• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.297-302
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• 2007

Vibrating test of vehicle component can be possible in lab-based simulators instead of field testing owing to the development of technology in control algorithm as well as computational process. Currently, Multi-Axial Simulation Table(MAST) is recommended as a vibrating equipment, which excites a target component for 3-directional translation and rotation motion simultaneously and hence, vibrational condition can be fully approximated to that of real road test. But, the vibration-free performance of target component is not guaranteed with MAST system, which is only simulator subjective to the operator. Rather, the reliability of multi-axial vibration test is dependent on the quality of input profile which should cover the required severity of vibrating condition on target component. In this paper, multi-axial vibration testing methodology of vehicle component is presented here, from data acquisition of vehicle accelerations to the obtaining the input profile of MAST using severe data at proving ground. To compare the severity of vibration condition, between real road test and proving ground one, energy principle of equivalent damage is proposed to calculate energy matrices of acceleration data and then, it is determined the optimal combination of special events on proving ground which is equivalent to real road test at the aspects of vibration fatigue using sequential searching optimal algorithm. To explain the vibration methodology clearly, seat and door component of vehicle are selected as a example.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.454-456
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• 1987

A more specialized area of transient evaluations is transmission line fault-detecting and protection system. During the first cycle or two following a power system fault, a high-speed protective relay is expected to make a decision as to the severity or location of the fault, usually based on 60 Hz information, i.e. the phase and magnitude of 60 Hz voltage or current signals. It is precisely at this time however that the signal is badly corrupted by noise, in the form of a de offset or frequencies above 50 Hz. One of several possible sources of transients in protection measuring signals is in the primary system for which protection is required in its response to the impact of short circuit fault on-set. Other sources are in the primary voltage and current transducers from which protection signals are derived, and, often of particular importance, in the interface circuits between the transducer secondaries and the comparator and measuring elements of the protection system. However, the noise signals that will be described in this paper are due to the main power system only and do not include errors due to current or voltage transducers.

• Structural Engineering and Mechanics
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• v.30 no.4
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• pp.445-466
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• 2008

This paper presents a novel structural damage detection method with a new damage index based on the statistical moments of dynamic responses of a structure under a random excitation. After a brief introduction to statistical moment theory, the principle of the new method is put forward in terms of a single-degree-of-freedom (SDOF) system. The sensitivity of statistical moment to structural damage is discussed for various types of structural responses and different orders of statistical moment. The formulae for statistical moment-based damage detection are derived. The effect of measurement noise on damage detection is ascertained. The new damage index and the proposed statistical moment-based damage detection method are then extended to multi-degree-of-freedom (MDOF) systems with resort to the leastsquares method. As numerical studies, the proposed method is applied to both single and multi-story shear buildings. Numerical results show that the fourth-order statistical moment of story drifts is a more sensitive indicator to structural stiffness reduction than the natural frequencies, the second order moment of story drift, and the fourth-order moments of velocity and acceleration responses of the shear building. The fourth-order statistical moment of story drifts can be used to accurately identify both location and severity of structural stiffness reduction of the shear building. Furthermore, a significant advantage of the proposed damage detection method lies in that it is insensitive to measurement noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.338-345
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• 2013

Induction motors play an increasing importance in industrial manufacturing. Therefore, the state monitoring systems also have been considering as the key in dealing with their negative effect by absorbing faulty symptoms in motors. There are numerous proposed systems in literature, in which, several kinds of signals are utilized as the input. To solve the multiple faults problem of induction motors, like the proposed system, the vibration signals is good candidate. In this study, a new signal processing scheme was utilized, which transforms the time domain vibration signal into the spatial domain as an image. Then the spatial features of converted image then have been extracted by applying the dominant neighbourhood structure (DNS) algorithm. In addition, these feature vectors were evaluated to obtain the fruitful dimensions, which support to discriminate between states of motors. Because of reliability, the conventional one-against-all (OAA) multi-class support vector machines (MCSVM) have been utilized in the proposed system as classifier module. Even though examined in severity levels of signal-to-noise ratio (SNR), up to 15dB, the proposed system still reliable in term of two criteria: true positive (TF) and false positive (FP). Furthermore, it also offers better performance than five state-of-the-art systems.

• Journal of Audiology & Otology
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• v.23 no.1
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• pp.1-7
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• 2019

Self-reported difficulties in speech-in-noise (SiN) recognition are common among tinnitus patients. Whereas hearing impairment that usually co-occurs with tinnitus can explain such difficulties, recent studies suggest that tinnitus patients with normal hearing sensitivity still show decreased SiN understanding, indicating that SiN difficulties cannot be solely attributed to changes in hearing sensitivity. In fact, cognitive control, which refers to a variety of top-down processes that human beings use to complete their daily tasks, has been shown to be critical for SiN recognition, as well as the key to understand cognitive inefficiencies caused by tinnitus. In this article, we review studies investigating the association between tinnitus and cognitive control using behavioral and brain imaging assessments, as well as those examining the effect of tinnitus on SiN recognition. In addition, three factors that can affect cognitive control in tinnitus patients, including hearing sensitivity, age, and severity of tinnitus, are discussed to elucidate the association among tinnitus, cognitive control, and SiN recognition. Although a possible central or cognitive involvement has always been postulated in the observed SiN impairments in tinnitus patients, there is as yet no direct evidence to underpin this assumption, as few studies have addressed both SiN performance and cognitive control in one tinnitus cohort. Future studies should aim at incorporating SiN tests with various subjective and objective methods that evaluate cognitive performance to better understand the relationship between SiN difficulties and cognitive control in tinnitus patients.

