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

INE/AUTC 10.0

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

Condition Monitoring of Power Cables

A National Grid funded research project at Southampton has investigated possible methodologies for data acquisition, transmission and processing that will facilitate on-line continuous monitoring of partial discharges in high voltage polymeric cable systems. A method that only uses passive components at the measuring points has been developed and is outlined in this paper. More recent work, funded through the EPSRC Supergen V, UK Energy Infrastructure (AMPerES) grant in collaboration with UK electricity network operators has concentrated on the development of partial discharge data processing techniques that ultimately may allow continuous assessment of transmission asset health to be reliably determined

FBG-based fibre-optic current sensors for power systems protection : laboratory evaluation

Conventional differential current unit protection schemes rely on a pair of electronic protection relays that measure current phasors separately at the boundaries of the protected zone. The scheme requires a separate, often optical, communications channel for the sharing of measurement information to enable the timely identification of and reaction to internal faults. The high voltage environment that the transducers must operate in poses a number of engineering problems stemming from the need for electrical isolation and requirement for transformation of high primary system current magnitudes. Additionally, when either the number of relays or distance between relays is increased, timing problems can arise due to the limited bandwidth, speed and changeable latencies of the communication channels and the increased computation requirements. Fibre-optical sensor systems are maturing as a technology and offer a number of advantages over conventional electronic sensor regimes, including the possession of inherent electrical isolation, chemical inertness, immunity to electromagnetic interference, and their small size and serial multiplexing capability. Fibre sensor systems are therefore experiencing increased uptake in industries that operate in harsh environments, such as oil and gas, or where specific requirements such as large step-out distances or resistance to radiation prohibit the use of electronic sensors. The Advanced Sensors Team within the Institute for Energy and Environment has developed fibre-optic point sensors for voltage and electrical current, based on fibre Bragg grating (FBG) technology, that have been applied successfully to power systems diagnostics. With the photonic systems capability to interrogate up to 100 km from source at kHz sample rates with up to 30 sensors in series, it is possible and highly desirable to adapt this technology for use in power systems protection, where immediate applications in unit and distance protection are clear. In this paper, the application of the FBG-based hybrid current sensor system to power systems protection is presented for the first time. Experimental tests of the response of an optical unit protection system to a range of internal and external fault scenarios are also reported. Secondary current inputs to the system are modelled using ATP and injected into the prototype test system via an APTS3 (Advanced Protection Testing System) unit. Fibre sensors, separated optically by 24 km of fibre, provide all measurement information via a single interrogation system situated at one end of the protected zone. Experimental results confirm high performance of the optical unit protection both in terms of sensitivity to internal faults and stability under external fault conditions. Therefore, the systems ability to overcome problems experienced in electronic relaying systems using conventional current sensing technologies is demonstrated. No separate communications channel is required in this configuration, with fault algorithms being deployed only at one location that need not be close to the protected zone. The fibre-optic current sensor systems capacity for long-distance interrogation and high sensor count qualify it for further applications in more complex protection schemes, or over larger distances, where a single fibre could form the basis of highly novel distributed protection schemes. This potential will also be discussed in detail in the paper

Extraction of the beam elastic shape from uncertain FBG strain measurement points

Aim of the present paper is the analysis of the strain along the beam that is equipped with Glass Fibers Reinforced Polymers (GFRP) with an embedded set of optical Fiber Bragg Grating sensors (FBG), in the context of a project to equip with these new structural elements an Italian train bridge. Different problems are attacked, and namely: (i)during the production process [1] it is difficult to locate precisely the FBG along the reinforcement bar, therefore the following question appears: How can we associate the strain measurements to the points along the bar? Is it possible to create a signal analysis procedure such that this correspondence is found?(ii)the beam can be inflected and besides the strain at some points, we would like to recover the elastic shape of the deformed beam that is equipped with the reinforcement bars. Which signal processing do we use to determine the shape of the deformed beam in its inflection plane?(iii)if the beam is spatially inflected, in two orthogonal planes, is it possible to recover the beam spatial elastic shape? Object of the paper is to answer to these questions

Applied Fiber Optic Measurement for Geohydraulic Engineering

Engineers have long sought the possibility of measuring parameters such as temperature and pressure continuously in the underground with high precision, high spatial resolution and high band width of parameters. Distributed fibre optic measurement offers the use of a very fast, robust, precise, light and small gauges with an high spatial resolution. In this paper we would like to compile fibre-optic measure-methods which are available now for projects in geohydraulical engineering. This paper will propose new problems for future research work on parameter identification for such parameters as conductivity and anisotropy