Resonant Frequency Band Research Articles

Fault Diagnosis and Verification of Rolling Bearings Based on Optimal Resonance Demodulation with Deconvolution MRSVD

As one of the important aviation equipment components, rolling bearings will bring hidden dangers to the safety of aviation equipment once they fail. In aviation equipment, the sensor is far away from the bearing, and the collected signal of the rolling bearing is relatively weak. In this paper, the deconvolution algorithm is used to compensate the transfer function, and the optimal resonance demodulation algorithm based on the improved multi-resolution singular value decomposition (MRSVD) is constructed to determine the resonance frequency band, and then the bearing fault state is determined by the normalized squared envelope spectrum. The analysis results of the rolling bearing seed fault experiment show that this algorithm can adaptively extract the periodic fault pulse components under strong noise; compared with the normal spectral analysis and fast spectral kurtosis methods, this algorithm can completely extract the bearing fault characteristic frequency components, and effectively improve the bearing fault diagnosis accuracy.

Passive and active low frequency sound absorption performance of the finite and large sized micro-perforated panel absorber on oblique incidence condition

This paper presents a comprehensive investigation on the passive and active low frequency sound absorption performance of the finite and large sized micro-perforated panel absorber (FLS-MPPA) for oblique incidence excitation (OIE), which is of great significance for the engineering implementation of this technic. The theoretical model of the FLS-MPPA is firstly established by applying the modal analysis approach. It is also validated by experimental test. Then, the passive sound absorption performance is explored and the underlying physical mechanisms of these peculiar findings are investigated thoroughly. Finally, the active control performance (applying point source to actively control the sound field) and physical mechanism of the sound absorption improvement of the FLS-MPPA are analyzed. Results obtained demonstrate some key findings. The high order cavity modes excited by OIE reflect most of the incident sound power and have little contribution to the sound absorption in the low frequency range owing to their strong mutual coupling effects and being greatly excited with high modal amplitudes. They also cannot produce additional sound absorption peaks due to their wide resonant frequency band. Weakening such mutual coupling effects can improve the sound absorption and produce additional absorption peaks. The low frequency sound absorption of the FLS-MPPA is significantly improved with control and the achievable maximum sound absorption coefficient is slightly greater than the difference between 1 and the sound power reflection coefficient of the MPP, which validates the feasibility of the active control method for OIE. The reflected sound power induced by the cavity modes is highly reduced and part of the reflected sound power produced by the MPP can even be absorbed by these modes when their amplitudes are reduced to the optimal value, which is the physical nature of the active control. Sensing and controlling the cavity sound field in the corner achieves almost equal sound absorption improvement as that of the optimal control state, based on which the error sensing strategy is constructed.

Design of miniaturized tri‐band antenna based on differential evolution algorithm

AbstractA novel highly miniaturized triple band structure based on Z‐slots‐shaped antenna is presented in this letter, with only 0.0015 footprint, where is the free space wavelength at 1.3 GHz. The proposed design can generates three resonant frequency bands (1.3–1.62 GHz), (2.22–2.59 GHz), and (3.24–3.65 GHz) with −10 dB reflection coefficient, a triple band function is achieved by etching tow connected Z‐shaped‐slots in the radiating element and the differential evolution algorithm is then used to control the currents path, the prototype of the proposed antenna is printed on a single substrate layer and fed via coplanar waveguide CPW technology. The measured and simulated results are in good agreement, and validate the design principle, the results show that the antenna has a compact size (19.5 × 17.6 mm2), aside from its planar design, simple manufacturing, and low cost to fabricate, this antenna exhibits stable omnidirectional radiation patterns in E plane as well as bidirectional radiation patterns in H plane, making it an ideal device for multiband applications.

Nonlinear fast kurtogram for the extraction of gear fault features with shock interference

The extraction of gearbox fault features under shock interference is an exceedingly difficult and valuable subject. The effective usage of the resonance frequency band is one of the solutions for this subject. However, the existing fast kurtogram (FK) method is prone to misdiagnosis due to the sensitivity of this method to aperiodic shocks. To overcome the sensitivity of the FK method to irrelevant shock, this paper proposes a nonlinear fast kurtogram (NFK) method. First, Z-score normalization is performed on the signal. Then, Sigmoid is used to improve the fault representation under shock interference. Third, the signal is divided into different frequency bands, and the band with the largest kurtosis is selected for filtering. Finally, the gear fault is analyzed by the square envelope spectrum. Simulation and experimental verification are used to demonstrate the effectiveness of the proposed method. The results show that gear fault features can be extracted under shock interference by the NFK method.

