LCR Meter Research Articles

Enhancement of microstructure characteristic and dielectric constant of BaMn0.05Ti0.95O3 ceramics

Barium Titanate or BaTiO3, a ferroelectric material with good dielectric properties, is widely studied. The performance of BT is influenced by synthesis and doping. Here, Barium Titanate has been doped with Manganese via the co-precipitation procedure sintered at 900°C and 1000°C. The purposes of this study were to examine the microstructure and dielectric constant of BaMn0.05Ti0.95O3 with variation sintering temperatures at 900°C and 1000°C. The testing employed X-Ray Diffraction (XRD), Fourier Transform Infrared (FTIR), and Resistance Capacitance Inductance (LCR Meter). The XRD data exposed that the crystal size of the BaMn0.05Ti0.9503 sample enlarged from 48.27 nm to 72.41 nm with increasing sintering temperature. The analysis results using FTIR exhibited the existence of Ba-O and Ti-O bonds which confirmed the perovskite structure of BaTiO3. FTIR data also indicated the presence of C-H atomic bonds, which is the peak of impurities in the carbonate phase. The C-H bond vibration decreased at the higher sintering temperature. The dielectric constant value was obtained from the measurements using an LCR meter. In conclusion, increasing the sintering temperature improved the dielectric constant of BaMn0.05Ti0.95O3 from 119 to 386.

Synthesis, structure, and improved frequency-dependent transport properties of copper doped zinc oxide nanoparticles at high temperatures

The nanostructures of ZnO are studied in this research utilizing a simple, eco-friendly, and cost-effective co-precipitation have a formula Zn 1 − x Cu ( x ) O with (x = 0.0, 0.03, 0.06, and 0.10). The effects of copper (Cu) doping on structure, morphology, impedance, dielectric, and electrical conductivity were investigated using an XRD, SEM, and LCR meter, respectively. All prepared samples have a hexagonal wurtzite structure, and the average crystalline size varies between 46 and 56 nm, according to the XRD spectra. Impedance measured data analyzes that a capacitance phase element perfectly modulates the fabricated samples with the equivalent circuits. Depending on the temperature, the examination of complex impedance and complex electrical modulus revealed a non-Debye types relaxation process. The Arrhenius plots for the conduction mechanism were used to investigate single activation energy. A correlated barrier hopping (CBH) model dominated the conduction process in un-doped and Cu-doped ZnO nanoparticles. The dielectric measurements in low-frequency at high temperatures regions exhibited high dielectric constant values for the prepared samples. Compared to undoped ZnO, the dielectric constant values increase with Cu concentration, also improving the ac conductivity of all Cu-doped ZnO nanoparticles, making them a suitable choice for energy storage applications. The electrical modulus displays a dual nature of relaxation times for all synthesized samples with lower values. • Pure ZnO and Cu-doped ZnO nanostructures have been fabricated using a Co-precipitation method. • The average crystalline size of ZnO and Cu-doped ZnO nanostructures lies at 46 nm to 56 nm. • The samples of pure and Cu-doped ZnO nanostructures showed negative temperature coefficient resistance (NTCR). • Dielectric and ac conductivity properties improved with the addition of Cu concentrations. • The Cu-doped ZnO nanostructures shall be beneficial for optoelectronics applications.

Magnetic field sensing characteristics of rGO/BiMnO3 nanocomposites loaded clad-modified optical fiber sensor

In this paper, the clad-modified multimode plastic optical fiber (POF) was developed using pristine BiMnO 3 (BMO) and BMO/rGO as a sensor material. The BMO and BMO/rGO were synthesized using the hydrothermal method. The structural, morphological, optical, and dielectric properties were studied using X-ray diffraction (XRD), Scanning electron microscope (SEM), Fourier transforms infrared spectroscopy (FT-IR), UV–vis spectrophotometer, and LCR meter. The magnetic field sensing characterization was performed using clad-modified optical fiber technology. Due to the magneto-optic and LSPR effect, the modified cladding with BMO/rGO sensor is highly sensitive to applied magnetic fields compared with the pristine BMO. The BMO/rGO sensor had achieved a high sensitivity response of 102.2% (693 nm) and 50.5% (772 nm) at 190 mT.

