A damage detection algorithm integrated with a wireless sensing system

Hsu, Ting-Yu; Huang, Shieh‐Kung; Lu, Kung-Chun; Loh, Chin‐Hsiung

doi:10.1088/1742-6596/305/1/012042

Cited by 6 publications

(3 citation statements)

References 18 publications

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“…Tran-Ngoc et al [21] proposed a hybrid metaheuristic algorithm approach to overcome the limitations of genetic algorithms, and used an improved cuckoo search technique for solving optimization issues and damage detection in a bridge structure. Hsu et al [22] studied the vibration response of a building structure using a wireless sensor for damage localization and quantification in a building structure. Feng et al [23] compared transmissibility function and cross-correlation analysis for damage detection in a tunnel structure, and proposed using both approaches for validation of the results.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Structural Health Monitoring and Damage Identification Using Frequency Response Functions along with Finite Element Model Updating Technique

Singh

Sehgal

Prakash

et al. 2022

Sensors

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Throughout service, damage can arise in the structure of buildings; hence, their dynamic testing becomes essential to verify that such buildings possess sufficient strength to withstand disturbances, particularly in the event of an earthquake. Dynamic testing, being uneconomical, requires proof of concept; for this, a model of a structure can be dynamically tested, and the results are used to update its finite element model. This can be used for damage detection in the prototype and aids in predicting its behavior during an earthquake. In this instance, a wireless MEMS accelerometer was used, which can measure the vibration signals emanating from the building and transfer these signals to a remote workstation. The base of the structure is excited using a shaking table to induce an earthquake-like situation. Four natural frequencies have been considered and six different types of damage conditions have been identified in this work. For each damage condition, the experimental responses are measured and the finite element model is updated using the Berman and Nagy method. It is seen that the updated models can predict the dynamic responses of the building accurately. Thus, depending on these responses, the damage condition can be identified by using the updated finite element models.

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Section: Introductionmentioning

confidence: 99%

Real-Time Structural Health Monitoring and Damage Identification Using Frequency Response Functions along with Finite Element Model Updating Technique

Singh

Sehgal

Prakash

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Also, centralized computational systems can become inoperable due to degradation of system components or loss of power during a natural hazard. In the past decade, researchers have given significant attention to the use of wireless data acquisition for structural health monitoring and control applications in lieu of wired methods . Wireless control improves upon tethered control in terms of cost and its inherent decentralized nature can improve reliability during disasters, but it introduces issues related to centralizing data for computations, reliability of data communication, and limited power to the wireless technology often supplied by batteries.…”

Section: Introductionmentioning

confidence: 99%

Wireless structural control using multi‐step TDMA communication patterning bandwidth allocation

Winter

Swartz

2017

Struct Control Health Monit

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As the number of sensors in a control network grows, it becomes increasingly difficult to transmit all sensor data during a single control step over the fixed wireless bandwidth. Because control force calculations rely on accurate state measurements or estimates, the use of staggered data communication may become necessary. It is not uncommon that a single sensor may be the only measurement source for an important section of a structure. This paper presents a means of selecting and evaluating different communication group sizes and wireless unit combinations for staggered communication that still provide information for highly accurate state estimates. Within each wireless unit, multiple estimator gains are stored on-board to perform state-estimation calculations using staggered data that may be received from different combinations of units. It is found that, in staggered communication schemes, state estimation and control performance are affected by the network topology used at each time step with some sensor combinations providing more useful information than others. Sensor placement theory is used to form sensor groups that provide consistently high-quality output information to the network over multiple time steps, so as to strategically report data from all sensors.

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“…To overcome the high cost for cable installation often associated with wired networks, the use of wireless technology has been gaining popularity research communities for civil engineering applications in the areas of damage detection and localization, health monitoring, parameter estimation, and structural control . Wireless control eliminates wiring and with some technology can effectively transmit data between nodes in a structure, and with clear line of sight, some systems transmit data up to a kilometer away .…”

Section: Introductionmentioning

confidence: 99%

Wireless structural control using stochastic bandwidth allocation and dynamic state estimation with measurement fusion

Winter

Swartz

2017

Struct Control Health Monit

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Summary Wireless sensor networks are becoming more popular for structural monitoring because of their low installation costs; in addition, coupling structural control with wireless data acquisition can also yield advantages. However, these systems have limited communication bandwidth, limiting their effectiveness as the number of devices in control networks grows large if centralized control approaches are used. Traditional methods for collocating data in wireless structural control network rely on time‐budgeted bandwidth or spatial decentralization, where the network is divided into smaller subnetworks. These methods are largely static and typically do not take into account any measure of data quality to prioritize transmissions. This study presents a dynamic approach for bandwidth allocation in wireless structural control networks that relies on an application‐specific, autonomous, and controller‐aware, carrier sense multiple access with collision detection protocol. Stochastic parameters are derived to strategically alter back‐off times in the carrier sense multiple access with collision detection algorithm based on nodal observability and output estimation error. Inspired by data fusion approaches, this paper presents 2 different methods for neighborhood state estimation using a dynamic form of measurement‐only fusion. Upon receiving data from the contended wireless medium, each wireless unit fuses incoming data using a precalculated static Kalman gain matrix for the corresponding dynamic neighborhood. Onboard, each wireless unit contains a library of Kalman gain matrices, to accommodate any possible set of communicated data. Both numerical simulations and small‐scale laboratory experimental results are presented.

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A damage detection algorithm integrated with a wireless sensing system

Cited by 6 publications

References 18 publications

Real-Time Structural Health Monitoring and Damage Identification Using Frequency Response Functions along with Finite Element Model Updating Technique

Real-Time Structural Health Monitoring and Damage Identification Using Frequency Response Functions along with Finite Element Model Updating Technique

Wireless structural control using multi‐step TDMA communication patterning bandwidth allocation

Wireless structural control using stochastic bandwidth allocation and dynamic state estimation with measurement fusion

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