• Title/Summary/Keyword: Mechanical fault

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Fault Detection and Damage Pattern Analysis of a Gearbox Using the Power Spectra Density and Artificial Neural Network (파워스펙트럼 및 신경망회로를 이용한 기어박스의 결함진단 및 결함형태 분류에 관한 연구)

  • Lee, Sang-Kwon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.4
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    • pp.537-543
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    • 2003
  • Transient vibration generated by developing localized fault in gear can be used as indicators in gear fault detection. This vibration signal suffers from the background noise such as gear meshing frequency and its harmonics and broadband noise. Thus in order to extract the information about the only gear fault from the raw vibration signal measured on the gearbox this signal is processed to reduce the background noise with many kinds of signal-processing tools. However, these signal-processing tools are often very complex and time waste. Thus. in this paper. we propose a novel approach detecting the damage of gearbox and analyzing its pattern using the raw vibration signal. In order to do this, the residual signal. which consists of the sideband components of the gear meshing frequent) and its harmonics frequencies, is extracted from the raw signal by the power spectral density (PSD) to obtain the information about the fault and is used as the input data of the artificial neural network (ANN) for analysis of the pattern of gear fault. This novel approach has been very successfully applied to the damage analysis of a laboratory gearbox.

A Study on Fault Diagnosis Algorithm for Rotary Machine using Data Mining Method and Empirical Mode Decomposition (데이터 마이닝 기법 및 경험적 모드 분해법을 이용한 회전체 이상 진단 알고리즘 개발에 관한 연구)

  • Yun, Sang-hwan;Park, Byeong-hui;Lee, Changwoo
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.15 no.4
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    • pp.23-29
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    • 2016
  • Rotary machine is major equipment in industry. The rotary machine is applied for a machine tool, ship, vehicle, power plant, and so on. But a spindle fault increase product's expense and decrease quality of a workpiece in machine tool. A turbine in power plant is directly connected to human safety. National crisis could be happened by stopping of rotary machine in nuclear plant. Therefore, it is very important to know rotary machine condition in industry field. This study mentioned fault diagnosis algorithm with statistical parameter and empirical mode decomposition. Vibration locations can be found by analyze kurtosis of data from triaxial axis. Support vector of data determine threshold using hyperplane with fault location. Empirical mode decomposition is used to find fault caused by intrinsic mode. This paper suggested algorithm to find direction and causes from generated fault.

Bayesian-based seismic margin assessment approach: Application to research reactor

  • Kwag, Shinyoung;Oh, Jinho;Lee, Jong-Min;Ryu, Jeong-Soo
    • Earthquakes and Structures
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    • v.12 no.6
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    • pp.653-663
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    • 2017
  • A seismic margin assessment evaluates how much margin exists for the system under beyond design basis earthquake events. Specifically, the seismic margin for the entire system is evaluated by utilizing a systems analysis based on the sub-system and component seismic fragility data. Each seismic fragility curve is obtained by using empirical, experimental, and/or numerical simulation data. The systems analysis is generally performed by employing a fault tree analysis. However, the current practice has clear limitations in that it cannot deal with the uncertainties of basic components and accommodate the newly observed data. Therefore, in this paper, we present a Bayesian-based seismic margin assessment that is conducted using seismic fragility data and fault tree analysis including Bayesian inference. This proposed approach is first applied to the pooltype nuclear research reactor system for the quantitative evaluation of the seismic margin. The results show that the applied approach can allow updating by considering the newly available data/information at any level of the fault tree, and can identify critical scenarios modified due to new information. Also, given the seismic hazard information, this approach is further extended to the real-time risk evaluation. Thus, the proposed approach can finally be expected to solve the fundamental restrictions of the current method.

Analysis of Fault Diagnosis of Regenerative Braking System for Fuel Cell Vehicle with EMB System (전기기계 브레이크가 적용된 연료전지 자동차의 회생제동 시스템의 고장해석)

  • Song, H.Y.;Choi, J.H.;Hwang, S.H.;Jeon, K.K.;Choi, S.J.
    • Journal of Drive and Control
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    • v.9 no.4
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    • pp.8-13
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    • 2012
  • Recently, researches about the eco-friendly vehicles such as hybrid electric vehicle, fuel cell vehicle and electric vehicle have been actively carried out. The regenerative braking system is a key technology to improve the vehicle energy utilization efficiency because it transforms the kinetic energy to the electric energy through the electric motor. This new braking system requires cooperative control between electric controlled brake and regenerative brake. Therefore, it is necessary to establish fault-diagnosis and fail-safe evaluation criteria to secure reliability of the regenerative braking system. In this paper, the failure types and causes in regenerative braking system were analyzed. The transient behavior characteristics were examined based on fault-diagnosis and fail-safe upon failure of regenerative braking system.

Fault Detection by Using an Adaptive Observer

  • Inoue, A.;Deng, M.;Yoshinaga, S.
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.710-713
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    • 2005
  • In this paper, a design method to detect faults in plants with uncertainties is proposed. When a plant has faults, the plant will be corrupted by an unknown fault signal. In addition, the plant also includes uncertainties, such as disturbances and plant parameter deviations. In this case, the proposed method estimates the fault signal by using an adaptive observer. Numerical examples are given to demonstrate the validity of the proposed method.