Study on the movements and bending stresses of hangers and control measures in self-anchored rail suspension bridges

As a critical component of suspension bridges, hangers face an increasingly prominent risk of deterioration and even breakage due to relative movement and fatigue stress, posing a serious threat to bridge safety. This study investigated longitudinal movements and bending stresses of short hangers in a typical self-anchored rail suspension bridge using transient dynamic analysis. We proposed an effective method to calculate the bending stresses of hangers based on a frame finite element model (FFEM). The effects of hanger breakage on the dynamic response of bridges were further analyzed. Results showed significant relative longitudinal movements between cables and girders, causing consequential periodic bending stresses on hangers. Furthermore, the bending stresses considerably increased as the lengths of these hangers decreased. The relative longitudinal movements and bending stresses of short hangers exhibited static characteristics in self-anchored suspension bridges. The breakage of hangers induced a significant dynamic response on adjacent hangers, which bore the most redistributed loads and became critical components. Based on the static deformation characteristics of self-anchored suspension bridges, two promising measures—adding central clamps or negative stay cables—were proposed to reduce the bending stresses and improve the fatigue performance of hangers. The improvements of the two measures were comprehensively analyzed and compared. The findings of this study are significant for improving the design of rail self-anchored suspension bridges in terms of hanger safety.

Modeling the Quantitative Assessment of the Condition of Bridge Components Made of Reinforced Concrete Using ANN

Bridges in Ukraine are one of the most important components of the infrastructure, requiring attention from government agencies and constant funding. The object of the study was the methodology for quantifying the condition of bridge components. The Artificial Neural Network-based (ANN) tool was developed to quantify the technical condition of bridge components. The literature analysis showed that in most cases the datasets were obtained during the inspection of bridges to solve the problems of assessing the current technical condition. The lack of such a database prompted the creation of a dataset on the basis of the Classification Tables of the Operating Conditions of the Bridge Components (CT). Based on CTs, five datasets were formed to assess the condition of the bridge components: bridge span, bridge deck, pier caps beam, piers and abutments, approaches. The next step of this study was creating, training, validating and testing ANN models. The network with ADAM loss function and softmax activation showed the best results. The optimal values of MAPE and R2 were achieved at the 100th epoch with 64 neurons in the hidden layer and were equal to 0.1% and 0.99998, respectively. The practical application of the ANN models was carried out on the most common type of bridge in Ukraine, namely, a road beam bridge of small length, made of precast concrete. The novelty of this study consists of the development of a tool based on the use of ANN model, and the proposal to modify the methodology for quantifying the condition of bridge components. This will allow minimizing the uncertainties associated with the subjective judgments of experts, as well as increasing the accuracy of the assessment.

Enhanced mechanical and electrical properties of ECR-glass reinforced polyimide composites with incorporation of TiO2 for insulation applications

This paper presents the mechanical behaviour of novel class composites consisting of ECR-glass type reinforced polyimide (PI) composite loaded with TiO2 nanoparticles. ECR glass reinforced PI composites were fabricated by adding TiO2 particles at three different concentrations namely; 2, 4, and 6 wt% using 3D-Turbula dispersion and Spark Plasma Sintering (SPS) method. The morphologies, crystallinity, mechanical, and electrical properties of the produced composites were evaluated using scanning electron microscope (SEM), X-ray diffractometer, nanoindentation test, and LCR meter device. The SEM results revealed that the TiO2 nanoparticles were homogenously dispersed into the PI composites. The mechanical properties, such as hardness, stiffness, and elastic modulus of the pure PI and ECR glass reinforced PI composite was improved by the incorporation of TiO2 nanoparticles. Maximum hardness and elastic modulus values of 2.19 GPa and 13.99 GP, respectively, was observed in ECR reinforced PI composited loaded with 6 wt% TiO2 nanoparticles. In addition, ECR glass reinforced PI composites with 6 wt% TiO2 nanoparticles depicted the lowest dielectric constant (1.18), dielectric loss (1.14) and electrical conductivity (3.16 × 10−6 S/cm). Finally, the findings suggest the easy processability of PI nanocomposites and their potential for mechanical and electrical insulation applications.

