Utilization of wireless structural health monitoring as decision making tools for a condition and reliability-based assessment of railroad bridges

Flanigan, Katherine A.; Johnson, Nephi R.; Hou, Rui; Ettouney, Mohammed M.; Lynch, Jerome P.

doi:10.1117/12.2262933

Cited by 6 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…accelerated fatigue accumulation). 15,16 Since this behavior is not explicitly accounted for in the design process, the alignment of parallel eyebar plates is a priority for the bridge owner. This is reflected in the bridge owner’s existing inspection methods, which require inspectors to estimate eyebar tautness manually during periodic inspections.…”

Section: Harahan Bridge Monitoring Systemmentioning

confidence: 99%

“…Figure 2 presents the system instrumentation plan which includes 4 triaxial accelerometers (sampled at 200 Hz), 12 uniaxial accelerometers (sampled at 200 Hz), 8 strain gages (sampled at 200 Hz with ×500 signal gain), 1 geophone, and 1 base station (Table 1). Flanigan et al 16 present the development of an FE model of the Harahan Bridge using CSiBridge. 22 The FE model discussed herein is not used to carry out the probabilistic fatigue analysis.…”

Section: Harahan Bridge Monitoring Systemmentioning

confidence: 99%

See 1 more Smart Citation

Probabilistic fatigue assessment of monitored railroad bridge components using long-term response data in a reliability framework

Flanigan

Lynch

Ettouney³

2020

Structural Health Monitoring

Self Cite

View full text Add to dashboard Cite

Fatigue is a primary concern for railroad bridge owners because railroad bridges typically have high live load to dead load ratios and high stress cycle frequencies. However, existing inspection and post-inspection analysis methods are unable to accurately consider the full influence of bridge behavior on the fatigue life of bridge components. Reliability-based fatigue analysis methods have emerged to account for uncertainties in analysis parameters such as environmental and mechanical properties. While existing literature proposes probabilistic fatigue assessment of bridge components, this body of work relies on train parameter estimates, finite element model simulations, or controlled loading tests to augment monitoring data. This article presents a probabilistic fatigue assessment of monitored railroad bridge components using only continuous, long-term response data in a purely data-driven reliability framework that is compatible with existing inspection methods. As an illustrative example, this work quantifies the safety profile of a fracture-critical assembly comprising of six parallel eyebars on the Harahan Bridge (Memphis, TN). The monitored eyebars are susceptible to accelerated fatigue damage because changes in the boundary conditions cause some eyebars to carry a greater proportion of the total assembly load than assumed during design and analysis; existing manual inspection practices aim to maintain an equal loading distribution across the eyebars. Consequently, the limit state function derived in this article accounts for the coupled behavior between fatigue and relative tautness of the parallel eyebars. The reliability index values for both the element (i.e. individual eyebars) and system (i.e. full eyebar assembly) reliability problems are assessed and indicate that under the conservative assumption that progressive failure is brittle, first failure within the parallel eyebar system is generally equivalent to system failure. The proposed method also serves as an intervention strategy that can quantify the influence of eyebar realignment on the future evolution of the reliability index.

show abstract

Section: Harahan Bridge Monitoring Systemmentioning

confidence: 99%

Section: Harahan Bridge Monitoring Systemmentioning

confidence: 99%

Probabilistic fatigue assessment of monitored railroad bridge components using long-term response data in a reliability framework

Flanigan

Lynch

Ettouney³

2020

Structural Health Monitoring

Self Cite

View full text Add to dashboard Cite

show abstract

“…The bridge damage can be detected from the bridge bashing or concrete cracking, stiffness, damping, and mass of the bridge which changes the vibration characteristics of the bridge. A railway truss bridge on the Mississippi River was investigated (Flanigan et al, 2017) and a finite element model was prepared for this bridge and vibration frequencies were estimated. The results from modeling were compared with actual measurements.…”

Section: Introductionmentioning

confidence: 99%

Bridge vibration energy harvesting for wireless IoT-based structural health monitoring systems: A review