Double Sided Wideband Concentric Ring Spatial Filters for Mid-Band 5G Devices

This paper presents the methodology, development, and implementation of the double concentric ring band-pass frequency selective surface (FSS) based spatial filters. The filters are designed to improve the active responses of the 5G antennas by incorporating them as superstrate or as substrates. A comparable circuit model is used to anticipate the resonant frequency bands required for predicting the FSS band-pass behavior. The designed spatial filter is composed of a combination of periodic circular loop structures engraved on both sides of a thin dielectric substrate. The proposed design of a double circular loop FSS exhibits band-pass characteristics for n77, n78, and n79 bands of the mid-band 5G spectrum (ranging from 3 GHz - 6 GHz) and provides insensitivity to polarization angles of the incident plane wave. The computed, simulated, and measured findings are all depicting a similar pattern that validates our structure.

A Novel Method for Enhanced Demodulation of Bearing Fault Signals Based on Acoustic Metamaterials

Rolling bearings fault diagnosis technology plays a significant role in modern industries. In this article, a novel method to diagnose bearing faults via acoustic metamaterials is proposed and experimentally validated by selecting and enhancing the optimal resonance frequency band for demodulation. The proposed method is performed by analysing acoustic signals, which is convenient due to its noncontact measurement. Different from conventional denoising techniques, the proposed method is implemented by enhancing the resonance frequency band via acoustic metamaterials instead of constructing filters to wipe out noise. Consequently, all the useful information of fault signals are remained and the detection limits of current acoustic sensing systems are improved because of the enhanced fault signals. Additionally, the optimal resonance band is sought by changing measured positions based on the frequency-selective enhancement property of the designed metamaterial. By comparing with spectral kurtosis-based method, the proposed method is more superior to extract bearing fault features at low signal to noise ratios. All the presented results indicate that the proposed method is effective to extract bearing fault features.

Evaluation of a wheel-based seismic acquisition system for a planetary rover

Prior to using in-situ planetary resources, efficient mapping of geochemical and physical characteristics of the near surface will be required. As part of an integrated geophysical instrument suite on exploration and prospecting vehicles, we investigated the suitability of seismic piezo-sensors rigidly mounted on the interior of a generic rover wheel. Factors that can compromise proper data acquisition for this system include the natural mechanical resonance of the wheel and wheel-to-ground coupling. We characterized the natural resonance frequency bands of a generic wheel with an electromagnetic shaker. We also collected seismic shot gathers for subsequent seismic surface-wave analysis using a wheel in both a dry, laboratory sand tank (1.8 × 1.8 × 0.6 m) and in frozen loess soils within the United States Army Corps of Engineers Permafrost Tunnel in Alaska. For our wheel, self-weighted coupling to the ground was found to be adequate, although suitable wheelbase dimensions can constrain field acquisition geometries. In unconsolidated sediments, represented by medium sand (0.25–0.5 mm), wheel resonance of 1 kHz does not affect the fundamental mode used in shear-wave-velocity-to-depth inversion. When analyzed, shot-gather data collected from both wheel-mounted sensors and sand-planted sensors, in loose dry sand, effectively captured similar fundamental surface-wave modes. This is evident in frequency-versus-phase velocity dispersion images. Because narrow frequency bands of wheel resonance exhibit a high signal-to-noise ratio, they also readily detect lateral attenuation changes. Thus, wheel resonance can also be used to capture soil attenuation changes, including those produced when pore H2O ice acts to cement the regolith or loose-grained soils.

