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1. Extraction of Bridge Fundamental Frequencies Utilizing a Smartphone MEMS Accelerometer

   https://doi.org/10.3390/s19143143  

   Elhattab, Ahmed; Uddin, Nasim; OBrien, Eugene (July 2019, Sensors)

   Smartphone MEMS (Micro Electrical Mechanical System) accelerometers have relatively low sensitivity and high output noise density. Therefore, it cannot be directly used to track feeble vibrations such as structural vibrations. This article proposes an effective increase in the sensitivity of the smartphone accelerometer utilizing the stochastic resonance (SR) phenomenon. SR is an approach where, counter-intuitively, feeble signals are amplified rather than overwhelmed by the addition of noise. This study introduces the 2D-frequency independent underdamped pinning stochastic resonance (2D-FI-UPSR) technique, which is a customized SR filter that enables identifying the frequencies of weak signals. To validate the feasibility of the proposed SR filter, an iPhone device is used to collect bridge acceleration data during normal traffic operation and the proposed 2D-FI-UPSR filter is used to process these data. The first four fundamental bridge frequencies are successfully identified from the iPhone data. In parallel to the iPhone, a highly sensitive wireless sensing network consists of 15 accelerometers (Silicon Designs accelerometers SDI-2012) is installed to validate the accuracy of the extracted frequencies. The measurement fidelity of the iPhone device is shown to be consistent with the wireless sensing network data with approximately 1% error in the first three bridge frequencies and 3% error in the fourth frequency. 

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2. Drive-By Bridge Frequency Identification under Operational Roadway Speeds Employing Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR)

   https://doi.org/10.3390/s18124207  

   Elhattab, Ahmed; Uddin, Nasim; OBrien, Eugene (December 2018, Sensors)

   Recently, drive-by bridge inspection has attracted increasing attention in the bridge monitoring field. A number of studies have given confidence in the feasibility of the approach to detect, quantify, and localize damages. However, the speed of the inspection truck represents a major obstacle to the success of this method. High speeds are essential to induce a significant amount of kinetic energy to stimulate the bridge modes of vibration. On the other hand, low speeds are necessary to collect more data and to attenuate the vibration of the vehicle due to the roughness of the road and, hence, magnify the bridge influence on the vehicle responses. This article introduces Frequency Independent Underdamped Pinning Stochastic Resonance (FI-UPSR) as a new technique, which possesses the ability to extract bridge dynamic properties from the responses of a vehicle that passes over the bridge at high speed. Stochastic Resonance (SR) is a phenomenon where feeble information such as weak signals can be amplified through the assistance of background noise. In this study, bridge vibrations that are present in the vehicle responses when it passes over the bridge are the feeble information while the noise counts for the effect of the road roughness on the vehicle vibration. UPSR is one of the SR models that has been chosen in this study for its suitability to extract the bridge vibration. The main contributions of this article are: (1) introducing a Frequency Independent-Stochastic Resonance model known as the FI-UPSR and (2) implementing this model to extract the bridge vibration from the responses of a fast passing vehicle. 

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3. Seismically Damaged Structure Assessment Under Subsequent Extreme Events

   https://doi.org/10.32548/RS.2018.024  

   Elsisi, Heba; Elhattab, Ahmed; Uddin, Nasim (October 2018, 27th ASNT Research Symposium)

   his article introduces a new approach for performing preliminary assessment for seismic damages and their severity by tracking the Fundamental Frequency of Damage (FFoD). Conventional damage assessment approaches monitor the global-behavior of the structure to capture anomalous structural responses. This requires for the damage to be severe enough to affect the overall structure behavior. The approach introduced in this article shifts from monitoring global structure, to monitoring the dynamic characteristics of the damage, namely the Fundamental Frequency of Damage (FFoD). The presence of structural damage will create a high-frequency oscillation, which characterizes the damage. FFoD is the frequency is of this oscillation. Identifying this oscillation is the recorded vibration is quite challenging since it often has low amplitude. To overcome this issue, the authors will utilize a new filtering technique that is capable of amplifying feeble signals by using rather than suppressing the noise, namely Underdamped Pinning Stochastic Resonance. With this filter, the signal is monitored at the FFoD to identify whether the damage present or not. A case study for a seismic moment frame is presented in this article. 

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4. Portable Bridge Weigh-In-Motion (P-B-WIM)

   Mohammed, Yahya M.; Tan, Changjun; Uddin, Nasim; Shi, Zhenhua (August 2019, th International Conference on Structural Health Monitoring of Intelligent Infrastructure)

   Bridge Weigh-in-Motion (B-WIM) is the concept of using measured strains on a bridge to calculate the axle weights of trucks as they pass overhead at full highway speed. There exist a consensus that conventional instrumentation faces substantial practical problems that halts the feasibility of this theory, namely cost, installation time and complexity. This article will go through a new concept by moving toward the first Portable Bridge Weigh-In-Motion (P-B-WIM) system. The system introduce flying sensor concept which consist of a swarm of drones that have accelerometers and able to latch bridge girders to record acceleration data. Some perching mechanisms have been introduce in this paper to allow drones to latch bridges girders. At the same time, a new algorithm is developed to allow the B-WIM system to use the acceleration data to estimate the truck weigh instead of the strain measurements. The algorithm uses the kalman-filter-based estimation algorithm to estimate the state vectors (displacement and velocities) using limited measured acceleration response (from drones). The estimated state vector is used to feed a moving force identification (MFI) algorithm that shows good results in estimating a quarter car model weight. 

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5. Extracting multiple bridge frequencies from test vehicle –a theoretical study

   https://doi.org/https://doi.org/10.1016/j.jsv.2020.115735  

   Zhenhua Shi, Nasim Uddin (September 2020, Journal of sound and vibration)

   null (Ed.)

   The coupled differential equation group for the vehicle bridge interaction system is reestablished to include both the vehicle and bridge damping effects. The equation group can be uncoupled and closed-form solutions for both the bridge and vehicle can be obtained under the assumption that the vehicle acceleration magnitude is much lower than the gravitational acceleration constant. Then based on a simply supported boundary condition scenario, several critical parameters including bridge damping, vehicle frequency, vehicle speed, vehicle mass, and vehicle damping are studied to investigate their effects on extracting multiple bridge frequencies from the vehicle. The results show that the bridge damping plays a significant role in the vibration behaviour of both the vehicle and the bridge compared to the vehicle damping. The vehicle is preferred to be designed with a high frequency beyond the interested bridge frequencies to be extracted since low vehicle frequency tends to attenuate bridge frequencies that are higher than the vehicle frequency. A camel hump phenomenon can be observed on the extracted bridge frequencies from the vehicle, especially for scenarios that involve high bridge vibration mode and high vehicle speed. Vehicle speed is preferred to be maintained low to meet the theoretical assumption and to reduce the camel hump phenomenon. Although vehicle mass is not necessarily limited in this study, there is a magnitude balance among vehicle mass, vehicle speed, and damping to meet the theoretical assumption. This theoretical work may give some indications for designing a special field test vehicle to monitor bridge in a more comprehensive way. 

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