• 제목/요약/키워드: Diagnosis of performance

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전사적 CRM 전략의 진단 및 평가 방법론 개발 (A Diagnosis and Assessment Methodology for Enterprise CRM Strategy)

  • 김형수;정한근
    • 한국경영과학회지
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    • 제37권3호
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    • pp.23-37
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    • 2012
  • As Customer Relationship Management (CRM) strategy is becoming a core competence more recently, many companies want a reliable CRM assessment system which enables measuring and diagnosing corporate customer strategies for building an optimized CRM strategy. However, there has been short of researches on developing the CRM diagnosis methodology that is directly applicable to real practices. Drawing upon the theoretical framework of CRM scorecard, we developed and suggested a corporate CRM diagnosis methodology that can systematically understand and assess the corporate CRM capability and performance, guiding their future directions. Companies can search the important but weak areas among various CRM strategy subjects through the proposed diagnostic procedures. This framework has a hierarchical structure that has four evaluative domains each of which has several evaluative subjects consisting of many evaluative themes: the score of upper factor is the weighted average of its subordinate factor scores. And the score of each evaluative theme is the weighted average of quantitative and qualitative evaluative indexes. Quantitative indexes are calculated by analyzing customer and sales data and qualitative ones are derived from survey data. Each evaluative index has more than one measure and its score can be derived from its own formula consisting of the measures. To prove the concept, we applied this framework to a real company and concluded that it might be appropriate to understand the corporate CRM strategy situation, find the pain points, and resolve them for better CRM implementation.

고장모사 시뮬레이션을 이용한 터보냉동기의 고장검출 및 진단 알고리즘 개발 (Development of a Fault Detection and Diagnosis Algorithm Using Fault Mode Simulation for a Centrifugal Chiller)

  • 한동원;장영수
    • 설비공학논문집
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    • 제20권10호
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    • pp.669-678
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    • 2008
  • When operating a complex facility, Fault Detection and Diagnosis (FDD) system is beneficial in equipment management by providing the operator with tools which can help find out a failure of the system. In this research, FDD algorithm was developed using the general pattern classifier method that can be applied to centrifugal chiller system. The simulation model for a centrifugal chiller system was developed in order to obtain characteristic data of turbo chiller system under normal and faulty operation. We tested FDD algorithm of a centrifugal chiller using data from simulation model at full load performance and 60% part load performance. In this research, we presented fault detection method using a normalized distance. Sensitivity analysis of fault detection was carried out with respect to fault progress. FDD algorithm developed in this study was found to indicate each failure modes accurately.

모터펌프의 지능형 진단시스템 구현에 관한 연구 (A Study on the Implementation of Intelligent Diagnosis System for Motor Pump)

  • 안재현;양오
    • 반도체디스플레이기술학회지
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    • 제18권4호
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    • pp.87-91
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    • 2019
  • The diagnosis of the failure for the existing electrical facilities was based on regular preventive maintenance, but this preventive maintenance was limited in preventing a lot of cost loss and sudden system failure. To overcome these shortcomings, fault prediction and diagnostic techniques are critical to increasing system reliability by monitoring electrical installations in real time and detecting abnormal conditions in the facility early. As the performance and quality deterioration problem occurs frequently due to the increase in the number of users of the motor pump, the purpose is to build an intelligent control system that can control the motor pump to maximize the performance and to improve the quality and reliability. To this end, a vibration sensor, temperature sensor, pressure sensor, and low water level sensor are used to detect vibrations, temperatures, pressures, and low water levels that can occur in the motor pump, and to build a system that can identify and diagnose information to users in real time.

전기적특성과 환경인자를 고려한 태양광모듈의 열화진단 알고리즘 개발 (Development of Aging Diagnosis Algorithm for Photovoltaic Modules by Considering Electric Characteristics and Environment Factors)

  • 이계호;최성식;김병기;정종윤;김찬혁;노대석
    • 전기학회논문지
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    • 제64권10호
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    • pp.1411-1417
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    • 2015
  • The installation of PV system to the power distribution system is being increased as one of solutions for environmental pollution and energy crisis. However, the efficiency of PV system is getting decreased because of the aging phenomenon and several operation obstacles. Therefore, The technology development of aging diagnosis of PV modules are required in order to improve operation performance of PV modules. This paper proposes evaluation algorithm for aging state in PV modules by using the electrical characteristics of PV modules and environmental factors. And also, this paper presents a operation evaluation system of PV modules based on the proposed aging diagnosis algorithm of PV modules. From the simulation results of proposed evaluation system, it is confirmed that the proposed algorithm is a useful tool for aging diagnosis of PV systems.

