• Title/Summary/Keyword: 포락처리

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Application of Envelop Analysis and Wavelet Transform for Detection of Gear Failure (기어 결함 검출을 위한 포락처리와 웨이블릿 변환의 적용)

  • Gu, Dong-Sik;Lee, Jeong-Hwan;Yang, Bo-Suk;Choi, Byeong-Keun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.32 no.11
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    • pp.905-910
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    • 2008
  • Vibration analysis is widely used in machinery diagnosis and the wavelet transform has also been implemented in many applications in the condition monitoring of machinery. In contrast to previous applications, this paper examines whether acoustic signal can be used effectively along vibration signal to detect the various local fault, in local fault of gearboxes using the wavelet transform. Moreover, envelop analysis is well known as useful tool for the detection of rolling element bearing fault. In this paper, a acoustic emission (AE) sensor is employed to detect gearbox damage by installing them around bearing housing at driven-end side. Signal processing is conducted by wavelet transform and enveloping to detect her fault all at once gearbox using AE signal.

Low Speed Rolling Bearing Fault Detection Using AE Signal Analyzed By Envelop Analysis Added DWT (웨이블릿변환이 접목된 포락처리를 이용한 저속 회전하는 구름요소베어링 결함 진단)

  • Kim, Byeong-Su;Kim, Won-Cheol;Gu, Dong-Sik;Kim, Jae-Gu;Choi, Byeong-Keun
    • Journal of Advanced Marine Engineering and Technology
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    • v.33 no.5
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    • pp.672-678
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    • 2009
  • Acoustic Emission (AE) technique is a non-destructive testing method and widely used for the early detection of faults in rotating machines in these days, because the sensitivity of AE transducers is higher than normal accelerometers. So it can detect low energy vibration signals. The faults in the rotating machines are generally occurred at bearings and gearboxes which are the principal parts of the machines. It was studied to detect the bearing faults by envelop analysis in several decade years. And the researches showed that AE had a possibility of the application in condition monitoring system(CMS) using the envelope analysis for the rolling bearing. And peak ratio (PR) was developed for expression of the bearing condition in condition monitoring system using AE. Noise level is needed to reduce to take exact PR value because the PR is calculated from total root mean square (RMS) and the harmonics peak levels of the defect frequencies of the bearing. Therefore, in this paper, the discrete wavelet transform (DWT) was added in the envelope analysis to reduce the noise level in the AE signals. And then, the PR was calculated and compared with general envelope analysis result and the result of envelope analysis added the DWT. In the experiment result about inner fault of bearing, defect frequency was difficult to find about only envelop analysis. But it's easy to find defect frequency after wavelet transform. Therefore, Envelop analysis added wavelet transform was useful method for early detection of default in signal process.

Comparison of Hilbert and Hilbert-Huang Transform for The Early Fault Detection by using Acoustic Emission Signal (AE 신호를 이용한 조기 결함 검출을 위한 Hilbert 변환과 Hilbert-Huang 변환의 비교)

  • Gu, Dong-Sik;Lee, Jong-Myeong;Lee, Jung-Hoon;Ha, Jung-Min;Choi, Byeong-Keun
    • Journal of Advanced Marine Engineering and Technology
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    • v.36 no.2
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    • pp.258-266
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    • 2012
  • Recently, Acoustic Emission (AE) technique is widely applied to develop the early fault detection system, and the problem about a signal processing method for AE signal is mainly focused on. In the signal processing method, envelope analysis is a useful method to evaluate the rolling element bearing problems and Wavelet transform is a powerful method to detect faults occurred on gearboxes. However, exact method for AE signal is not developed yet. Therefore, in this paper, two methods, which is Hilbert transforms (HT) and Hilbert-Huang transforms (HHT), will be compared for development a signal processing method for early fault detection system by using AE. AE signals were measured through a fatigue test. HHT has better advantages than HT because HHT can show the time-frequency domain result. But, HHT needs long time to process a signal, which has a lot of data, and has a disadvantage in de-noising filter.

Vibration Characteristic Analysis using Acoustic Emission Signal (AE신호를 이용한 기어 정렬불량의 진동 특성 분석)

  • Gu, Dong-Sik;Kim, Byeong-Su;Lee, Jeong-Hwan;Yang, Bo-Suk;Choi, Byeong-Keun
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2008.11a
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    • pp.43-48
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    • 2008
  • Gear system has been widely used in industrial applications and unexpected failures of gears are not only extremely damaging but also lead to economic losses. So, early detection of fault is important for diagnosis machine condition. And acoustic emission is an efficient non destructive testing technique for the diagnosis of machine health and is useful technique for early detection of fault because it can find low-amplitude and high-frequency signal on account of high sensibility. Therefore, in this paper, the AE signal was measured and preprocessed using envelop analysis for gearbox with misalignment between pinion and gear. And then the vibration characteristic of gear misalignment was analyzed.

