Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Application of fiber optic sensors for vibration and ignition monitoring of a belt conveyor system

The belt conveyor serves as the main coal transport equipment in a coal mine and its safe operation is the lifeline of safety in coal mine production. However, traditionally, monitoring for ignition and for roller faults along the belt conveyor is problematic and so this paper puts forward an approach using radial grating vibration sensing technology for both belt conveyor roller vibration monitoring. This can then be used to predict the fault state in the roller and its position, using distributed optical fiber temperature measurement technology which can be used for hot spot monitoring'. This enables better fire prevention along the belt conveyor, which plays a positive and effective role in better mine safety

Review: optical fiber sensors for civil engineering applications

Optical fiber sensor (OFS) technologies have developed rapidly over the last few decades, and various types of OFS have found practical applications in the field of civil engineering. In this paper, which is resulting from the work of the RILEM technical committee “Optical fiber sensors for civil engineering applications”, different kinds of sensing techniques, including change of light intensity, interferometry, fiber Bragg grating, adsorption measurement and distributed sensing, are briefly reviewed to introduce the basic sensing principles. Then, the applications of OFS in highway structures, building structures, geotechnical structures, pipelines as well as cables monitoring are described, with focus on sensor design, installation technique and sensor performance. It is believed that the State-of-the-Art review is helpful to engineers considering the use of OFS in their projects, and can facilitate the wider application of OFS technologies in construction industry

Structural health monitoring and bridge condition assessment

Thesis (Ph.D.) University of Alaska Fairbanks, 2016This research is mainly in the field of structural identification and model calibration, optimal sensor placement, and structural health monitoring application for large-scale structures. The ultimate goal of this study is to identify the structure behavior and evaluate the health condition by using structural health monitoring system. To achieve this goal, this research firstly established two fiber optic structural health monitoring systems for a two-span truss bridge and a five-span steel girder bridge. Secondly, this research examined the empirical mode decomposition (EMD) method’s application by using the portable accelerometer system for a long steel girder bridge, and identified the accelerometer number requirements for comprehensively record bridge modal frequencies and damping. Thirdly, it developed a multi-direction model updating method which can update the bridge model by using static and dynamic measurement. Finally, this research studied the optimal static strain sensor placement and established a new method for model parameter identification and damage detection.Chapter 1: Introduction -- Chapter 2: Structural Health Monitoring of the Klehini River Bridge -- Chapter 3: Ambient Loading and Modal Parameters for the Chulitna River Bridge -- Chapter 4: Multi-direction Bridge Model Updating using Static and Dynamic Measurement -- Chapter 5: Optimal Static Strain Sensor Placement for Bridge Model Parameter Identification by using Numerical Optimization Method -- Chapter 6: Conclusions and Future Work

Damage identification in structural health monitoring: a brief review from its implementation to the Use of data-driven applications

The damage identification process provides relevant information about the current state of a structure under inspection, and it can be approached from two different points of view. The first approach uses data-driven algorithms, which are usually associated with the collection of data using sensors. Data are subsequently processed and analyzed. The second approach uses models to analyze information about the structure. In the latter case, the overall performance of the approach is associated with the accuracy of the model and the information that is used to define it. Although both approaches are widely used, data-driven algorithms are preferred in most cases because they afford the ability to analyze data acquired from sensors and to provide a real-time solution for decision making; however, these approaches involve high-performance processors due to the high computational cost. As a contribution to the researchers working with data-driven algorithms and applications, this work presents a brief review of data-driven algorithms for damage identification in structural health-monitoring applications. This review covers damage detection, localization, classification, extension, and prognosis, as well as the development of smart structures. The literature is systematically reviewed according to the natural steps of a structural health-monitoring system. This review also includes information on the types of sensors used as well as on the development of data-driven algorithms for damage identification.Peer ReviewedPostprint (published version

Design of a new method for detection of occupancy in the smart home using an FBG sensor

This article introduces a new way of using a fibre Bragg grating (FBG) sensor for detecting the presence and number of occupants in the monitored space in a smart home (SH). CO2 sensors are used to determine the CO2 concentration of the monitored rooms in an SH. CO2 sensors can also be used for occupancy recognition of the monitored spaces in SH. To determine the presence of occupants in the monitored rooms of the SH, the newly devised method of CO2 prediction, by means of an artificial neural network (ANN) with a scaled conjugate gradient (SCG) algorithm using measurements of typical operational technical quantities (indoor temperature, relative humidity indoor and CO2 concentration in the SH) is used. The goal of the experiments is to verify the possibility of using the FBG sensor in order to unambiguously detect the number of occupants in the selected room (R104) and, at the same time, to harness the newly proposed method of CO2 prediction with ANN SCG for recognition of the SH occupancy status and the SH spatial location (rooms R104, R203, and R204) of an occupant. The designed experiments will verify the possibility of using a minimum number of sensors for measuring the non-electric quantities of indoor temperature and indoor relative humidity and the possibility of monitoring the presence of occupants in the SH using CO2 prediction by means of the ANN SCG method with ANN learning for the data obtained from only one room (R203). The prediction accuracy exceeded 90% in certain experiments. The uniqueness and innovativeness of the described solution lie in the integrated multidisciplinary application of technological procedures (the BACnet technology control SH, FBG sensors) and mathematical methods (ANN prediction with SCG algorithm, the adaptive filtration with an LMS algorithm) employed for the recognition of number persons and occupancy recognition of selected monitored rooms of SH.Web of Science202art. no. 39

