A bayesian probabilistic approach to structural health monitoring

A Bayesian probabilistic methodology for on-line structural health monitoring which addresses the issue of parameter uncertainty inherent in problem is presented. The method uses modal parameters for a limited number of modes identified from measurements taken at a restricted number of degrees of freedom of a structure as the measured structural data. The application presented uses a linear structural model whose stiffness matrix is parameterized to develop a class of possible models. Within the Bayesian framework, a joint probability density function (PDF) for the model stiffness parameters given the measured modal data is determined. Using this PDF, the marginal PDF of the stiffness parameter for each substructure given the data can be calculated.

Monitoring the health of a structure using these marginal PDFs involves two steps. First, the marginal PDF for each model parameter given modal data from the undamaged structure is found. The structure is then periodically monitored and updated marginal PDFs are determined. A measure of the difference between the calibrated and current marginal PDFs is used as a means to characterize the health of the structure. A procedure for interpreting the measure for use by an expert system in on-line monitoring is also introduced.

The probabilistic framework is developed in order to address the model parameter uncertainty issue inherent in the health monitoring problem. To illustrate this issue, consider a very simplified deterministic structural health monitoring method. In such an approach, the model parameters which minimize an error measure between the measured and model modal values would be used as the "best" model of the structure. Changes between the model parameters identified using modal data from the undamaged structure and subsequent modal data would be used to find the existence, location and degree of damage. Due to measurement noise, limited modal information, and model error, the "best" model parameters might vary from one modal dataset to the next without any damage present in the structure. Thus, difficulties would arise in separating normal variations in the identified model parameters based on limitations of the identification method and variations due to true change in the structure. The Bayesian framework described in this work provides a means to handle this parametric uncertainty.

The probabilistic health monitoring method is applied to simulated data and laboratory data. The results of these tests are presented.

Some statistical aspects of the long-term gill net monitoring programme for pike Esox lucius in Windermere (English Lake District)

For more than 55 years, data have been collected on the population of pike Esox lucius in Windermere, first by the Freshwater Biological Association (FBA) and, since 1989, by the Institute of Freshwater Ecology (IFE) of the NERC Centre for Ecology and Hydrology. The aim of this article is to explore some methodological and statistical issues associated with the precision of pike gill net catches and catch-per-unit-effort (CPUE) data, further to those examined by Bagenal (1972) and especially in the light of the current deployment within the Windermere long-term sampling programme. Specifically, consideration is given to the precision of catch estimates from gill netting, including the effects of sampling different locations, the effectiveness of sampling for distinguishing between years, and the effects of changing fishing effort.

Stillwaters monitoring programme summary results 2000

This is the Stillwaters monitoring programme summary results 2000 from the Environment Agency. In May 1997, a Stillwaters meeting was held to discuss the way forward in stillwaters monitoring. It decided upon the establishment of a three year rolling programme, in which three stillwaters would be monitored three times a year, every third year. During 2000, stillwaters monitored for the fourth year of the Stillwaters Monitoring Programme were Hatch Mere, Marbury Big Mere, Comber Mere, Tabley Mere, Tatton Mere and Melchett Mere. Algal, zooplankton and water chemical samples were taken on all meres. Surveys of Tabley Mere and Comber Mere continued on from last year when water quality concerns were highlighted. Continuous monitoring in Oak Mere, including water level data continued in 2000. Fish surveys were carried out in Tatton Mere and Comber Mere. Tabley Mere survey was abandoned due to the awkward bathymetry of the mere. No invertebrate samples were taken in 2000 due to lack of resources.

Stillwaters monitoring programme. Summary results 2001 and 2002

This is the Stillwaters monitoring programme. Summary results 2001 and 2002 from the Environment Agency North West. Until January 2001 the South Area Stillwaters Sampling Programme consisted of a rolling programme where five to six stillwaters were sampled three times a year (spring, summer and autumn). However, this method was not yielding the water quality information required for long term monitoring. Local weather conditions influence short-term water quality events, e.g. algal blooms, nutrient consumption, stratification, super-saturation etc, so results from one day sampling could only be regarded as individual ‘spot’ samples. Therefore year-on-year comparisons could not be made. It was decided that long-term water quality monitoring of the stillwaters would benefit more from sampling nutrient abundance over winter months. This would give an insight into the carry-over of nutrients available for algal growth the following year and so year-on-year productivity could be assessed. Survey results shown in this report were from: The Mere, Rostherne Mere, Melchett Mere, Tabley Mere, Tatton Mere, Hatchmere, Oak Mere, Black Lake, Chapel Mere, Bar Mere, Oss Mere, Marbury Big Mere, Comber Mere and Betley Mere.