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Proposition and Application of Novel DWT Mother Function for AE signature (AE 신호를 위한 새로운 DWT 기저함수 제안 및 적용)

  • Gu, Dong-Sik;Kim, Jae-Gu;Choi, Byeong-Keun
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2011.04a
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    • pp.582-587
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    • 2011
  • Acoustic Emission(AE) is widely used for early detection of faults for rotating machinery in these days because of its high sensitivity. AE signal has to need for transferring to low frequency range for the spectrum analysis included the fault mechanism. In transferring process, we lose a lot of fault information caused by unusable signal processing method. Discrete Wavelet Transform(DWT) is a method of signal processing for AE signatures, but the pattern of its mother function is not optimized with AE signals. So, we can lose the fault information when we want to use the DWT for AE signal. Therefore, in this paper, we will propose a novel pattern for DWT mother function, which is optimized with AE signals. And it will be applied to compare the results of DWT by daubechie and novel pattern.

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Vibration Characteristic Analysis Using Acoustic Emission Signal (AE신호를 이용한 기어 정렬불량의 진동 특성 분석)

  • Gu, Dong-Sik;Lee, Jeong-Hwan;Kim, Byeong-Su;Yang, Bo-Suk;Choi, Byeong-Keun
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.12
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    • pp.1243-1249
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    • 2008
  • Gear system has been widely used in industrial applications and unexpected failures of gears are not only extremely damaging but also leading to economic losses. So, early detection of fault is important for diagnosis machine condition. And acoustic emission is an efficient non-destructive testing technique fur the diagnosis of machine health and is useful technique far early detection of fault because it can find low-amplitude and high-frequency signal on account of high sensibility. Therefore, in this paper, the AE signal was measured and preprocessed using envelope analysis for gearbox with misalignment between pinion and gear. And then the gear misalignment's vibration characteristic were analyzed.

A Study on the Efficiency and Its Determinants in Korea's Service Sectors Using DEA (자료포락분석(DEA)를 이용한 우리나라 서비스산업의 효율성과 결정요인 분석)

  • Bae, Se-Young
    • Journal of Digital Convergence
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    • v.19 no.10
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    • pp.339-348
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    • 2021
  • This paper aims to analyze the production efficiency in Korea's ten service sectors using DEA and its determinants utilizing a truncated-Tobit regression model and a censored-Tobit regression model in 2010-2019. This paper found: First, the Korean service sector's production efficiency in general has been significantly low and polarized. Especially, the inefficiency resulted from the scale inefficiency in the 'sewerage waste management industry.' Second, in the determinants analysis, the results show the positive effect of the investment and R&D expenses on technical efficiency, while FDI and lobbying expenses illustrate the negative impact. Moreover, it seems that the larger the industry, the higher the efficiency. Thus, the future Korean government's economic policy for the service sectors requires a mixed and integrated policy of the macroeconomic aspect such as active investment and R&D activities with microeconomic aspect including a convergence of FDI and human capital.

On the Study of the Period Measurement of Ultrasonic Signal in Damaged Vehicle Tire (자동차 타이어 손상에 의한 초음파 신호 주기 측정에 관한 연구)

  • Park, Jung-Im;Lim, Seung-Gak;Kang, Dae-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.5
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    • pp.47-52
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    • 2011
  • We studied about the damaged tire decision algorithm that measured dominant period of ultrasonic signal due to a foreign material on the friction between tire and road surface. We computed the power spectrum about the envelope of ultrasonic signal acquired from the damaged tire, then proposed the dominant period decision algorithm by statistical power threshold value. As the result of simulation, when driving by the speed of 80km/h, the 100ms of dominant period that measured in the proposed algorithm is more accurate than the 97.6ms of power spectrum peak period referenced on the average period of ultrasonic signal envelope peak, 101.24ms.

The Recognition of Korean Single vowels by Use of the Diffusion Filter Bank as a Pre-processor (확산필터뱅크를 전처리기로 사용한 한국어 단모음인식)

  • Huh, Man-Tak;Kim, Jae-Chang
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.1
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    • pp.81-87
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    • 1997
  • In this paper, a new pre-processing method for the recognition of single vowels by use of spectrum envelope is presented. We use new extraction method of a spectrum envelope using the diffusion filter bank. By dividing analysis band of a diffusion filter bank into subbands, we decreased the number of diffusion process. And, by increasing the number of difference, we got higher selectivity. As a result of them, we reduced the total processing time, and got higher enhancement of discrimination. By getting 88.3% of average recognition rate for single vowels of natural voice through computer simulation. We confirmed it to be useful for speech recognition which use spectrum analysis of the voice signal to have many frequency components.

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