Thermal and electronic states of exfoliated gC3N4-based nanocomposite with ZrO2 nanoparticles as a robust emissive layer

Metal-free graphitic carbon nitride (gC3N4) is proving as a growing star of the carbon nitride family due to its glamorous electrical, optical, and thermal properties. Blending of zirconium oxide (ZrO2) semiconductor with different weight percentages improves the properties of the pure gC3N4. In this work, we used the ultrasonic sound wave method to synthesize gC3N4/ZrO2 nanocomposite. Characterization techniques such as X-ray powder diffraction (XRD), field emission scanning electron microscopy (FESEM), high-resolution transmission electron microscopy (HR-TEM), Fourier transforms infrared microscopy (FTIR), UV–visible, and photoluminescence were carried out to characterize the as-synthesized gC3N4, ZrO2, and gC3N4/ZrO2 nanocomposite. The XRD measurement method confirmed the composite's average particle size and crystalline nature. Fourier transform infrared (FTIR) spectroscopy was performed to examine the presence of functional groups in synthesized materials. Bandgap energy of 2.98 eV and light absorbed in the range of 250 nm–450 nm was recorded by UV visible spectroscopy. Photoluminescence spectroscopy revealed photon emission in the range of 450 nm–530 nm of the synthesized materials. Dielectric constant, refractive index (n = 1.5), and electrical conductivity (2.63 × 10−3 S/cm) were computed using an LCR meter and I–V graph. Lower dielectric constant, refractive index, optimized optical band gap energy, and higher electron-hole recombination rate of gC3N4/ZrO2 illustrated a successful emissive layer for organic light-emitting diode applications.

Automated bridge component recognition using close-range images from unmanned aerial vehicles

Unmanned aerial vehicles (UAVs), in conjunction with computer vision techniques, have shown great potential for bridge inspections. Close-range images captured in proximity to the structural surface are generally required to detect damage and also need to be linked to the corresponding structural component to enable assessment of the health of the global structure. However, the lack of contextual information makes automated identification of bridge components in close-range images challenging. This study proposes a framework for automated bridge component recognition based on close-range images collected by UAVs. First, a 3D point cloud is generated from the UAV survey of the bridge and segmented into bridge components. The segmented point cloud is subsequently projected onto the camera coordinates to categorize each of the images into the bridge component. The proposed approach is successfully validated using a local highway bridge, pointing the way for improved inspection of full-scale bridges.

A Practical Approach to Identify the Phases Sequence in Five Phase Machines with Combined Star–Pentagon Configuration

Due to the significant advantages of a high torque density, better fault tolerance and high efficiency, the combined star–pentagon winding has recently gained researchers’ interest. In this paper, a simple method to identify the sequence of phases of a five-phase machine with combined star–pentagon winding was proposed. This was accomplished using resistance measurements between adjacent and non-adjacent phases. The analysis was conducted to clarify the phase sequence identification method. A case study of a 5.5 kW five-phase synchronous reluctance motor with combined star–pentagon winding was considered to simply apply the proposed method using an LCR meter for resistance measurements. The parasitic and wire resistances are dominant in the studied case, and this did not influence the accuracy of this method.

