• Smart Structures and Systems
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• v.2 no.3
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• pp.275-293
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• 2006

For health monitoring purpose usually the structure is instrumented with a large scale and multichannel measurement system. In case of highway bridges, operating vehicle could be utilized to reduce the number of measuring devices. First this paper presents a static damage detection algorithm of using operating vehicle load. The technique has been validated by finite element simulation and simple laboratory test. Next the paper presents an approach of using this technique to field application. Here operating vehicle load data has been used by instrumenting the bridge at single location. This approach gives an upper hand to other sophisticated global damage detection methods since it has the potential of reducing the measuring points and devices. It also avoids the application of artificial loading and interruption of any traffic flow.

• Smart Structures and Systems
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• v.13 no.5
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• pp.775-796
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• 2014

This study presents a vibration-based health monitoring strategy for short span bridges utilizing an inspection vehicle. How to screen the health condition of short span bridges in terms of a drive-by bridge inspection is described. Feasibility of the drive-by bridge inspection is investigated through a scaled laboratory moving vehicle experiment. The feasibility of using an instrumented vehicle to detect the natural frequency and changes in structural damping of a model bridge was observed. Observations also demonstrated the possibility of diagnosis of bridges by comparing patterns of identified bridge dynamic parameters through periodical monitoring. It was confirmed that the moving vehicle method identifies the damage location and severity well.

• Journal of Auto-vehicle Safety Association
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• v.12 no.1
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• pp.52-61
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• 2020

In recent years, the increasing interest in health-care requires the industrial products to be well-designed ergonomically. In the commercial vehicle industry, several researchers have demonstrated the driver's posture has great effect on the orthopedic desease such as fatigue, back pain, scoliosis, and so on. However, the existing sensor systems developed for measuring the driver posture in real time have suffered from inaccuracy and low reliability issues. Here, we suggest our smart vehicle seat system capable of real-time driver posture monitoring by using the air bag sensor package with high sensitivity and reliability. The ergonomic numerical model which can evaluate a driver's posture has been developed on the basis of the human body segmentation method followed by simulation-based validation. Our experimental analysis of obtained pressure distribution of a vehicle seat under the different driver's postures revealed our smart vehicle system successfully achieved the driver's real-time posture data in great agreement with our numerical model.

• Journal of Power Electronics
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• v.11 no.4
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• pp.424-429
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• 2011

In this paper, the simulator of an on-line monitoring system for the range extender electric vehicle has been developed. The messages from the four control modules, the air pressure and fuel level sensors data, and the on/off switching states of 31 indicator lamps can be received through the control area network (CAN), and displayed on the graphic panel. The simulator was designed using the four DSP boards, variable resistors, and toggle switches instead of the four control modules, sensors, and switching state of indicator lamps on an actual series hybrid electric vehicle (SHEV) bus, respectively. The performance of the monitoring technologies was verified with the simulator at the laboratory, and then it was tested on an actual SHEV bus. The simulator is very useful at the initial development of the monitoring system at the hybrid-type or electrical vehicles.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.909-910
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• 2006

In this paper, the transfer function to the vehicle is derived from using system identification algorithm in connection with the driving vehicle. We design the adaptive cruise controller using the derived transfer function, and make it possible to monitoring and control the vehicle in real time using embedded system and technology of Internet.

• Structural Monitoring and Maintenance
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• v.9 no.4
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• pp.305-321
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• 2022

Bridge structural health monitoring with the aim of continuously assessing structural safety and reliability represents a topic of major importance for worldwide infrastructure managers. In the last two decades, due to their potential economic and operational advantages, drive-by approaches experienced growing consideration from researcher and engineers. This work addresses two technical topics regarding indirect frequency estimation methods: bridge and vehicle dynamics overlapping, and bridge expansion joints impact. The experimental campaign was conducted on a mixed multi-span bridge located in Lombardy using a Ford Galaxy instrumented with a mesh of wireless accelerometers. The onboard time series were acquired for a number of 10 passages over the bridge,performed at a travelling speed of 30 km/h, with no limitations imposed to traffic. Exploiting an ad-hoc sensors positioning, pitch vehicle motion was compensated, allowing to estimate the first two bridge bending frequencies from PSD functions; moreover, the herein adopted approach proved to be insensitive to joints disturbance. Conclusively, a sensitivity study has been conducted to trace the relationship between estimation accuracy and number of trips considered in the analysis. Promising results were found, pointing out a clear positive correlation especially for the first bending frequency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.98-101
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• 2009

