An advanced binary slime mould algorithm for feature subset selection in structural health monitoring data

The 2022 Civil Engineering Research in Ireland (CERI) and Irish Transportation Research Network (ITRN) Conference, Dublin, Ireland, 25-26th August 2022Feature selection (FS) is an important task for data analysis, pattern classification systems, and data mining applications. In this paper, an advanced version of binary slime mould algorithm (ABSMA) is introduced for feature subset selection to enhance the capability of the original slime mould algorithm (SMA) for processing of measured data collected from monitoring sensors installed on structures. In the first step, structural response signals under ambient vibration are pre-processed according to statistical characteristics for feature extraction. In the second step, extracted features of a structure are reduced using an optimization algorithm to find a minimal subset of salient features by removing noisy, irrelevant and redundant data. Finally, the optimized feature vectors are used as inputs to the surrogate models based on radial basis function neural network (RBFNN). A benchmark dataset of a wooden bridge model is considered as a test example. The results indicate that the proposed ABSMA shows better performance and convergence rate in comparison with four well-known metaheuristic optimizations. Furthermore, it can be concluded that the proposed feature subset selection method has the capability of more than 80% data reduction.Science Foundation Irelan

On the estimation of foundation damping of mono pile-supported offshore wind turbines

This paper investigates the estimation of foundation damping in a monopile supported offshore wind turbine. The soil-structure interaction is modelled using the commercial geotechnical Finite Element (FE) software, Plaxis 3D. This allows for a more rigorous consideration of the soil response and its effect on the overall dynamic behaviour of the system. A free vibration test is simulated by applying and removing a constant horizontal static load at the top of the tower. The structure starts free vibration when the load is removed. The free decay displacement response is measured at the point of loading. The well-known logarithmic decrement method is used for the estimation of overall damping from the free decay response. The damping is estimated at different time steps along the signal to provide an instantaneous damping. It is shown that the damping varies with the amplitude of the decaying displacement response

An integrated dynamic analysis of a 5MW monopile-supported offshore wind turbine under environmental loads

The 2022 Civil Engineering Research in Ireland (CERI) and Irish Transportation Research Network (ITRN) Conference, Dublin, Ireland, 25-26th August 2022This paper investigates the dynamic behaviour of an offshore wind turbine (OWT) supported on medium dense sand using an integrated load assessment. An integrated modelling approach is introduced to allow for considering aerodynamic and hydrodynamic loading and also soil-structure interaction. A numerical model of the NREL 5MW monopile-supported OWT is initially developed in OpenFAST software. The foundation of the structure is modelled using SESAM software where soilstructure interaction is adopted using API curves and integrated to the OpenFAST model using the stiffness values at mudline level. The integrated model provides a better understanding of the structural behaviour of OWT under various environmental conditions.Irish Research Counci

Use of mode shape ratios for pier scour monitoring in two-span integral bridges under changing environmental conditions

In this paper, a novel pier scour indicator is introduced, which uses the ratio between mode shape amplitudes identified at two points on an integral bridge structure to monitor the progression of scour erosion. The Mode Shape Ratio (MSR) is investigated as an additional parameter to complement the use of changes in natural frequency as a scour indicator. The approach is demonstrated using numerical modelling and the MSR is extracted from acceleration signals arising in the structure due to modelled ambient and vehicle-induced vibrations. The MSR shows higher sensitivity to scour erosion than the more commonly researched natural frequency. Furthermore, the variation in MSR under temperature fluctuations is inversely related to that of frequency, in that it increases with increasing temperature whereas frequency decreases with increasing temperature. This inverse relationship potentially enables the separation of the scour effect from the temperature influence on the dynamics of the system

Drive-by scour monitoring of railway bridges using a wavelet-based approach

This paper numerically investigates the feasibility of using bogie acceleration measurements from a passing train to detect the presence of bridge scour. The Continuous Wavelet Transform is used to process the simulated acceleration measurements for a number of train passages over a scoured bridge, with scour represented as a local reduction in stiffness at a given pier. Average Wavelet coefficients are calculated for a batch of train runs passing over the same bridge. A scour indicator is developed as the difference in average coefficients between batches from the healthy bridge and when the bridge is damaged by scour. The method is assessed using a blind test, whereby one author simulated trains passing over a bridge in various states of health. The remaining authors were provided only with the train accelerations and had to predict the state of scour without any prior knowledge. This scour indicator performed quite well in the blind test for normal vehicle operating conditions