Comparison of Structural, dielectric and magnetic investigation of Cr3+ substituted Mg-Cu, Mg-Zn, and Mg-Ni ferrites system

• Studied the effect of Cr 3+ substitution on the structural, dielectric, and magnetic properties of Mg 0.5 M 0.5 Fe 1.5 Cr 0.5 O 4 (M = Cu, Zn, and Ni) ferrite system prepared by sol–gel method. • The XRD patterns showed a single spinel phase. • The magnetic saturation (M s ), magnetic moment (M r ), and Coercivity (H c ) is found to be the highest for the Cr substituted Mg-Ni ferrite system. • All the synthesized samples showed ferrimagnetic behavior. • Thus, the magnetic and structural properties of (Mg 0.5 M 0.5 Fe 1.5 Cr 0.5 O 4 (M = Cu, Zn, and Ni) NPs can be favorable for their potential use in high-density recording media applications. Effect of Cr 3+ substitution on the structural, dielectric, and magnetic properties of Mg 0.5 M 0.5 Fe 1.5 Cr 0.5 O 4 (M = Cu, Zn, and Ni) ferrite system prepared by sol–gel method. All ferrites prepared samples’ powder; X-ray diffraction patterns confirmed the formation of single-phase cubic spinel structures with Fd -3 m space group. It possesses a monophasic cubic-spinel lattice structure with an average crystallite size ranging from 25 to 44 nm. The lattice constant determined by XRD analysis falls between 8.497 Å and 8.392 Å. Furthermore, the crystallite size determined by XRD data is well matched with the particle size determined by scanning electron microscopy images. Using an LCR Meter, the dielectric parameters of the samples, such as dielectric constant ( ε ’) and dielectric loss tangent (tan δ ), were studied as a function of frequency in the range of 100 Hz to 5 MHz at room temperature. The dielectric constant and loss tangent among the samples show a normal dielectric behavior with a frequency which reveals that the dispersion is a result of the Maxwell-Wagner type interfacial polarization and hopping of electrons between the Fe 2+ and Fe 3+ ions. The hysteresis curve exhibits the particles are soft ferrimagnetic with maximum saturation magnetization, Ms = 38.55 emu/g due to Cr substituted Mg-Ni ferrite. The squareness ratios were discovered to be less than 0.5, indicating that our particles have a single-domain ferrimagnetic isotropic nature. Thus, the magnetic and structural properties of (Mg 0.5 M 0.5 Fe 1.5 Cr 0.5 O 4 (M = Cu, Zn, and Ni) NPs can be favorable for their potential use in high-density recording media applications.

Optimal UAV Image Overlap for Photogrammetric 3D Reconstruction of Bridges

Unmanned Aerial Vehicles (UAVs) and photogrammetry have been widely used to reconstruct a photo-realistic 3D model of physical bridges for documentation of cultural bridges or remote bridge inspection. However, the optimal image overlap for photogrammetric bridge reconstruction that can trade off the model quality and overall mission time has not yet been studied. In this paper, a comparative experiment was conducted on a real girder bridge with three typical overlap configurations being implemented to capture corresponding UAV image sets, based on which bridge models were reconstructed using a commercial photogrammetry software package. Time consumption and the quality of reconstructed bridge models of these three experimental cases were compared and analysed. The results showed that the configuration of 66.7% forward overlap and 50% side overlap is the optimal overlap configuration for the reconstruction of a variety of bridge components, which can result in the minimum number of images while saving the overall mission time for image acquisition and processing. The overlap recommendation may also be applicable to the 3D reconstruction of other types of bridges and buildings with similar structural components.

