• Smart Structures and Systems
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• v.23 no.3
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• pp.279-293
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• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1957-1963
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• 2017

This paper has proposed a new-type groundwater auto-monitoring system based on Multi-Sensor Device. The system adopted Multi-Sensor Device as host computer of data acquisition, used Windows Mobile which was prevalent operation system of Multi-Sensor Device. It adopted serial port CAN and RS485 as the communication interface between goundwater sensor Device and monitor host machine and utilized serial-linked multi-sensor design to measure effectively according to the depth of groundwater. We present a design for a groundwater monitoring system based on a network of wirelessly linked sensors. The proposed solution will enable groundwater researchers and decision makers to have quick access to the groundwater data with less effort and cost. Though our design is initially meant for groundwater monitoring, it can be easily adapted to other fields of environmental monitoring.

• Journal of Auto-vehicle Safety Association
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• v.3 no.2
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• pp.28-33
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• 2011

This paper presents driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. Through data collection, yaw rate filtering based road curvature and vision sensor road curvature characteristics are analyzed. Yaw rate filtering based road curvature and vision sensor road curvature are fused into the one curvature by weighting factor which are considering characteristics of each curvature data. The proposed driving path estimation algorithm has been investigated via simulation performed on a vehicle package Carsim and Matlab/Simulink. It has been shown via simulation that the proposed driving path estimation algorithm improves primary target detection rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.4
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• pp.344-365
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• 2009

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

• Journal of Welding and Joining
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• v.25 no.2
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• pp.49-54
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• 2007

Since the wall thickness can be up to 6" or greater, welds must be made in many layers, each layer containing several passes. However, the welding time for the conventional welding processes such as SAW(Submerged Arc Welding) and FCAW(Flux Cored Arc Welding) can be required many hours. The aim of this paper is to develop a high speed welding system with multi-torch and laser vision sensor for increasing the production speed on the line and to remove the need for the operator so that the system can run automatically for the complete multi-torch multi-layer weld. It was shown that the developed laser vision sensor and analysis of arc blow for multi-torch were effective for multi-pass seam tracking and stable arc. A new automated multi-torch welding systems for thick wall applications has been proved in several production lines.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.901-904
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• 2012

In this paper, we proposed the context-aware system which can estimate the information on the objects and transmit video information by utilizing multi-sensors. The proposed system is to reduce the excessive video information from a system capturing videos outdoor. This system uses the human-detect sensor attached on the multi-sensor board and four ultrasonic sensor to measure the object's size and movement speed, to recognize the human body's information, and finally to send videos. In order to assess the performance of the context-aware system based on the multi sensor, a comparison has been made between video system and human-detect sensor. As a result, The body human-detect sensor had more reliable images and transmitted information more effectively than when the images were sent by server without sensors attached.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.88.3-88
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• 2001

In this paper, an on-line multi-sensor visual inspection technique for seamless steel pipe´s straightness is developed. The basic principle of the visual measuring method is detailed. The modeling of visual sensor, measurement system and data processing are presented. In order to test the accuracy of the multi-sensor visual inspection, an experiment inspecting the straightness of a 1500mm long seamless steel pipe is made. The experiment results show that the visual inspection technique can achieve on-line measurement and offers high precision and stability.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.780-786
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• 2012

Surveillance has become one of promising application areas of wireless sensor networks which allow for pervasive monitoring of concerned environmental phenomena by facilitating context awareness through sensor fusion. Existing systems that depend on a postmortem context analysis of sensor data on a centralized server expose several shortcomings, including a single point of failure, wasteful energy consumption due to unnecessary data transfer as well as deficiency of scalability. As an opposite direction, this paper proposes an energy-efficient distributed context-aware surveillance in which sensor nodes in the wireless sensor network collaborate with neighbors in a distributed manner to analyze and aware surrounding context. We design and implement multi-modal sensor stations for use as sensor nodes in our wireless sensor network implementing our distributed context awareness. This paper presents an initial experimental performance result of our proposed system. Results show that multi-modal sensor performance of our sensor station, a key enabling factor for distributed context awareness, is comparable to each independent sensor setting. They also show that its initial performance of context-awareness is satisfactory for a set of introductory surveillance scenarios in the current interim stage of our ongoing research.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.31-38
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• 2012

The geo-referencing accuracy of the images acquired by a UAV based multi-sensor system is affected by the accuracy of the mounting parameters involving the relationship between a camera and a GPS/INS system as well as the performance of a GPS/INS system. Therefore, the estimation of the accurate mounting parameters of a multi-sensor system is important. Currently, we are developing a low altitude multi-sensor system based on a UAV, which can monitor target areas in real time for rapid responses for emergency situations such as natural disasters and accidents. In this study, we suggest a system calibration method for the estimation of the mounting parameters of a multi-sensor system like our system. We also generate simulation data with the sensor specifications of our system, and derive an effective flight configuration and the number of ground control points for accurate and efficient system calibration by applying the proposed method to the simulated data. The experimental results indicate that the proposed method can estimate accurate mounting parameters using over five ground control points and flight configuration composed of six strips. In the near future, we plan to estimate mounting parameters of our system using the proposed method and evaluate the geo-referencing accuracy of the acquired sensory data.

• Journal of Auto-vehicle Safety Association
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• v.8 no.4
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• pp.31-37
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• 2016

Since real road experiments have many restrictions, a multi-vehicle traffic simulator can be an effective tool to develop and evaluate fully automated driving systems. This paper presents multi-vehicle environment simulation tool to develop and evaluate motorway automated driving systems. The proposed simulation tool consists of following two main parts: surrounding vehicle model and environment sensor model. The surrounding vehicle model is designed to quickly generate rational complex traffic situations of motorway. The environment sensor model depicts uncertainty of environment sensor. As a result, various traffic situations with uncertainty of environment sensor can be proposed by the multi-vehicle environment simulation tool. An application to automated driving system has been conducted. A lane changing algorithm is evaluated by performance indexes from the multi-vehicle environment simulation tool.