Chin An Tan

Modeling of Traffic Excitation for System Identification of Bridge Structures

System input (traffic excitation) is difficult to measure, so system identification is often performed based only on the system output (bridge vibration responses) in long-term health monitoring of bridge structures. Traffic excitation is commonly modeled as spatially uncorrelated white noise to facilitate the identification of the bridge properties. A physical model of a stationary stream of vehicles (moving loads) arriving in accordance with a Poisson process, traversing an elastic beam, shows that the traffic excitation is spatially correlated. Employing the dynamic nodal loading approach, this spatial correlation results in a frequency-dependent excitation spectrum density matrix, and shifts the response spectra obtained from those excited by spatially uncorrelated white noise. It is shown that the application of system identification techniques based on the conventional excitation model may result in misleading structural properties. Hence, this study further proposes an output-only gray-box identification technique for bridge structures, in which knowledge about the nature of the traffic excitation, such as its spatial correlation, is implanted into an autoregressive-moving-average (ARMA) model. The identifiability of the ARMA model so constructed is assured and the feasibility of the proposed identification technique is demonstrated by a numerical example. With the proposed physics-based excitation model and the gray-box identification technique, information collected about traffic will directly contribute to improving the identification of structural structural properties.

Dynamic Response of Battery Tabs Under Ultrasonic Welding

Ultrasonic metal welding (USMW) for battery tabs must be performed with 100% reliability in battery pack manufacturing as the failure of a single weld essentially results in a battery that is inoperative or cannot deliver the required power due to the electrical short caused by the failed weld. In ultrasonic metal welding processes, high-frequency ultrasonic energy is used to generate an oscillating shear force (sonotrode force) at the interface between a sonotrode and few metal sheets to produce solid-state bonds between the sheets clamped under a normal force. These forces, which influence the power needed to produce the weld and the weld quality, strongly depend on the mechanical and structural properties of the weld parts and fixtures in addition to various welding process parameters, such as weld frequencies and amplitudes. In this work, the effect of structural vibration of the battery tab on the required sonotrode force during ultrasonic welding is studied by applying a longitudinal vibration model for the battery tab. It is found that the sonotrode force is greatly influenced by the kinetic properties, quantified by the equivalent mass, equivalent stiffness, and equivalent viscous damping, of the battery tab and cell pouch interface. This study provides a fundamental understanding of battery tab dynamics during ultrasonic welding and its effect on weld quality, and thus provides a guideline for design and welding of battery tabs from tab dynamics point of view.

Feasibility of energy harvesting for powering wireless sensors in transportation infrastructure applications

In recent years, wireless sensors technologies are attracted many researchers in the field of structural health monitoring (SHM) of civil, mechanical and aerospace systems. Another potential application of wireless sensors is in the Vehicle-Infrastructure Integration (VII) which is an initiative by the U.S. Department of Transportation to improve road safety and reduce congestion, through as part of its Intelligent Transportation System program. However, fundamental issues remain unresolved before a broad application of the wireless SHM or VII sensor network concept is the question of sustainable power source for each independent sensor mounted on infrastructures. With a vast number of sensors nodes/networks in the infrastructure, connecting them to the grid power source is simply uneconomical in the era of wireless technology. The other option, which is providing power to each sensor from battery sources, has its own setbacks, as batteries can only provide power for a limited period, have to be replaced periodically (often difficult and costly), and their disposal creates environmental hazard. This study addresses the feasibility of energy harvesting from the ambient vibration of transportation infrastructures to power wireless sensors. Based on the vibration responses from simulation and field tests, vehicle induced vibrations on bridge and pavement were obtained and the theoretical power output from such vibration sources were computed. The expected results from this study will be demonstrated by avoiding complex wiring to the sensors by which the associated cost of wiring and batteries will be significantly reduced, and at the same time the technology can easily be deployed, meaning it is one step forward in improving the SHM and VII applications.