Ahmad

Khan

2023

Journal of Intelligent Material Systems and Structures

View full text Add to dashboard Cite

Vibration energy has the advantage of abundant availability in the environment of the bridge structure due to consistent traffic flow and high-speed wind blowing. The vibration energy present at the bridge site can be harvested for powering the wireless sensors mounted on the bridge for health monitoring and making the system self-powered. The bridge vibrations are usually low frequency and low acceleration excitations, therefore, its transduction to useful electrical energy is a challenge. However, several techniques are being utilized to harvest the bridge vibration and a variety of bridge energy harvesters are being developed for this purpose. This work has reviewed energy harvesters claimed to be designed for bridge vibrations. The study is split into two categories, first section discusses the energy harvesters developed for bridge vibrations tested only in-lab environments. The second section is about the harvesters that have been characterized on real bridge structures to verify their effectiveness. The study reveals that the bridge energy harvesters can extract enough power to operate the wireless sensors for the health monitoring of bridge structures. Moreover, the architecture, fabrication, input excitation, and output performance of the reported harvesters with modeling techniques are discussed.

show abstract

“…Therefore, in order to harvest energy effectively from low frequency environment, another harvesting technique, which is widely used is frequency-upconversion (FUC) method. The energy output is Low Frequency RT11 Postdam bridge (USA) 3.1 [10] Pershagen bridge (Sweden) 7.8 0.072 [11] Pioneer bridge (Singapore) 5.47-29.33 0.025 [12] SB-A1 bridge (USA) 6.39 0.23 [13] North Highway bridge (France) 3.9-14.5 0.059 [14] SB-C-1 bridge (USA) 4.82 0.13 [13] Ypsilanti bridge (USA) 2-30 0.001-0.0035 [15] Skidträsk bridge (Sweden) 3.8-4.5 0.005 [16] Chulitana river bridge (USA) 2-45 0.023 [17] Komtur bridge (Germany) 2-2.6 [18] Porto bridge (Portugal) 0.7-4.6 [19] Harahan bridge (USA) 0.679-1.5 [20] B15 bridge (Belgium) 1.88-8.93 [21] 3rd Nongro bridge (Korea) 2.74-4.10 0.025 [22] Golden Gate bridge (USA) 0-1.5 0.061 [23] Medium Frequency Clothes dryer 59 0.43 [24] Diesel engine (4-stroke) 50 2.19 [25] Steam turbo generator (250 MW) 50 5.4 [26] Household, 5.25 kVA electrical generator (New)…”

Section: Introductionmentioning

confidence: 99%

Review of frequency up‐conversion vibration energy harvesters using impact and plucking mechanism

Ahmad

Khan

2021

Int J Energy Res

View full text Add to dashboard Cite

One of the main challenges in the field of vibration energy harvesting is to extract energy from the low-frequency ambient vibrations. Since the voltage and power production in vibration energy harvesters depends on the relative velocity (frequency), therefore, comparatively high power levels are produced at a high frequency of vibrations. For low-frequency excitation of the base, technique such as frequency up-conversion (FUC) is widely utilised. In FUC method, a very low-frequency vibration is efficiently harvested using the plucking mechanism. FUC harvesters are comprised of a low-frequency mechanism (primary system) and a high-frequency mechanism (secondary system), which are either coupled operationally through freely moving mass, mechanical plucking, magnetic plucking or mechanical impact. The mechanical contact plucking or magnetic plucking mechanism is used for exciting a secondary system that has a much higher frequency for efficiently harvesting more energy. This work provides a detailed review of the FUC energy harvesters that are utilising freely moving mass, plucking mechanism and mechanical impact techniques reported in the literature. Information about the harvesters' architecture, working, fabrication and output performance is performed with an emphasis on input low frequency, input acceleration, converted high frequency, voltage generation, power levels and power density values reported in the literature. Moreover, all techniques developed for low-frequency vibration applications are compared and the effectiveness of each mechanism used for low-frequency energy harvesting is discussed.

show abstract

Utilization of wireless structural health monitoring as decision making tools for a condition and reliability-based assessment of railroad bridges

Cited by 6 publications

References 10 publications

Probabilistic fatigue assessment of monitored railroad bridge components using long-term response data in a reliability framework

Probabilistic fatigue assessment of monitored railroad bridge components using long-term response data in a reliability framework

Bridge vibration energy harvesting for wireless IoT-based structural health monitoring systems: A review

Review of frequency up‐conversion vibration energy harvesters using impact and plucking mechanism

Contact Info

Product

Resources

About