• Smart Structures and Systems
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• v.2 no.2
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• pp.127-140
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• 2006

In this study, a wavelet-based covariance-driven system identification technique is proposed for damage assessment of structures under ambient excitation. Assuming the ambient excitation to be a white-noise process, the covariance computation is shown to be able to separate the effect of random excitation from the response measurement. Wavelet transform (WT) is then used to convert the covariance response in the time domain to the WT magnitude plot in the time-scale plane. The wavelet coefficients along the curves where energy concentrated are extracted and used to estimate the modal properties of the structure. These modal property estimations lead to the calculation of the stiffness matrix when either the spectral density of the random loading or the mass matrix is given. The predicted stiffness matrix hence provides a direct assessment on the possible location and severity of damage which results in stiffness alteration. To demonstrate the proposed wavelet-based damage assessment technique, a numerical example on a 3 degree-of-freedom (DOF) system and an experimental study on a three-story building model, which are all under a broad-band excitation, are presented. Both numerical and experimental results illustrate that the proposed technique can provide an accurate assessment on the damage location. It is however noted that the assessment of damage severity is not as accurate, which might be due to the errors associated with the mode shape estimations as well as the assumption of proportional damping adopted in the formulation.

• Smart Structures and Systems
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• v.15 no.1
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• pp.227-244
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• 2015

This study develops a two stage procedure to identify the structural damage based on the optimized artificial neural networks. Initially, the modal strain energy index (MSEI) is established to extract the damaged elements and to reduce the computational time. Then the genetic algorithm (GA) and artificial neural networks (ANNs) are combined to detect the damage severity. The input of the network is modal strain energy index and the output is the flexural stiffness of the beam elements. The principal component analysis (PCA) is utilized to reduce the input variants of the neural network. By using the genetic algorithm to optimize the parameters, the ANNs can significantly improve the accuracy and convergence of the damage identification. The influence of noise on damage identification results is also studied. The simulation and experiment on beam structures shows that the adaptive parameter selection neural network can identify the damage location and severity of beam structures with high accuracy.

• Smart Structures and Systems
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• v.30 no.4
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• pp.397-410
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• 2022

It is essential to monitor the working conditions of bolt-connected joints, which are widely used in various kinds of steel structures. The looseness of bolts may directly affect the stability and safety of the entire structure. In this study, a guided wave-based method for bolt looseness detection and localization is presented for a joint structure with multiple bolts. SH waves generated and received by a small number (two pairs) of magnetostrictive transducers were used. The bolt looseness index was proposed based on the changes in the reconstructed responses excited by the time reversal signals of the measured unit impulse responses. The damage locations and local damage severities were estimated using the damage indices from several wave propagation paths. The back propagation neural network (BPNN) technique was employed to identify the local damages. Numerical and experimental studies were conducted on a lap joint with eight bolts. The results show that the total damage severity can be successfully detected under the effect of external force and measurement noise. The local damage severity can be estimated reasonably for the experimental data using the BPNN constructed by the training patterns generated from the finite element simulations.

• Journal of the Korean Society for Railway
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• v.10 no.6
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• pp.678-684
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• 2007

This research has defined the factors of noise in cars during subway train services, which is surfacing as a new environmental trouble. It shows additional accomplishment of a discerning analysis on the standard of noise regulation as well as its seriousness. According to the Enforcement Regulations for Noise and Vibration under the Ministry of Environment and its standard noise regulation figure 70dB, we divided two groups of which train noise figures are over and under 70dB respectively, and used their 359 results about noise, geometric structures and operation elements, for this analysis. The results and suggestions are following. First of all, when we discern the seriousness of noise in a train, the track type has mattered in geometric structure and the velocity in operation elements. Therefore, when we construct subway from now on, we should take the track type in consideration and establish plans to keep proper speed in respect of operation. Secondly, the established discernment model in this research can be used in making alternative plans or improvement of subway trains hereafter, showing relatively high accuracy of estimation. Consequently, the readjustment of geometric structure and operation elements is needed, not to make it over the regulation standard of noise in case the noise in train is serious. The discriminant model of this research can be used as elementary material for comfortable and safe subway trains, making the estimation of noise seriousness possible.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.789-796
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• 2012

Radiated noise analysis from a ship structure is a challenging topic owing to difficulties in the accurate calculation of the fluid-structure interaction as well as owing to a massive degree of freedom of the problem. To reduce the severity of the problem, a new fluid-structure interaction formulation is proposed in this paper. The complex frequency-dependent added mass and damping matrices are calculated using the high-order Burton-Miller boundary integral equation formulation to obtain accurate values over all frequency bands. The calculated fluid-structure interaction effects are added to the structural matrices calculated by commercial finite element software, MSC/NASTRAN. Then, the impedance and underwater radiation noise due to an excitation of structure are calculated. The present formulation is applied to a ship to calculate the underwater radiated noise.