Dynamic Stress Analysis of Battery Tabs Under Ultrasonic Welding

Ultrasonic metal welding is widely used for joining multiple layers of dissimilar metals, such as aluminum/copper battery tabs welding onto copper busbars. It is therefore important to have a robust product/process design using ultrasonic metal welding that ensures consistent welds with desired quality. In this work, the effects of longitudinal and flexural vibrations of the battery tab during ultrasonic welding on the development of axial normal stresses that occasionally cause cracks near the weld area are studied by applying a one-dimensional continuous vibration model for the battery tab. Analysis results indicate that fracture could occur near the weld area, due to low cycle fatigue as a result of large dynamic stresses induced by resonant flexural vibration of the battery tab during welding. This study provides a fundamental understanding of battery tab dynamics during ultrasonic welding and its effects on weld quality, and can be used to develop guidelines for product/process design of ultrasonically welded battery tabs.

Dielectric Elastomer Energy Harvesting and its Application to Human Walking

Human walking requires sophisticated coordination of muscles, tendons, and ligaments working together to provide a constantly changing combination of force, stiffness and damping. In particular, the human knee joint acts as a variable damper, dissipating greater amounts of energy when the knee undergoes large rotational displacements during walking, running or hopping. Typically, this damping results from the dissipation, or loss, of metabolic energy. It has been proven to be possible however; to collect this otherwise wasted energy through the use of electromechanical transducers of several different types which convert mechanical energy to electrical energy. When properly controlled, this type of device not only provides desirable structural damping effects, but the energy generated can be stored for use in a wide range of applications. A novel approach to an energy harvesting knee joint damper is presented using a dielectric elastomer (DE) smart material based electromechanical transducer. Dielectric elastomers are extremely elastic materials with high electrical permittivity which operate based on electrostatic effects. By placing compliant electrodes on either side of a dielectric elastomer film, a specialized capacitor is created, which couples mechanical and electrical energy using induced electrostatic stresses. Dielectric elastomer energy harvesting devices not only have a high energy density, but the material properties are similar to that of human tissue, making it highly suitable for wearable applications. A theoretical framework for dielectric elastomer energy harvesting is presented along with a mapping of the active phases of the energy harvesting to the appropriate phases of the walking stride. Experimental results demonstrating the energy harvesting capability of a DE generator undergoing strains similar to those experienced during walking are provided for the purpose of verifying the theoretical results. The work presented here can be applied to devices for use in rehabilitation of patients with muscular dysfunction and transfemoral prosthesis as well as energy generation for able-bodied wearers.Copyright

A video assisted approach for structural health monitoring of highway bridges under normal traffic

Structural condition assessment of highway bridges is traditionally performed by visual inspections or nondestructive evaluation techniques, which are either slow, unreliable or detects only local flaws. Instrumentation of bridges with accelerometers and other sensors, however, can provide real-time data useful for monitoring the global structural conditions of the bridges due to ambient and forced excitations. This paper reports a video-assisted approach for structural health monitoring of highway bridges, with results from field tests and subsequent offline parameter identification. The field tests were performed on a short-span instrumented bridge. Videos of vehicles passing by were captured, synchronized with data recordings from the accelerometers. For short-span highway bridges, vibration is predominantly due to traffic excitation. A stochastic model of traffic excitation on bridges is developed assuming that vehicles traversing a bridge (modeled as an elastic beam) form a sequence of Poisson process moving loads and that the contact force of a vehicle on the bridge deck can be converted to equivalent dynamic loads at the nodes of the beam elements. Basic information of vehicle types, arrival times and speeds are extracted from video images to develop a physics-based simulation model of the traffic excitation. This modeling approach aims at circumventing a difficulty in the system identification of bridge structural parameters. Current practice of system identification of bridge parameters is often based on the measured response (or system output) only, and knowledge of the input (traffic excitation) is either unknown or assumed, making it difficult to obtain an accurate assessment of the state of the bridge structures. Our model reveals that traffic excitation on bridges is spatially correlated, an important feature that is usually incorrectly ignored in most output-only methods. A recursive Bayesian filtering is formulated to monitor the evolution of the state of the bridge. The effectiveness and viability of this video-assisted approach are demonstrated by the field results.

Chaotic Motions of a Duffing Oscillator Subjected to Combined Parametric and Quasiperiodic Excitation

The forced response of a Mathieu-Duffing oscillator subjected to a two-frequency quasiperiodic excitation is examined in the context when the ratio of the excitation frequencies is large. Numerical results are obtained by the spectral balance method and compared with those predicted by direct numerical integrations. Characteristics of the response as a frequency parameter is tuned are investigated in terms of the time histories, frequency spectra, Poincaré sections and Lyapunov exponents. It is observed that routes to chaotic motions are different for frequency ranges near the natural frequency of the linear system and near the parametric resonance frequency. It is also shown that the contribution of the small frequency component is important in the prediction of chaotic motions.

