Damage Identification in Warren Truss Bridges by Two Different Time–Frequency Algorithms

Recently, a number of authors have been focusing on drive-by monitoring methods, exploiting sensors mounted on the vehicle rather than on the bridge to be monitored, with clear advantages in terms of cost and flexibility. This work aims at further exploring the feasibility and effectiveness of novel tools for indirect health monitoring of railway structures, by introducing a higher level of accuracy in damage modelling, achieve more close-to-reality results. A numerical study is carried out by means of a FE 3D model of a short span Warren truss bridge, simulating the dynamic interaction of the bridge/track/train structure. Two kinds of defects are simulated, the first one affecting the connection between the lower chord and the side diagonal member, the second one involving the joint between the cross-girder and the lower chord. Accelerations gathered from the train bogie in different working conditions and for different intensities of the damage level are analyzed through two time-frequency algorithms, namely Continuous Wavelet and Huang-Hilbert transforms, to evaluate their robustness to disturbing factors. Compared to previous studies, a complete 3D model of the rail vehicle, together with a 3D structural scheme of the bridge in place of the 2D equivalent scheme widely adopted in the literature, allow a more detailed and realistic representation of the effects of the bridge damage on the vehicle dynamics. Good numerical results are obtained from both the two algorithms in the case of the time-invariant track profile, whereas the Continuous Wavelet Transform is found to be more robust when a deterioration of track irregularity is simulated.

Eksplorasi dan analisis kondisi perkerasan jalan pada jembatan rangka baja Soekarno-Hatta Malang pada bulan Maret 2015 menggunakan metode ground penetrating radar (GPR)

This research that purpose to explore and analyz the structure condition of pavement on the Soekarno-Hatta’s Malang truss bridge by using GPR method. GPR is used to knowing type of material objects based on dielectric constant of every materials, and to showing deformation, cracking, release structure, and water seepage. Data collected by observation techniques and retrieval of data sanples at 101 point of the track. Analysis starts from the stage of processing by using Ms.Excel, notepad, paint, software GeoScan32, and interpreted using software Surfer 9.0. The result is showing that the road pavement structure consists of a flexible pavement asphalt and rigid pavement concrete by identified the type of material is dry asphalt, wet asphalt, dry concrete, wet concrete, and air on surface. Deformation occurred in all of track pavement and there are a few sample points are experienced track surface defect such as cracks and release the structure. The most damage with average value 1.67and 1.69 that occur on the second and third of track, start from track 34-67 and 68-100. The postiton is located in point 33-66 m dan 67-99 m from Surabaya (north of bridge). Mapping result of cracking and release structure showing that 90 percent of pavement on Soekarno-Hatta’s bridge are damage. Water seepage that occur when the water breaking through the subsurface layers (asphalt) until concrete layer in base ground by content wet materal. Data distribution of pavement area that most occur water seepage on track 35-67 it’s on point 33-66 m. Penelitian ini bertujuan untuk mengeksplorasi dan menganalisis kondsi struktur lapisan perkerasan jalan pada jembatan rangka baja Soekarno-Hatta Malang dengan metode Ground Penetratig Radar (GPR). GPR digunakan untuk mengetahui jenis material objek berdasarkan konstanta dielektrik yang dimiliki setiap material, serta untuk melihat adanya defomasi, retak, pelepasan struktur, serta rembesan air. Pengumpulan data dilakukan dengan menggunakan teknik observasi lapangan dan pengambilan data sampel pada 101 titik lintasan di analisis dengan teknik deskriptif kuantitaif menggunakan Ms.Excel, notepad, paint, software GeoScan32, dan di interpretasikan dalam software Surfer 9.0. Hasil penelitian menunjukkan bahwa struktur perkerasan jalan terdiri dari perkerasan lentur aspal dan perkerasan kaku beton yang diketahui berupa lantai kendaraan dengan jenis material pada perkerasan yang dapat teridentifikasi adalah aspal kering, aspal basah, beton kering, beton basah,dan adanya udara dipemukaan. Deformasi terjadi pada semua lintasan dan di beberapa titik lintasan teridentifikasi mengalami retak dan pelepasan struktur. Kerusakan terbanyak dengan nilai rata-rata 1,67 dan 1,69 diketahui terjadi pada bagian yang kedua dan ketiga, yaitu dimulai pada lintasan ke 34-67 dan 68-100. Posisi terletak pada bentang ke 33-66 meter dan 67-99 meter dari arah Surabaya (utara jembatan). Hasil pemetaan retak dan pelepasan lapisan menunjukkan 90 persen dari perkerasan jalan pada Jembatan Soekaro-Hatta telah mengalami kerusakan. Rembesan terjadi ketika air menerobos lapisan permukaan (aspal) bagian bawah hingga menembus lapisan beton di dasar permukaan dengan indikator konten material basah. Data persebaran daerah perkerasan jalan yang banyak mengalami rembesan air terjadi pada lintasan 35-67 yaitu pada posisi bentang ke 33-66 meter.

Damage detection and characterization of a scaled model steel truss bridge using combined complete ensemble empirical mode decomposition with adaptive noise and multiple signal classification approach

This study aims to investigate the performance of a new damage detection method proposed based on the combination of two signal processing techniques which are complete ensemble empirical mode decomposition with adaptive noise and multiple signal classification (CEEMDAN-MUSIC). The proposed damage detection approach begins with determining the power density spectrum, namely, the pseudospectrum, from the acceleration response of a structure. Then, the CEEMDAN algorithm is used to decompose the vibration signal into a set of intrinsic mode functions (IMFs). Furthermore, the MUSIC algorithm is applied to the first IMF of the processed signal to determine the frequency pseudospectrum, prior to and post the damage states of the structure. The effectiveness of the proposed methodology is experimentally validated using a laboratory-scale model of a steel truss bridge exposed to a white noise excitation. The damage states of the truss bridge are implemented by replacing a specified diagonal element with reduced cross-sectional stiffness. The experimental results demonstrate the superiority of the CEEMDAN-MUSIC method in comparison with the performance of pure MUSIC and traditional frequency domain techniques. The advantages of the proposed technique are also discussed in terms of identifying the presence of the damage, addressing its location, and quantifying the damage levels which are summarized as the damage detection and characterization.