Development of Time-Reversal Method for Impact Source Identification on Plate Structures

Reconstruction of Impact Force on Curved Panel using Piezoelectric Sensors

This paper describes development of an impact detection system by using the anisotropy of output voltage of metal-core piezoelectric fiber/aluminum composite. A metal-core piezoelectric ceramic fiber is very fragile and reactive with molten aluminum. Therefore general fabrication processes such as dimision bonding and casting are hard to be applied. However, embedding the metal-core piezoelectric fiber into an aluminum matrix was succeeded by using IF/B method. Furthermore, output voltage characteristics of fabricated composite were evaluated, and anisotropy of the output voltage was observed. In this study, impact location and energy detection system was developed by using anisotropy of output voltage of the composite. It is expected to reduce the number of sensors compared to conventional systems and keep accuracy by using this anisotropy. As the results, the impact energy and impact location detection was successfully by using the model of the output voltage of the composites and signals that were obtained from composites disposed in two different positions. In addition, the error of impact location was 8.88 mm at the maximum, and this result is caused by the anisotropy of output voltage of metal-core piezoelectric fiber/aluminum composite.

The authors utilized both experimental and finite element modeling methods earlier to develop both a classical inverse approach as well as a root mean square (RMS) method to estimate the magnitude of wheel impact forces on railway track-like structures. This study presents some results from the field trials of the techniques developed in (Lee, M.L., Chiu, W.K. and Koss, L.L (2005). A numerical study into the reconstruction of impact forces on railway track-like structures. Structural Health Monitoring: An International Journal, 4(1), 19–45. Lee, M.L. and Chiu, W.K (2005). The reconstruction of dynamic impact forces on a railway track-like structure by using an inverse analysis technique. In: Proceedings of the 4th Australasian Congress of Applied Mechanics, pp. 605–610, Melbourne, Australia. Lee, M.L. and Chiu, W.K. (2005). A comparative study on impact force prediction on a railway track-like structure. Structural Health Monitoring: An International Journal, 4(4), 355–376.). A length of track carrying freight rail traffic and situated along the Melbourne–Geelong line (Victoria, Australia) is instrumented with accelerometers and shear-bridges. The instrumentation consists of five rail cribs instrumented with a shear-bridge and an accelerometer on the rail foot at the midspan of each crib. Using the shear-bridge instrumentation as a check, it is found that the proposed inverse analysis method (IAM) shows potential in not only reconstructing clean impact strikes but also in reconstructing strikes occurring outside of the shear-bridge effective zone within a single crib. Furthermore, based on the principle of superposition governing linear systems, multiple impact strikes within a single crib of rail are also able to be reconstructed. Regarding the RMS method, it is found that while a good correlation (R ≈ 0.8) existed between wheel impact force and track response RMS, a significant spread existed in the data.

The article consists of a Powerpoint presentation on EMI analysis method. The areas discussed include: coupling path analysis method; source identification method; antenna identification method; far field setup method; data analysis method; semi-broadband signal; port impedance; transfer function and direct injection analysis.

This article introduces a dynamic weighted graph neural network (DWGNN) for precise reconstruction of impact force time histories under both fault and nonfault conditions in sensor networks. The DWGNN model integrates a one-dimensional convolutional neural network for extracting features from sensor signals and a graph neural network that dynamically adjusts its weight matrix based on node feature similarity, thereby reducing the impact of faulty sensor signals. Incorporating physical constraints, such as the distances between impact and sensor locations, improves the model’s performance. This innovative approach enables the accurate reconstruction of impact forces using only nonfaulty training data. Experimental validation on a stiffened metal plate, with mixed artificially generated and real measured signals, demonstrates the DWGNN model’s high accuracy and robustness. Data augmentation with fault signals significantly enhances the model’s accuracy under challenging fault conditions, proving the DWGNNs potential for real-time structural health monitoring and fault diagnosis in complex engineering structures.

