scholarly journals Standardization construction and development trend of bridge health monitoring systems in China

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Guang-Dong Zhou ◽  
Ting-Hua Yi ◽  
Wen-Jie Li ◽  
Ji-Wei Zhong ◽  
Guan-Hua Zhang
Keyword(s):  
Data Storage ◽  
Health Monitoring ◽  
Development Trend ◽  
Common Belief ◽  
Comprehensive Overview ◽  
Practical Applications ◽  
Healthy Development ◽  
Existing Problems ◽  
Bridge Health Monitoring ◽  
Industry Standards

AbstractBridge health monitoring (BHM) technology has been widely accepted as a powerful tool to assess structural performance and has moved from research to practice. Driven by the enormous demand of ensuring bridge safety, the application of BHM technology is particularly active in China and has become an emerging industry in the civil engineering community. It is a common belief among civil engineers that the development and implementation of industry standards will be of paramount importance in guiding the healthy development of BHM and increasing the transfer of professional knowledge and techniques to practical applications. This paper presents a comprehensive overview of the standardization construction and development trend for BHM in China. The achievements, characteristics, and challenges of China’s bridge construction are first introduced. Then, the existing problems of BHM and the necessity of constructing the standardization system for the BHM industry are discussed. Following that, these standards published for guiding BHM system design, construction, management, and maintenance, especially sensor selection, sensor placement, sensor installation, data transmission, data storage, data processing, and early warning, are outlined. Finally, work requiring further efforts in the near future is drawn.

Recent Patents on the Angular Contact Ball Bearing of High-Speed Motorized Spindle

2020 ◽  
Vol 13 ◽  
Author(s):  
Yudong Bao ◽  
Linkai Wu ◽  
Yanling Zhao ◽  
Chengyi Pan
Keyword(s):  
High Speed ◽  
Ball Bearing ◽  
Rapid Development ◽  
Ceramic Materials ◽  
Development Trend ◽  
Numerical Control ◽  
Angular Contact Ball Bearing ◽  
Practical Applications ◽  
High Speed Cutting ◽  
Advantages And Disadvantages

Background:: Angular contact ball bearings are the most popular bearing type used in the high speed spindle for machining centers, The performance of the bearing directly affects the machining efficiency of the machine tool, Obtaining a higher value is the direction of its research and development. Objective:: By analyzing the research achievements and patents of electric spindle angular contact bearings, summarizing the development trend provides a reference for the development of electric spindle bearings. Methods:: Through the analysis of the relevant technology of the electric spindle angular contact ball bearing, the advantages and disadvantages of the angular contact ball bearing are introduced, and the research results are combined with the patent analysis. Results:: With the rapid development of high-speed cutting and numerical control technology and the needs of practical applications, the spindle requires higher and higher speeds for bearings. In order to meet the requirements of use, it is necessary to improve the bearing performance by optimizing the structure size and improving the lubrication conditions. Meanwhile, reasonable processing and assembly methods will also have a beneficial effect on bearing performance. Conclusion:: With the continuous deepening of bearing technology research and the use of new structures and ceramic materials has made the bearing's limit speed repeatedly reach new highs. The future development trend of high-speed bearings for electric spindles is environmental protection, intelligence, high speed, high precision and long life.

scholarly journals Numerical Parametric Study on the Effectiveness of the Contact-Point Response of a Stationary Vehicle for Bridge Health Monitoring

2021 ◽  
Vol 11 (15) ◽  
pp. 7028
Author(s):  
Ibrahim Hashlamon ◽  
Ehsan Nikbakht ◽  
Ameen Topa ◽  
Ahmed Elhattab
Keyword(s):  
Numerical Model ◽  
Health Monitoring ◽  
Contact Point ◽  
Response Spectra ◽  
Roughness Effects ◽  
Moving Vehicle ◽  
Bridge Health Monitoring ◽  
Vehicle Response ◽  
Instrumented Vehicle ◽  
The Time Domain

Indirect bridge health monitoring is conducted by running an instrumented vehicle over a bridge, where the vehicle serves as a source of excitation and as a signal receiver; however, it is also important to investigate the response of the instrumented vehicle while it is in a stationary position while the bridge is excited by other source of excitation. In this paper, a numerical model of a stationary vehicle parked on a bridge excited by another moving vehicle is developed. Both stationary and moving vehicles are modeled as spring–mass single-degree-of-freedom systems. The bridges are simply supported and are modeled as 1D beam elements. It is known that the stationary vehicle response is different from the true bridge response at the same location. This paper investigates the effectiveness of contact-point response in reflecting the true response of the bridge. The stationary vehicle response is obtained from the numerical model, and its contact-point response is calculated by MATLAB. The contact-point response of the stationary vehicle is investigated under various conditions. These conditions include different vehicle frequencies, damped and undamped conditions, different locations of the stationary vehicle, road roughness effects, different moving vehicle speeds and masses, and a longer span for the bridge. In the time domain, the discrepancy of the stationary vehicle response with the true bridge response is clear, while the contact-point response agrees well with the true bridge response. The contact-point response could detect the first, second, and third modes of frequency clearly, unlike the stationary vehicle response spectra.

