Wireless sensor network for structural health monitoring: A contemporary review of technologies, challenges, and future direction

Abdulkarem, Mohammed; Samsudin, Khairulmizam; Rokhani, Fakhrul Zaman; Rasid, Mohd Fadlee A.

doi:10.1177/1475921719854528

Cited by 260 publications

(146 citation statements)

References 154 publications

Supporting

Mentioning

122

Contrasting

Unclassified

Order By: Relevance

“…The main aim of SHM technology is not solely detecting structural failures/deterioration, but also providing an early indication of materialistic damage. Consequently, those provided early warnings can be used to determine repair strategies before the structural damage results in failure [4], [5].…”

Section: Introductionmentioning

confidence: 99%

Using Hybrid Filter-Wrapper Feature Selection With Multi-Objective Improved-Salp Optimization for Crack Severity Recognition

2020

View full text Add to dashboard Cite

The emerging technology of Structural Health Monitoring (SHM) paved the way for spotting and continuous tracking of structural damage. One of the major defects in historical structures is cracking, which represents an indicator of potential structural deterioration according to its severity. This paper presents a novel crack severity recognition system using a hybrid filter-wrapper with multi-objective optimization feature selection method. The proposed approach comprises two main components, namely, (1) feature extraction based on hand-crafted feature engineering and CNN-based deep feature learning and (2) feature selection using hybrid filter-wrapper with a multi-objective improved salp swarm optimization. The proposed approach is trained and validated by utilizing 10 representative UCI datasets and 4 datasets of crack images. The obtained experimental results show that the proposed system enhances the performance of crack severity recognition with ≈ 37% and ≈ 31% increase in recognition average accuracy and F-measure, respectively. Also, a reduction rate of ≈ 67% is achieved in the extracted feature set with all the tested datasets compared to the conventional classification approaches using the whole set of features. Moreover, the proposed approach outperforms other approaches with classical feature selection methods in terms of feature reduction rate and computational time. It is noticed that using VGG16 learned features outperforms using the fused hand-crafted features by 17.7%, 15.9%, and 23.5% for fine, moderate, and severe crack recognition, respectively. The significance of this paper is to investigate and highlight the impact of applying multi-feature dimensionality reduction through adopting hybrid filter-wrapper with multi-objective optimization methods for feature selection considering the case study of crack severity recognition for SHM.

show abstract

Section: Introductionmentioning

confidence: 99%

Using Hybrid Filter-Wrapper Feature Selection With Multi-Objective Improved-Salp Optimization for Crack Severity Recognition

2020

View full text Add to dashboard Cite

show abstract

“…Recently, scour monitoring using structural health monitoring (SHM) has been proposed as an alternative to traditional scour measurement devices. SHM offers an alternative method for estimating the integrity of a structure during periods of flooding to infer scour, though suitable analysis of in situ parameters [11]. The use of SHM reduces the reliance on visual inspections of bridges, which can often fail to find evidence of any damage to the structure, e.g.…”

Section: Scour Detectionmentioning

confidence: 99%

Tracking bridge tilt behaviour using sensor fusion techniques

Faulkner

Wang

Huseynov

2020

J Civil Struct Health Monit

View full text Add to dashboard Cite

The resilience of the built environment to extreme weather events is fundamental for the day-today operation of our transport network, with scour representing one of the biggest threats to bridges built over flowing water. Condition monitoring of the bridge using a structural health monitoring system enhances resilience by reducing the time needed to return the bridge to normal use by providing timely information on structural condition and safety. The work presented in this report discusses use of rotational measurements in structural health monitoring. Traditionally tiltmeters (which can be a form of DC accelerometer) are used to measure rotation but are known to be affected by dynamic movements, while gyroscopes react quickly to dynamic motion but drift over time. This review will introduce gyroscopes as a complementary sensor for accelerometer rotational measurements and use sensor fusion techniques to combine the measurements from both sensors to get an optimised rotational result. This method was trialled on a laboratory scaled model, before the system was installed on an in-service single-span skewed railway bridge. The rotational measurements were compared against rotation measurements obtained using a vision-based measurement system to confirm the validity of the results. An introduction to gyroscopes, field test measurement results with the sensors and their correlation with the vision-based measurement results are presented in this article.

show abstract

“…*Due to the vast applications, the Wireless Sensor Network (WSNs) has witnessed notable considerations in recent research and development (Alemdar and Ersoy, 2010;Abdulkarem et al, 2020). The energy of the nodes is usually limited, which has to be consumed economically in order to prolong the lifetime of the network, otherwise leads to sensor voids (Fu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Progressive energy efficient least edge computation (P-ELEC) routing protocol in wireless sensor networks

al.¹

2021

Int. j. adv. appl. sci.

View full text Add to dashboard Cite

The energy of nodes in Wireless Sensor Networks (WSNs) is usually limited, which has to be consumed economically in order to prolong the lifetime of the network. The imbalanced use degrades the sensor node energy quickly and leads to sensor voids, which further cause the routing hole problem. The routing hole problem ultimately affects network performance. To solve the routing hole problem, an Energy Efficient Least Edge Computation routing protocol (ELEC) is proposed in the literature. The simulation results show that ELEC achieves nearly double network lifetime by equal energy consumption in various parts of the network as compared to other existing routing techniques such as GRACE, LEACH, and AODV-EHA. This work presents a progressive Energy Efficient Least Edge Computation (P-ELEC) routing protocol, where a cluster head percentage is incremented periodically. Incrementing the cluster head minimizes the workload of each cluster head, and in turn, enhances the lifetime of the network. The simulation result shows the prolongation of a lifetime under various scenarios and modes of operation.

show abstract

Wireless sensor network for structural health monitoring: A contemporary review of technologies, challenges, and future direction

Cited by 260 publications

References 154 publications

Using Hybrid Filter-Wrapper Feature Selection With Multi-Objective Improved-Salp Optimization for Crack Severity Recognition

Using Hybrid Filter-Wrapper Feature Selection With Multi-Objective Improved-Salp Optimization for Crack Severity Recognition

Tracking bridge tilt behaviour using sensor fusion techniques

Progressive energy efficient least edge computation (P-ELEC) routing protocol in wireless sensor networks

Contact Info

Product

Resources

About