High gain frequency reconfigurable multifunctional antenna for modern wireless and mobile communication systems

This article proposes a novel multifunctional wideband reconfigurable antenna with a frequency selective surface (FSS) reflector to improve gain across all operating bands. Initially, a wideband trapezoidal monopole antenna with a 138% impedance bandwidth (1.53–8.45 GHz) on a FR-4 substrate with a thickness of 0.80 mm and an area of 51 × 56 mm2 was designed. In order to achieve multifunctionality, two inverted L structures with two rectangular slots were introduced at the ground plane. Each slot functions as a filter, producing various resonating bands. To obtain the desired resonating frequency bands, the effective length of the slot was changed by strategically placing RF switching element PIN diodes. The proposed reconfigurable antenna can switch between 10 different frequency bands. To improve the gain of the proposed reconfigurable antenna, a novel FSS reflector with a 5 × 5 array of elements is placed 1.01λ (34.54 mm) below the proposed antenna. The application of the FSS results in a 3–6 dBi improvement in antenna gain, not only for the wideband range, but also for all operating frequency bands. Over the entire operating bandwidth, the radiation efficiency ranges from 93% to 75%. For GPS, RADAR, LTE42/43, WLAN, WiMAX, STM-Link, and UMTS applications, the proposed antenna operates in a wideband state, three single band states, four dual band states, and three tri band states. This work provides more antenna functionality at a lower cost, as well as significantly reduced size and space requirements. The proposed antenna can be easily integrated into portable electronic devices for a variety of wireless applications due to its broad switching capability and unique feasibility.

Validating a physics-based automatic classification scheme for Impact Echo signals on data from a concrete slab with known defects

Impact Echo (IE) is capable of locating subsurface defects in concrete slabs from vibrational response of the slab to mechanical impact. For an intact slab (‘good’ condition), the frequency spectrum of IE is dominated by a peak corresponding to the slab’s ‘thickness resonance frequency’ since much of the impact energy is reflected from the bottom of the deck. The presence of subsurface defects (‘fair’ or ‘poor’ conditions) could manifest in various ways such as multiple distinct peaks at frequencies higher or lower than the thickness resonance. Energy distribution across different frequency bands varies with the type and extent of damage. In previous research, the authors have proposed a frequency partitioning of the spectrum for IE signal classification. First, the thickness resonance frequency band is identified using Gaussian Mixture modeling. Next, IE signals are represented by their energy distribution in three bands – frequencies less than, within and greater than thickness resonance. IE signals are reduced to feature vectors representing the proportion of energy in each band. Following the feature extraction, an unsupervised clustering approach is used to identify the centroids for each signal class – good, fair, poor, which is used to classify any test signal into one of the three classes. The classification is developed by training on unlabeled IE signals from real bridge deck data (Federal Highway Administration’s (FHWA) InfoBridge dataset) without making use of any labeled data. This study aims to validate the proposed methodology developed based on field data on a labeled dataset of eight reinforced concrete specimens constructed at FHWA Advanced Sensing Technology NDE laboratory with known artificial defects: shallow and deep delamination, honeycombing and voids. Findings indicate that the physics-based feature definition and the method developed on real bridge data is robust and can classify IE signals in the labeled data with high accuracy.

전력변환장치 캐비넷에서의 내부발열 개선을 위한 열유동 분석 및 유통안전성 향상을 위한 진동특성 분석

PCS needs to freely switch AC and DC to connect the battery, external AC loads and renewable energy in both directions for energy efficiency. Whenever converting happens, power loss inevitably occurs. Minimization of the power loss to save electricity and convert it for usage is a very critical function in PCS. PCS plays an important role in the ESS(Energy Storage System) but the importance of stabilizing semiconductors on PCB(Printed Circuit Board) should be empathized with a risk of failure such as a fire explosion. In this study, the temperature variation inside PCS was reviewed by cooling fan on top of PCS, and the vibration characteristics of PCS were analyzed during truck transportation for reliability of the product. In most cases, a cooling fan is mounted to control the inner temperature at the upper part of the PCS and components generating the heat placed on the internal aluminum cooling plate to apply the primary cooling and the secondary cooling system with inlet fans for the external air. Results of CFD showed slightly lack of circulating capacity but simulated temperatures were durable for components. The resonance points of PCS were various due to the complexity of components. Although they were less than 40 Hz which mostly occurs breakage, it was analyzed that the vibration displacement in the resonance frequency band was very insufficient. As a result of random-vibration simulation, the lower part was analyzed as the stress-concentrated point but no breakage was shown. The steel sheet could be stable for now, but for long-term domestic transportation, structural coupling may occur due to accumulation of fatigue strength. After the test completed, output voltage of the product had lost so that extra packaging such as bubble wrap should be considered.