Stillwaters monitoring programme.Summary results 2003 and 2004

This is the Stillwaters monitoring programme. Summary results 2003 and 2004 from the Environment Agency North West. This report is focuses in The Winter Monitoring of Stillwaters Programme, which began in January 2001 with the aim of gathering long term data on nutrient abundance over winter months. This allows assessment of nutrient ‘carry-over’ available for algal growth in the following year, plus year-on-year productivity. 14 stillwaters are monitored each year. The environmental issues associated with each Stillwater are summarised in the table below. Bank-side water samples are taken for nutrients (N, P and S) and chlorophyll. A YSI multi-parameter sonde measures temperature, pH, specific conductivity and dissolved oxygen (% saturation). Survey results shown in this report came from: Oak Mere and Bar mere.

Stillwaters monitoring programme. Summary results 2004 and 2005

This is the Stillwaters monitoring programme. Summary results 2004 and 2005 from the Environment Agency North West. This report focuses on the 5th year of winter monitoring analysis in 14 stillwaters in Cheshire. The 14 stillwaters analysed are: Comber Mere, Oss Mere, Marbury Big Mere, Chapel Mere, Bar Mere, Oak Mere, Hatch Mere, Black Lake, Betley Mere, Tabley Mere, Melchett Mere, Tatton Mere, Rostherne Mere and Mere mere. Nutrient availability in the stillwaters analysed is used to look into the productivity of the waterbody. Bank-side water samples were taken for nutrients (Nitrogen and Phosphorous) and chlorophyll. A YSI multi-parameter sonde measures temperature, pH, specific conductivity and dissolved oxygen (% saturation).

Analysis of structural health monitoring data from hammersmith flyover

There has recently been considerable research published on the applicability of monitoring systems for improving civil infrastructure management decisions. Less research has been published on the challenges in interpreting the collected data to provide useful information for engineering decision makers. This paper describes some installed monitoring systems on the Hammersmith Flyover, a major bridge located in central London (United Kingdom). The original goals of the deployments were to evaluate the performance of systems for monitoring prestressing tendon wire breaks and to assess the performance of the bearings supporting the bridge piers because visual inspections had indicated evidence of deterioration in both. This paper aims to show that value can be derived from detailed analysis of measurements from a number of different sensors, including acoustic emission monitors, strain, temperature and displacement gauges. Two structural monitoring systems are described, a wired system installed by a commercial contractor on behalf of the client and a research wireless deployment installed by the University of Cambridge. Careful interpretation of the displacement and temperature gauge data enabled bearings that were not functioning as designed to be identified. The acoustic emission monitoring indicated locations at which rapid deterioration was likely to be occurring; however, it was not possible to verify these results using any of the other sensors installed and hence the only method for confirming these results was by visual inspection. Recommendations for future bridge monitoring projects are made in light of the lessons learned from this monitoring case study. © 2014 This work is made available under the terms of the Creative Commons Attribution 4.0 International license,.

Towards persistent structural health monitoring through sustainable wireless sensor networks

This paper documents the design, implementation and characterisation of a wireless sensor node (GENESI Node v1.0), applicable to long-term structural health monitoring. Presented is a three layer abstraction of the hardware platform; consisting of a Sensor Layer, a Main Layer and a Power Layer. Extended operational lifetime is one of the primary design goals, necessitating the inclusion of supplemental energy sources, energy awareness, and the implementation of optimal components (microcontroller(s), RF transceiver, etc.) to achieve lowest-possible power consumption, whilst ensuring that the functional requirements of the intended application area are satisfied. A novel Smart Power Unit has been developed; including intelligence, ambient available energy harvesting (EH), storage, electrochemical fuel cell integration, and recharging capability, which acts as the Power Layer for the node. The functional node has been prototyped, demonstrated and characterised in a variety of operational modes. It is demonstrable via simulation that, under normal operating conditions within a structural health monitoring application, the node may operate perpetually.

Bridge-vehicle interaction for structural health monitoring: potentials, applications, and limitations

Structural Health Monitoring (SHM) is an integral part of infrastructure maintenance and management systems due to socio-economic, safety and security reasons. The behaviour of a structure under vibration depends on structure characteristics. The change of structure characteristics may suggest the change in system behaviour due to the presence of damage(s) within. Therefore the consistent, output signal guided, and system dependable markers would be convenient tool for the online monitoring, the maintenance, rehabilitation strategies, and optimized decision making policies as required by the engineers, owners, managers, and the users from both safety and serviceability aspects. SHM has a very significant advantage over traditional investigations where tangible and intangible costs of a very high degree are often incurred due to the disruption of service. Additionally, SHM through bridge-vehicle interaction opens up opportunities for continuous tracking of the condition of the structure. Research in this area is still in initial stage and is extremely promising. This PhD focuses on using bridge-vehicle interaction response for SHM of damaged or deteriorating bridges to monitor or assess them under operating conditions. In the present study, a number of damage detection markers have been investigated and proposed in order to identify the existence, location, and the extent of an open crack in the structure. The theoretical and experimental investigation has been conducted on Single Degree of Freedom linear system, simply supported beams. The novel Delay Vector Variance (DVV) methodology has been employed for characterization of structural behaviour by time-domain response analysis. Also, the analysis of responses of actual bridges using DVV method has been for the first time employed for this kind of investigation.