Experimental Demonstration of a Mode Shape-Based Scour-Monitoring Method for Multispan Bridges with Shallow Foundations

A vibration-based scour monitoring approach applicable to bridges with multiple simply supported spans on shallow foundations is experimentally investigated in this paper. A monitoring strategy based on the relative changes in pier mode shape amplitudes due to scour is postulated. The first global mode shape of a bridge structure with multiple spans is extracted from acceleration measurements using an output-only approach, Frequency Domain Decomposition (FDD). The relative changes of the pier mode shape amplitudes under scour are then tracked. Here, each pier mode shape value is compared with the mean values of the remaining piers in a process that creates a Mean-Normalised Mode Shape (MNMS). The approach is demonstrated on a scaled model of a bridge with four spans, supported on sprung foundations, where scour is simulated by the replacement of springs with springs of lower stiffness corresponding to a reduction in foundation stiffness. It is shown that at a given ‘scoured’ pier, significant increases in the MNMS value occur, suggesting that the location of the scour can be identified. The magnitude of the MNMS at a given pier also increases with an increase in stiffness loss due to scour. In practice, the approach would work best by carrying out a visual inspection of the bridge to establish the initial health condition at the time of sensor installation. After this initial process, the bridge can be monitored remotely for scour on an ongoing basis

Railway Track Monitoring Using Train Measurements: An Experimental Case Study

This paper investigates the use of drive-by train measurements for railway track monitoring. An in-service Irish Rail train was instrumented while using accelerometers and a global positioning system. The measurements were taken over two months and the train bogie accelerations from 60 passes on the Dublin-Belfast line were used for this study. A 6 km section of the line is the particular focus, where the maintenance measurements from a Track Recording Vehicle (TRV) were available. The Hilbert transform is used to obtain the instantaneous amplitudes of the acceleration signals. A new representation of the signal is proposed to show the signal energy level as a function of train location. It is shown that the forward speed of the train has a significant influence on the energy level of the signals. Therefore, a two-step speed correction is applied to the data. First, data from passes with forward speed below a certain limit are removed from the data set. Subsequently, a scaling factor is defined for the remaining signals and the energy levels of those signals are scaled while using online speed measurements. The scaled amplitudes are compared with the TRV data. It is shown that the energy levels of the signals match the TRV measurements very well

On the use of drive-by measurement for indirect bridge monitoring

Indirect bridge monitoring methods, using the responses measured from vehicles passing over bridges, are under development for about a decade. A major advantage of these methods is that they use sensors mounted on the vehicle – no sensors or data acquisition system needs to be installed on the bridge. Most of the proposed methods are based on the identification of dynamic characteristics of the bridge from responses measured on the vehicle, such as natural frequency, mode shapes and damping. In addition, some of the methods seek to directly detect bridge damage based on the interaction between the vehicle and the bridge. A critical review of indirect methods for bridge monitoring is presented and discussion and recommendations on the challenges to be overcome for successful implementation in practice are provided.A novel Short Time Frequency Domain Decomposition (STFDD) method is proposed to estimate bridge mode shapes from the dynamic response of the vehicle. In Frequency Domain Decomposition (FDD), several segments are defined on the bridge and the measurement is performed using two instrumented axles. Here, the FDD method is employed in a multi-stage procedure applied to the bridge segments in sequence. A rescaling process is used to construct the global mode shape vector. Numerical case studies are investigated using Finite Element (FE) models of vehicle bridge interaction (VBI) to validate the effectiveness and performance of the proposed method. In other indirect bridge identification methods, the road profile may excite the vehicle, making it difficult to detect the bridge modes. This is addressed using two concepts: applying external excitation to the bridge and subtracting signals in the axles of successive trailers towed by the vehicle. The results obtained from the numerical investigation demonstrate that the proposed method can estimate the bridge mode shapes with acceptable accuracy. The sensitivity of the method to added white noise is also investigated.A novel algorithm for bridge damage detection based on the mode shapes estimated from a passing vehicle is also presented. The bridge response at the moving coordinate is measured from an instrumented vehicle with laser vibrometers and accelerometers. A modified version of the Short Time Frequency Domain Decomposition (STFDD) method is applied to the measured responses. The bridge mode shapes are estimated with high resolution as is appropriate for damage detection. A damage index based on mode shape squares (MOSS) is used to detect the presence and location of the damage. A numerical case study of a half-car model passing over a bridge is described which validates the performance of the proposed approach. Several damage scenarios are considered including different locations and severities. It is shown that the presence and location of the damage can be detected with acceptable accuracy when the vehicle is moving very slowly. In addition, the performance of the method using higher vehicle speeds is investigated and shows that the approach works well for speeds up to 8 m/s. The sensitivity of the algorithm to measurement noise is also studied by adding several levels of noise to the responses measured on the vehicle.It is shown theoretically that such a response includes three main components; vehicle frequency, bridge natural frequency and a vehicle speed pseudo-frequency component. The Empirical Mode Decomposition (EMD) method is used to decompose the signal into its main components. A damage detection method is proposed using the Intrinsic Mode Functions (IMFs) corresponding to the vehicle speed component of the response measured on a passing vehicle. Numerical case studies using Finite Element modelling of Vehicle Bridge Interaction are used to show the performance of the proposed method. It is demonstrated that it can successfully localise the damage location in the absence of road profile. A difference in the acceleration signals of healthy and corresponding damaged structures is used to identify the damage location in the presence of road profile.A truck-trailer system is assumed, equipped with an external excitation at a frequency close to one of the bridge natural frequencies. The excitation makes the bridge response dominant at its natural frequency. The acceleration responses are measured on two following axles of the vehicle. It is shown that the amplitude of the signal includes the bridge mode shape data. The energy of the responses measured on two following axles is obtained using the Hilbert Huang Transform. It is shown that the bridge mode shape can be constructed with high resolution using a rescaling process. The presence of road roughness introduces additional contributions to the response measured on the vehicle, in addition to the bridge response. The concept of subtraction of the responses measured from two identical axles is used to remove the effect of road roughness

