Condition assessment of structures under unknown support excitation

A new method is proposed to assess the condition of structures under unknown support excitation by simultaneously detecting local damage and identifying the support excitation from several structural dynamic responses. The support excitation acting on a structure is modeled by orthogonal polynomial approximations, and the sensitivities of structural dynamic response with respect to its physical parameters and orthogonal coefficients are derived. The identification equation is based on Taylor＇s first order approximation, and is solved with the damped least-squares method in an iterative procedure. A fifteen-story shear building model and a five-story three-dimensional steel frame structure are studied to validate the proposed method. Numerical simulations with noisy measured accelerations show that the proposed method can accurately detect local damage and identify unknown support excitation from only several responses of the structure. This method provides a new approach for detecting structural damage and updating models with unknown input and incomplete measured output information.

Review Article on Condition Assessment of Structures Using Electro-Mechanical Impedance Technique

Structural health monitoring(SHM)is a process for determination of presence,location,severity of damages and remaining life of the infrastructures.SHM is widely applied in aerospace,mechanical and civil engineering sys-tems to assess the conditions of structures to improve the operation,safety,serviceability and reliability,respec-tively.There are various SHM techniques for monitoring the health of structures such as global response based and local techniques.Damages occur in the structures due to its inability to withstand intended design loadings,physical environment and chemical environment.Therefore,damage identification is necessary to improve the durability of the structures for protection against catastrophic failure.The research paper is focused on elec-tro-mechanical impedance(EMI)technique which is one of the techniques based on smart materials.The smart materials are utilized for monitoring the health of the structures.These are used for damage determination and its quantification for the interrogated structures.Variation in admittance or impedance signature shows the existence of damage in the structures.Furthermore,the different statistical methods viz.,root mean square deviation(RMSD),mean absolute percentage deviation(MAPD),covariance(Cov),and correlation coefficient(CC)are used for the quantification of damage.Smart material such as piezoelectric materials,its properties and applica-tions are also considered.In this paper,the implementation of EMI technique based on different recent advances in smart materials and their appropriateness have been described.Subsequently,the reviewed investigations are significant for the monitoring of real-life infrastructures.The presented paper is the compact state-of-the-art for EMI technique which is used for SHM.This examination will be valuable to infrastructural health monitoring and engineering applications in respect to innovative research directions.

Comprehensive health condition assessment on partial sewers in a southern Chinese city based on fuzzy mathematic methods

A self-developed sewer health assessment system using the fuzzy comprehensive evaluation and analytical hierarchy process was applied to give a comprehensive health condition evaluation on part of the local sewers in a southern Chinese city based on the sewer video data collected by a sewer inspection closed circuit television （CCTV） robot. Aside from the overall condition evaluation, the structure, function, and stability status of the sewer were also analyzed using the method. A comprehensive index H was proposed to give the overall health condition of pipes with different defects, and Ht, Hs, and If were used to quantify the defects affecting the tightness, stability, and function of the pipe, respectively. Results show that 48% of the inspected pipes were in good condition （0〈H〈0.25）, and about 33% of the sewer pipes analyzed were categorized to be at severe or urgent condition levels （H 〉 0.5）, although most of the pipes were installed only within five years. Frequent sedimentation affects the function of the sewer, and deformation and joint damage affect the structure of the sewer.

Assessment of Structural Damage Condition Based on Fuzzy Pattern Recognition

This paper presents a new method of damage condition assessment that allows accommodating other types of uncertainties due to ambiguity, vagueness, and fuzziness that are statistically nondescribable. In this method, healthy observations are used to construct a fury set representing sound performance characteristics. Additionally, the bounds on the similarities among the structural damage states are prescribed by using the state similarity matrix. Thus, an optimal group fuzzy sets representing damage states such as little, moderate, and severe damage can be inferred as an inverse problem from healthy observations only. The optimal group of damage fuzzy sets is used to classify a set of observations at any unknown state of damage using the principles of fitzzy pattern recognition based on an approximate principle . This method can be embedded into the system of Structural Health Monitoring （SHM） to give advice about structural maintenance and life predictio comes from Reference [ 9 ] for damage pattern recognition is presented n. Finally, a case and discussed. The study, which compared result illustrates our method is more effective and general, so it is very practical in engineering.

