Scour Monitoring System Research Articles

Monitoring-based adaptive water level thresholds for bridge scour risk management

Riverbed scour is the leading cause of bridge failure worldwide. Recent developments in sensor technology for structures have resulted in more bridges being instrumented and monitored. However, alongside scour monitoring systems, there is a need of techniques to handle the data obtained and exploit them to inform the management of the bridge scour risk. This paper illustrates the development of a decision support system (DSS) for bridge scour risk management, which is based on a probabilistic framework for scour risk estimation, enhanced by real-time information from scour monitoring systems and in line with current risk procedures used by transport agencies. The proposed DSS provides bridge operators with adaptive measurement-informed water level thresholds triggering bridge closure to traffic under heavy floods. The application of the DSS is illustrated by considering a case study of three bridges at risk of scour managed by Transport Scotland. It is shown that information from scour sensors within the proposed DSS allows reducing the uncertainty in the scour estimates and yields adaptive water level thresholds triggering bridge closure to traffic that can differ significantly from those currently considered by transport agencies. This can ultimately result in a reduction of false alarms and unnecessary bridge closures.

The Growing Infrastructure Crisis: The Challenge of Scour Risk Assessment and the Development of a New Sensing System

Scour action is one of the main factors that add significant stress to the growing infrastructure crisis as it is considered one of the most destructive flood-related hazards occurring around underwater foundation elements. Recent cases of bridge failures have highlighted the need for a reliable scour monitoring and early warning system to assess flood and geo-hazards in real-time, providing advanced key info for repair and maintenance actions. Despite the past efforts to provide such a system for scour assessment, most of the developed instruments were not able to offer a reliable solution for scour monitoring, due to technical and cost issues. As a result, there currently exists a gap in the knowledge and understanding of scour mechanism during flood incidents. This study presents the development of a new sensing system to assess hydro-hazards at bridge infrastructure. It initially focuses on factors contributing to the growing infrastructure crisis and provides an overview of the current practices and assessment procedures to assess scour processes and a summary of advantages and limitations of existing monitoring efforts. A new monitoring concept for assessing scour and sediment deposition processes is then presented focusing on modelling the geometric components of a new sensor which is evaluated in simulations under different environments that represent prospective field conditions. Main results are analysed and presented focusing on key criteria that maximize sensitivity of the sensor to scour and sedimentation processes. The obtained results indicate that the sensor has the potential to provide a new monitoring device for scour and sediment deposition monitoring, and it is proposed to be further developed and assessed in laboratory and field conditions. This study aspires to contribute to the ongoing discourse on the use of sensing techniques to monitor, assess, and manage scour action effectively.

The Artificial Intelligence of Things Sensing System of Real-Time Bridge Scour Monitoring for Early Warning during Floods.

Scour around bridge piers remains the leading cause of bridge failure induced in flood. Floods and torrential rains erode riverbeds and damage cross-river structures, causing bridge collapse and a severe threat to property and life. Reductions in bridge-safety capacity need to be monitored during flood periods to protect the traveling public. In the present study, a scour monitoring system designed with vibration-based arrayed sensors consisting of a combination of Internet of Things (IoT) and artificial intelligence (AI) is developed and implemented to obtain real-time scour depth measurements. These vibration-based micro-electro-mechanical systems (MEMS) sensors are packaged in a waterproof stainless steel ball within a rebar cage to resist a harsh environment in floods. The floodwater-level changes around the bridge pier are performed using real-time CCTV images by the Mask R-CNN deep learning model. The scour-depth evolution is simulated using the hydrodynamic model with the selected local scour formulas and the sediment transport equation. The laboratory and field measurement results demonstrated the success of the early warning system for monitoring the real-time bridge scour-depth evolution.