SEISMIC VULNERABILITY ANALYSIS OF CABLE-STAYED BRIDGE DURING ROTATION CONSTRUCTION

Due to the swivel construction, the structural redundancy of cable-stayed bridge is reduced, and its seismic vulnerability is significantly higher than that of non-swirling construction structure and its own state of formation. Therefore, it is particularly important to study the damage changes of each component and stage system during the swivel construction of cable-stayed bridge under different horizontal earthquakes. Based on the construction of Rotary Cable-stayed Bridge in Haxi Street, the calculation formula of damage exceeding probability is established based on reliability theory, and the damage calibration of cable-stayed bridge components is carried out, and the finite element model of cable-stayed bridge rotating structure is established. The vulnerable parts of the main tower and the stay cable components of the cable-stayed bridge are identified and the incremental dynamic analysis is carried out. Finally, the seismic vulnerability curves of the main tower section, the stay cable and the rotating system are established. The results of the study show that the vulnerable areas of the H-shaped bridge towers are the abrupt changes in the main tower section near the upper and lower beams, and the vulnerable diagonal cables are the long cables anchored to the beam ends and the short cables near the main tower；At the same seismic level, the damage exceedance probability of main tower vulnerable section of cable-stayed bridge under transverse earthquake is greater than that under longitudinal earthquake, the damage exceedance probability of vulnerable stay cables under transverse seismic action is less than that under longitudinal seismic action；On the premise of the same damage probability, the required ground motion intensity of the system can be reduced by 0.35g at most compared with the component；Under the same seismic intensity, the system damage probability is 6.60 % higher than the component damage probability at most. The research results have reference significance for the construction of rotating cable-stayed bridges in areas lacking seismic records.

Suspension rheology of polyaniline coated manganese ferrite particles under electric/magnetic fields

Manganese ferrite (MnFe2O4) nanoparticles initially fabricated using a solvothermal process were coated with conducting polyaniline (PANI) to produce core/shell-structured MnFe2O4/PANI nanoparticles. An electro/magnetorheological (E/MR) fluid was prepared by suspending MnFe2O4/PANI particles in silicone oil, and the rheological properties under either electric or magnetic fields were investigated. Scanning electron microscope and transmission electron microscope provided the particle morphology and size information. X-ray diffraction and Fourier transform infrared spectroscopy were used to analyze the crystal structure and chemical composition of the particles. Chain formation in E/MR fluids under electric or magnetic fields was observed by optical microscopy, and the rheological properties were evaluated using a rheometer. Steady shear and dynamic oscillatory tests were conducted to confirm the effective E/MR characteristics while varying the electric/magnetic field strength. The dielectric properties of the particles measured using an LCR meter were analyzed based on the Cole-Cole model. The E/MR fluids composed of MnFe2O4/PANI showed a reversible and fast electro/magnetic response.

FRP Bridges in the Flanders Region: Experiences from the C-Bridge Project

At the start of the C-Bridge project in 2018, the number of fibre-reinforced composite bridges in the Flanders region of Belgium was limited to a handful. These limited achievements were largely due to the poor knowledge of clients (public and private), project managers, design engineers, and contractors, which made the option of composites either unknown or still viewed with a certain degree of suspicion. In addition, there were no standards at the Belgian or European level for the design of such constructions. The C-Bridge project (roadmap into design, guidelines, and execution of composite bridges in Flanders) aimed to stimulate the design, the realization and the construction of composite bridges in Flanders by providing the necessary knowledge to the construction sector in the most suitable form. This knowledge consists of the current state of the art of composites in bridge construction, selection criteria for composite bridges, recommendations for specification texts, and in situ testing of composite bridges and structural and vibration analysis. This C-Bridge project should allow the awarding authorities and contractors to be able to make informed choices regarding fibre-reinforced polymer (fibre composite) bridges but also offer the possibility of making the necessary transformation to this new and promising material to various Flemish companies. The results of the project enable Flemish clients to draw up specifications for FRP bridges in the correct manner. Moreover, they can correctly interpret the calculation notes made available and make a correct assessment. The Flemish engineering firms, on the other hand, will be able to make their own designs of FRP bridges and bridge components. They can also build up a value chain within Flanders with Flemish contractors and producers. From the producers and suppliers’ point of view, the results of the project will lead to a clearer profile of their products on the public and private market. Finally, the general contractors and constructors will be armed to withstand the challenges that FRP bridges entail to subcontractors in terms of execution, follow-up, delivery, and maintenance. The findings are helpful for the acceptance of fibre-reinforced composite bridges as an alternative to timber, steel, or concrete bridges and should generate a market expansion for FRP in the traditionally conservative bridge-building sector first in Flanders and later internationally.