Fast prediction of the mechanical response for layered pavement under instantaneous large impact based on random forest regression

The layered pavements usually exhibit complicated mechanical properties with the effect of complex material properties under external environment.In some cases,such as launching missiles or rockets,layered pavements are required to bear large impulse load.However,traditional methods cannot non-destructively and quickly detect the internal structural of pavements.Thus,accurate and fast prediction of the mechanical properties of layered pavements is of great importance and necessity.In recent years,machine learning has shown great superiority in solving nonlinear problems.In this work,we present a method of predicting the maximum deflection and damage factor of layered pavements under instantaneous large impact based on random forest regression with the deflection basin parameters obtained from falling weight deflection testing.The regression coefficient R^(2)of testing datasets are above 0.94 in the process of predicting the elastic moduli of structural layers and mechanical responses,which indicates that the prediction results have great consistency with finite element simulation results.This paper provides a novel method for fast and accurate prediction of pavement mechanical responses under instantaneous large impact load using partial structural parameters of pavements,and has application potential in non-destructive evaluation of pavement structure.

Application of Serum Apelin and MMP-9 in Evaluation of Silicosis and Their Correlation with Lung Function

[Objectives]This study was conducted to explore the combination of serum Apelin and MMP-9 in the assessment of silicosis and their correlation with lung function. [Methods] From January 2020 to January 2021, eight patients with silicosis(including 3, 2 and 3 patients with silicosis in stages I, II and III respectively) were selected as the observation group, and eight persons frees of silicosis were selected as the control group during the same period. All patients were detected for serum APJ endogenous ligand(Apelin) of G protein-coupled receptor, matrix metalloproteinase-9(MMP-9) and pulmonary function indexes. The levels of serum Apelin and MMP-9 and lung function in the two groups were compared, and the correlation between serum Apelin and MMP-9 indexes and lung function was analyzed. [Results] The serum Apelin and lung function in the observation group were lower than those in the control group, and the level of MMP-9 in the observation group was higher than that in the control group, and the differences were statistically significant(P<0.05). The MMP-9 index in patients with silicosis in stage III was higher than those in patients with silicosis in stage II and stage I, and the MMP-9 index in patients with silicosis in stage II was higher than that in patients with silicosis in stage I, and the differences were statistically significant(P<0.05). The serum Apelin and lung function indexes of patients with silicosis in stage III were lower than those of patients with silicosis in stage II and stage I, and the serum Apelin and lung function indexes of patients with silicosis in stage II were lower than those of patients with silicosis in stage I, and the differences were statistically significant(P<0.05). The correlation analysis showed a positive correlation between serum Apelin and lung function indexes, and a negative correlation between MMP-9 and lung function indexes. [Conclusions] A lower serum Apelin and a higher MMP-9 value in patients with silicosis indicate severer lung function impairment, and the combined detection of serum Apelin and MMP-9 is conducive to effective evaluation of the disease of silicosis. The serum Apelin index was negatively correlated with silicosis, and the level of MMP-9 was positively correlated with silicosis, which could provide a scientific basis for clinical diagnosis and treatment.