Machine Learning Solutions for Bridge Scour Forecast Based on Monitoring Data

Bridge scour is a challenge throughout the U.S.A. and other countries. Despite the scale of the issue, there is still a substantial lack of robust methods for scour prediction to support reliable, risk-based management and decision making. Throughout the past decade, the use of real-time scour monitoring systems has gained increasing interest among state departments of transportation across the U.S.A. This paper introduces three distinct methodologies for scour prediction using advanced artificial intelligence (AI)/machine learning (ML) techniques based on real-time scour monitoring data. Scour monitoring data included the riverbed and river stage elevation time series at bridge piers gathered from various sources. Deep learning algorithms showed promising in prediction of bed elevation and water level variations as early as a week in advance. Ensemble neural networks proved successful in the predicting the maximum upcoming scour depth, using the observed sensor data at the onset of a scour episode, and based on bridge pier, flow and riverbed characteristics. In addition, two of the common empirical scour models were calibrated based on the observed sensor data using the Bayesian inference method, showing significant improvement in prediction accuracy. Overall, this paper introduces a novel approach for scour risk management by integrating emerging AI/ML algorithms with real-time monitoring systems for early scour forecast.

Assessing the suitability of bridge-scour-monitoring devices

Bridge scour is a complex bridge-management problem. It is also a difficult forensic engineering challenge, as the greatest risk occurs during large flows and flood events, when visual inspection of the bridge piers is often not possible. This paper presents a review of scour prediction and modelling methods, whose results are used to determine the key parameters that scour-monitoring systems need to capture. Then, a review of existing monitoring approaches and technologies for scour monitoring is presented. The paper concludes with the proposal of a novel rating system for evaluating different scour-monitoring techniques. The new rating system is trialled ex-post for seven previously published bridge-scour-monitoring case studies to illustrate the use of the new methodology.

Using Bayesian networks for the assessment of underwater scour for road and railway bridges

Flood-induced scour is among the most common external causes of bridge failures worldwide. In the United States, scour is the cause of 22 bridges fails every year, whereas in the UK, it contributed significantly to the 138 collapses of bridges in the last century. Scour assessments are currently based on visual inspections, which are time-consuming and expensive. Nowadays, sensor and communication technologies offer the possibility to assess in real time the scour depth at critical bridge locations; yet, monitoring an entire infrastructure network is not economically feasible. A way to overcome this limitation is to instal scour monitoring systems at critical bridge locations, and then extend the piece of information gained to the other assets exploiting the correlations present in the system. In this article, we propose a scour hazard model for road and railway bridge scour management that utilises information from a limited number of scour monitoring systems to achieve a more confined estimate of the scour risk for a bridge network. A Bayesian network is used to describe the conditional dependencies among the involved random variables and to update the scour depth distribution using data from monitoring of scour and river flow characteristics. This study constitutes the first application of Bayesian networks to bridge scour risk assessment. The proposed probabilistic framework is applied to a case study consisting of several road bridges in Scotland. The bridges cross the same river, and only one of them is instrumented with a scour monitoring system. It is demonstrated how the Bayesian network approach allows to significantly reduce the uncertainty in the scour depth at unmonitored bridges.

Applicability and limitations of time domain reflectometry bridge scour monitoring system in general field conditions

A real-time and durable system for scour process monitoring with sufficient spatial precision is in pressing need for bridge safety management. In light of this, an innovative bundled time domain reflectometry sensing cable was recently proposed to enhance the time domain reflectometry technique for scour monitoring. However, current development only dealt with the construction of bundled sensing cable and the corresponding new data reduction method. Before it can be put into practical use, issues related to the effect of hydrological conditions, long-distance measurement, and actual field implementation are yet to be investigated. This study used both numerical simulations and laboratory experiments to examine the time domain reflectometry signals in response to both scour and deposition in different water-level conditions. As a result, the first guideline of waveform classification and interpretation is newly proposed to validly determine scour depth under various field conditions. Since field measurements often come with significant signal attenuation from resistance loss of long cable and dielectric and conductive loss in the sensing section, numerical simulations and a series of full-scale experiments were also conducted to assess the time domain reflectometry scour measurement range. The maximum measurement range of the latest time domain reflectometry scour sensing cable was found to be about 6 m. Within this range, the maximum error of scour estimation is within 0.2 m. Considering the new findings, a field time domain reflectometry scour monitoring system using the bundled time domain reflectometry sensing cable was designed accordingly and implemented at a bridge for the first time. The monitoring system successfully captured the scour process during a storm event and revealed some practical issues for future improvement as well.

