A novel sensitivity-based method for damage detection of structures under unknown periodic excitations

This paper presents a technique for damage detection in structures under unknown periodic excitations using the transient displacement response. The method is capable of identifying the damage parameters without finding the input excitations. We first define the concept of displacement space as a linear space in which each point represents displacements of structure under an excitation and initial condition. Roughly speaking, the method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering this novel geometrical viewpoint, an equation called kernel parallelization equation (KPE) is derived for damage detection under unknown periodic excitations and a sensitivity-based algorithm for solving KPE is proposed accordingly. The method is evaluated via three case studies under periodic excitations, which confirm the efficiency of the proposed method.     

A direct transmissibility formulation for experimental statistical energy analysis with no input power measurements

An experimental statistical energy analysis method is proposed that requires neither input power measurements nor strong restrictive hypothesis on the nature of coupling between subsystems. Coupling loss factors are obtained from direct or blocked energy transmissibilities provided that total or internal loss factors are known, for instance, from application of the energy decay rate method. In turn, direct transmissibilities are computed from standard measurable energy transmissibilities, following the ideas of the direct transfer approach to transmission path analysis. The theoretical background of the proposed formulation is presented together with a numerical example to indicate how it could be applied in a practical case.     

Sequential structural damage diagnosis algorithm using a change point detection method

This paper introduces a damage diagnosis algorithm for civil structures that uses a sequential change point detection method. The general change point detection method uses the known pre- and post-damage feature distributions to perform a sequential hypothesis test. In practice, however, the post-damage distribution is unlikely to be known a priori, unless we are looking for a known specific type of damage. Therefore, we introduce an additional algorithm that estimates and updates this distribution as data are collected using the maximum likelihood and the Bayesian methods. We also applied an approximate method to reduce the computation load and memory requirement associated with the estimation. The algorithm is validated using a set of experimental data collected from a four-story steel special moment-resisting frame and multiple sets of simulated data. Various features of different dimensions have been explored, and the algorithm was able to identify damage, particularly when it uses multidimensional damage sensitive features and lower false alarm rates, with a known post-damage feature distribution. For unknown feature distribution cases, the post-damage distribution was consistently estimated and the detection delays were only a few time steps longer than the delays from the general method that assumes we know the post-damage feature distribution. We confirmed that the Bayesian method is particularly efficient in declaring damage with minimal memory requirement, but the maximum likelihood method provides an insightful heuristic approach.     

Estimation of excitation and transmissibility from output measurements,with application to gear drives

Methods are presented by which both harmonic input magnitudes and dynamic transmissibility can be estimated when only the output of a system can be measured. This is possible when the input to a system consists of components whose amplitude remains constant although their time scale changes with speed. An example of this occurs with gear induced vibration where the forcing function is provided by errors which remain constant in amplitude. Examples given show how the methods can be used to estimate the static transmission error components of gear drives from dynamic response measurements where drive speeds are restricted.     

The interpolation damage detection method for frames under seismic excitation

In this paper a new procedure, addressed as Interpolation Damage Detecting Method (IDDM), is investigated as a possible mean for early detection and location of light damage in a structure struck by an earthquake. Damage is defined in terms of the accuracy of a spline function in interpolating the operational mode shapes (ODS) of the structure. At a certain location a decrease (statistically meaningful) of accuracy, with respect to a reference configuration, points out a localized variation of the operational shapes thus revealing the existence of damage. In this paper, the proposed method is applied to a numerical model of a multistory frame, simulating a damaged condition through a reduction of the story stiffness. Several damage scenarios have been considered and the results indicate the effectiveness of the method to assess and localize damage for the case of concentrated damage and for low to medium levels of noise in the recorded signals. The main advantage of the proposed algorithm is that it does not require a numerical model of the structure as well as an intense data post-processing or user interaction. The ODS are calculated from Frequency Response Functions hence responses recorded on the structure can be directly used without the need of modal identification. Furthermore, the local character of the feature chosen to detect damage makes the IDDM less sensitive to noise and to environmental changes with respect to other damage detection methods. For these reasons the IDDM appears as a valid option for automated post-earthquake damage assessment, able to provide after an earthquake, reliable information about the location of damage.     

Reconstructing unknown quantum states using variational layerwise method

In order to gain comprehensive knowledge of an arbitrary unknown quantum state, one feasible way is to reconstruct it, which can be realized by finding a series of quantum operations that can refactor the unitary evolution producing the unknown state. We design an adaptive framework that can reconstruct unknown quantum states at high fidelities, which utilizes SWAP test, parameterized quantum circuits (PQCs) and layerwise learning strategy. We conduct benchmarking on the framework using numerical simulations and reproduce states of up to six qubits at more than 96% overlaps with original states on average using PQCs trained by our framework, revealing its high applicability to quantum systems of different scales theoretically. Moreover, we perform experiments on a five-qubit IBM Quantum hardware to reconstruct random unknown single qubit states, illustrating the practical performance of our framework. For a certain reconstructing fidelity, our method can effectively construct a PQC of suitable length, avoiding barren plateaus of shadow circuits and overuse of quantum resources by deep circuits, which is of much significance when the scale of the target state is large and there is no a priori information on it. This advantage indicates that it can learn credible information of unknown states with limited quantum resources, giving a boost to quantum algorithms based on parameterized circuits on near-term quantum processors.     

