The High Speed Railway Hub of Florence: 4D-monitoring – data integration and real-time post-processing during construction phase

2013 ◽  
pp. 1387-1394
Author(s):  
P Cucino ◽  
G Eccher ◽  
C Meyer
2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Ding Youliang ◽  
Wang Gaoxin

Studies on dynamic impact of high-speed trains on long-span bridges are important for the design and evaluation of high-speed railway bridges. The use of the dynamic load factor (DLF) to account for the impact effect has been widely accepted in bridge engineering. Although the field monitoring studies are the most dependable way to study the actual DLF of the bridge, according to previous studies there are few field monitoring data on high-speed railway truss arch bridges. This paper presents an evaluation of DLF based on field monitoring and finite element simulation of Nanjing DaShengGuan Bridge, which is a high-speed railway truss arch bridge with the longest span throughout the world. The DLFs in different members of steel truss arch are measured using monitoring data and simulated using finite element model, respectively. The effects of lane position, number of train carriages, and speed of trains on DLF are further investigated. By using the accumulative probability function of the Generalized Extreme Value Distribution, the probability distribution model of DLF is proposed, based on which the standard value of DLF within 50-year return period is evaluated and compared with different bridge design codes.


Agriculture ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 180 ◽  
Author(s):  
Ha Quang Thinh Ngo ◽  
Thanh Phuong Nguyen ◽  
Hung Nguyen

The supervision and feeding of grazing livestock are always difficult missions. Since animals act based on habits, the real-time monitoring data logger has become an indispensable instrument to assist farmers in recognizing the status of livestock. Position-tracked and acoustic monitoring have become commonplace as two of the best methods to characterize feeding performance in ruminants. Previously, the existing methods were limited to desktop computers and lacked a sound-collecting function. These restrictions impacted the late interventions from feeders and required a large-sized data memory. In this work, an open-source framework for a data collector that autonomously captures the health information of farm animals is introduced. In this portable hardware, a Wireless Location Acoustic Sensing System (WiLASS) is integrated to infer the health status through the activities and abnormal phenomena of farming livestock via chew–bite sound identification. WiLASS involves the open modules of ESP32-WROOM, GPS NEO-6M, ADXL335 accelerometer, GY-MAX4466 amplifier, temperature sensors, and other signal processing circuits. By means of wireless communication, the ESP32-WROOM Thing micro-processor offers high speed transmission, standard protocol, and low power consumption. Data are transferred in a real-time manner from the attached sensing modules to a digital server for further analysis. The module of GPS NEO-6M Thing brings about fast tracking, high precision, and a strong signal, which is suitable for highland applications. Some computations are incorporated into the accelerometer to estimate directional movement and vibration. The GY-MAX4466 Thing plays the role of microphone, which is used to store environmental sound. To ensure the quality of auditory data, they are recorded at a minimum sampling frequency of 10 KHz and at a 12-bit resolution. Moreover, a mobile software in pocket devices is implemented to provide extended mobility and social convenience. Converging with a cloud-based server, the multi-Thing portable platform can provide access to simultaneously supervise. Message Queuing Telemetry Transport (MQTT) protocol with low bandwidth, high reliability, and bi-direction, and which is appropriate for most operating systemsOS, is embedded into the system to prevent data loss. From the experimental results, the feasibility, effectiveness, and correctness of our approach are verified. Under the changes of climate, the proposed framework not only supports the improvement of farming techniques, but also provides a high-quality alternative for poor rural areas because of its low cost and its ability to carry out a proper policy for each species.


2020 ◽  
Vol 53 (3-4) ◽  
pp. 757-763
Author(s):  
Jingbo Xu ◽  
Xiaomeng Cui ◽  
Wenbo Ma

Changes in temperature and stress will lead to the rail creeping of high-speed railway, which becomes a hidden danger in the operation of trains. This paper studies a real-time visual measurement system for creeping displacement monitoring. The bilateral line extraction to determine the target location overcomes the influence of ambient light on image grayscale. The dynamic region of interest setting method is produced to lock and track the target. The self-calibration technology makes the system suitable for field application. The remote transmission of monitoring data is realized through narrow band internet of things (NB-IOT). These methods solve the problems in practical application. The monitoring system provides a reliable guarantee for the safe and stable operation of high-speed railway.


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