Intelligent monitoring of dam safety

15 June 2007



Eliane Alves Portela presents an overview of the use of intelligent systems in the safety control of dams, emphasising the role of information technology to enhance the structures safety assessment and potential for new developments in the future


A successful monitoring programme for evaluating dam safety conditions is one that provides the right type and amount of data, at the right time, with an acceptable level of accuracy and in a form that can be readily processed and interpreted. To set up a monitoring system it is necessary to have a good knowledge of the engineering problem under consideration and to know and fully understand the objectives of the monitoring programme. This provides the basis for deciding on what to monitor, when to make observations, for how long, and at how many points.

All parameters of rock and concrete used in the structure design are measured and tested on a small scale; since it is not economically feasible or practical to install enough instruments to monitor the whole area of a dam. Thus, the location and the number of measurement points must be selected carefully. This is normally done on the basis of engineering judgment derived from past experience, supported by numerical modelling to determine beforehand the most beneficial locations to place instruments.

For the structure safety control the collection of unnecessary data should be avoided so that attention can be focused on the critical parameters that need to be monitored and which will provide early indication of a developing safety problem. Subsets of instruments can be assigned for real-time monitoring to track the vital signs of the structure and can be used as a primary detection network. Thus, less frequent readings are possible for the designated secondary instruments. However, care should be taken in selecting the primary detection instruments to assure that adequate coverage is achieved so that an undesirable developing condition will be detected.

The ultimate measure of success of monitoring programmes lies in the quality and completeness of the data obtained from instruments and the ability to efficiently process and evaluate data collected from extensive instrumentation arrays – particularly delivered by the automatic data acquisition systems. Emerging techniques present a new challenge in the field of structural health monitoring and encourage the development of new practical monitoring methodologies.

A framework for dam monitoring

Electronics and internet technologies are increasingly facilitating real-time monitoring. The advances in wireless communications are allowing practical deployment for large extended systems. Sensor data, including video signals, can be used for long-term condition assessment, emergency response and safety assessment applications. Computer-based automated signal-analysis algorithms routinely process the incoming data and determine anomalies based on pre-defined response thresholds. Upon authentication, appropriate action may be authorised for a strategy, data from thousands of sensors can be analysed with real-time and long-term assessment and decision making implications.

The framework for dam monitoring should network and integrate online real-time heterogeneous sensor data, database and archiving systems, computer vision information, data analysis and interpretation strategies, numerical simulation of complex structural systems, visualisation, probabilistic risk analysis, historical case strategies, and rational statistical decision-making procedures. Such a decision-support system will no doubt contribute to a large extent to overcome the old dilemma ‘data-rich, information-poor: the modern monitoring syndrome’.

The objective is to improve usability of information technology applications and services and access the knowledge they embody in order to encourage their wider adoption and faster deployment. The focus is on technologies to support the process of acquiring and modelling, navigating and retrieving, representing and visualising, interpreting and sharing knowledge.

Intelligent interfaces can provide more effective ways of accessing ubiquitous information and hide the complexity of technology by supporting a seamless human interaction between humans, humans and devices, virtual and physical objects and the knowledge embedded in everyday environments. This includes research on virtual and augmented reality.

Figure 1 depicts a framework for dam safety assessment. This framework integrates web-based environment key elements for dam monitoring and for the structure safety assessment.

The benefits of using new technology may include: (1) increased data reliability; (2) reduction in the labour required to collect and evaluate data; (3) timely results allowing efforts to be focused on the evaluation of the data rather than the process of data collection/reduction; (4) allowing real-time monitoring of the structure performance; and (5) a better understanding of the structure’s performance so that changes can be identified in a timely manner and corrective actions taken.

Data and information storage capabilities

Dam performance assessment relies not only in the seeing eyes of the monitoring system – the instrumentation – but rather in a complexity of data sources, including different types of sensors, photos and video inspection data, geodetic survey data, design history (material properties, hydrology and hydraulics, seismicity, geology and geotechnic), construction history (foundation preparation, materials of construction, seepage control, joint sealing), operational history (rapid drawdown, earthquakes, extreme flooding), and regulatory requirements, etc.

To provide storage capabilities and on hand access for such a complex set of information a high-performance database management system is required. The capabilities of the database management system include: capture or extract data from different sources (including multimedia objects) for inclusion in the database; update (add, delete, edit, change) data records and files; interrelate data from different sources; retrieve data from the database for queries and reports; provide comprehensive data security (such as protection from unauthorised access recovery capabilities); and perform complex data manipulation tasks based on queries.

Enhanced analysis capability

Modelling structural behaviour is a complex process in which one should consider the nonlinear behaviour of materials, interaction between the structure and its foundation, influence of water load on the structure and its foundation bedrock and environmental actions, such as the influence of ambient temperature. However, despite the complexity of the model, they encompass a number of simplifications of the real world, uncertainties of model parameters are always present.

