• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.5
• /
• pp.864-871
• /
• 2002

Acoustic emission(AE) technique has been applied to not only mechanical property testing but also on-line monitoring of the entire structure or a limit zone only. Although several AE devices have already been developed for on-line monitoring, the price of these systems is very high and it is difficult for the field to apply yet. In this study, we developed a specially designed PC-based leak detection system using A/D board. In this paper, AE technique has been applied to detect leak for heat exchanger by analyzing the characteristics of signal obtained from leak. It was confirmed that the characteristics of the signal generated by the turbulence of gas in the heat exchanger is narrow band signal having between 130-250kHz. Generally, the amplitude of leak signal is increased as the leak size increasing, but showed no significant change at frequency characteristic. Leak source location can be found by determining for the paint of highest signal amplitude by comparing with several fixed sensors. In this paper, AE results are compared with the PC-based leak detection system using A/D board.

• Smart Structures and Systems
• /
• v.18 no.5
• /
• pp.1063-1085
• /
• 2016

Taking advantage of the high sensitivity and long-distance detection capability of acoustic emission (AE) technique, this paper focuses on the crack detection in rail head, which is one of the most vulnerable parts of rail track. The AE source location and noise cancellation were studied on the basis of practical rail profile, material and operational noise. In order to simulate the actual AE events of rail head cracks, field tests were carried out to acquire the AE waves induced by pencil lead break (PLB) and operational noise of the railway system. Wavelet transform (WT) was first utilized to investigate the time-frequency characteristics and dispersion phenomena of AE waves. Here, the optimal mother wavelet was selected by minimizing the Shannon entropy of wavelet coefficients. Regarding the obvious dispersion of AE waves propagating along the rail head and the high operational noise, the wavelet transform-based modal analysis location (WTMAL) method was then proposed to locate the AE sources (i.e. simulated cracks) respectively for the PLB-induced AE signals with and without operational noise. For those AE signals inundated with operational noise, the Hilbert transform (HT)-based noise cancellation method was employed to improve the signal-to-noise ratio (SNR). Finally, the experimental results demonstrated that the proposed crack detection strategy could locate PLB-simulated AE sources effectively in the rail head even at high operational noise level, highlighting its potential for field application.

• ETRI Journal
• /
• v.39 no.6
• /
• pp.832-840
• /
• 2017

Recently, deep recurrent neural networks have achieved great success in various machine learning tasks, and have also been applied for sound event detection. The detection of temporally overlapping sound events in realistic environments is much more challenging than in monophonic detection problems. In this paper, we present an approach to improve the accuracy of polyphonic sound event detection in multichannel audio based on gated recurrent neural networks in combination with auditory spectral features. In the proposed method, human hearing perception-based spatial and spectral-domain noise-reduced harmonic features are extracted from multichannel audio and used as high-resolution spectral inputs to train gated recurrent neural networks. This provides a fast and stable convergence rate compared to long short-term memory recurrent neural networks. Our evaluation reveals that the proposed method outperforms the conventional approaches.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.11
• /
• pp.156-163
• /
• 2015

In the using of FBG(Fiber Bragg Grating) developed in home land, we designed and manufactured united FBG acoustic transducers the first in Korea. they are being applied to multi-point signal detection of FBG Hydrophone used Hopper WDM(national patent NO 10-1502954) in the underwater. On united FBG transducers manufactured, we made an demonstrated on respective frequency response peculiarities in the underwater and analyzed the special characters. As the experimental result on frequency response peculiarities, we made it possible underwater acoustic detection on united FBG acoustic transducers type to maximum 30Hz~2.5KHz. it's the optimum conditions of 1.2KHz frequency in detection. And for the purpose of realization on multi-point signal detection on wide scope in the underwater, in the using of WDM(Wavelength Division Multiplexing) method and passive band-pass filter system, established arrays system and succeeded in multi-point underwater acoustic signal detection to the frequency 200Hz~1.3KHz out of the two united type FBG transducers. Additionally, it would be possible directivity detection for the object of its source as the intensity of detection signal varies with the sound source's direction and angle. From now on we prepared a new moment on the practical use study on FBG hydrophone in the future.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2005.05a
• /
• pp.342-345
• /
• 2005