Implementation of a Mathematical Model for the Prediction of the Future Condition Rating for Bridge Components

Bridges are continuously exposed to environmental changes and dynamic loading effects caused by moving loads. As a result, bridge deterioration is a critical problem in the U.S.A. The National Bridge Inventory (NBI) database contains historical bridge condition information for bridges in the U.S.A. and currently it is the best available database for describing the historical condition of bridges in the U.S.A. The objective of this paper is to develop a mathematical model that can be used to predict the future condition ratings of each bridge component and, more specifically, to estimate the probability of each bridge component being at any condition rating at any future year. Two different types of future condition rating prediction models, namely the current practice model (CPM) and the deterioration prediction model (DPM), were developed. The CPM is capable of simulating the effects of historical maintenance activities when predicting the future condition rating probabilities, whereas the DPM does not consider the effects of historical maintenance activities when predicting the future condition rating probabilities. Both models were illustrated and validated using most current NBI data. The performance of both models was evaluated on hundreds of bridges in the states of Iowa and Wisconsin. The results indicated that the CPMs tend to converge to condition rating 6 within 15 years, whereas the DPMs tend to converge to condition rating 4 with 15 years. This suggests that conducting current maintenance activities helps to keep the nation’s bridges in at least “satisfactory condition.” However, a lack of performing any maintenance could lead to bridges being structurally deficient within 15 years.

Semantic segmentation of bridge components and road infrastructure from mobile LiDAR data

Emerging mobile LiDAR mapping systems exhibit great potential as an alternative for mapping urban environments. Such systems can acquire high-quality, dense point clouds that capture detailed information over an area of interest through efficient field surveys. However, automatically recognizing and semantically segmenting different components from the point clouds with efficiency and high accuracy remains a challenge. Towards this end, this study proposes a semantic segmentation framework to simultaneously classify bridge components and road infrastructure using mobile LiDAR point clouds while providing the following contributions: 1) a deep learning approach exploiting graph convolutions is adopted for point cloud semantic segmentation; 2) cross-labeling and transfer learning techniques are developed to reduce the need for manual annotation; and 3) geometric quality control strategies are proposed to refine the semantic segmentation results. The proposed framework is evaluated using data from two mobile mapping systems along an interstate highway with 27 highway bridges. With the help of the proposed cross-labeling and transfer learning strategies, the deep learning model achieves an overall accuracy of 84% using limited training data. Moreover, the effectiveness of the proposed framework is verified through test covering approximately 42 miles along the interstate highway, where substantial improvement after quality control can be observed.

Fabrication of a lead-free ternary ceramic system for high energy storage applications in dielectric capacitors.

The importance of electroceramics is well-recognized in applications of high energy storage density of dielectric ceramic capacitors. Despite the excellent properties, lead-free alternatives are highly desirous owing to their environmental friendliness for energy storage applications. Herein, we provide a facile synthesis of lead-free ferroelectric ceramic perovskite material demonstrating enhanced energy storage density. The ceramic material with a series of composition (1-z) (0.94Na0.5Bi0.5TiO3-0.06BaTiO3)-zNd0.33NbO3, denoted as NBT-BT-zNN, where, z = 0.00, 0.02, 0.04, 0.06, and 0.08 are synthesized by the conventional solid-state mix oxide route. Microphases, microstructures, and energy storage characteristics of the as-synthesized ceramic compositions were determined by advanced ceramic techniques. Powder X-ray diffraction analysis reveals pure single perovskite phases for z = 0 and 0.02, and secondary phases of Bi2Ti2O7 appeared for z = 0.04 and 0.08. Furthermore, scanning electron microscopy analysis demonstrates packed-shaped microstructures with a reduced grain size for these ceramic compositions. The coercive field (Ec) and remnant polarization (Pr) deduced from polarization vs. electric field hysteresis loops determined using an LCR meter demonstrate decreasing trends with the increasing z content for each composition. Consequently, the maximum energy storage density of 3.2J/cm3, the recoverable stored energy of 2.01J/cm3, and the efficiency of 62.5% were obtained for the z content of 2mol% at an applied electric field of 250kV/cm. This work demonstrates important development in ceramic perovskite for high power energy storage density and efficiency in dielectric capacitors in high-temperature environments. The aforementioned method makes it feasible to modify a binary ceramic composition into a ternary system with highly enhanced energy storage characteristics by incorporating rare earth metals with transition metal oxides in appropriate proportions.