scholarly journals Challenges in Bridge Health Monitoring: A Review

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4336
Author(s):  
Piervincenzo Rizzo ◽  
Alireza Enshaeian
Keyword(s):  
United States ◽  
Health Monitoring ◽  
Highway Bridges ◽  
The United States ◽  
Anomalous Behavior ◽  
Existing Structures ◽  
Bridge Health Monitoring ◽  
Using Data ◽  
The Many ◽  
Major Factors

Bridge health monitoring is increasingly relevant for the maintenance of existing structures or new structures with innovative concepts that require validation of design predictions. In the United States there are more than 600,000 highway bridges. Nearly half of them (46.4%) are rated as fair while about 1 out of 13 (7.6%) is rated in poor condition. As such, the United States is one of those countries in which bridge health monitoring systems are installed in order to complement conventional periodic nondestructive inspections. This paper reviews the challenges associated with bridge health monitoring related to the detection of specific bridge characteristics that may be indicators of anomalous behavior. The methods used to detect loss of stiffness, time-dependent and temperature-dependent deformations, fatigue, corrosion, and scour are discussed. Owing to the extent of the existing scientific literature, this review focuses on systems installed in U.S. bridges over the last 20 years. These are all major factors that contribute to long-term degradation of bridges. Issues related to wireless sensor drifts are discussed as well. The scope of the paper is to help newcomers, practitioners, and researchers at navigating the many methodologies that have been proposed and developed in order to identify damage using data collected from sensors installed in real structures.

Hierarchical Reinforcement Learning

2021 ◽  
Vol 54 (5) ◽  
pp. 1-35
Author(s):  
Shubham Pateria ◽  
Budhitama Subagdja ◽  
Ah-hwee Tan ◽  
Chai Quek
Keyword(s):  
Reinforcement Learning ◽  
Future Research ◽  
Comprehensive Overview ◽  
Open Problems ◽  
Practical Applications ◽  
Hierarchical Reinforcement Learning ◽  
The Past ◽  
Agent Learning ◽  
Multi Agent ◽  
Supplementary Material

Hierarchical Reinforcement Learning (HRL) enables autonomous decomposition of challenging long-horizon decision-making tasks into simpler subtasks. During the past years, the landscape of HRL research has grown profoundly, resulting in copious approaches. A comprehensive overview of this vast landscape is necessary to study HRL in an organized manner. We provide a survey of the diverse HRL approaches concerning the challenges of learning hierarchical policies, subtask discovery, transfer learning, and multi-agent learning using HRL. The survey is presented according to a novel taxonomy of the approaches. Based on the survey, a set of important open problems is proposed to motivate the future research in HRL. Furthermore, we outline a few suitable task domains for evaluating the HRL approaches and a few interesting examples of the practical applications of HRL in the Supplementary Material.

scholarly journals Automatic Detection Technology of Sonar Image Target Based on the Three-Dimensional Imaging

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Wanzeng Kong ◽  
Jinshuai Yu ◽  
Ying Cheng ◽  
Weihua Cong ◽  
Huanhuan Xue
Keyword(s):  
Data Storage ◽  
3D Imaging ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Automatic Detection ◽  
Classification Model ◽  
Image Detection ◽  
Practical Applications ◽  
Sonar Image ◽  
Detection Technology

With 3D imaging of the multisonar beam and serious interference of image noise, detecting objects based only on manual operation is inefficient and also not conducive to data storage and maintenance. In this paper, a set of sonar image automatic detection technologies based on 3D imaging is developed to satisfy the actual requirements in sonar image detection. Firstly, preprocessing was conducted to alleviate the noise and then the approximate position of object was obtained by calculating the signal-to-noise ratio of each target. Secondly, the separation of water bodies and strata is realized by maximum variance between clusters (OTSU) since there exist obvious differences between these two areas. Thus image segmentation can be easily implemented on both. Finally, the feature extraction is carried out, and the multidimensional Bayesian classification model is established to do classification. Experimental results show that the sonar-image-detection technology can effectively detect the target and meet the requirements of practical applications.

Krankheitstheorien und Versorgungserwartung von Patienten sichtbar machen

Rhetorik ◽  
2018 ◽  
Vol 37 (1) ◽  
pp. 176-196
Author(s):  
Pablo Pirnay-Dummer ◽  
Inga Kampmann
Keyword(s):  
Mental Models ◽  
Large Data ◽  
Data Sets ◽  
Common Belief ◽  
Comprehensive Overview ◽  
Knowledge Maps ◽  
Comprehensive Knowledge ◽  
General Kind ◽  
Health Model ◽  
Patient Concerns

Abstract In this chapter, we present a new method for the medical field, which can contribute to patient-oriented care, especially in shared decision making. The mental models and conceptions of patients about their illness and the expected care determines their perception, decision and use of the care system - and thus they also influence the adherence. If the illness-health-model as part of the health literacy of the patients is known and recognized by the doctors throughout the decision-relevant processes, this facilitates a working patient-doctor relationship not only on a level of general kind communication. It helps doctors to better understand why patients decide in a certain way and why. By using the computer-linguistic methodology and software presented in this chapter, it is possible to automatically and objectively analyse, aggregate and cluster large data sets of written mental models and beliefs based on the patientsʼ models to create a comprehensive overview of common belief clusters. The results can be visualized on comprehensive knowledge maps and then used by the treating physicians. The knowledge maps are disease-specific and can - after a successful instruction and training - be used by physicians to improve the factual understanding of patient concerns.

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