• Title/Summary/Keyword: Vibration Diagnosis

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Chaotic Behaviour of Vibration signal for Rolling Mill Bearing Diagnistics (압연기 베어링진단을 위한 진동 신호의 카오스적 거동)

  • 배영철;김이곤;최남섭;김경민;정양희;최홍준;김서영;유권종
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.4
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    • pp.759-765
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    • 2000
  • A diagnosis system that provides early warnings regarding machine malfunction is very important for rolling mill so as to avoid great losses resulting from unexpected shutdown of the production line. But it is very difficult to provide early warnings in rolling mill. Because dynamics of rolling mill is non-linear. This paper shows a chaotic behavior of vibration signal in rolling mill using embedding method. Not only phase plane and Poincare map are implemented but also FH and histogram of vibration signal in rolling mill is presented by embedding method.

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Predictive Maintenance Plan based on Vibration Monitoring of Nuclear Power Plants using Industry 4.0 (4차 산업기술을 활용한 원전설비 진동감시기반 예측정비 방안)

  • Do-young Ko
    • Transactions of the Korean Society of Pressure Vessels and Piping
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    • v.19 no.1
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    • pp.6-10
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    • 2023
  • Only about 10% of selected equipment in nuclear power plants are monitored by wiring to address failures or problems caused by vibration. The purpose is primarily for preventive maintenance, not for predictive maintenance. This paper shows that vibration monitoring and diagnosis using Industrial 4.0 enables the complete predictive maintenance for all vibrating equipments in nuclear power plants with the convergence of internet of things; wireless technology, big data through periodic collection and artificial intelligence. Predictive maintenance using wireless technology is possible in all areas of nuclear power plants and in all systems, but it should satisfy regulatory guides on electromagnetic interference and cyber security.

Development of the Multichannel Vibration Monitoring System (다채널 진동 모니터링 장치 개발)

  • Hong, Tae-Yong;Park, Soo-Hong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.11 no.7
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    • pp.671-676
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    • 2016
  • This study is about design for the Rotational Instrument of the Industry factory which is used management safety and maintenance. We developed the multichannel vibration monitering system of the self-diagnosis for middle level CMS(Condition Monitoring System) market, and that system are new features to the expandability and flexibility. Normally one channel is used for treating one signal, but developed instrument can treat four channel with one signal processing card. One rack have redundant power supply and displace and it can check vibration measurement value in field without computer. Bearing fault detection is fundamental of vibration surveillance, but sometimes can not check with vibration velocity and acceleration. So it need the filtering and the amplitude modulation on the acceleration enveloping technology when irregular vibration is happened. We developed the vibration analysis instrument which is applied such technology. And the development prototype shows activated within the vibration error limit.

Defect Detection and Defect Classification System for Ship Engine using Multi-Channel Vibration Sensor (다채널 진동 센서를 이용한 선박 엔진의 진동 감지 및 고장 분류 시스템)

  • Lee, Yang-Min;Lee, Kwang-Young;Bae, Seung-Hyun;Jang, Hwi;Lee, Jae-Kee
    • The KIPS Transactions:PartA
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    • v.17A no.2
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    • pp.81-92
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    • 2010
  • There has been some research in the equipment defect detection based on vibration information. Most research of them is based on vibration monitoring to determine the equipment defect or not. In this paper, we introduce more accurate system for engine defect detection based on vibration information and we focus on detection of engine defect for boat and system control. First, it uses the duplicated-checking method for vibration information to determine the engine defect or not. If there is a defect happened, we use the method using error part of vibration information basis with error range to determine which kind of error is happened. On the other hand, we use the engine trend analysis and standard of safety engine to implement the vibration information database. Our simulation results show that the probability of engine defect determination is 100% and the probability of engine defect classification and detection is 96%.

A Study on the fault diagnosis of a cantilever beam using the Bispectrum (바이스펙트럼을 이용한 외팔보의 결함 진단에 관한 연구)

  • Ahn, Young-Chan;Lee, Hae-Jin;Kang, Won-Ho;Lee, Jung-Yoon;Oh, Jae-Eung
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2006.11a
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    • pp.591-596
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    • 2006
  • This study is base on the fault detection and diagnosis when a crack is happened a structure. A crack in a structure will affect the modal parameters. We are searched a percentage of changes in the natural frequencies according to changes of location and propagation of the crack using the Rayleigh's energy method. This method is presented to identify the presence of a crack and its location. The study is carried out both theoretically and experimentally and the results are presented in this paper. The location of the crack is also moved from the fixed end to the free end along its length. The changes in natural frequencies are observed from theoretically study, due to the presence of the crack at different locations and depths, and the percentage change in frequency values are calculated. These results are confirmed by the experiments. And then, a difference between a cracked beam and uncracked beam observed using the bispectrum as high-order spectrum.