A nonlinear signal-based control method and its applications to input identification for nonlinear SIMO problems

The problem of control system design can be conceptualised as identifying an input signal to a plant (the system to be controlled) so that the corresponding output matches that of a pre-defined reference signal. Primarily, this problem is solved via well-known techniques based upon the principle of feedback design, an essential component for ensuring stability and robustness of the controlled system. However, feedforward design techniques also have a large part to play, whereby (in the absence of feedback control and assuming that the plant is stable) a model of the plant dynamics can be used to modify the reference signal so that the resultant feedforward input signal generates a plant output signal that is sufficiently close to the original reference signal.     

A function cascade synchronization method with unknown parameters and applications

This paper investigates the function cascade synchronization of chaos system. Combining cascade synchronization scheme, parametric adaptive control and projective synchronization scheme, it proposes a new function cascade synchronization scheme to address a generalized-type synchronization problem of three famous chaotic systems: the Lorenz system, Liu system and R\"{o}ssler system, the states of two identical chaotic systems with unknown parameters can be asymptotically synchronized by choosing different special suitable error functions. Numerical simulations are used to verify the effectiveness of the proposed synchronization techniques.     

A function cascade synchronization method with unknown parameters and applications

This paper investigates the function cascade synchronization of chaos system. Combining cascade synchronization scheme, parametric adaptive control and projective synchronization scheme, it proposes a new function cascade synchronization scheme to address a generalized-type synchronization problem of three famous chaotic systems： the Lorenz system, Liu system and RSssler system, the states of two identical chaotic systems with unknown parameters can be asymptotically synchronized by choosing different special suitable error functions. Numerical simulations are used to verify the effectiveness of the proposed synchronization techniques.     

Chaotic system optimal tracking using data-based synchronous method with unknown dynamics and disturbances

We develop an optimal tracking control method for chaotic system with unknown dynamics and disturbances. The method allows the optimal cost function and the corresponding tracking control to update synchronously. According to the tracking error and the reference dynamics, the augmented system is constructed. Then the optimal tracking control problem is defined. The policy iteration(PI) is introduced to solve the min-max optimization problem. The off-policy adaptive dynamic programming(ADP) algorithm is then proposed to find the solution of the tracking Hamilton–Jacobi–Isaacs(HJI) equation online only using measured data and without any knowledge about the system dynamics. Critic neural network(CNN), action neural network(ANN), and disturbance neural network(DNN) are used to approximate the cost function, control, and disturbance. The weights of these networks compose the augmented weight matrix, and the uniformly ultimately bounded(UUB) of which is proven. The convergence of the tracking error system is also proven. Two examples are given to show the effectiveness of the proposed synchronous solution method for the chaotic system tracking problem.     

A time-domain approach for damage detection in beam structures using vibration data with a moving oscillator as an excitation source

The problem of detecting local/distributed change of stiffness in bridge structures using ambient vibration data is considered. The vibration induced by a vehicle moving on the bridge is taken to be the excitation source. A validated finite element model for the bridge structure in its undamaged state is assumed to be available. Alterations to be made to this initial model, to reflect the changes in bridge behaviour due to occurrence of damage, are determined using a time-domain approach. The study takes into account complicating features arising out of dynamic interactions between vehicle and the bridge, bridge deck unevenness, spatial incompleteness of measured data and presence of measurement noise. The inclusion of vehicle inertia, stiffness and damping characteristics into the analysis makes the system time variant, which, in turn, necessitates treatment of the damage detection problem in time domain. The efficacy of the procedures developed is demonstrated by considering detection of localized/distributed damages in a beam-moving oscillator model using synthetically generated vibration data.     

Electron impact excitation of Ni XIX using theR-matrix method

Collision strengths for all the transitions between the 15 lowest states of neon-like Ni XIX have been calculated for electron impact in the 80–140 Ry energy range. Configuration-interaction wavefunctions have been used to represent the target states. The standardR-matrix code has been used to calculate the lower scattering partial waves (L≤9), while a no-exchange version of the same code has been used to compute efficiently the higher partial waves (L≥10). Effective collision strengths for 105 excitation transitions between the ground state 2s ²2p ^{6 1} S ^e and the 142s ²2p ⁵3l Rydberg states are tabulated for electron temperatures in the range logT=5.40 to logT=7.00, withT expressed in °K.     

Generalized projective synchronization of chaotic systems with unknown dead-zone input: observer-based approach

In this paper we investigate the synchronization problem of drive-response chaotic systems with a scalar coupling signal. By using the scalar transmitted signal from the drive chaotic system, an observer-based response chaotic system with dead-zone nonlinear input is designed. An output feedback control technique is derived to achieve generalized projective synchronization between the drive system and the response system. Furthermore, an adaptive control law is established that guarantees generalized projective synchronization without the knowledge of system nonlinearity, and/or system parameters as well as that of parameters in dead-zone input nonlinearity. Two illustrative examples are given to demonstrate the effectiveness of the proposed synchronization scheme.     