The approximation of a fractional order PIλDμ-controller transfer function using a chain fraction theory is considered. Analytical expressions for the approximation of s±α components of the transfer functions of PIλDμ-controllers were obtained through the application of the chain fraction theory. Graphs of transition functions and frequency characteristics of Dμ (α = μ = 0.5) and Iλ (α = λ = −0.5) parts for five different decomposition orders were obtained and analyzed. The results showed the possibility of applying the approximation of the PIλDμ-controller transfer function by the method of chain fractions with different valuesof λ and μ. For comparison, the transfer functions with the same order polynomials, obtained by the methods of Oustaloup transformation and chain fractions, were approximated for α = ±0.5. The analysis proved the advantages of using the chain fraction method to approximate the transfer function of the PIλDμ-controller. The performed approximation opens up the possibility of developing engineering methods for the technical implementation of PIλDμ-controllers. The accuracy of the same order transfer function approximation is higher when the method of chain fractions is used. It has been established that the adequacy of the frequency characteristics of the transfer functions obtained by the chain fraction method also depends on the approximation order.

A method to identify both the impact location and the transverse impact force history from the strain responses at certain points on a rectangular plate is presented. The governing equations of the plate were obtained by applying the Reissner-Mindlin plate theory and the Rayleigh-Ritz method. The strain response was related to the impact force by solving the above equations using the eigenmode expansion method. A mutuality relationship among any pairs of strain responses was used to find the impact location without knowing in advance the impact force history. The force history was subsequently determined after the impact location was identified. The conjugate gradient method was adopted to search for the optimal impact location as well as the force history. Numerical verification was performed using randomly generated impact locations and force histories to simulate impact events. The excellent agreement showed the effectiveness and the validity of the proposed method.

This paper investigates the use of waveform-based acoustic emission (AE) techniques for location of low velocity impact in composite plates. An eight-ply [0 degrees/90 degrees/0 degrees/90 degrees], laminated glass/epoxy plate is investigated. The plate is impacted with a steel ball using a drop tower. Three broadband AE sensors are mounted on the surface of the composite plate. The response signals of the AE transducers are amplified by broadband AE preamplifiers and fed into a fracture wave detector made by Digital Wave Corporation. The signals are instantaneously sampled and stored in a pentium computer. The digitized AE signals are processed in the time and frequency domains. The raw AE signals were pre- processed to remove reflections from the plate boundaries that cause location error. The Gaussian cross-correlation method and Hilbert transformation are used to obtain arrival time differences among sensors and to overcome dispersion problems. Theoretical flexural wave velocities are calculated using the first order shear deformation plate theory. The calculated arrival time differences among sensors and the flexural velocities are used to determine impact location. The experimental results show that the flexural wave is the dominant mode for low velocity impact of the composite plate. Little or no extensional waves were observed. The locations of impact points are successfully determined. The location error varied from 0.00984 to 0.4807 radial inch for the 11.5' by 11.5' composite plate investigated. The method of using the Gaussian cross-correlation technique to determine AE arrival time differences among AE sensors is suitable for AE wave propagation detection due to low velocity impact.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Parameter estimation is one of the most challenging tasks in large‐scale distributed modeling, because of the high dimensionality of the parameter space. Relating model parameters to catchment/landscape characteristics reduces the number of parameters, enhances physical realism, and allows the transfer of hydrological model parameters in time and space. This study presents the first large‐scale application of automatic parameter transfer function (TF) estimation for a complex hydrological model. The Function Space Optimization (FSO) method can automatically estimate TF structures and coefficients for distributed models. We apply FSO to the mesoscale Hydrologic Model (mHM, mhm-ufz.org), which is the only available distributed model that includes a priori defined TFs for all its parameters. FSO is used to estimate new TFs for the parameters “saturated hydraulic conductivity” and “field capacity,” which both influence a range of hydrological processes. The setup of mHM from a previous study serves as a benchmark. The estimated TFs resulted in predictions in 222 validation basins with a median NSE of 0.68, showing that even with 5 years of calibration data, high performance in ungauged basins can be achieved. The performance is similar to the benchmark results, showing that the automatic TFs can achieve comparable results to TFs that were developed over years using expert knowledge. In summary, the findings present a step toward automatic TF estimation of model parameters for distributed models.

A digital twin is a promising evolving tool for prognostic health monitoring. However, in rotating machinery, the transfer function between the rotating components and the sensor distorts the vibration signal, hence, complicating the ability to apply a digital twin to new systems. This paper demonstrates the importance of estimating the transfer function for a successful transfer across different machines (TDM). Furthermore, there are few algorithms in the literature for transfer function estimation. The current algorithms can estimate the magnitude of the transfer function without its original phase. In this study, a new approach is presented that enables the estimation of the transfer function with its phase for a gear signal. The performance of the new algorithm is demonstrated by measured signals and by a simulated transfer function.

