• 대한기계학회논문집
• /
• 제18권2호
• /
• pp.323-338
• /
• 1994

This paper outlines a framework for performing intelligent sensor validation for a diagnostic expert system while reasoning under uncertainty. The emphasis is on the algorithmic preprocess technique. A companion paper focusses on heuristic post-processing. Sensor validation plays a vital role in the ability of the overall system to correctly detemine the state of a plant monitored by imperfect sensors. Especially, several theoretical developments were made in understanding uncertain sensory data in statistical aspect. Uncertain information in sensory values is represented through probability assignments on three discrete states, "high", "normal", and "low", and additional sensor confidence measures in Algorithmic Sv.Upper and lower warning limits are generated from the historical learning sets, which represents the borderlines for heat rate degradation generated in the Algorithmic SV initiates a historic data base for better reference in future use. All the information generated in the Algorithmic SV initiate a session to differentiate the sensor fault from the process fault and to make an inference on the system performance. This framework for a diagnostic expert system with sensor validation and reasonig under uncertainty applies in HEATXPRT$^{TM}$, a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants.

• 한국한의학연구원논문집
• /
• 제13권3호
• /
• pp.105-110
• /
• 2007

This work reports the pulse diagnosis system using FBG sensors which can display pulse signals detected while oriental medical doctors are conducting pulse diagnoses and simultaneously pressing the sensors by three fingers. Each optical fiber has five FBG sensing units fabricated in 2 mm width and 2 mm inter-sensor spacing. Three optical fibers with the FBG units in the parallel line configuration are then placed on each finger-pressing region and thus overall 9 fibers are used for the pulse measurements on the so-called "chon", "gwan", and "ch대k". A fixture holding the optical fiber arrays is able to adjust the height of the FBG sensing units while placing the fibers on the wrist. The pulse signals detected by the FBG sensors from chon, kwan, and chuk have been analyzed using 4 channel spectrum analyzer connected to the optical fibers. The measured pulse signals exhibit variations due to the nonuniform pressure distributions applied. resulting in the differences in the detected pulse signals between fiber lines. However. this work is the first step towards objective and quantitative analyses of the pulse diagnosis in oriental medicine which has traditionally been performed on subjective basis. Future works will be devoted to improving sensor stability, developing the way applying pressure and algorithms reporting the objective classification of the pulse status from systemic measurements using the sensors instead of relying on the clinicians' diagnoses subjectively performed. A successful pulse diagnosis system emerging in the future is expected to contribute to education as well as promoting pulse diagnosis in oriental medicine to the scientific research area.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
• /
• pp.204-210
• /
• 1998

This paper discusses an on-line fuzzy dynamic model(FDM) identification of nonlinear processes for the design of fuzzy model based fault detection and isolation(FDI). The dynamic behavior of a nonlinear process is represented by a fuzzy aggregation of a set of local linear models. The identification is divided into two procedures. The first is the off-line identification of membership function. The second is the on-line identification of the local linear models. Then, we propose a residual generation scheme based on the parameters of local linear models and show that the scheme can be used for the design of FDI

• Journal of Biosystems Engineering
• /
• 제36권5호
• /
• pp.319-325
• /
• 2011

This study was conducted to figure out the diagnosis basis of cooling performance depending on water amount in the refrigerant of air conditioner, which can be estimated by the temperatures and pressures along the refrigerant circulation line. A car air conditioner of SONATA III (Hyundai motor Co., Korea) was tested at maximum cooling condition at the engine speed of 1500 rpm in the room controlled at 33~$35^{\circ}C$ air temperature and 55~57% relative humidity conditionally. Measured variables were temperature differences between inlet and outlet pipe surfaces of the compressor, condenser, receive drier and evaporator; and high pressure and low pressure in the refrigerant circulation line; and temperature difference between inlet and outlet air of the cooling vent of evaporator. In this study, changes of the water amount in the refrigerant were correlated to the temperatures and pressure changes and also water amount caused poor cooling performance. As water amount increased in the refrigerant in the air conditioner, the performance of the cooling or the heat transfer became worse. Temporal variations of the surface temperature of the evaporator outlet pipe and the low-side pressure showed various patterns that could estimate the water amount. When the water amount caused bad cooling performance, the patterns of the temperature of the evaporator outlet pipe indicated irregular fluctuation greater than $5^{\circ}C$. When the diagnosis system is using just external sensors of the low-side pressure and the temperatures of inlet and outlet air of cooling vent of the evaporator, the precise pattern of bad cooling performance caused by excess water amount in the cooling line was irregular pressure fluctuation, 25 kPa under 120 kPa, and temperature, $12^{\circ}C$ and less.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
• /
• pp.110-112
• /
• 1999

Recently the substation automation is actively researched at each country. Since the substation automation is an integrated system that consist of electrical, electronic and computer technologies, performance evaluation is very important to inspect the developed system's applicable possibility for real power system. Most studies are verified using computer simulation, because it is hard to apply them to real power systems. Therefore development of a substation simulator is necessary for the performance evaluation of many application systems such as operator aid system. This paper introduces a substation simulator. An intelligent fault diagnosis and restorative control expert system is also introduced UDP/IP is applied as a protocol for data transport between expert system and SC(station computer). As to the Graphic User Interface, C++ Language and Visual Basic is used in the Windows NT operating system together with four Pentium II systems.