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Development of intelligent fault diagnostic system for mechanical element of wind power generator (지능형 풍력발전 기계적 요소 고장진단 시스템 개발)

  • Moon, Dea-Sun;Kim, Sung-Ho
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.1
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    • pp.78-83
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    • 2014
  • Recently, a rapid growth of wind power system as a leading renewable energy source has compelled a number of companies to develop intelligent monitoring and diagnostic system. Such systems can detect early mechanical faults, which prevents from costly repairs. Generally, fault diagnostic system for wind turbines is based on vibration and process signal analysis. In this work, different type of mechanical faults such as mass unbalance and shaft misalignment which can always happen in wind turbine system is considered. The proposed intelligent fault diagnostic algorithm utilizes artificial neural network and Wavelet transform. In order to verify the feasibility of the proposed algorithm, mechanical fault generation experimental system manufactured by Gaon corporation is utilized.

Experimental research on the effect of water-rock interaction in filling media of fault structure

  • Faxu, Dong;Zhang, Peng;Sun, Wenbin;Zhou, Shaoliang;Kong, Lingjun
    • Geomechanics and Engineering
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    • v.24 no.5
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    • pp.471-478
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    • 2021
  • Water damage is one of the five disasters that affect the safety of coal mine production. The erosion of rocks by water is a very important link in the process of water inrush induced by fault activation. Through the observation and experiment of fault filling samples, according to the existing rock classification standards, fault sediments are divided into breccia, dynamic metamorphic schist and mudstone. Similar materials are developed with the characteristics of particle size distribution, cementation strength and water rationality, and then relevant tests and analyses are carried out. The experimental results show that the water-rock interaction mainly reduces the compressive strength, mechanical strength, cohesion and friction Angle of similar materials, and cracks or deformations are easy to occur under uniaxial load, which may be an important process of water inrush induced by fault activation. Mechanical experiment of similar material specimen can not only save time and cost of large scale experiment, but also master the direction and method of the experiment. The research provides a new idea for the failure process of rock structure in fault activation water inrush.

Analysis on Physical and Mechanical Properties of Fault Materials using Laboratory Tests (실내시험을 통한 단층물질의 물리·역학적 특성 분석)

  • Moon, Seong-Woo;Yun, Hyun-Seok;Seo, Yong-Seok;Chae, Byung-Gon
    • The Journal of Engineering Geology
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    • v.27 no.1
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    • pp.91-101
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    • 2017
  • Fault materials has various properties depending on their areas, rock types, and components because they are formed by heterogeneous and complicated mechanisms. In this study, to understand the physical and mechanical properties of fault materials, 109 fault materials distributed in South Korea were collected to conduct various laboratory tests with them and analyze their physical and mechanical properties (unit weight, specific gravity, porosity, gravel content, silt/clay content, clay mineral content, friction angle, and cohesion) according to areas, rock types, and components. As for the physical and mechanical properties by rock type, gneiss shows the highest medians in the unit weight ($17.1kN/m^3$) and specific gravity (2.73), granite does so in the porosity (45.5%), schist does so in the gravel content (20.0 wt.%) and cohesion (38.1 kPa), and phyllite does so in the silt/clay content (54.4 wt.%), clay mineral content (30.1 wt.%), and friction angle ($38.2^{\circ}$). With regard to the physical and mechanical properties by component, fault gouge was shown to have lower values than cataclasite and damage zones in all factors other than porosity and silt/clay contents.

Condition Monitoring of an LCD Glass Transfer Robot Based on Wavelet Packet Transform and Artificial Neural Network for Abnormal Sound (LCD 라인의 음향 특성신호에 웨이브렛 변환과 인경신경망회로를 적용한 공정로봇의 건정성 감시 연구)

  • Kim, Eui-Youl;Lee, Sang-Kwon;Jang, Ji-Uk
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.7
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    • pp.813-822
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    • 2012
  • Abnormal operating sounds radiated from a moving transfer robot in LCD (liquid crystal display) product lines have been used for the fault detection line of a robot instead of other source signals such as vibrations, acoustic emissions, and electrical signals. Its advantage as a source signal makes it possible to monitor the status of multiple faults by using only a microphone, despite a relatively low sensitivity. The wavelet packet transform for feature extraction and the artificial neural network for fault classification are employed. It can be observed that the abnormal operating sound is sufficiently useful as a source signal for the fault diagnosis of mechanical components as well as other source signals.

Model-based Sensor Fault Detection Algorithm for EMB System (EMB 시스템의 모델 기반 센서 고장 검출 알고리즘 개발)

  • Hwang, Woo-Hyun;Yang, I-Jin;Huh, Kun-Soo
    • Transactions of the Korean Society of Automotive Engineers
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    • v.20 no.1
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    • pp.1-7
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    • 2012
  • The brake-by-wire technology is a new automotive chassis system that allows standard braking operations by electronic components with lighter weights and faster response. The brake-by-wire units such as EMB (Electro-Mechanical Brake) are controlled by electronic sensors and actuators and, thus, the fault diagnosis is essential for implementation. In this study, a model-based fault diagnosis system is developed for the sensors based on the analytical redundancy method. The fault detection algorithm is verified in simulations for various faulty cases. A test bench is built including the EMB unit and the performance of the proposed fault diagnosis system is evaluated through the experiment.