Power transmission risk assessment considering component condition

This paper proposes a new method for power transmission risk assessment considering historical failure statistics of transmission systems and operation failure risks of system components.Component failure risks are integrated into the new method based on operational condition assessment of components using the support vector data description(SVDD)approach.The traditional outage probability model of transmission lines has been modified to build a new framework for power transmission system risk assessment.The proposed SVDD approach can provide a suitable mechanism to map component assessment grades to failure risks based on probabilistic behaviors of power system failures.Under the new method,both up-todate component failure risks and traditional system risk indices can be processed with the proposed outage model.As a result,component failure probabilities are not only related to historical statistic data but also operational data of components,and derived risk indices can reflect current operational conditions of components.In simulation studies,the SVDD approach is employed to evaluate component conditions and link such conditions to failure rates using up-to-date component operational data,including both on-line and off-line data of components.The IEEE 24-bus RTS-1979 system is used to demonstrate that component operational conditions can greatly affect the overall transmission system failure risks.

裂纹和污秽瓷绝缘子的电磁场辐射信号特征(英文)

Porcelain cap and pin insulators are by far the most popular suspension insulators in high voltage(HV) distribution networks all around the world.Inspection and condition monitoring of HV insulators is also very important to the utility companies because of the critical and vital role that they play in distribution systems.In terms of safety, practicality and ease of use,remote detection methods are more popular among the line technicians.A new remote condition assessment method based on electromagnetic radiations from porcelain insulators is presented in this paper. In a lab environment,a string of two porcelain insulators is energized by a 45 kV transformer.Electromagnetic radiations due to the partial discharge activities inside the porcelain insulator are captured by passive sensors and antennas. Two cases of defective insulators on a two insulator string are studied here.The first case focuses on the effect of contaminated porcelain shells on radiation signature of partial discharges.A polluted porcelain shell with ESDD level of 0.03 mg/cm^2 was first tested.The second case studies the effect of cracks of an intentionally-cracked porcelain shell. The cracked insulator is also tested on a two insulator string.To compare the partial discharge radiation signature of different faulty insulators,phase resolved graphs were developed.The electromagnetic radiated signature of a polluted insulator and a cracked insulator was calculated and compared using phase resolved graphs.

An assessment model of water pipe condition using Bayesian inference

An accurate understanding of the condition of a pipe is important for maintaining acceptable levels of service and providing appropriate strategies for maintenance and rehabilitation in water supply systems. Many factors contribute to pipe deterioration. To consolidate information on these factors to assess the condition of water pipes, this study employed a new ap-proach based on Bayesian configuration against pipe condition to generate factor weights. Ten pipe factors from three pipe ma-terials (cast iron, ductile cast iron and steel) were used in this study. The factors included size, age, inner coating, outer coating, soil condition, bedding condition, trench depth, electrical recharge, the number of road lanes, material, and operational pressure. To address identification problems that arise when switching from pipe factor information to actual pipe condition, informative prior factor weight distribution based on the literature and previous knowledge of water pipe assessment was used. The influence of each factor on the results of pipe assessment was estimated. Results suggested that factors that with smaller weight values or with weights having relative stable posterior means and narrow uncertainty bounds, would have less influence on pipe conditions. The model was the most sensitive to variations of pipe age. Using numerical experiments of different factor combinations, a simplified model, excluding factors such as trench depth, electrical recharge, and the number of road lanes, is provided. The proposed Bayesian inference approach provides a more reliable assessment of pipe deterioration.

GEOCHEMISTRY STUDY OF GOLD SILVER DEPOSITS IN THE MIDDLE UPPER PROTEROZOIC SUBERATHEM IN SOUTHERN QINLING METALLOGENETIC ZONE

According to Ihe combinations of mctallogcnetic elements and minerals assemblages,the Au-Ag deposits in the Middle-Upper Proterozoic Suberathcm of the middle of northern margin of Yangtze Platform could be classified into four types,(l)Au-Ag-Pb-Zn type,(2)Au-Ag-Te type,(3)Au-quartz vein type,(4)Au-Ag-Pb-Zn-Ba type.The Yangpin formation and the upper Dangyuhe subformation,which belong to Wudangshan group,are regarded as favorable strata for Au-Ag mineralization by systematic assessments for Au-Ag bearing ability of the strata,as well as the felsic rocks of Bikou group.The mctallogcnetic physicochemical conditions and the stable isotopic compositions(S.Pb,H.O,C)have been studied in this paper.The sources of metallogenetic materials,origins of fluids and genesis of various deposits have also been studied.

