• Journal of the Korean Society for Precision Engineering
• /
• v.9 no.3
• /
• pp.117-121
• /
• 1992

There have been many studies on chatter vibration in machining but there seems to be no regulations to decide the commencing point of chatter objectively. The development of an objective method which can estimate and detect chatter commencement is very much in need for automatic manufacturing systems, dynamic performance tests for machine tools, and so on. In this study, an approach for in-process monitoring and for deciding commencing point of the chatter vibration using the frequency band-energy method was proposed. From this method, in-process monitoring system for detection the chatter vibration was developed, and investigated its practical possibility. As a result, it is shown by experiments that the chatter vibtation can be detected accurately. Since the changing pattern of the signal energy in certain frequency band during chattering is seldom affected by the variation of cutting conditions, if adequate pre-measures are taken, this method can be widely used in most machining processes.

• Journal of the Korean Society for Precision Engineering
• /
• v.8 no.3
• /
• pp.73-81
• /
• 1991

There have been many studies on chatter vibration in machining but there seems to be no regulations to decide the commencing point of chatter objectively. The development of an objective method which can estimate and detect chatter commencement is very much in need for automatic manufacturing systems, dynamic performance tests for machine tools, so on. In this study, therefore, the estimation and the in-process detection of chatter have been experi- mentally investigated for the turning process. As a result, the commencing point of chatter can be decided from the behavior of the maximum amplitude of the dynamic component of cutting force, where the maximum amplitude is suddenly increasing with the chatter commencement. Then the commencing point of chatter can be estimated practically by this method before the occurrence of excessive vibration. Also, it is possible to detect the occurence of chatter vibration through the in-process measurement, by monitoring the maximum amplitude of the dynamic component of cutting force.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.18 no.12
• /
• pp.1243-1249
• /
• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.05a
• /
• pp.985-990
• /
• 2004

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. This sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300m.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.19 no.9
• /
• pp.935-942
• /
• 2009

In this paper, the purpose is to investigate the natural frequency of a cracked Timoshenko cantilever beams by FEM(finite element method) and experiment. In addition, a method for detection of crack in a cantilever beams is presented based on natural frequency measurements. The governing differential equations of a Timoshenko beam are derived via Hamilton's principle. The two coupled governing differential equations are reduced to one fourth order ordinary differential equation in terms of the flexural displacement. The crack is assumed to be in the first mode of fracture and to be always opened during the vibrations. The detection method of a crack location in a beam based on the frequency measurements is extended here to Timoshenko beams, taking the effects of both the shear deformation and the rotational inertia into account. The differences between the actual and predicted crack positions and sizes are less than 6 % and 23 % respectively.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.16 no.1 s.106
• /
• pp.27-33
• /
• 2006

Fault diagnosis and condition monitoring for rotating machines are important for efficiency and accident prevention. The process of fault diagnosis is to extract the feature of signals and to classify each state. Conventionally, fault diagnosis has been developed by combining signal processing techniques for spectral analysis and pattern recognition, however these methods are not able to diagnose correctly for certain rotating machines and some faulty phenomena. In this paper, we add a minimum detection error algorithm to the previous method to reduce detection error rate. Vibration signals of the induction motor are measured and divided into subband signals. Each subband signal is processed to obtain the RMS, standard deviation and the statistic data for constructing the feature extraction vectors. We make a study of the fault diagnosis system that the feature extraction vectors are applied to K-means clustering algorithm and minimum detection error algorithm.

• Steel and Composite Structures
• /
• v.42 no.5
• /
• pp.685-697
• /
• 2022

In this paper, a vibration-based method using the change ratios of modal data and the experience-based learning algorithm is presented for quantifying the position, size, and interface layer of delamination in laminated composites. Three types of objective functions are examined and compared, including the ones using frequency changes only, mode shape changes only, and their combination. A fine three-dimensional FE model with constraint equations is utilized to extract modal data. A series of numerical experiments is carried out on an eight-layer quasi-isotropic symmetric (0/-45/45/90)s composited beam for investigating the influence of the objective function, the number of modal data, the noise level, and the optimization algorithms. Numerical results confirm that the frequency-and-mode-shape-changes-based technique yields excellent results in all the three delamination variables of the composites and the addition of mode shape information greatly improves the accuracy of interface layer prediction. Moreover, the EBL outperforms the other three state-of-the-art optimization algorithms for vibration-based delamination detection of composites. A laboratory test on six CFRP beams validates the frequency-and-mode-shape-changes-based technique and confirms again its superiority for delamination detection of composites.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.19 no.3 s.73
• /
• pp.313-322
• /
• 2006

In the genetic algoricm (GA) based damage detection methods using vibration of structures, the selection of modal properties is important to improve the accuracy of damage detection. The objective of this study is to improve the accuracy of damage detection using natural frequency and modal strain energy, The following approaches are used to achieve the goal. First, modal strain energy is formulated and a new GA-based damage detection technique using natural frequency and modal strain energy is proposed. Next, to verify the efficiency of proposed technique, damage scenarios for free-free beam are designed and vibration modal tests of the target structure are conducted. Finally, the feasibility of the proposed technique is verified in comparison with other GA-based damage detection technique using natural frequency and mode shape.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.35 no.5
• /
• pp.307-313
• /
• 2015

Leak detection in a pipeline usually involves acoustic emission sensors such as contact type sensors. These contact type sensors pose difficulties for installation and cannot operate in areas having high temperature and radiation. Therefore, recently, many researchers have studied the leak detection phenomenon by using a camera. Leak detection by using a camera has the advantages of long distance monitoring and wide area surveillance. However, the conventional leak detection method by using difference images often mistakes the vibration of a structure for a leak. In this paper, we propose a method for steam leakage detection by using the moving average of difference images and histogram analysis. The proposed method can separate the leakage and the vibration of a structure. The working performance of the proposed method is verified by comparing with experimental results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2009.10a
• /
• pp.124-125
• /
• 2009