Dynamic amplification in masonry arch railway bridges

Dynamic amplification of loads in masonry arch railway bridges is not well understood. There is a scarcity of experimental data and previous numerical studies have only addressed a few specific bridge geometries. Despite this, guidance documents provide empirical and unvalidated formulae to calculate dynamic amplification for masonry arch railway bridges. To improve our fundamental understanding of the problem, determine appropriate modelling strategies and evaluate the reliability of guidance documents, simple 2D and 3D models are explored in this paper. The 2D approach idealises key bridge components (pier, arch, fill and backing elements) with straight Timoshenko beams, springs and lumped masses. It uses an analytical dynamic stiffness formulation, which is computationally efficient and well-suited to explore a range of bridge models. The higher fidelity 3D modelling approach uses shell and solid finite elements and is used to evaluate the limitations of 2D models. In both approaches, linear-elastic material behaviour is assumed and train loads are idealised as moving vertical loads distributed over an effective area. The modelling results indicate a complex relationship between train speed and dynamic amplification that depends critically on bridge geometry and axle spacing. In general, the multi-span bridge configurations experienced higher dynamic amplification over operational train speeds. The results also higlight deficiencies in existing code provisions and demonstrates how efficient numerical models may replace these provisions.

Static Deflection Difference-Based Damage Identification of Hanger in Arch Bridges

As the most critical force transmitting and bearing components of arch bridges, the hanger is also the weakest link of the bridge. Damage to the hanger leads to a redistribution of the internal forces and potentially even the collapse of the bridge. Therefore, this paper proposes a new damage detection method for hangers. Based on the principle of superposition, the relationship between the static deflection change and cable force is studied. Then, a new index is proposed for identifying the damage to arch bridge hangers. Numerical and laboratory investigations demonstrate that this method can successfully locate damage regardless of its location; moreover, the degree of damage can be relatively quantified. In addition, the method is easy to operate and suitable for practical engineering applications.

Post‐earthquake damage recognition and condition assessment of bridges using UAV integrated with deep learning approach

Rapid and accurate assessment of the damage to bridge structures after an earthquake can provide a basis for decision-making regarding post-earthquake emergency work. However, the traditional structural damage inspection techniques are subjective, time-consuming, and inefficient. This paper proposed a framework for rapid post-earthquake structural damage inspection and condition assessment by integrating the technologies of satellite, unmanned aerial vehicle (UAV), and smartphone with the deep learning approach. The images of structural components of post-earthquake bridges can be obtained by UAVs and smartphones. Furthermore, the multi-task high-resolution net (MT-HRNet) model was adopted to recognize the structural components and damage conditions by weighting and combining the loss functions of a single-task HRNet model. The performance of the proposed MT-HRNet model and the single-task HRNet model was verified based on the Tokaido dataset, which includes 2000 images of post-earthquake bridges. The results showed that the MT-HRNet model and the HRNet model exhibited equivalent recognition accuracy, while the number of floating-point-operations (FLOPs) and the parameters of the MT-HRNet model were reduced by 46.48% and 49.58% compared with the HRNet model. In addition, a method for the determination of the safety risk level of the post-earthquake bridge structures was developed, and the evaluation indices were established by considering the damage type, the spalling area, and the width of cracks as well as the recognition statistics of all images in Tokaido dataset. This study will provide a valuable reference for the rapid determination of structural safety level and the corresponding treatment measures of post-earthquake bridges.