Thus, careful monitoring of the dam and its surroundings is required in order to verify and enhance the model. Once the model is set up, by comparing results of monitoring measurements with a prediction model it is possible to determine if the structure still behaves as expected.

A number of different techniques are being used for structural modelling. It is not always clear whether one technique gives better results than another. Some rules of thumb are emerging regarding the selection and choice of method. Innovative ways of combining the different techniques, especially when data is limited or incomplete, or when there is complementary additional knowledge available, are opening up a number of different areas for research.

In dam engineering, the set up of the monitored quantities expected range is very often based on statistical and/or deterministic models, also referred as behaviour models. New areas of research include techniques such as data-mining for complex query processing to provide query support to the structural analyst and neural network for prediction of monitored quantities. Neural networks do not require information concerning the phenomenological nature of the system being investigated, which makes them a robust means for representing model-unknown systems encountered in specific dam engineering problems.

In such cases, the data-driven model is dependent entirely on the data. There is real danger here since there is a strong temptation to focus the modelling on the available data and to ignore the physical situation. In fact it could be stated that data driven modelling cannot be guaranteed to give a safe and reliable result unless there is proper attention given to the physics of the problem [1].

The model base managements major tasks are: create models easily and quickly, either from scratch or from existing models; allow users to manipulate models so that they can conduct experiments and sensitivity analysis ranging from what-if to goal seeking; storage, retrieving and managing a wide variety of different types of models in a logical and integrated manner; catalogue and display the directory of models; track model data and application use; interrelate models with appropriate linkages with the database; manage and maintain the model base with management functions: store, access, run, update, link, catalogue, and query; and finally use multiple models to support problem solving.

Knowledge-base capabilities

Skill and judgement are required to properly evaluate dam performance. The value of using experienced engineering judgment cannot be underestimated. However, a number of factors are common to the performance of all dams. Moreover, there very often exist interrelationships among the common factors and other performance factors. An understanding of these factors is important in making the transition from data to knowledge and in unravelling the mysteries of dam performance [2].

The objectives of knowledge management systems are to create knowledge repositories, improve knowledge access, enhance the knowledge environment, and manage knowledge as an asset.

Highly increasing computing power and technology could make possible the use of complex intelligent systems architectures for diagnosis, decision-making, modelling and analysis, taking advantage of more than one intelligent technique, not in a competitive, but rather in a collaborative sense.

Intelligent interfaces

A well-designed, intuitive, and appealing user interface is crucial to the success of the structure monitoring and assessment system. Ambient intelligence1 will become an important part of the framework puzzle and it will become unthinkable to demand users become acquainted with hundreds of systems; rather, these systems themselves have to be usable in an efficient and appealing way, must be adaptive and intuitive, context-sensitive and, often, personalised. Therefore, new approaches to automatic, on-the-fly creation of user oriented, ergonomic interfaces must be pursued.

The GestBarragens project

An evolving project named GestBarragens [3, 4, 5], which is the result of a close collaboration of three Portuguese institutions (LNEC2, INESC-ID3 and EDP4), depicts key elements of the envisioned integrated dam monitoring framework. The overall research project was proposed by LNEC and is currently deployed in the organisational context of LNEC and EDP. GestBarragens is a result of a successful partnership between dam experts and information system professionals.

An integrated system of structural dam monitoring, GestBarragens is a multi-user web-based solution and was built on the basis of a modular approach. In this way the system is accessible via a web client (e.g., Internet Explorer or Mozilla) in an Intranet or Internet context by a proper user access authentication control.

System background

GestBarragens system was designed and developed to replace the previous system used to store monitoring data from the main Portuguese concrete dams. This system was written in the 70’s, in Fortran, and the underlying information was stored in binary and ASCII files. Through the years new requirements have arisen concerning the type and variety of information to be stored as well as the functionalities offered by the system.

Thus, the primary goal of the GestBarragens system was to import and store data from previous data repositories into an integrated information system, ensuring the security continuity and follow up of the previous system. Data collected over 50 years from more then 50 dams migrated to GestBarragens without loosing its integrity.

GestBarragens requirements were set up by a team of dam experts and included, among others, the following features:

• Multi-user and remote access for information sharing.

• Security by using predefined personal profile and personal privileges.

• Acquisition and storage of manual, semi-automatic and automatic measurements as well as remarks related to the data acquisition process, instrumentation, or information concerning any unusual event, such as a change on the reading devices or leakages in drain sealing. It should also be possible to store a dam biography.

• Generic software, embracing all types of instruments in use and allowing the easy addition of new types of instruments.

• Immediate and on site checking of the plausibility of the measurements results (based on data history or simple models).

• Easy transfer of data to graphic interpreter.

• Remote access to the database for storing and/or exporting operations either by modem, cable net or through the Web.

• Clear, automatic and unique system of identification of each measuring point.

• Checking and validation of data.

• Easy to expand.

• Friendly and intelligent user interface.

GestBarragens modules

The main modules of the GestBarragens system are shown in Figure 2 and described below:

• GB-Support – this module integrates tasks such as users/entities management (users/entities with different roles or functions in the safety control process), dam attributes and history.

