Characterization of Electro-Active Paper Vibration Sensor by Impact Testing and Random Excitation

2015 ◽  
Vol 07 (04) ◽  
pp. 1550065 ◽  
Author(s):  
Zafar Abas ◽  
Dong Ho Yang ◽  
Heung Soo Kim ◽  
Moon Kyu Kwak ◽  
Jaehwan Kim
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Polyvinylidene Fluoride ◽  
Frequency Response Function ◽  
Low Frequency ◽  
Random Excitation ◽  
Impact Testing ◽  
Vibration Sensor ◽  
Dynamic Strain ◽  
The Time Domain

We characterized a vibration sensor made of piezoelectric paper by measuring the frequency response function of an aluminum cantilever that was subjected to impulse loading and random excitation. The dynamic characteristics of the device were measured by recording the transient response of the smart cantilever beam with a pair of electro-active paper (EAPap) and polyvinylidene fluoride (PVDF) sensors located at a 5 mm distance from the clamped end as well as from a second pair of piezoelectric sensors located at a distance of 140 mm. The responses were measured by impacting the cantilever at its tip and at its mid-point. A fast Fourier transform was applied on the time domain data to measure the resonant frequencies of the vibrating structure. Both the EAPap and the PVDF sensors were observed to be very sensitive to varying levels of dynamic strain. The EAPap sensor showed a low strain sensitivity that was found to be desirable due to the inherent piezoelectricity and eco-friendly behavior of the material. The results revealed that the dynamic sensing ability of the EAPap at a low frequency range was quite comparable to that of PVDF when monitoring structural vibrations. The frequency response function was also measured via random excitation, piezoelectricity of the EAPap sensor shows potential for sensing vibrations with a dynamic response.

Identification of Rotating Asymmetry in Rotating Machines by Using Reverse dFRF

1999 ◽  
Author(s):  
Chong-Won Lee ◽  
Kye-Si Kwon
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Modal Testing ◽  
Vibration Sensor ◽  
Response Functions ◽  
Physical Realization ◽  
Simple Method ◽  
Testing Method ◽  
Asymmetric Rotor

Abstract A quick and easy but comprehensive identification method for asymmetry in an asymmetric rotor is proposed based on complex modal testing method. In this work, it is shown that the reverse directional frequency response function (reverse dFRF), which indicates the degree of asymmetry, can be identified with a simple method requiring only one vibration sensor and one exciter. To clarify physical realization associated with estimation of the reverse dFRF, its relation to the conventional frequency response functions, which are defined by the real input (exciter) and output (vibration sensor), are extensively discussed.

Use of experimental dynamic substructuring to predict the low frequency structural dynamics under different boundary conditions

2017 ◽  
Vol 23 (11) ◽  
pp. 1444-1455
Author(s):  
Walter D’Ambrogio ◽  
Annalisa Fregolent
Keyword(s):  
Boundary Conditions ◽  
Rigid Body ◽  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Low Frequency ◽  
Response Functions ◽  
Frequency Response Functions ◽  
Different Boundary Conditions ◽  
Rigid Body Modes

Flexible structural components can be attached to the rest of the structure using different types of joints. For instance, this is the case of solar panels or array antennas for space applications that are joined to the body of the satellite. To predict the dynamic behaviour of such structures under different boundary conditions, such as additional constraints or appended structures, it is possible to start from the frequency response functions in free-free conditions. In this situation, any structure exhibits rigid body modes at zero frequency. To experimentally simulate free-free boundary conditions, flexible supports such as soft springs are typically used: with such arrangement, rigid body modes occur at low non-zero frequencies. Since a flexible structure exhibits the first flexible modes at very low frequencies, rigid body modes and flexible modes become coupled: therefore, experimental frequency response function measurements provide incorrect information about the low frequency dynamics of the free-free structure. To overcome this problem, substructure decoupling can be used, that allows us to identify the dynamics of a substructure (i.e. the free-free structure) after measuring the frequency response functions on the complete structure (i.e. the structure plus the supports) and from a dynamic model of the residual substructure (i.e. the supporting structure). Subsequently, the effect of additional boundary conditions can be predicted using a frequency response function condensation technique. The procedure is tested on a reduced scale model of a space solar panel.

The Improved Frequency Response Function and its Effect on Modal Circle Fits

1984 ◽  
Vol 51 (3) ◽  
pp. 657-663 ◽  
Author(s):  
K. B. Elliott ◽  
L. D. Mitchell
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
System Analysis ◽  
Resonance Region ◽  
Random Excitation ◽  
Structural Parameter ◽  
Parameter Estimates ◽  
Average Percentage ◽  
Fitting Error

When structures are excited by random force excitation the circle fits of the data around resonance are usually poor. The structural parameter estimates, which result from this fit, are usually erroneous. No matter how elegant the circle or the multimodal fit, the results will be poor if the frequency response function (FRF) is a poor representation of the actual structural response. In general for the random excitation case, this is the case. The conventional fast Fourier transform (FFT) method which is used to estimate the frequency response function, is given by H1 (f) = Gxy/Gxx. This produces poor results when the coherence of the data falls in the resonance region. A drop in the coherence usually indicates noise at the input of the structure for this case. H1 (f) is quite sensitive to such noise giving erroneous estimates. This paper investigates an alternative method for computing the frequency response function, H2 (f) = Gyy/Gyx, and its impact on the accuracy of the circle fit procedure used in modal analysis. This new estimator is not sensitive to input noise like the currently used H1 (f). H2(f) provides the best estimate at or around resonance even in the presence of noise on the input signal. If one defines the average percentage fit error in the circle fit operation as 100 times the average radial deviation of the data points from the radius of the statistically fit circle divided by the fit circle radius, one can compute the circle fit accuracy for each of the proposed methods of data treatment. Typically, the percentage fitting error for H1 (f) might be 10 percent while the fitting error for H2 (f) using exactly the same data will be 0.5 percent. Thus, the proposed method eliminates long-standing system analysis errors through the use of a simple revision of the way the data are treated in the FFT processor around the resonance regions.