• 한국CDE학회논문집
• /
• 제17권4호
• /
• pp.274-281
• /
• 2012

This paper proposed a control simulation method for design and verification of the transport system in an automobile assembly line based on digital manufacturing system. The design of the transport system involves two major activities: mechanical design (device specification) and electrical design (device behavior and system control). Conventionally, the simulation and emulation system of the transport system focuses on the abstract level, which mainly deals with design verification, alternative comparison, and system diagnosis. Although it can provide overall system visibility in monitoring how well it works in the process and view, its simulation models are not sufficiently realistic to be used for a detailed design or for implementation purposes. In this paper, a digital simulation model for a transport system in an automotive assembly line is constructed by adapting a digital manufacturing methodology. We use the concept of the "Virtual Probe", which transport a carrier instead of the belt of the conveyor. In conclusion, the proposed method is valuable in the process of test run in the shop floor. This method would reduce the time and effort for validating the manufacturing system and improve the productivity and integrity of the control program.

• Korean Journal of Radiology
• /
• 제22권3호
• /
• pp.354-365
• /
• 2021

Objective: To investigate the diagnostic performance of contrast-enhanced ultrasound (CEUS) and its role as a second-line imaging modality after gadoxetate-enhanced MRI (Gd-EOB-MRI) in the diagnosis of hepatocellular carcinoma (HCC) among at risk observations. Materials and Methods: We prospectively enrolled participants at risk of HCC with treatment-naïve solid hepatic observations (≥ 1 cm) of Liver Imaging Reporting and Data System (LR)-3/4/5/M during surveillance and performed Gd-EOB-MRI. A total of one hundred and three participants with 103 hepatic observations (mean size, 28.2 ± 24.5 mm; HCCs [n = 79], non-HCC malignancies [n = 15], benign [n = 9]; diagnosed by pathology [n = 57], or noninvasive method [n = 46]) were included in this study. The participants underwent CEUS with sulfur hexafluoride. Arterial phase hyperenhancement (APHE) and washout on Gd-EOB-MRI and CEUS were evaluated. The distinctive washout in CEUS was defined as mild washout 60 seconds after contrast injection. The diagnostic ability of Gd-EOB-MRI and of CEUS as a second-line modality for HCC were determined according to the European Association for the Study of the Liver (EASL) and the Korean Liver Cancer Association and National Cancer Center (KLCA-NCC) guidelines. The diagnostic abilities of both imaging modalities were compared using the McNemar's test. Results: The sensitivity of CEUS (60.8%) was lower than that of Gd-EOB-MRI (72.2%, p = 0.06 by EASL; 86.1%, p < 0.01 by KLCA-NCC); however, the specificity was 100%. By performing CEUS on the inconclusive observations in Gd-EOB-MRI, HCCs without APHE (n = 10) or washout (n = 12) on Gd-EOB-MRI further presented APHE (80.0%, 8/10) or distinctive washout (66.7%, 8/12) on CEUS, and more HCCs were diagnosed than with Gd-EOB-MRI alone (sensitivity: 72.2% vs. 83.5% by EASL, p < 0.01; 86.1% vs. 91.1% by KCLA-NCC, p = 0.04). There were no false-positive cases for HCC on CEUS. Conclusion: The addition of CEUS to Gd-EOB-MRI as a second-line diagnostic modality increases the frequency of HCC diagnosis without changing the specificities.

• 한국조명전기설비학회:학술대회논문집
• /
• 한국조명전기설비학회 2007년도 춘계학술대회 논문집
• /
• pp.274-279
• /
• 2007

The fault identification of electrical rotating machinery have been special interests due to one of important elements in the industrial production line. It is directly related with products quality and production costs. The sudden breakdown of a motor will affect to the shut down of the whole processes. Therefore, rotating machines are required to a periodic diagnosis and maintenance for improving its reliability and increasing their lifetime. The objective of this work is to develop the diagnosis system with current signals for the effective identification of healthy and faulty motors using the developed diagnosis algorithm, which consists of the feature calculation, feature extraction, and feature classification procedures.

• Journal of Electrical Engineering and Technology
• /
• 제6권1호
• /
• pp.111-118
• /
• 2011

In recent years, various types of partial discharge (PD) methods such as capacitive, inductive, electromagnetic, and acoustic coupling techniques have been developed for diagnosing rotating machines. An electromagnetic (EM) probe, which is an inductively coupled type of sensor, is required for detecting corona and internal discharges during off-line tests. In this study, a new technique for enhancing the measurement sensitivities for corona and internal discharge based on an EM inductive position sensor is proposed. An EM probe that winds wires around horseshoe-shaped and cylindershaped ferrites as helices is designed and optimized for the implementation of off-line PD monitoring of the stator winding of a rotating machine. The measurement system based on this design is implemented, and it is verified from the results of the experiment performed in this study that the probe provides similar performance as existing commercial products.

• KIEE International Transactions on Electrophysics and Applications
• /
• 제5C권3호
• /
• pp.138-142
• /
• 2005

In this paper, we compared recognition rates between NN(neural networks) and clustering method as a scheme of off-line PD(partial discharge) diagnosis which occurs at the stator coil of traction motor. To acquire PD data, three defective models are made. PD data for classification were acquired from PD detector. And then statistical distributions are calculated to classify model discharge sources. These statistical distributions were applied as input data of two classification tools, BP(Back propagation algorithm) and ANFIS(adaptive network based fuzzy inference system) pre-processed FCM(fuzzy c-means) clustering method. So, classification rate of BP were somewhat higher than ANFIS. But other items of ANFIS were better than BP; learning time, parameter number, simplicity of algorithm.