Frequency reconfigurable circular microstrip patch antenna with slots for cognitive radio

In this paper, a novel multi-frequency microstrip antenna with complementary ring slot resonator (CRSR) structure that satisfies Bluetooth, worldwide interoperability for microwave access (WiMAX), and wireless local area network (WLAN) applications is proposed. The conventional antenna consists of a circular microstrip patch at a resonance frequency band of 2.5 GHz. By loading two CRSR at the radiating element, three operating frequency bands 2.5 GHz, 3.6 GHz, and 5.2 GHz are achieved. The operational bands covered by the antenna are Bluetooth 2.5 GHz, WiMAX 3.6 GHz, and WLAN 5.2 GHz. The insertion of CRSR to patch antenna has made it possible to compact and simple design, and miniaturized antenna for cognitive radio. Moreover, the directivity of the proposed antenna is adequate with acceptable radiation properties and perfectly matches with the simulated and measured results.

Bearing failure impulse enhancement method using multiple resonance band centre positioning and envelope integration

Due to the complex structure of electromechanical systems, impulse components with a transient duration will excite multi-resonance phenomena and generate diverse peak-like bands in the spectra of vibration signals. Resonance bands excited by bearing failure-induced impulses that characterise failure area and form, are confused with frequency components caused by impulsive interference and background noise. Given the imperceptibility of the failure features of on-machine bearings, a better identification strategy is to extract the information of multiple predominate resonance bands excited by failure, referred to as effective resonance frequency bands (ERFBs), and to then integrate them, instead of locating only the optimal resonance frequency band (ORFB). In this paper, a multiple resonance band centre positioning and envelope integration method is proposed to enhance the bearing failure features. To this end, a robust indicator, ratio of cyclic content (RCC), is utilised to construct an Improved-Protrugram to position the centres of ERFBs correctly. Then, a dichotomy is introduced to establish an iterative search algorithm for improving position efficiency. Further, the positioned sub-band components are filtered and demodulated to obtain the envelopes of failure-induced multiple resonances. Finally, a variable weighting envelop integration strategy is proposed to eliminate interference that does not coexist between different sub-band components. The effectiveness of the proposed method is verified using both simulated and experimental bearing failure signals. The results indicate that the proposed method is superior to ORFB location methods for on-machine bearing failure identification.

Bearing multi-fault diagnosis with iterative generalized demodulation guided by enhanced rotational frequency matching under time-varying speed conditions

The rotational frequency (RF) is an important information for multi-fault features detection of rolling bearing under varying speed conditions. In the traditional methods, such as the computed order analysis (COA) and the time–frequency analysis (TFA), the RF should be measured using an encoder or extracted by a complex algorithm, which bring challenge to bearing fault diagnosis. In order to address this issue, a novel iterative generalized demodulation (IGD) based method guided by the instantaneous fault characteristic frequency (IFCF) extraction and enhanced instantaneous rotational frequency (IRF) matching is proposed in this paper. Specifically, the resonance frequency band excited by bearing fault is first obtained by the band-pass filter, and its envelope time–frequency​ representation (TFR) is calculated using the Hilbert transform and the short-time Fourier transform (STFT). Second, the IFCF is extracted using the harmonic summation-based peak search algorithm from the envelope TFR. Third, the time-varying RF ridge is transformed into a line paralleling to the time axis using the IGD with the phase function (PF). The PF is calculated by the IFCF function and fault characteristic coefficient (FCC). Lastly, the iterative generalized demodulation spectrum (IGDS) is obtained using the fast Fourier transform (FFT) for identifying fault type corresponding to the extracted IFCF. Based on obtained fault type and FCC ratios, new PFs and frequency points (FPs) are calculated for detecting other faults. Both simulated and experimental results validate that multi-fault features of rolling bearing under time-varying rotational speeds can be effectively identified without RF measurement and extraction.