Road pavement condition diagnostics using smartphone-based data crowdsourcing in smart cities

The purpose of the paper is to analyse the effectiveness of a solution known as road condition tool(RCT)based on data crowdsourcing from smartphones users in the transport system.The tool developed by the author of the paper,enabling identification and assessment of road pavement defects by analysing the dynamics of vehicle motion in the road network.Transport system users equipped with a smartphone with the RCT mobile application on board record data of linear accelerations,speed,and vehicle location,and then,without any intervention,send them to the RCT server database in an aggregated form.The aggregated data are processed in the combined time and location criterion,and the road pavement condition assessment index is estimated for fixed 10 m long measuring sections.The measuring sections correspond to the sections of roads defined in the pavement management systems(PMS)used by municipal road infrastructure administration bodies.Both the research in question and the results obtained by the method proposed for purposes of the road pavement condition assessment were compared with a set of reference data of the road infrastructure administration body which conducted surveys using highly specialised measuring equipment.The results of this comparison,performed using binary classifiers,confirm the potential RCT solution proposed by the author.This solution makes it possible to global monitor the road infrastructure condition on a continuous basis via numerous users of the transport system,which guarantees that such an assessment is kept up to date.

Review and prospect of maintenance technology for traction system of high-speed train

In the past few decades,high-speed trains have witnessed tremendous and vigorous development with the appearance of the oil crisis and industrialization,which became a significant trend in the transportation industry the world over.With the increase of high-speed railway mileage,the amount of high-speed train has grown sharply,the service life of the trains has increased gradually and the components of the vehicle traction system have become worn and aged as a result.Therefore,advanced maintenance technology and its application are key factors to reduce maintenance cost,human resource input and ensure safe,stable and reliable operation of trains.This paper summarizes and discusses the development,application mode,maintenance management and maintenance technology of high-speed railways of the major countries in the world,especially discusses the condition-based maintenance and the key technology of the traction electrical system,and offers the prospect of research direction and the development of traction maintenance technology.

Implementation of a drainage information, analysis and management system

An integrated drainage information, analysis and management system （DIAMS） was developed and implemented for the New Jersey Department of Transportation （N/DOT）. The purpose of the DIAMS is to provide a useful tool for managers to evaluate drainage infrastructure, to facilitate the determination of the present costs of preserving those in- frastructures, and to make decisions regarding the optimal use of their infrastructure budgets. The impetus for DIAMS is the culvert information management system （CIMS）, which is developed to manage the data for culvert pipes. DIAMS maintains and summa- rizes accumulated inspection data for all types of drainage infrastructure assets, including pipes, inlet/outlet structures, outfalls and manufactured treatment devices. DIAMS capa- bilities include identifying drainage infrastructure, maintaining inspection history, map- ping locations, predicting service life based on the current condition states, and assessing present asset value. It also includes unit cost values of 72 standard items to estimate the current cost for new assets with the ability to adjust for future inflation. In addition, DIAMS contains several different repair, rehabilitation and replacement options to remedy the drainage infrastructure. DIAMS can analyze asset information and determine decisions to inspect, rehabilitate, replace or do nothing at the project and network levels by comparing costs with risks and failures. Costs may be optimized to meet annual maintenance budget allocations by pfioritizing drainage infrastructure needing inspection, cleaning and repair. DIAMS functional modules include vendor data uploading, asset identification, system administration and financial analysis. Among the significant performance feature of DIAMS is its proactive nature, which affords decision makers the means of conducting a comprehensive financial analysis to determine the optimal proactive schedule for the proper maintenance actions and to prioritize them accordingly. Benefits of DIAMS include long-term savings that accrue by adopting optimized preventive maintenance strategies and facilitating compliance with Governmental Accounting Standards Board （GASB） and federal storm water regulations.