Electromagnetic Sensors for Underwater Scour Monitoring

Scour jeopardises the safety of many civil engineering structures with foundations in riverbeds and it is the leading cause for the collapse of bridges worldwide. Current approaches for bridge scour risk management rely mainly on visual inspections, which provide unreliable estimates of scour and of its effects, also considering the difficulties in visually monitoring the riverbed erosion around submerged foundations. Thus, there is a need to introduce systems capable of continuously monitoring the evolution of scour at bridge foundations, even during extreme flood events. This paper illustrates the development and deployment of a scour monitoring system consisting of smart probes equipped with electromagnetic sensors. This is the first application of this type of sensing probes to a real case-study for continuous scour monitoring. Designed to observe changes in the permittivity of the medium around bridge foundations, the sensors allow for detection of scour depths and the assessment of whether the scour hole has been refilled. The monitoring system was installed on the A76 200 Bridge in New Cumnock (S-W Scotland) and has provided a continuous recording of the scour for nearly two years. The scour data registered after a peak flood event (validated against actual measurements of scour during a bridge inspection) show the potential of the technology in providing continuous scour measures, even during extreme flood events, thus avoiding the deployment of divers for underwater examination.

Design and Implementation of Realtime Scour Monitoring of Hangzhou Bay Sea-Crossing Bridge Pier Based on Dual-Axis Scanning Sonar

This paper introduces the design and implementation of the realtime scour monitoring system for piers of Hangzhou Bay Sea-Crossing Bridge, including the construction of the monitoring system for the scour of the piers and the key technologies of the monitoring system. Through integration of dual axis scanning sonar technology and monitoring software, real-time seabed topography observation, data processing, analysis and data release based on the Internet is realized, qualitative, quantitative and locational decision support for management departments is provided.

Visible Light Communication System for Offshore Wind Turbine Foundation Scour Early Warning Monitoring

Offshore wind farms have a superior wind source to terrestrial wind farms, but they also face more severe environmental conditions such as severe storms, typhoons, and sea waves. Scour leads to the excavation of sediments around the foundations of structures, reducing the safe capacity of the structures. The phenomenon of pier scour is extremely complex because of the combined effects of the vortex system involving time-dependent flow patterns and sediment transport mechanisms. A real-time scour monitoring system can improve the safety of structures and afford cost-effective operations by preventing premature or unnecessary maintenance. This paper proposes an on-site scour monitoring system using visible light communication (VLC) modules for offshore wind turbine installations. A flume experiment revealed that the system was highly sensitive and accurate in monitoring seabed scour processes. This arrayed-VLC sensory system, proposed in this paper, has considerable potential for safety monitoring and also can contribute to improving the accuracy of empirical scour formulas for sustainable maintenance in the life cycle of offshore structures.

Densely distributed and real-time scour hole monitoring using piezoelectric rod sensors

This study aims to validate a piezoelectric driven-rod scour monitoring system that can sense changes in scour depth along the entire rod at its instrumented location. The proposed sensor is a polymeric slender rod with a thin strip of polyvinylidene fluoride that runs through its midline. Extraction of the fundamental frequency allows the direct calculation of the exposed length (or scour depth) of the slender rod undergoing fluid flow excitation. First, laboratory validation in dry conditions is presented. Second, hydrodynamic testing of the sensor system in a soil-bed flume is discussed. Each rod was installed using a three-dimensional-printed footing designed for ease of installation and stabilization during testing. The sensors were installed in a layout designed to capture symmetric scour conditions around a scaled pier. In order to analyze the system out of steady-state conditions, water velocity was increased in stages during testing to induce different degrees of scour. As ambient water flow excited the portion of the exposed rods, the embedded piezoelectric element outputted a time-varying voltage signal. Different methods were then employed to extract the fundamental frequency of each rod, and the results were compared. Further testing was also performed to characterize the relationship between frequency outputs and flow velocity, which were previously thought to be independent. In general, the proposed driven-rod scour monitoring system successfully captured changing frequencies under varied flow conditions.