Global structural condition assessment of highway bridges by ambient vibration monitoring

Structural condition assessment of highway bridges has long been relying on visual inspection, which, however, involves subjective judgment of the inspector and detects only local flaws. Local flaws might not affect the global performance of the bridge. By instrumenting bridges with accelerometers and other sensors, one is able to monitor ambient or forced vibration of the bridge and assess its global structural condition. Ambient vibration measurement outwits forced vibration measurement in that it requires no special test arrangement, such as traffic control or a heavy shaker. As a result, it can be continuously executed while the bridge is under its normal serving condition. For short-to mid-span highway bridges, ambient vibration is predominantly due to traffic excitation, inducing the bridge to vibrate mainly in vertical direction. Based on its physical nature, traffic excitation is modeled as moving loads from the passing vehicles whose arrivals and speeds are extracted from digital video. Traffic-induced vibration provides valuable information for assessing the health of super-structure, but is less sensitive to possible seismic damage in the sub-structure. During earthquakes, bridges are excited in all directions by short-duration un-stationary ground motion, and are expected to better reveal their sub-structure integrity. Therefore, traffic-induced and ground-motion-induced ambient vibration data are treated separately in this paper for different assessment objectives, because of the different characteristics and measurability of the excitation. By continuously monitoring the ambient vibration of the instrumented bridge, its global structural conditions of both super- and sub-structures can be evaluated with possible damage locations identified, which will aid local non-destructive evaluation or visual inspection to further localize and access the damage.

Integration of traffic information in the structural health monitoring of highway bridges

Structural condition assessment of highway bridges is traditionally performed by visual inspections or nondestructive evaluation techniques, which are either slow, unreliable or detects only local flaws. Instrumentation of bridges with accelerometers and other sensors, however, can provide real-time data useful for monitoring the global structural conditions of the bridges due to ambient and forced excitations. Traditionally, videos are used for surveillance purposes and environmental monitoring of civil structures. In this paper the potential for the utilization of videos in an integrated structural health monitoring of highway bridges beyond the mentioned traditional applications are reported. Results obtained from the field tests, which were carried out on a short-span instrumented bridge, are presented. Videos of vehicles passing by, together with signals from laser beam sensors placed on the side of the bridge, were captured, and synchronized with data recordings from the accelerometers. For short-span highway bridges, vibration is predominantly due to traffic excitation. A stochastic model of traffic excitation on bridges is developed assuming that vehicles traversing a bridge (modeled as an elastic beam) form a sequence of Poisson process moving forces and that the contact force of a vehicle on the bridge deck can be converted to equivalent dynamic loads at the nodes of the beam elements. Basic information of vehicle types, arrival times and speeds are extracted from the video images to develop a physics-based simulation model of the traffic excitation. This modeling approach aims at circumventing a difficulty in the system identification of bridge structural parameters. Current practice of system identification of bridge parameters is often based on the measured response (or system output) only, and knowledge of the input (traffic excitation) is either unknown or assumed, making it difficult to obtain an accurate assessment of the state of the bridge structures. The effectiveness and viability of this video-assisted approach are demonstrated by the field results. Finally, a technique on how to integrate the weights of vehicles in the image processing algorithm is proposed.

Transfer Function Modeling of Distributed Piezoelectric Vibration Energy Harvesters

Extensive research has been conducted on vibration energy harvesting utilizing a distributed piezoelectric beam structure. A fundamental issue in the design of these harvesters is the understanding of the response of the beam to arbitrary external excitations (boundary excitations in most models). The modal analysis method has been the primary tool for evaluating the system response. However, a change in the model boundary conditions requires a reevaluation of the eigenfunctions in the series and information of higher-order dynamics may be lost in the truncation. In this paper, a frequency domain modeling approach based in the system transfer functions is proposed. The transfer function of a distributed parameter system contains all of the information required to predict the system spectrum, the system response under any initial and external disturbances, and the stability of the system response. The methodology proposed in this paper is valid for both self-adjoint and non-self-adjoint systems, and is useful for numerical computer coding and energy harvester design investigations. Examples will be discussed to demonstrate the effectiveness of this approach for designs of vibration energy harvesters.Copyright