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Structural health monitoring

About: Structural health monitoring is a research topic. Over the lifetime, 11727 publications have been published within this topic receiving 186231 citations.


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Journal ArticleDOI
TL;DR: The FBG sensors-based in situ monitoring technology can be well applied in the loess tunnel structure safety assessment and results indicate that the safety factors of various liner sections all meet the code requirements, which verify the safety and stability of the tunnel liner structure.
Abstract: Compared with electrical strain gauges, fiber Bragg grating (FBG) sensing technology is a relatively novel method for tunnel structural health monitoring, which has a number of advantages including high accuracy, multiplexing, electromagnetic interference resistance, and good repeatability. In order to study the internal force of the tunnel liner and detect the potential safety hazards, series of strain monitoring tests of a loess tunnel, taking into account the complex stress and strain variation of the loess during tunnelling, were performed by employing the tandem linear FBG sensor arrays controlled by the wavelength division multiplexing (WDM) technology. The concrete strain has obvious linear characteristics over time in the early stage and then gradually tends to a stable value. Moreover, after the necessary temperature compensation, loess tunnel structure safety was assessed through the analysis of real-time strain and internal force of the liner concrete, and the FBG monitoring data and safety assessment results indicate that the safety factors of various liner sections all meet the code requirements, which verify the safety and stability of the tunnel liner structure. The FBG sensors-based in situ monitoring technology can be well applied in the loess tunnel structure safety assessment.

99 citations

Journal ArticleDOI
TL;DR: A number of different damage detection algorithms for structural health monitoring of a typical cable-stayed bridge are investigated, comparing the viability of simplified techniques for practical applications and the relative merits and shortcomings of the damage detection methods in long-span cable-Stayed bridges.
Abstract: : This study investigated a number of different damage detection algorithms for structural health monitoring of a typical cable-stayed bridge. The Bayview Bridge, a cable-stayed bridge in Quincy, Illinois, was selected for the study. The focus was in comparing the viability of simplified techniques for practical applications. Accordingly, the numerical analysis involved development of a precise linear elastic finite element model (FEM) to simulate various structural health monitoring test scenarios with accelerometers. The Effective Independence Method was employed to locate the best distribution of the accelerometers along the length of the bridge. The simulated accelerometer data based on the FEM analysis was employed for the evaluation of the four damage identification methods investigated here. These methods included the Enhanced Coordinate Modal Assurance Criterion, Damage Index Method, Mode Shape Curvature Method, and Modal Flexibility Index Method. Some of these methods had been previously applied only to a number of specific bridges. However, the investigation here provides the relative merits and shortcomings of the damage detection methods in long-span cable-stayed bridges.

99 citations

Journal ArticleDOI
TL;DR: In this article, a multilayer data-driven framework for robust structural health monitoring based on a comprehensive application of machine learning and signal processing techniques is introduced for damage detection in a steel pipe under environmental and operational variations.
Abstract: A multilayer data-driven framework for robust structural health monitoring based on a comprehensive application of machine learning and signal processing techniques is introduced. This paper focuses on demonstrating the effectiveness of the framework for damage detection in a steel pipe under environmental and operational variations. The pipe was instrumented with piezoelectric wafers that can generate and sense ultrasonic waves. Damage was simulated physically by a mass scatterer grease-coupled to the surface of the pipe. Benign variations included variable internal air pressure and ambient temperature over time. Ultrasonic measurements were taken on three different days with the scatterer placed at different locations on the pipe. The wave patterns are complex and difficult to interpret, and it is even more difficult to differentiate the changes produced by the scatterer from the changes produced by benign variations. The sensed data were characterized by 365 features extracted from a variety of...

99 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present multiple-parameter sensing fiber optic sensors which may be embedded into roadway and bridge structures to provide an internal measurement and assessment of its health, which is paramount in determining if remedial or preventative maintenance should be performed on such structures.
Abstract: The problems associated with the application of chloride-based deicing agents to roadways and specifically bridges include chemical pollution and accelerated corrosion of strength members (especially the rebar) within the structure. In many instances, local ordnances are attempting to force state agencies to reduce, if not eliminate, the use of these chlorides (typically at the cost of increased driving hazards). With respect to the corrosion aspects of chloride application, cracks that occur in the roadway/bridge pavement allow water to seep into the pavement carrying the chloride to the rebar with the resultant increase in corrosion. In tandem with these efforts has been the continuing use of embedded fiber optic sensors for identification of faults or cracks within a highway structure - i.e., structural health monitoring. In this paper, we present multiple-parameter sensing fiber optic sensors which may be embedded into roadway and bridge structures to provide an internal measurement and assessment of its health. Such issues are paramount in determining if remedial or preventative maintenance should be performed on such structures. Laboratory results, comparisons with conventional sensing methods as well as a review of real-world issues in highway sensing are presented.

99 citations

Journal ArticleDOI
TL;DR: This paper targets to provide accurate compensation for stationary and compressible acceleration signals obtained from structural health monitoring (SHM) systems with data loss ratio below 20%.
Abstract: Lossy transmission is a common problem for monitoring systems based on wireless sensors. Reliable communication protocols, which enhance communication reliability by repetitively transmitting unreceived packets, is one approach to tackle the problem of data loss. An alternative approach allows data loss to some extent and seeks to recover the lost data from an algorithmic point of view. Compressive sensing (CS) provides such a data loss recovery technique. This technique can be embedded into smart wireless sensors and effectively increases wireless communication reliability without retransmitting the data; the promise of this approach is to reduce communication and thus power savings. The basic idea of CS-based approach is that, instead of transmitting the raw signal acquired by the sensor, a transformed signal that is generated by projecting the raw signal onto a random matrix, is transmitted. Some data loss may occur during the transmission of this transformed signal. However, according to the theory of CS, the raw signal can be effectively reconstructed from the received incomplete transformed signal given that the raw signal is compressible in some basis and the data loss ratio is low. Specifically, this paper targets to provide accurate compensation for stationary and compressible acceleration signals obtained from structural health monitoring (SHM) systems with data loss ratio below 20%. This CS-based technique is implemented into the Imote2 smart sensor platform using the foundation of Illinois Structural Health Monitoring Project Service Tool-suite. To overcome the constraints of limited onboard resources of wireless sensor nodes, a method called random demodulator (RD) is employed to provide memory and power efficient construction of the random sampling matrix. Adaptation of RD sampling matrix is made to accommodate data loss in wireless transmission and meet the objectives of the data recovery. The embedded program is tested in a series of sensing and communication experiments. Examples and parametric study are presented to demonstrate the applicability of the embedded program as well as to show the efficacy of CS-based data loss recovery for real wireless SHM systems.

99 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023600
20221,374
2021776
2020746
2019803
2018708