부분최소제곱법 모델의 파라미터 추정을 이용한 화학공정의 이상진단 모델 개발 (The Development of a Fault Diagnosis Model based on the Parameter Estimations of Partial Least Square Models)

  • 이광오;이창준
    • 한국안전학회지
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    • 제34권4호
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    • pp.59-67
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    • 2019
  • Since it is really hard to construct process models based on prior process knowledges, various statistical approaches have been employed to build fault diagnosis models. However, the crucial drawback of these approaches is that the solutions may vary according to the fault magnitude, even if the same fault occurs. In this study, the parameter monitoring approach is suggested. When a fault occurs in a chemical process, this leads to trigger the change of a process model and the monitoring parameters of process models is able to provide the efficient fault diagnosis model. A few important variables are selected and their predictive models are constructed by partial least square (PLS) method. The Euclidean norms of parameters of PLS models are estimated and a fault diagnosis can be performed as comparing with parameters of PLS models based on normal operational conditions. To improve the monitoring performance, cumulative summation (CUSUM) control chart is employed and the changes of model parameters are recorded to identify the type of an unknown fault. To verify the efficacy of the proposed model, Tennessee Eastman (TE) process is tested and this model can be easily applied to other complex processes.

The Role of Quantitative Electroencephalogram in the Diagnosis and Subgrouping of Attention-Deficit/Hyperactivity Disorder

  • Bong, Su Hyun;Kim, Jun Won
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • 제32권3호
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    • pp.85-92
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    • 2021
  • Attention-deficit/hyperactivity disorder (ADHD) leads to functional decline in academic performance, interpersonal relationships, and development in school-aged children. Early diagnosis and appropriate intervention can significantly reduce the functional decline caused by ADHD. Currently, there is no established biological marker for ADHD. Some studies have suggested that various indicators from the quantitative electroencephalogram (QEEG) may be useful biological markers for the diagnosis of ADHD. Until the 2010s, theta/beta ratio (TBR) was a biomarker candidate for ADHD that consistently showed high diagnostic value. However, limitations of TBR have recently been reported. Studies have demonstrated that phase-amplitude coupling, especially theta phase-gamma amplitude coupling, are related to cognitive dysfunction and may assist in the diagnosis of ADHD. As yet, the underlying mechanism is not clearly established, and the clinical efficacy of these biomarkers needs to be proven through well-controlled studies. Based on the heterogeneous characteristics of ADHD, subgrouping through QEEG plays a key role in diagnosis and treatment planning. Sophisticated, well-designed studies and meta-analyses are necessary to confirm these findings.

Fault Diagnosis of Transformer Based on Self-powered RFID Sensor Tag and Improved HHT

  • Wang, Tao;He, Yigang;Li, Bing;Shi, Tiancheng
    • Journal of Electrical Engineering and Technology
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    • 제13권5호
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    • pp.2134-2143
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    • 2018
  • This work introduces a fault diagnosis method for transformer based on self-powered radio frequency identification (RFID) sensor tag and improved Hilbert-Huang transform (HHT). Consisted by RFID tag chip, power management circuit, MCU and accelerometer, the developed RFID sensor tag is used to acquire and wirelessly transmit the vibration signal. A customized power management including solar panel, low dropout (LDO) voltage regulator, supercapacitor and corresponding charging circuit is presented to guarantee constant DC power for the sensor tag. An improved band restricted empirical mode decomposition (BREMD) which is optimized by quantum-behaved particle swarm optimization (QPSO) algorithm is proposed to deal with the raw vibration signal. Compared with traditional methods, this improved BREMD method shows great superiority in reducing mode aliasing. Then, a promising fault diagnosis approach on the basis of Hilbert marginal spectrum variations is brought up. The measured results show that the presented power management circuit can generate 2.5V DC voltage for the rest of the sensor tag. The developed sensor tag can achieve a reliable communication distance of 17.8m in the test environment. Furthermore, the measurement results indicate the promising performance of fault diagnosis for transformer.