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Development of a Real-time Fault Diagnosis System for Electric Motors using radiated sound signals (방사음을 이용한 모터 결함 판정용 실시간 전문가 시스템 개발)

  • 경용수;김상명;왕세명
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2001.05a
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    • pp.603-608
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    • 2001
  • In order to distinguish fault electric motors automatically in real time. an intelligent diagnosis technique may be required. This paper presents an automatic fault detection system for electric motors by using their acoustic noises. Time signals of each candidate motor were measured in an anechoic chamber for further analysis. Spectral analysis was first carried out and they showed that two typical types of fault motors could be successfully distinguished in the frequency domain; bearing faults and scratches. Unlike the trend of normal motors that shows only a single dominant peak at around 2000 ㎐, several peaks are bunched together in bearing fault motors. On the other hand, large frequency noises at around 6500 ㎐ are newly arisen in scratchy fault motors. However, the processing time for spectral analysis was rather long for a real time application in production lines. Thus, a number of band-pass filters were used in the time domain instead for a real time application. Before applying filters, the bands of filters were set from the information of spectral analysis. By applying a set of band-pass filters, the RMS values of each filtered signal were calculated, and thus the normal and damaged motors could be successfully distinguished.

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Diagnostic System for Crashing and Damping Signals in Engine-Assembly Line (엔진 양산라인의 충격성 불량유형 신호 진단을 위한 진단시스템 개발)

  • Oh, Se-Do;Kim, Young-Jin;Seo, Hae-Yun;Lee, Tae-Hwi;Lee, Jae-Won
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.35 no.8
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    • pp.965-970
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    • 2011
  • We develop a diagnostic system to monitor failures in an engine-assembly line. Existing techniques such as sensory analysis, time domain analysis, frequency analysis, and statistical analysis have limitations in the diagnosis of engine-assembly failure when there are abnormal vibration waveforms (crashing and damping signals) during the assembly. We use a wavelet technique to deal with crashing and damping signals. We also implement a new technique for developing diagnostic rules from sensor data, and we demonstrate its validity.

An Availability of Low Cost Sensors for Machine Fault Diagnosis

  • SON, JONG-DUK
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2012.10a
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    • pp.394-399
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    • 2012
  • In recent years, MEMS sensors show huge attraction in machine condition monitoring, which have advantages in power, size, cost, mobility and flexibility. They can integrate with smart sensors and MEMS sensors are batch product. So the prices are cheap. And the suitability of it for condition monitoring is researched by experimental study. This paper presents a comparative study and performance test of classification of MEMS sensors in target machine fault classification by 3 intelligent classifiers. We attempt to signal validation of MEMS sensor accuracy and reliability and performance comparisons of classifiers are conducted. MEMS accelerometer and MEMS current sensors are employed for experiment test. In addition, a simple feature extraction and cross validation methods were applied to make sure MEMS sensors availabilities. The result of application is good for using fault classification.

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Application of Neural Network for Damage Diagnosis of Marine Engine Cylinder Liner (선박 엔진의 실린더 라이너의 손상 진단을 위한 신경회로망의 적용)

  • Cho, Yonsang;Koo, Hyunhoo;Park, Junhong;Park, Heungsik
    • Tribology and Lubricants
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    • v.30 no.6
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    • pp.356-363
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    • 2014
  • Marine diesel engines operate in environments in which damage easily occurs from corrosion. Recently, damage to cylinder liners has increased from corrosion wear caused by increased engine power. This damage can cause serious problems in the economy. Thus, many researchers have treated and studied damaged cylinder liners. However, a method is necessary for real-time monitoring of damage to cylinder liners during operation of the engine, before serious damage can occur. This study carries out reciprocating friction and wear tests on a cast iron specimen under various corrosion atmospheres and verifies the variations of friction coefficient and friction surface. Additionally, the friction coefficient and friction status are predicted by using a neural network that learns the vibration and frequency spectrum data from an acceleration sensor. According to our conclusions, amplitude is distributed highly at high frequencies, and values of standard deviation and kurtosis are high when damage to the friction surface is serious. The accuracy rate of the friction coefficient predicted by the neural network is over 80% of the real measured value without NaCl, and application of the neural network is very effective for diagnosing the friction condition and damage to the cylinder liner.

Study on the Damage Diagnosis of an Cantilever Beams using PZT Actuator and PVDF Sensor (PZT 액추에이터와 PVDF센서를 이용한 외팔보의 손상 진단에 관한 연구)

  • 권대규;임숙정;유기호;이성철
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.5
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    • pp.73-82
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    • 2004
  • This paper presents the study on damage diagnosis of an intelligent cantilevered beams using PZT actuator and PVDF sensor This study provides the theoretical and experimental verification to examine structural damage. Time domain analysis for the non-destructive detection of damage is presented by parameterized partial differential equations and Galerkin approximation techniques. The time histories of the vibration response of structure were used to identify the presence of damage. Furthermore, this systematic approach permits one to use the piezomaterials to both excite and sense the vibration of structures. We also carried out the experimental verification about reliability of theoretical methods fur detecting the damage of a composite beam with PZT actuator and PVDF sensor. Experimental results are presented from tests on cantilevered composite beams which is damaged at different location and different dimensions. The results were compared with the simulation results. Good agreement between the results was found for the time shifts and amplitude difference in transients response of the cantilevered beam.