On the tuning of variable piezoelectric transducer circuitry network for structural damage identification

The concept of using piezoelectric transducer circuitry with tunable inductance has been recently proposed to enhance the performance of frequency-shift-based damage identification method. While this approach has shown promising potential, a piezoelectric circuitry tuning methodology that can yield the optimal damage identification performance has not been synthesized. This research aims at advancing the state-of-the-art by exploring the characteristics of inductance tuning such that the enrichment of frequency measurements can be effectively realized to highlight the damage occurrence. Analysis shows that when the inductance is tuned to accomplish eigenvalue curve veering, the change of system eigenvalues induced by structural damage will vary significantly with respect to the change of inductance. Therefore, by tuning the inductance near the curve-veering range, one may obtain a family of frequency response functions that could effectively reflect the damage occurrence. When multiple tunable piezoelectric transducer circuitries are integrated to the mechanical structure, multiple eigenvalue curve veering can be simultaneously accomplished, and a series of inductance tunings can be formed by accomplishing curve veering between different pairs of system eigenvalues. It will then be shown that, to best characterize the damage occurrence, the favorable inductance tuning sequence should be selected as that leads to a “comprehensive” set of eigenvalue curve veering, i.e., all measurable natural frequencies undergo curve veering at least once. An iterative second-order perturbation-based algorithm is used to identify the locations and severities of the structural damages based on the frequency measurements before and after the damage occurrence. Numerical analyses on benchmark beam and plate structures have been carried out to examine the system performance. The effects of measurement noise on the effectiveness of the proposed damage identification method are also evaluated. It is demonstrated that the damage identification results can be significantly improved by using the variable piezoelectric transducer circuitry network with the favorable inductance-tuning scheme proposed in this research.     

Vibration-based damage detection and evaluation of sheet materials using a remote acoustic excitation

A simple method of damage severity assessment on sheet materials is suggested and proved by theory and experiment. The investigated defect types are in forms of added mass and crack. The method is based on the frequency shift measurement of a material vibrating as a membrane subjected to static tension and irradiated by an acoustic wave. It is shown both theoretically and experimentally that the natural frequency of the damaged membrane is shifted relative to its position in the ideal material. A local increase in thickness (or addition of mass) shifts the natural frequency down, while a crack shifts the frequency up. The method can be considered as acoustic weighting through the frequency shift. The sensitivity of this method can be high because frequency measurement is one of the most accurate measurements in physics and metrology. Published in Russian in Akusticheskiĭ Zhurnal, 2008, Vol. 54, No. 1, pp. 147–155. The text was submitted by the authors in English.     

Collisional excitation of neon-like Ni XIX using the Breit-PauliR-matrix method

Collision strength for the transition within the first five fine-structure levels in Ni XIX are calculated using the Breit-PauliR-matrix method. Configuration interaction wave functions are used to represent the target states included in theR-matrix expansion. The relativistic effects are incorporated in the Breit-Pauli approximation by including the one-body mass correction, Darwin and spin-orbit interaction terms in scattering equations.     

衰减匹配的超声Barker码激励方法

为增加超声穿透高声衰减介质的能力,提出了一种衰减匹配的超声Barker码激励方法。基于换能器高斯响应与材料非频散线性衰减的假设,得到了Barker码激励的信号模型,求解旁瓣抑制滤波后脉冲压缩的信噪比表达式可知,该方法仅需要根据材料衰减特性与轴向分辨率的要求,分别调整Barker码的中心频率与时长,便可以获得更高的信噪比。取衰减系数为1.4 Np/(MHz·cm)、厚度为5 cm的橡胶为试样进行验证。当与方波激励方法的轴向分辨率相近时,衰减匹配的Barker码激励方法比传统Barker码激励方法的信噪比增益提高接近5 dB;当牺牲一定轴向分辨率时,信噪比增益提高接近11 dB。结果表明,衰减匹配的Barker码激励方法可以降低依频率衰减对脉冲压缩的影响,有效提高衰减回波的信噪比。     

Ultrasonic Barker-coded excitation method with attenuation matching

In order to increase the ability of ultrasound to penetrate high-attenuation medium,an attenuation matching method of ultrasonic Barker-coded excitation is prop...     

GUW-based structural damage detection using WPT statistical features and multiclass SVM

Recently, guided ultrasonic waves (GUW) are widely used for damage detection in structural health monitoring (SHM) of different engineering structures. In this study, an intelligent damage detection method is proposed to be used in SHM applications. At first, GUW signal is de-noised by discrete wavelet transform (DWT). After that, wavelet packet transform (WPT) is employed to decompose the de-noised signal and the statistical features of decomposed packets are extracted as damage-sensitive features. Finally, a multiclass support vector machine (SVM) classifier is used to detect the damage and estimate its severity. The proposed method is employed for GUW-based structural damage detection of a thick steel beam. The effects of different parameters on the sensitivity of the method are surveyed. Furthermore, by comparing with some other similar algorithms, the performance of the proposed method is verified. The experimental results demonstrate that the proposed method can appropriately detect a structural damage and estimate its severity.