Design a bridge scour monitoring system by pressing the fiber Bragg grating with a rolling pulley mechanism

In this paper, we design an optical fiber sensor based on fiber Bragg grating (FBG) for real-time bridge scour monitoring. The sensing element of the FBG is embedded in the silicone rubber, and the two ends of the rubber are fixed on the metal plate. The pulley has a circumference of 0.2 m and will drive the threaded screw, has a pitch of 1 mm, forward to press the rubber. When the rubber is pressed by the threaded screw, we can measure the reflection central wavelength shift from FBG sensor to obtain the scour depth. Bridge scour is one of the main causes of bridge failures that is resulted by the interaction of flood water and soil-structure at the bottom of the river. Monitoring scour is very important to ensure the continued safe operation of the bridge traffic and the passing through person’s life and property. A prototype of temperature-insensitive scour sensing system was designed and fabricated to test its sensing characteristics in the laboratory. The design criterion of scour sensor is to achieve the highest sensing pier scour depth of ≥ 4 m. The robust experimental results prove that the proposed system will ensure the effectiveness and feasibility in the field.

A Study on the Development of Scour Monitoring System Using TDR

Scour is a critical factor that affects the stability of a bridge. This paper presents a fundamental study on the development of a Time Domain Reflectometry (TDR) system for monitoring scour around a bridge pier. The laboratory experiments were conducted using a small-scale model pier with inner and outer diameters of 70 and 75 mm, respectively and a height of 200 mm. The model pier was embedded in a soil tank. Electrodes were installed in a circular array alongside the model pier to configure two-conductor transmission lines. Electromagnetic waves were generated and detected using the TDR. The experimental results indicate that the round-trip travel time of the electromagnetic waves increase with an increase in the scour depth. In addition, the estimated scour depth is approximately the same as the actual depth. This study demonstrates that the TDR is an effective tool for monitoring scour. Keywords: Bridge, Electromagnetic Wave, Scour, Time Domain Reflectometry

Prediction of Bridge Pier Scour Depth and Field Scour Depth Monitoring

In practice, it is a major challenge in real-time simulation and prediction of bridge pier scour depth, especially using 3-D numerical model. The simulation time spend too much to use 3-D numerical model simulation and inefficiently to predict bridge pier scour depth in real-time. With heavy rainfall during flood season in Taiwan, abundant sediment with flash flood from upstream watershed is transported to downstream river reaches and transportation time is limited within one day. The flood flow tends to damage bridge structures and affect channel stabilization in fluvial rivers. In addition, the main factors affecting the erosional depth around bridge piers and river bed stabilization are hydrological and hydrographic characteristics in river basin, the scouring and silting of river bed section near the bridge piers, the bridge geometry and protection works of bridge piers. Therefore, based on the observed rainfall data provided by the Central Weather Bureau and the hydrological conditions provided by the Water Resources Agency during flood event as the boundary condition, we develop an effective simulation system for scour depth of bridge piers. The scour depth at the bridge pier is observed by the National Center for Research on Earthquake Engineering for model calibration. In this study, an innovative scour monitoring system using vibration-based Micro-Electro Mechanical Systems (MEMS) sensors was applied. This vibration-based MEMS sensor was packaged inside a stainless sphere with the proper protection of the full-filled resin, which can measure free vibration signals to detect scouring/deposition processes at the bridge pier. It has demonstrated that the measurement system for monitoring bridge scour depth evolution is quite successful in the field.

Scour Monitoring System Using Fiber Bragg Grating Sensors and Water-Swellable Polymers

Scour Monitoring System Using Fiber Bragg Grating Sensors and Water-Swellable Polymers

Field Application of an Innovative Bridge Scour Monitoring System with Fiber Bragg Grating Sensors

AbstractBridge scour has attracted enormous attention because of its catastrophic influence on bridge safety. In order to measure and monitor scour depth variations including deposition process, a scour monitoring system was developed in the authors’ previous study. An instrument with fiber Bragg grating (FBG) sensors was designed together with a reliable sensor-protection measure, of which the performance has been tested in the laboratory. In the present paper, the proposed system was applied on a field bridge with a critical scour history. Two test piles were manufactured and each was assembled with six standard 0.9 m-long (3 ft-long) segments. The two test piles were then installed beside two foundation piles of the field bridge, respectively, for long-term monitoring. Up until now, the measured sensor responses have verified the functionality of the proposed system. The estimated scour depths based on the sensor data to date match qualitatively well with the actual scour depths observed on the bridge ...