To detect external acoustic signal, fiber optic sensor array using Fabry-Perot interferometer which had benefit of minimize and light-weight was used. The sensor head has 1cm in length, total length of fiber is 9.5cm, and the sensor supported at both ends, simply. External sound applied in lateral direction and detected two signals were compared each other. It was confirmed that the Fabry-Perot interferometric sensor array detected acoustic signal, effectively.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.2
• /
• pp.203-208
• /
• 2016

This paper presents a fault detection and data processing algorithm for acoustic sensor systems using the multiple sensor algorithm that has originally developed for the wireless sensor nodes. The multiple sensor algorithm can increase the reliability of the sensor systems by utilizing and comparing the measurements of the multiple sensors. In the acoustic sensor system, the equivalent sound level($L_{eq}$) is used to detect the faulty sensor. The experiment was conducted to demonstrate the feasibility of the multiple acoustic sensor algorithm, and the results show that the algorithm can detect the faulty sensor and validate the data.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.13 no.4
• /
• pp.68-74
• /
• 1999

Ths paper does acoustic detection of partial discharge using acoustic sensor in polymer. Time sequential rreasurement of acoustic emission characteristic obtained acoustic sensor deal with statistics process. and 5 characteristic quantities were introduced into this paper. Resulting fann analysis of $\psi$-AEA-n pattern (phase-acoustic emission amplitude-pulse number) and AE quantities ,it can know useful statistics quantities that AE average inception amplitude TEX>$(\overline{AEA_{inc}})$ and AE average maximum amplitude TEX>$(\overline{AEA_{max}})$ make diagnosis of the middle stage of deterioration, AE pulse number and AE average maximum phase $(\overline{\theta{max}})$ make diagnosis of the last stage of deterioration. it obtained that these AE quantities are useful for dias,mosis deterioration form experiment results.esults.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.4
• /
• pp.136-141
• /
• 2011

In this paper, we propose an approach to improve the data detection performance of the acoustic data transmission system based on the modulated complex lapped transform (MCLT). We first present an effective analysis of the features and the detection method of data in the acoustic data transmission system. And then feature vectors which are applied to the Gaussian mixture model (GMM) are selected from relevant parameters of the previous system for the efficient data detection. For the purpose of evaluating the performance of the proposed algorithm, Bit error rate (BER) of the received data was measured at different environments (music genres (rock, pop, classic, jazz) and different distances (1m∼5m) from the loudspeaker to the microphone in a office room) and yields better results compared with the conventional scheme of the acoustic data transmission system based on the MCLT.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.5
• /
• pp.468-475
• /
• 2020

A good acoustic word embedding that can well express the characteristics of word plays an important role in wake-up word detection (WWD). However, the representation ability of acoustic word embedding may be weakened due to various types of environmental noise occurred in the place where WWD works, causing performance degradation. In this paper, we proposed triplet loss based Domain Adversarial Training (tDAT) mitigating environmental factors that can affect acoustic word embedding. Through experiments in noisy environments, we verified that the proposed method effectively improves the conventional DAT approach, and checked its scalability by combining with other method proposed for robust WWD.

• Journal of Animal Science and Technology
• /
• v.64 no.5
• /
• pp.813-829
• /
• 2022

Internal and external defects of eggs should be detected to prevent cross-contamination of intact eggs by abnormal eggs during storage. Emerging detection technologies for abnormal eggs were introduced as an alternative to human inspection. The advanced technologies could rapidly detect abnormal eggs. Abnormal egg detection technologies using acoustic response, machine vision, and spectroscopy have been commercialized in the poultry industry. Non-destructive egg quality assessment methods meanwhile could preserve the value of eggs and improve detection efficiency. In order to improve detection efficiency, it is essential to select a proper algorithm for classifying the types of abnormal eggs. This review deals with the performance of the detection technologies for various types of abnormal eggs in recently published resources. In addition, the discriminant methods and detection algorithms of abnormal eggs reported in the published literature were investigated. Although the majority of the studies were conducted on a laboratory scale, the developed detection technologies for internal and external defects in eggs were technically feasible to obtain the excellent detection accuracy. To apply the developed detection technologies to the poultry industry, it is necessary to achieve the detection rates required from the industry.