Optical Coherence Tomography Applications for Dental Diagnostic Imaging: Prototype System Performance and Preclinical Trial

  • Eun Seo Choi;Won-Jin Yi;Chang-Seok Kim;Woosub Song;Byeong-il Lee
    • Current Optics and Photonics
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    • 제7권3호
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    • pp.283-296
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    • 2023
  • An intraoral spectral domain optical coherence tomography (SD-OCT) system has been developed, using a custom-built hand-held scanner and spectrometer. The hand-held OCT probe, based on a microelectromechanical systems scanner and a self-built miniaturized drive circuit, had a field of view sufficient for dental diagnosis. The spectrometer using a fabricated f-theta lens provided the image depth required for dental diagnosis. The axial and transverse resolutions of the OCT system in air were 7.5 ㎛ and 12 ㎛ respectively. The hand-held probe could scan an area of 10 × 10 mm2, and the spectrometer could image along a depth of 2.5 mm. To verify the utility of the developed OCT system, OCT images of tooth hard and soft tissues were acquired, and a user-interface program for diagnosis was developed. Early caries and microcracks that were difficult to diagnose with existing methods could be found, and the state of restoration could be observed. Measuring the depth of the gingival sulcus, distinguishing subgingival calculus, and detecting an implant under the gingiva suggested the possibility of the SD-OCT system as a diagnostic for dental soft tissues. Through the presented OCT images, the capability of the developed SD-OCT system for dental diagnosis was demonstrated.

A Fault Diagnosis Method in Cascaded H-bridge Multilevel Inverter Using Output Current Analysis

  • Lee, June-Hee;Lee, June-Seok;Lee, Kyo-Beum
    • Journal of Electrical Engineering and Technology
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    • 제12권6호
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    • pp.2278-2288
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    • 2017
  • Multilevel converter topologies are widely used in many applications. The cascaded H-bridge multilevel inverter (CHBMI), which is one of many multilevel converter topologies, has been introduced as a useful topology in high and medium power. However, it has a drawback to require a lot of switches. Therefore, the reliability of CHBMI is important factor for analyzing the performance. This paper presents a simple switch fault diagnosis method for single-phase CHBMI. There are two types of switch faults: open-fault and short-fault. In the open-fault, the body diode of faulty switch provides a freewheeling current path. However, when the short-fault occurs, the distortion of output current is different from that of the open-fault because it has an unavailable freewheeling current flow path due to a disconnection of fuse. The fault diagnosis method is based on the zero current time analysis according to zero-voltage switching states. Using the proposed method, it is possible to detect the location of faulty switch accurately. The PSIM simulation and experimental results show the effectiveness of proposed switch fault diagnosis method.

밸브누설 진단용 PZT 및 Pb-Free 음향센서의 압전특성 비교 연구 (Study on the Comparison of Piezoelectric Property of Acoustic Sensor for Valve Leak Diagnosis)

  • 이상국;박성근
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2007년도 춘계학술대회B
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    • pp.3383-3388
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    • 2007
  • To compare the sensor performance of AE leak diagnosis system which can measure valve leak conditions, AE activities such as RMS voltage level, AE signal trend, leak rate degree according to AE database, FFT spectrum were measured on valve of the simulated test system for power plant. AE activities were recorded and analyzed from various operating conditions including different temperature, pressure difference, valve size and fluid using both piezoelectric acoustic emission sensor and Pb-Free acoustic emission sensor. The results of this study are utilized to select the type of sensors, the frequency band for filtering and thereby to improve the signal-to-noise ratio for diagnosis or monitoring of valves in operation. As the final result of application study above, portable type leak diagnosis system by AE was developed. The outcome of the study can be definitely applied as a means of the diagnosis or monitoring system for energy saving and prevention of accident for power plant valve.

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