Recently, there is use of the vehicle network for vehicle diagnostic method and Increased use of the vehicle protocol such as (CAN(Controller Area Network), MOST, LIN, FlexRay), Distributed control and data about the vehicle are being sought methods for real-time observation and monitoring and trend tends to have gone into this. In this case of automotive diagnostic module in today, there is Primarily to use DLC(Data Link Connector)Connector called self-check terminal. Generally, vehicle Diagnoses to use DLC Connector such as OBD2(On Board Diagnostics) Through Diagnostic Module(scanner). But there limit diagnostic as engine and powertrain part, and not consider user's perspective In this paper, By designing Vehicle diagnostic monitoring system using Ethernet Port, transmit and Receives CAN protocol vehicle data, and implement Easily monitoring system that provide and Diagnoses to provide vehicle's state and information to use PC.

• Smart Structures and Systems
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• v.24 no.6
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• pp.723-732
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• 2019

Globally road transport networks are subjected to continuous levels of stress from increasing loading and environmental effects. As the most popular mean of transport in the UK the condition of this civil infrastructure is a key indicator of economic growth and productivity. Structural Health Monitoring (SHM) systems can provide a valuable insight to the true condition of our aging infrastructure. In particular, monitoring of the displacement of a bridge structure under live loading can provide an accurate descriptor of bridge condition. In the past B-WIM systems have been used to collect traffic data and hence provide an indicator of bridge condition, however the use of such systems can be restricted by bridge type, assess issues and cost limitations. This research provides a non-contact low cost AI based solution for vehicle classification and associated bridge displacement using computer vision methods. Convolutional neural networks (CNNs) have been adapted to develop the QUBYOLO vehicle classification method from recorded traffic images. This vehicle classification was then accurately related to the corresponding bridge response obtained under live loading using non-contact methods. The successful identification of multiple vehicle types during field testing has shown that QUBYOLO is suitable for the fine-grained vehicle classification required to identify applied load to a bridge structure. The process of displacement analysis and vehicle classification for the purposes of load identification which was used in this research adds to the body of knowledge on the monitoring of existing bridge structures, particularly long span bridges, and establishes the significant potential of computer vision and Deep Learning to provide dependable results on the real response of our infrastructure to existing and potential increased loading.

• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.259-266
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• 2005

In this paper, we developed a vehicle condition monitoring system that checks vehicle conditions, and transmits and displays them to a driver for safety and effective maintenance. We used a CAN controller and transceiver to establish the CAN communication that has been used commonly inside an actual vehicle for the collection of vehicle's status information. To validate the operation of the developed system, we have confirmed the accuracy and stability of data transmission and reception of vehicle information.

• Smart Structures and Systems
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• v.13 no.5
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• pp.755-773
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• 2014

The natural frequency of a bridge is an important parameter in many engineering applications such as bridge seismic design and modal-based bridge health monitoring. The natural frequency of a bridge vibrating alone may differ from that vibrating along with a vehicle. Although such vehicle-induced variability in bridge frequency is revealed in several experimental and numerical simulation studies, few attempts have been made on the theoretical descriptions. In this study, both theoretically and experimentally, the variability in the bridge frequency induced by a parked vehicle is verified, and is therefore suggested to be considered in bridge-related engineering, especially for those cases with near vehicle-bridge resonance conditions or with large vehicle-to-bridge mass ratios. Moreover, the variability ranges could be estimated by an analytical formula presented herein.