An innovative piezoelectric energy harvester inspired by a line tooth: design, dynamic model and broadband harvesting conditions

Piezoelectric energy harvesting is commonly considered to be a promising field of development for microelectronic devices due to its potential to address a variety of key supply problems. However, due to their geometric designs, traditional piezoelectric energy harvesters (PEHs) tend to only be able to cultivate energy from vibrations flowing in one direction. The results of PEHs only capable of harvesting mono-directional vibrations are that they suffer from narrow resonance frequency bands and low energy conversion efficiency. To overcome these difficulties, this paper proposes a PEH inspired by a line tooth (PEH-ILT) with the ability to collect three-dimensional stochastic vibrations. To do so, the PEH-ILT possesses a nonlinear geometric shape which can, in theory, be designed arbitrarily. An example PEH-ILT is illustrated in this paper as well corresponding nonlinear piezoelectric constitutive equations. The cylindrical spiral curve is inspired by the line tooth design and is intended to replicate a nonlinear electro-mechanical model and its electrical output. Furthermore, the PEH-ILT is evaluated in this study by interacting with the four basic vibrations such devices are expected to encounter. In addition, the broadband piezoelectric energy harvesting conditions of the PEH-ILT are parsed and determined through the Melnikov theory, providing a theoretical explanation to the broadband conditions of the harvester. And this study can lay the theoretical basis for practical applications.

A Dual-Band High-Sensitivity THz Metamaterial Sensor Based on Split Metal Stacking Ring

Terahertz (THz)-detection technology has been proven to be an effective and rapid non-destructive detection approach in biomedicine, quality control, and safety inspection, among other applications. However, the sensitivity of such a detection method is limited due to the insufficient power of the terahertz source and the low content, or ambiguous characteristics, of the analytes to be measured. Metamaterial (MM) is an artificial structure in which periodic sub-wavelength units are arranged in a regular manner, resulting in extraordinary characteristics beyond those possessed by natural materials. It is an effective method to improve the ability of terahertz spectroscopy detection by utilizing the metamaterial as a sensor. In this paper, a dual-band, high-sensitivity THz MM sensor based on the split metal stacking ring resonator (SMSRR) is proposed. The appliance exhibited two resonances at 0.97 and 2.88 THz in the range of 0.1 to 3 THz, realizing multi-point matching between the resonance frequency and the characteristic frequency of the analytes, which was able to improve the reliability and detection sensitivity of the system. The proposed sensor has good sensing performance at both resonant frequencies and can achieve highest sensitivities of 304 GHz/RIU and 912 GHz/RIU with an appropriate thickness of the analyte. Meanwhile, the advantage of multi-point matching of the proposed sensor has been validated by distinguishing four edible oils based on their different refractive indices and demonstrating that the characteristics obtained in different resonant frequency bands are consistent. This work serves as a foundation for future research on band extension and multi-point feature matching in terahertz detection, potentially paving the way for the development of high-sensitivity THz MM sensors.

Power spectral density-guided variational mode decomposition for the compound fault diagnosis of rolling bearings

Compound fault diagnosis with stochastic interfering impulses remains to be a tricky task due to the difficulty of determining multiple resonant frequency bands. Variational mode decomposition (VMD) can extract instinct mode functions (IMFs) adaptively and effectively reduce the modal aliasing issue. However, such adaptivity requires a pre-known number of IMFs, which cannot be automatically determined. This paper develops a novel VMD method for compound fault diagnosis guided by power spectral density (PSD), which enables the estimation of the IMF amount and optimization of VMD processes by applying PSD’s representation for energy distribution in the frequency domain. Several model amount determination methods and empirical wavelet transform (EWT) method are used to compare with the proposed method. Through comparative experiments of simulation and challenging experimental data sets, the proposed method has remarkable advantages in terms of fault feature detection capability and result display, and shows superior robustness.

IGIgram: An Improved Gini Index-Based Envelope Analysis for Rolling Bearing Fault Diagnosis

The transient impulse features caused by rolling bearing faults are often present in the resonance frequency band which is closely related to the dynamic characteristics of the machine structure. Informative frequency band identification is a crucial prerequisite for envelope analysis and thereby accurate fault diagnosis of rolling bearings. In this paper, based on the ratio of quasi-arithmetic means and Gini index, improved Gini indices (IGIs) are proposed to quantify the transient impulse features of a signal, and their effectiveness and advantages in sparse quantification are confirmed by simulation analysis and comparisons with traditional sparsity measures. Furthermore, an IGI-based envelope analysis method named IGIgram is developed for fault diagnosis of rolling bearings. In the new method, an IGI-based indicator is constructed to evaluate the impulsiveness and cyclostationarity of the narrow-band filtered signal simultaneously, and then a frequency band with abundant fault information is adaptively determined for extracting bearing fault features. The performance of the IGIgram method is verified on the simulation signal and railway bearing experimental signals and compared with typical sparsity measures-based envelope analysis methods and log-cycligram. The results demonstrate that the proposed IGIs are efficient in quantifying bearing fault-induced transient features and the IGIgram method with appropriate power exponent can effectively achieve the diagnostics of different axle-box bearing faults.

