• Journal of Electrical Engineering and Technology
• /
• 제13권5호
• /
• pp.2134-2143
• /
• 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.

• Current Optics and Photonics
• /
• 제7권3호
• /
• pp.283-296
• /
• 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.

• Journal of Electrical Engineering and Technology
• /
• 제12권6호
• /
• pp.2278-2288
• /
• 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.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2007년도 춘계학술대회B
• /
• pp.3383-3388
• /
• 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.

• 의료ㆍ복지 건축 : 한국의료복지건축학회 논문집
• /
• 제26권4호
• /
• pp.29-38
• /
• 2020

Purpose: The first thing to be done in promoting community care is local diagnosis. Therefore, this study attempted to derive the physical infrastructure to be diagnosed, and to develop diagnostic items and diagnostic indicators applicable to this. Methods:: First, the physical infrastructure related to the community care is derived. And the diagnosis items are derived using the checklist of 'community support and health services' in the WHO Guide for Global age-friendly cities. Next, by analyzing previous studies, we develop diagnostic indicators for each diagnostic item and explore their applicability. Results: As a result of deriving the physical infrastructure for each area of housing, health service, and nursing care for community care, 22 facilities were derived for 9 types. Diagnosis items for the facilities are 1)regional equity, 2)proximity between facilities, 3)transportation access, 4)regional use, 5)barrier-free design, 6)diversity of facilities, and a total of 14 diagnostic indicators was derived. We reviewed and suggested the applicability of diagnostic items and indicators by each physical infrastructure. Implications: For the realization of community care, local diagnosis should not be limited to sim- ply grasping the presence or absence of facilities and the total amount. Instead it should strengthen capabilities by conducting diagnosis to understand the performance of facilities.

• 한국통신학회논문지
• /
• 제31권5C호
• /
• pp.483-489
• /
• 2006

Somani와 Peleg은 k개의 부정확한 진단을 용인함으로써 결함의 개수가 t(차원)개를 초과할 경우에도 시스템을 진단하는 t/k-dignosable 시스템을 제안하였다. 한편 Kranakis와 Pelc는 결함의 개수가 t개를 초과하지 않는 경우에 하이퍼큐브를 보다 효율적으로 진단하는 알고리즘을 제안하였다. 이 논문에서는 Somani등이 제안한 것처럼 k=1, 2, 3개의 부정확한 진단을 용인하는 경우에 Kranakis등이 제안한 효율적인 방법을 기반으로 하이퍼큐브를 진단하는 알고리즘을 제안한다. 그리고 제안한 알고리즘이 약 두 배 이상 더 많은 결함을 진단하면서도 기존의 알고리즘보다 효율이 거의 떨어지지 않는다는 사실을 분석을 통하여 확인할 수 있었다.

• Journal of Advanced Marine Engineering and Technology
• /
• 제37권5호
• /
• pp.520-526
• /
• 2013

전력설비 용량의 증가와 기술의 진보에 따라 회전기가 대용량, 고전압화 되고 있다. 그러므로 발전기 고장예방을 위한 진단시스템의 필요성이 점차 증대되고 있다. 따라서 본 논문에서는 동기발전기 불시 정지 사고에 따른 피해를 예방할 수 있는 고장진단 시스템을 개발하였다. 고장진단 시스템을 검증하기 위해 실제 동기발전기와 권선구조가 같은 소규모의 시험장비를 제작하였다. 또한 회전자권선의 단락을 진단하기 위해 홀센서와 검출시스템을 구성하여 정상상태 뿐 아니라 회전자권선 단락 등 다양한 고장상태에 대한 공극자속파형을 검출하였다.

• 한국소음진동공학회논문집
• /
• 제21권11호
• /
• pp.1020-1028
• /
• 2011

As rotating machines play an important role in industrial applications such as aeronautical, naval and automotive industries, many researchers have developed various condition monitoring system and fault diagnosis system by applying artificial neural network. Since using obtained signals without preprocessing as inputs of neural network can decrease performance of fault classification, it is very important to extract significant features of captured signals and to apply suitable features into diagnosis system according to the kinds of obtained signals. Therefore, this paper proposes a neural-network-based fault diagnosis system using AR coefficients as feature vectors by LPC(linear predictive coding) and EIV(errors-in variables) analysis. We extracted feature vectors from sound, vibration and current faulty signals and evaluated the suitability of feature vectors depending on the classification results and training error rates by changing AR order and adding noise. From experimental results, we conclude that classification results using feature vectors by EIV analysis indicate more than 90 % stably for less than 10 orders and noise effect comparing to LPC.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
• /
• pp.763-765
• /
• 1999

Due to the improvement of PC Performance and Windows-based OS, PC-based control system is gradually taking over industrial control in the industry site. In this paper, we suggest the method to configure PC-based fault diagnosis system of I/O cards and the method to generate test signals to find out the short conditions of adjacent channels of cables which connect I/O cards with terminal blocks.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1992년도 추계학술대회 논문집
• /
• pp.293-297
• /
• 1992

For the computerized monitoring and diagnosis of the undesirable chip chatter which are major obstacles to FMS, a pattern recognition system based on multi-layer perception neural network is developed and the performance of the system is experimentally evaluated. Experimental results show that recognition of the two class state of normal or abnormal cutting gives satisfactory results with success rate of 81`91%. Therefore, the proposed system has possibility for use in monitoring and diagnosis of automatic manufacturing system