.2), and 99.7% (95% CI, 99.7 to 99.8), respectively. Conclusion We found that EMS provider-assessed cardiac symptoms had moderate sensitivity and high specificity for diagnosis of AMI. EMS policymakers can use these data to evaluate the pertinence of specific prehospital treatment of AMI.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2612-2616
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• 2003

Method for performance monitoring and diagnosis of a MIMO control system has been studied aiming at application to model predictive control (MPC) for industrial processes. The performance monitoring part is designed on the basis of the traditional SPC/SQC method. To meet the underlying premise of Schwart chart observation that the observed variable should be univariate and independent, the process variables are decorrelated temporally as well as spatially before monitoring. The diagnosis part was designed to identify the root of performance degradation among the controller, process, and disturbance. For this, a method to estimate the model-error and disturbance signal has been devised. The proposed methods were evaluated through numerical examples.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.1
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• pp.44-51
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• 2023

The RCP is one of the main components in nuclear power plants and plays an important role in circulating coolant to the RCS system. Currently, nuclear plants are monitored using various monitoring systems. However, since they operate independently according to their functional purpose, it is not able to analyze vibration and operation/performance information comprehensively, and thus failure diagnosis accuracy is limited. In addition, these systems do not provide some important information (such as fault type, parts and cause) necessary for emergency actions, but provide only alarm information. To improve these technical problems, this study proposes a diagnosis technique (M/L, Rule-based model, Data-driven model, Narrow band model) and methodology for comprehensive analysis.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.33 no.4
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• pp.367-374
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• 2007

Purpose: The diagnostic relevancies and characteristics and of clinical methods in the diagnosis of internal derangement(ID) were tested by comparing the results of them with those of magnetic resonance imaging(MRI). Methods: 75 patients(150 temporomandibular joints; TMJs), who were suspected to have ID by clinical diagnoses, were included. Clinical diagnoses including mouth opening pathway and TMJ sound were conducted and MRI takings were done. Accuracies, sensitivities, specificities, positive predictive values, and negative predictive values of clinical diagnosis, mouth opening pathway, and TMJ sound were calculated by comparing with diagnoses with MRIs. Results: Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of clinical diagnosis were 59.3%, 83%, 49%, 81%, and 51%. They were 59%, 82%, 25%, 73%, and 35% for mouth opening pathways. Although deviation was somewhat accurate for representing disc displacement with reduction(ADDWR), other discrepancies on opening pathways were not clinically relevant. Accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of clicking sounds were 85%, 49%, 78%, 85%, and 37%. TMJs with crepitus were only three. But all TMJs with crepitus were diagnosed to have disc displacement without reduction(ADDWOR). Conclusion: When compared with diagnoses with MRIs, clinical diagnoses for ID were not so accurate. But they were suitable for screening tests for ID. Opening pathways and TMJ sounds were not so relevant in the diagnoses of IDs and so it was concluded that considerations for other factors must be included in the diagnoses of IDs.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1608-1617
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• 2018

The rapid and correct isolation of faulty submodules (SMs) is of great importance for improving the reliability of modular multilevel converters (MMCs). Therefore, a fast diagnosis method containing fault detection and fault location determination was presented in this paper. An improved incremental predictive model of arm current was proposed to detect failures, and the multi-step prediction method was used to eliminate the negative impact of disturbances. Moreover, a control method was proposed to strengthen the fault characteristics to rapidly locate faulty arms and faulty SMs by detecting the variation rate of the SM capacitor voltage. The proposed method can rapidly and easily locate faulty SMs under different load conditions without the need for additional sensors. The experimental results have validated the effectiveness of the proposed method by using a single-phase MMC with four SMs per arm.

• Clinics in Shoulder and Elbow
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• v.4 no.1
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• pp.13-16
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• 2001

Object: To determine the sensitivity, specificity, and positive and negative predictive values of an empty can test for diagnosing supraspinatus tendon tear. Methods: We reviewed 146 patients who have shoulder pain with limited active range of motion. We evaluated patients according to empty can test. Sensitivity, specificity, and positive and negative predictive values for supraspinatus test was estimated using arthroscopic evaluation. Results: A hundred and twenty-four of 127 cases with positive empty can test had supraspinatus tendon tear. Of 19 samples with negative empty can test, 15 had no supraspinatus tear. Sensitivity, specificity, and positive and negative predictive values for the empty can test were 97.6%, 83.3%, 97.6%, and 78.9%, respectively. Conclusions: Empty can test was found to have a high sensitivity and good positive predictive value in identifying the tear of rotator cuff tendon. We concluded that empty can test of the shoulder is a reliable diagnostic method which could be used for the diagnosis of rotator cuff tear.

• The Korean Journal of Cytopathology
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• v.1 no.1
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• pp.27-35
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• 1990

The authors report series of 360 cases of transthoracic fine-needle aspiration cytology (TFNA) from Oct. 1982, through Aug. 1986 at the Seoul National University Hospital. A diagnosis of neoplastic lesion was established in 50.3% of the cases. A non-neoplastic diagnosis was made in 38.5%, nondiagnostic one in 6.5% and inadequate one in 4.7% of the total. Statistical findings on cytological diagnoses were as follows. Specificity was 100% ; sensitivity, 92% ; predictive value for positive, 1.0 ; predictive value for negative, 0.9 ; concordance rate, 84.2% ; diagnostic accuracy in non-neoplastic lesion, 65.4%, and typing accuracy in malignant tumor, 0.77.