Research progress on coal mine laser methane sensor

This paper discusses the research progress of low-power technology of laser methane sensors for coal mine. On the basis of environment of coal mines, such as ultra-long-distance transmission and high stability, a series of studies have been carried out. The preliminary results have been achieved in the research of low power consumption, temperature and pressure compensation and reliability design. The technology is applied to various products in coal mines, and achieves high stability and high reliability in products such as laser methane sensor, laser methane detection alarm device, wireless laser methane detection alarm device, and optic fiber multichannel laser methane sensor. Experimental testing and analysis of the characteristics of laser methane sensors, combined with the actual application

A Survey on Communication Networks for Electric System Automation

Published in Computer Networks 50 (2006) 877–897, an Elsevier journal. The definitive version of this publication is available from Science Direct. Digital Object Identifier:10.1016/j.comnet.2006.01.005In today’s competitive electric utility marketplace, reliable and real-time information become the key factor for reliable delivery of power to the end-users, profitability of the electric utility and customer satisfaction. The operational and commercial demands of electric utilities require a high-performance data communication network that supports both existing functionalities and future operational requirements. In this respect, since such a communication network constitutes the core of the electric system automation applications, the design of a cost-effective and reliable network architecture is crucial. In this paper, the opportunities and challenges of a hybrid network architecture are discussed for electric system automation. More specifically, Internet based Virtual Private Networks, power line communications, satellite communications and wireless communications (wireless sensor networks, WiMAX and wireless mesh networks) are described in detail. The motivation of this paper is to provide a better understanding of the hybrid network architecture that can provide heterogeneous electric system automation application requirements. In this regard, our aim is to present a structured framework for electric utilities who plan to utilize new communication technologies for automation and hence, to make the decision making process more effective and direct.This work was supported by NEETRAC under Project #04-157

Effectiveness of OPC for systems integration in the process control information architecture

A Process is defined as the progression to some particular end or objective through a logical and orderly sequence of events. Various devices (e.g., actuators, limit switches, motors, sensors, etc.) play a significant role in making sure that the process attains its objective (e.g., maintaining the furnace temperature within an acceptable limit). To do these things effectively, manufacturers need to access data from the plant floor or devices and integrate those into their control applications, which maybe one of the off the shelf tools such as Supervisory Control and Data Acquisition (SCADA), Distributed Control System (DCS), or Programmable Logic Controllers (PLC). A number of vendors have devised their own Data Acquisition Networks or Process Control Architectures (e.g., PROFIBUS, DEVICENET, INTERBUS, ETHERNET I/P, etc.) that claim to be open to or interoperable with a number of third party devices or products that make process data available to the Process or Business Management level. In reality this is far from what it is claimed to be. Due to the problem of interoperability, a manufacturer is forced to be bound, either with the solutions provided by a single vendor or with the writing of a driver for each hardware device that is accessed by a process application. Today\u27s manufacturers are looking for advanced distributed object technologies that allow for seamless exchange of information across plant networks as a means of integrating the islands of automation that exist in their manufacturing operations. OLE for Process Control (OPC) works to significantly reduce the time, cost, and effort required in writing custom interfaces for hundreds of different intelligent devices and networks in use today. The objective of this thesis is to explore the OLE for Process Control (OPC) technology in depth by highlighting its need in industry and by using the OPC technology in an application in which data from a process controlled by Siemens Simatic S7 PLC are shared with a client application running in LabVTEW6i

Fiber bragg grating sensors for mainstream industrial processes

This paper reviews fiber Bragg grating sensing technology with respect to its use in mainstream industrial process applications. A review of the various types of sensors that have been developed for industries such as power generation, water treatment and services, mining, and the oil and gas sector has been performed. A market overview is reported as well as a discussion of some of the factors limiting their penetration into these markets. Furthermore, the author’s make recommendations for future work that would potentially provide significant opportunity for the advancement of fiber Bragg grating sensor networks in these mainstream industries