Development of a real-time scour monitoring system for bridge safety evaluation

The fact that hydraulic problems are major factors in bridge collapse has made bridge scour monitoring an important research topic. In view of the complex nonlinear behavior of bridge structure/soil/water interactions, the fundamental frequency of the bridge may gradually change as the height of the bed drops during scour. With an insufficient embedded depth, the bridge may collapse or sink unexpectedly without warning. As experimental investigation in past research has shown that bridge failure may be governed by rigid body motion, a real-time bridge scour monitoring system to distinguish the influence of rigid body motion from the vibration frequency of the bridge is proposed. The signal measured from the superstructure of the bridge is decomposed into a structural vibration set controlling the fundamental frequency change and a rigid body motion set controlling the rigid body motion, and an instability index to examine the safety condition of the bridge is further proposed. Following a successful preliminary single-pile scour experiment, the method is applied to a series of full-bridge testing. According to analysis result, the instability index deviated considerably from its original range before the bridge piles began tilting significantly, allowing an early warning alert for bridge safety evaluation.

Design and evaluation of a high sensitivity spiral TDR scour sensor

Bridge scour accounts for more than half of the reported bridge failures in the United States. Scour monitoring technology based on time domain reflectometry (TDR) features the advantages of being automatic and inexpensive. The senior author’s team has developed a few generations of a TDR bridge scour monitoring system, which have succeeded in both laboratory and field evaluations. In this study, an innovative spiral TDR sensor is proposed to further improve the sensitivity of the TDR sensor in scour detection. The spiral TDR sensor is made of a parallel copper wire waveguide wrapped around a mounting rod. By using a spiral path for the waveguide, the TDR sensor achieves higher sensitivity than the traditional straight TDR probes due to longer travel distance of the electromagnetic (EM) wave per unit length in the spiral probe versus traditional probe. The performance of the new TDR spiral scour sensor is validated by calibration with liquids with known dielectric constant and wet soils. Laboratory simulated scour-refilling experiments are performed to evaluate the performance of the new spiral probe in detecting the sediment–water interface and therefore the scour-refill process. The tests results indicate that scour depth variation of less than 2 cm can be easily detected by this new spiral sensor. A theory is developed based on the dielectric mixing model to simplify the TDR signal analyses for scour depth detection. The sediment layer thickness (directly related to scour depth) varies linearly with the square root of the bulk dielectric constant of the water–sediment mixture measured by the spiral TDR probe, which matches the results of theoretical prediction. The estimated sediment layer thickness and therefore scour depth from the spiral TDR sensor agrees very well with that by direct physical measurement. The spiral TDR sensor is four times more sensitive than a traditional straight TDR probe.

BP neural network recognition algorithm for scour monitoring of subsea pipelines based on active thermometry

Scour monitoring is an important concern for subsea pipeline systems. The active-thermometry-based scour monitoring is based on the difference of heat transfer properties between sediment and sand, recognizes the surrounding media though temperature changing patterns during heating and cooling processes, and hence detects the free spans. Based on the scour monitoring system, a two-layer BP neural network was employed to process the monitoring data and achieved media recognition. The network's inputs were normalized temperature time histories. The network's outputs denoted different media: sediment and water. To validate the method, three experiments were conducted; one was used for training the network and the other two for testing. Also, the effect of noise on the network's performance was studied through simulation. The results demonstrated the feasibility and robustness of the neural network.

Pier scour monitoring system by bed-level image tracking

A scour monitoring system with a micro camera tracking the bed-level images is proposed in this study. Two image recognition algorithms have been developed to support the bed-level image tracking approach. Through the laboratory experiments of pier scour, this study demonstrates that the proposed system is able to accurately monitor the scour-depth evolution in real time. In addition, five commonly-used temporal scour models are employed to simulate scour-depth evolution and their results are compared with monitoring data. In general, the results indicate that the proposed scour monitoring system has the potential for further applications in the field.