Rapid Measurement of Modal Properties Using FFT Analyzers With Random Excitation

1986 ◽  
Vol 108 (4) ◽  
pp. 394-398 ◽  
Author(s):  
P. Cawley ◽  
L. G. Rigner
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Random Excitation ◽  
Nyquist Plot ◽  
Frequency Resolution ◽  
Testing Time ◽  
Rapid Measurement ◽  
Modal Amplitude ◽  
Time Required

The use of a Nyquist plot of the H2 (Syy/Sxy*) frequency response function estimates produced by an FFT based spectrum analyzer with random excitation to obtain modal amplitudes and hence modal constants has been investigated. It has been proved that, irrespective of the frequency resolution used, the H2 estimates always lie on the true modal circle so even at coarse frequency resolution, a circle fitted to these points gives accurate values of modal amplitude. The conventional H1 (Sxy/Sxx) estimates lie inside the true modal circle. Use of the H2 technique results in major savings in the testing time required for a modal survey, particularly when measurements are to be taken at many points on the test structure.

The Accuracy of Frequency Response Function Measurements Using FFT-Based Analyzers With Transient Excitation

1986 ◽  
Vol 108 (1) ◽  
pp. 44-49 ◽  
Author(s):  
P. Cawley
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Random Excitation ◽  
Frequency Resolution ◽  
Impact Excitation ◽  
Analogue Computer ◽  
Bias Error ◽  
Response Measurement ◽  
Theoretical Predictions

The accuracy of the frequency response measurement obtained using impact excitation and a Fast Fourier Transform based spectrum analyzer has been investigated. It has been shown that with impact excitation, provided the impacts are reproducible and the extraneous noise level is low, the coherence estimates obtained from the analyzer are unity, irrespective of the frequency resolution employed. Hence the H1 (Sxy/Sxx) and H2 (Syy/Sxy*) frequency response function estimates are identical. However, these frequency response function estimates are affected by a bias error caused by inadequate frequency resolution so unity coherence does not necessarily imply accurate results. The results with impact excitation are compared with those obtained using random excitation where both the coherence and frequency response function estimates are affected by bias error. The bias error in the frequency response function estimates with impact excitation is intermediate between that in the H1 and H2 estimates when random excitation is used. The theoretical predictions have been verified by tests on an analogue computer and on a built-up structure.

scholarly journals The Researches on Damage Detection Method for Truss Structures

2018 ◽  
Vol 38 ◽  
pp. 03030
Author(s):  
Meng Hong Wang ◽  
Xiao Nan Cao
Keyword(s):  
Numerical Simulation ◽  
Frequency Response ◽  
Response Function ◽  
Time Domain ◽  
Experimental Analysis ◽  
Frequency Response Function ◽  
Principal Component ◽  
Truss Structures ◽  
Time Domain Signal ◽  
The Time Domain

This paper presents an effective method to detect damage in truss structures. Numerical simulation and experimental analysis were carried out on a damaged truss structure under instantaneous excitation. The ideal excitation point and appropriate hammering method were determined to extract time domain signals under two working conditions. The frequency response function and principal component analysis were used for data processing, and the angle between the frequency response function vectors was selected as a damage index to ascertain the location of a damaged bar in the truss structure. In the numerical simulation, the time domain signal of all nodes was extracted to determine the location of the damaged bar. In the experimental analysis, the time domain signal of a portion of the nodes was extracted on the basis of an optimal sensor placement method based on the node strain energy coefficient. The results of the numerical simulation and experimental analysis showed that the damage detection method based on the frequency response function and principal component analysis could locate the damaged bar accurately.

scholarly journals Road Roughness Estimation Based on the Vehicle Frequency Response Function

Actuators ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 89
Author(s):  
Qingxia Zhang ◽  
Jilin Hou ◽  
Zhongdong Duan ◽  
Łukasz Jankowski ◽  
Xiaoyang Hu
Keyword(s):  
Frequency Response ◽  
Response Function ◽  
Frequency Response Function ◽  
Gaussian White Noise ◽  
Estimation Method ◽  
Time Shift ◽  
Ride Quality ◽  
The Road ◽  
Road Roughness ◽  
Measured Response

Road roughness is an important factor in road network maintenance and ride quality. This paper proposes a road-roughness estimation method using the frequency response function (FRF) of a vehicle. First, based on the motion equation of the vehicle and the time shift property of the Fourier transform, the vehicle FRF with respect to the displacements of vehicle–road contact points, which describes the relationship between the measured response and road roughness, is deduced and simplified. The key to road roughness estimation is the vehicle FRF, which can be estimated directly using the measured response and the designed shape of the road based on the least-squares method. To eliminate the singular data in the estimated FRF, the shape function method was employed to improve the local curve of the FRF. Moreover, the road roughness can be estimated online by combining the estimated roughness in the overlapping time periods. Finally, a half-car model was used to numerically validate the proposed methods of road roughness estimation. Driving tests of a vehicle passing over a known-sized hump were designed to estimate the vehicle FRF, and the simulated vehicle accelerations were taken as the measured responses considering a 5% Gaussian white noise. Based on the directly estimated vehicle FRF and updated FRF, the road roughness estimation, which considers the influence of the sensors and quantity of measured data at different vehicle speeds, is discussed and compared. The results show that road roughness can be estimated using the proposed method with acceptable accuracy and robustness.

Sign in / Sign up

Export Citation Format

Share Document