Meander and Koch Hybrid Fractal Curve Based Dual Hexagonal Radiating Patch Antenna for Quad Band Wireless Applications

A unique dual hexagonal-shaped radiating patch design with hybrid fractal curves (Meander and Koch) is presented for quad-band wireless applications. Initially, the antenna from 0th to 2nd iteration of hybrid fractal curves with PGP (Partial Ground Plane) is designed and investigated. Further, to get better results of the designed antenna in respect of Bandwidth (BW) and coefficient of reflection these hybrid curves are superimposed on the limited ground plane of 1st and 2nd iteration of the antenna and the generated antennas are designated as Antenna–1 and Antenna–2. A comparison between both the antennas has been made and it is observed that Antenna–2 shows better results in respect of improved BW and coefficient of reflection. The proposed antenna exhibits four resonant frequency bands 1.6, 4.8, 6.9, and 8.8 GHz with improved corresponding impedance BW of 2.09, 1.36, 0.86, and 1.51 GHz. The designed antenna is simulated and made on FR4 glass epoxy substrate with an overall size of 20 × 40 × 1.6 mm3. The fabricated proposed antenna is tested experimentally for the authentication of simulated results with experimental results and these are compatible with each other. The other performance indicators like radiation pattern, peak realized gain, and radiation efficiency are also determined for the proposed Hybrid Fractal Antenna (HFA) and all are found satisfactory. Due to the improved operational parameters, the designed HFA can be considered as a suitable applicant for distinct wireless applications in anticipated operational frequency ranges.

Fault diagnosis of SKF-6205 bearing with modified empirical mode decomposition

Rolling element bearings are broadly used in the rotating machines to support static and dynamic loads. In this research, the advance signal processing techniques are use for processing of bearing fault signals. Experimental validation with genuine vibration signals calculated from bearings with seeded defects on bearing elements. The model-based fault diagnosis method has attempted to diagnose incipient fault detection and classification of bearing with data driven approach. Feature extraction technique has been developed with hybrid signal processing technique based on the band pass filter nature of Empirical mode decomposition (EMD), the resonant frequency bands have owed in specific mono component signals called Intrinsic Mode Functions (IMFs). Synchronized resonant frequency band (SRFB) is obtained on based of orthogonal real wavelet using spectral kurtosis. Biorthogonal 5.5 wavelet, a real wavelet has been selected as a suitable wavelet for WPT based on “Maximum Relative Wavelet Energy” and “Maximum Energy-to-Shannon entropy ratio”. Three, Feature extraction techniques like continuous wavelet transform (CWT), wavelet packet transform (WPT) and modified Hilbert Huang Transforms (HHT) are compared on bases of their classification accuracy with different classification algorithm and filters. Various supervised classifiers have been compared through a common platform of Waikato Environment for Knowledge Analysis (WEKA) and concluded the k- nearest neighbour (KNN) as an effective available classifier for rolling element bearing. Further, asymmetric proximity function based KNN (APF-KNN) has out performs with modified feature selection criteria. Feature extraction through modified HHT and APFKNN has been future as a most effectual fault classification method. For testing any unknown data, simplified method has been demonstrated, which make the proposed data driven approach more realistic, faster and automated.

Highly sensitive vibration measurement method of nanomechanical resonators using a convolutional neural network

Nanomechanical resonators can detect various small physical quantities. It is necessary to increase the sensitivity of nanomechanical resonators. In this study, a deep learning-based method is developed for sensitive detection of vibration states of nanomechanical resonators. It enables one to explore the most highly sensitive vibration states without missing targets while conventional methods focus only on the resonant frequency. The proposed method was evaluated with laser intensity. Sensitive measurement of laser intensity has the potential for applications in laser wavelength measurement. The proposed method could identify laser intensity at intervals of 0.03 mW at which the resonance frequency did not shift. Grad-CAM was used to clarify features on the vibration spectra used in the convolutional neural network. Frequency bands other than the resonance frequency band were used for the laser intensity measurement. This result implies that there is a possibility that highly sensitive vibration behavior exists outside the resonance frequency.