Significant arterio-venous differences in nicotine concentrations have been observed during and after cigarette smoking, nicotine nasal spray, and intravenous nicotine administration. In this paper we describe a novel mathematical method for estimating arterial blood levels from venous blood level data. The model allows to quantify: (i) the influence of the microcirculation in the hands and forearm on the distribution of nicotine, and (ii) the influence of disregarding the venous to arterial circulation in the estimate of systemic inputs. We also (iii) propose a general method to predict arterial concentrations and inputs given venous data. The basic model we adopt is based on the relationship Cv = T * Ca, where Cv and Ca are the concentration in the venous and arterial site, respectively, T is the arterio-venous transfer function and * indicates convolution. We use empirical data to estimate T. We then compare estimates of systemic inputs to the venous site obtained taking into account the transfer function or, as usually done, disregarding it. The relationship we use to compare estimated inputs are: Cv = T * ka * A (where Ka is the arterial disposition function and A the systemic input), and Cv = Kv * A (where Kv is the venous disposition function), respectively. Finally, the estimated transfer function allows to estimate (average) Ca or A given arbitrary venous data. (i) Our analysis suggests that a bi-exponential T is needed to describe observed arterial-venous differences. The estimated transfer function indicates that no elimination of nicotine is involved in the forearm. (ii) Disregarding T, as usually done, erroneously obtains too complex venous input functions (because these input functions incorporate T). (iii) Disregarding T erroneously estimates significantly higher total inputs. (iv) Using the proposed model and previously published venous nicotine level data we predict substantial arterial-venous differences in blood nicotine levels for smokeless tobacco and nicotine gum. The use of disposition functions obtained from venous data may lead to erroneous estimation of the rates of entry into the circulation and systemic bioavailability for many drugs.

Quantification, localization, and reconstruction of impact force on interval composite structures

This paper addresses the blind dereverberation problem of a single-input multiple-output acoustic system. Many conventional approaches require a precise order of the transfer functions. In this paper, we propose an equalization algorithm that is less sensitive to the order misadjustment of the transfer functions. First, the transfer functions are estimated using an overestimated order, and the inverse filter set for these estimated transfer functions is calculated. Since the estimated transfer functions contain a common polynomial, the signal processed by the inverse filter set suffers from the effect of this common polynomial. Then, we extract this polynomial to compensate for the distortion. The proposed algorithm recovers input signal as long as the channel is overestimated. Simulation results show that the proposed method works well even when the order is highly overestimated.

A fractional-order accumulative regularization filter for force reconstruction

Baroreflex modulates both the ventricular and vascular properties and stabilizes arterial pressure (AP). However, how changes in those mechanical properties quantitatively impact the dynamic AP regulation remains unknown. We developed a framework of circulatory equilibrium, in which both venous return and cardiac output are expressed as functions of left ventricular (LV) end-systolic elastance (Ees), heart rate (HR), systemic vascular resistance (R), and stressed blood volume (V). We investigated the contribution of each mechanical property using the framework of circulatory equilibrium. In six anesthetized dogs, we vascularly isolated carotid sinuses and randomly changed carotid sinus pressure (CSP), while measuring the LV Ees, aortic flow, right and left atrial pressure, and AP for at least 60 min. We estimated transfer functions from CSP to Ees, HR, R, and V in each dog. We then predicted these parameters in response to changes in CSP from the transfer functions using a data set not used for identifying transfer functions and predicted changes in AP using the equilibrium framework. Predicted APs matched reasonably well with those measured (r2=0.85-0.96, P<0.001). Sensitivity analyses indicated that Ees and HR (ventricular properties) accounted for 14±4 and 4±2%, respectively, whereas R and V (vascular properties) accounted for 32±4 and 39±4%, respectively, of baroreflex-induced AP regulation. We concluded that baroreflex-induced dynamic AP changes can be accurately predicted by the transfer functions from CSP to mechanical properties using our framework of circulatory equilibrium. Changes in the vascular properties, not the ventricular properties, predominantly determine baroreflex-induced AP regulation.