• GB-Observations – this is the module where all data collected from existing monitoring systems are stored, including data from manual, semi-automatic or automatic acquisition systems. Data validation and check for anomalies is carried out before storage. The management of instruments and measurement devices can be done in this module (location, installation date, measuring devices features, calibration details, etc.). It is also possible to prepare a field inspection sheet which will support the field personnel during an inspection. This module has a special component to support geodetic inspections. The module has basic functionalities such as data capture, storage and recall, presentation and report facilities.

• GB-Visual Inspection – this module allows the storage of all information collected by the field personnel during visual inspections. Reports on routine or special visual inspection can be easily retrieved from the system and integrated with numerical data collected from the monitoring system for the structure safety assessment.

• GB-Tests and Analysis – this module stores information on material properties provided by specific tests and analysis.

• GB-Models – supports the dam modelling process. It assists the user with a user-friendly interface to perform structural analysis based on available models or provide support for the creation of new models.

• GB-Documental – stores historical documents, reports, photos drawings, etc. Any document can be uploaded to the system in digital format and linked to the dam and to a specific inspection and become available to system users upon proper user authentication.

• GB-SIG – the visualisation component of GestBarragens integrates geo-referenced information acting as a graphical user interface and allows database inquires. Special attention is dedicated to data analysis with spatial visualisation of the dam; on the top of the structure, it is possible to show different layers that represent specific types of instruments. It provides drawings of the dam and its elements, key cross-sections, key location of instruments, basic graphics functionalities such as time history plots, scatter/correlation plots, position plots (data from multiple instruments at a particular cross section and time), attachment of comments to data points, etc.

The web interface provides mechanisms that allow users to easily navigate and explore physical elements of the dam. They are able to monitor mouse click events for instance to select a dam or an instrument type; or activate common GIS features such as zoom, pan, undo, redo , measures, printing, spatial objects identification and information.

Reports for all modules are available on user request in the web interface or they can be produced for MsWord, MsExcel, or Adobe Acrobat outputs. They include text, tables and graphs; pre-defined report sets of tables and graphs; data maximum and minimum values; correlation reports between model pre-defined values and observed values; alarm thresholds; instrument configuration report and instrument history report; inspections and observations reports; photos, videos and documents reports.

Due to modularity and expandability of the GestBarragens system new modules can be added to the system in the future. Current on-going efforts are directed towards the implementation of the GestBarragens system for large concrete dams in Portugal (approximately 120 structures).

Future developments include its extension to other types of dams and the development of new modules to improve real-time condition assessment.

Conclusions

Increased awareness of safety issues in modern society call for an increased level of sophistication of means and methods of control. Sound decisions must be based on relevant and reliable information that is readily accessible through an affordable medium. The evolution of intelligent information systems has been a major contributing factor to the development, implementation and maturation of computerised systems to support safety control activities of civil engineering works.

There is no doubt that for the engineers in charge to assess the performance of their many dam projects and preparing the annual safety reports is a very labour-intensive and unpopular task. The implementation of intelligent information systems can significantly reduce the labour effort required and improve the quality of the information.

The end result is that engineering personnel will be able to utilise their time evaluating data in a timely manner to continually monitor the performance of the many dams that they are responsible for. Assessing the short and long term safety conditions is extremely easy and data are permanently at the disposal of the engineers and the experts in charge of the dams.

This paper reports the application of an integrated framework system to support the safety control activities of concrete dams, the GestBarragens system. The technologies and processes discussed in the context of dam engineering can be extrapolated with benefits to other areas of civil engineering.


Footnotes

1. The term Ambient Intelligence is defined by the Advisory Group to the European Community’s Information Society Technology Program (ISTAG) as ‘the convergence of ubiquitous computing, ubiquitous communication, and interfaces adapting to the user’.
2. Laboratorio Nacional de Engenharia Civil, Lisbon, Portugal
3. Instituto de Engenharia de Sistemas e Computadores, Investigacao e Desenvolvimento, Lisbon, Portugal
4. Electricidade de Portugal, Porto, Portugal
5. Programa de Incentivos a Modernizacao da Economia, Portuguese Ministry of Economy – Medida 5. Accao C, Projecto 03/00289

Author Info:

Elaine Alves Portela, Concrete dams Department, Laboratório Nacional de Engenharia Civil (LNEC), Portugal

Support of GestBarragens project was provided by PRIME5 and LNEC.

GestBarragens is the outcome of an interdisciplinary and multi-institutional collaboration research team (LNEC, INESC-ID and EDP) leading to a versatile integrated web-based framework for monitoring and assessment of concrete dams. The author wishes to acknowledge the contribution of all participants in the GestBarragens project (http://lacerta.lnec.pt/gestbarragens).

This paper is based on a presentation given at the 5th International Conference on Dam Engineering, held from 14-16 February 2007 in Lisbon, Portugal. For more details on the event visit www.cipremier.com or email [email protected]



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