Investigating the Contact-Point Response for Drive-By Damage Detection in Bridges

The Civil Engineering Research Association of Ireland Conference 2020 (CERAI 2020), Cork, Ireland (held online due to coronavirus outbreak), 27-28 August 2020Bridges are critical elements in any road or rail transport network and ensuring their safety is paramount. Recent years have seen significant research efforts to develop cost-effective techniques for bridge monitoring on a large scale. Drive-by bridge inspection techniques, whereby sensors inside a vehicle are used to monitor bridge condition, are at the focus of much of this work. This paper develops a relationship between the measured response in a vehicle and the contact-point response between the wheel and the surface of a bridge using a quarter-car representation of the vehicle. Numerical simulations are carried out to examine the feasibility of using the contact-point response as an indicator of damage. A number of passages of the quarter-car vehicle model traversing a Finite Element representation of a bridge are simulated and the contact-point response is evaluated for each passage. Varying levels of damage are simulated in the bridge to assess whether the presence of damage can be detected by the contact-point response. Results show that the method is very effective at identifying the bridge frequencies and can also detect changes in bridge frequency with increasing damage levels. A major advantage of using the contact-point response as a damage indicator lies in its ability to detect bridge frequencies without being influenced by the vibrational frequencies of the vehicle itself. The contact-point response shows promise for implementation into drive-by bridge inspection regimes, however further work is required to investigate the feasibility of the approach at higher vehicle speeds

Examining Changes in Bridge Frequency due to Damage using the Contact-Point Response of a Passing Vehicle

Ongoing inspection and maintenance of bridges poses a challenging task for infrastructure owners who must manage large bridge stocks with limited budgets. Drive-by monitoring approaches, using sensors in a vehicle, provide a promising solution to this challenge. This paper investigates the use of the response at the point-of-contact between the tyre and the bridge as a means of monitoring bridge frequency. An expression is derived to allow the contact-point (CP) response to be inferred directly from in-vehicle measurements, expanding on previous studies by allowing the vehicle suspension characteristics to be considered. The sensitivity of the CP-response to the pavement characteristics is investigated in detail and a rigid-disk model is used to overcome issues with how existing vehicle-bridge interaction models consider the interaction between the wheel and the pavement. The feasibility of the CP-response as a measure of bridge condition is investigated and results show that the CP-response significantly outperforms the response measured directly on the vehicle. The CP-response is successful in identifying the bridge frequency and changes caused by damage, without being influenced by the vehicle frequencies. Incorporating the CP-response into drive-by bridge monitoring will improve accuracy over existing methods which use the vehicle response alone