Wireless structural health monitoring from research to reliable application

Transcription

1 Wireless structural health monitoring from research to reliable application Markus Krüger MPA Universität i Stuttgart & TTI GmbH TGU Smartmote The Gartner Hyper Cycle

2 The Gartner Hyper Cycle 2010 Important aspects of using WSNs 4 Restrictions of WSNs for structural monitoring limited it energy limited sampling rates Limited reliability limited calculation power & limited bandwidth (wireless communication) usability limited robustness costs Solutions Power efficient hardware and software (sensors, network topology, communication protocols, time synchronisation etc.) In-mote processing is strongly recommended (low-power analysis techniques and algorithms that allow efficient data reduction) Automation of analysis 2

3 Wireless Structural Health Monitoring 5 The problem: No one wants to have Gigabytes of data without knowing how to use it There are questions that have to be answered which could be: Does the measured structural behavior correspond to the structural design? Are there deterioration processes I can conclude from the monitoring? Could I predict the remaining lifetime of the structure? When and how do I have to maintain the structure? The large amount of complex data has to be reduced to only a few values which are sufficient to answer these questions (Data fusion and adequate analysis methods and models) SMooHS project EU Project 7 th framework program Smart Monitoring of Historic Structures (SMooHS) Call Environmental Technologies: Protection, conservation and enhancement of cultural heritage, including human habitat 14 Partners Project start: December 2008 Duration: 36 month Coordinator: Markus Krüger 3

4 SMooHS consortium Research oriented partners Technological oriented partners End-user organisations and conservation-restoration oriented partners N NAME SHORT NAME COUNTRY 1 MPA Universität Stuttgart MPA.USTUTT Germany 2 AuRA Restorer AURA Germany 3 IWB Universität Stuttgart USTUTT Germany 4 Accademia Europea Bolzano EURAC Italy 5 Alma Mater Studiorum Universitá di Bologna UNIBO Italy 6 Rathgen Research Laboratory - National Museums Berlin RRL Germany 7 Polish Academy of Sciences PASc Poland 8 Technisches h Büro Käferhaus TBK Austria 9 TTI GmbH TGU Smartmote TTI Germany 10 Metalmobile S.R.L. Metalmobile Italy 11 Artemis srl Artemis Italy 12 Consorzio Cetma CETMA Italy 13 Riwaq - Centre for Architectural Conservation RIWAQ Palestinianadministered areas 14 University of Zagreb UNIZAG Croatia SMooHS - Motivation Establish smart monitoring systems based on wireless sensors that are inexpensive, robust and can support the preservationists The main deterioration causes of historic structures are related to: environmental factors (such as temperature, humidity, frost, wind, rain, air pollution,...) mechanical actions (loads, vibrations, ground settlements,...) ageing To this aim it is necessary: to completely know the deterioration causes and processes to have a continuous knowledge of the actual health state of the structure to receive in real time alarms of critical situations 4

5 SMooHS Project Goals Consequently the needs are: increasing i the number and variety of parameters to be monitored using wireless systems (aesthetical reasons, applicability) cost reduction development of models capable of interpreting the data acquired and their trends, with reference to damage situations and evolution, in order to assess the actual health state sending out warnings in real time, in order to trigger subsequent actions Project distribution of work MONITORING Temperature Humidity Dust Gases Light CONTINUOUS Salts INPUT Deformation Crack opening Acoustic emissions Accelerations Vibrations DATA FUSION Methods & algorithms for data reduction, e.g. material & deterioration models ONE-T TIME INP UT TESTING Material characteristics Other parameters for the models CONTINUOUS OUTPUT Information Deterioration rate Accumulated dose Alarms (e.g. sound, light, automatic SMS, etc.) Actions (e.g.window opening/closing, ventilation on/off, heating on/off, etc.) INFORMATION WARNINGS ACTIONS 5

6 Project structure WP 1 Management WP 2 Technical Guidance Core work packages WP 3 Monitoring techniques WP 4 WP 5 Modelling & Analysis Comparative Testing WP 6 Case Studies WP 7 Dissemination & Exploitation Examples of sensor node platforms 12 Intel (imote ) Moteiv Infineon Crossbow Teco UC Berkeley 6

7 Smart wireless sensor nodes Smartmote WS Wireless Sensor Multi-Sensor Board Multi-Sensor Board Wireless Communication Module (Backside of Processor Board) Power Supply Acceleration Sensor Board Processor Board Programming Adapter (USB/JTAG) Examples of sensors (under evaluation) Acceleration (Si-Flex SF1500L) Event detection (acceleration) (Bosch SMB380) Inclination (VTI SCA830-D07) Air velocity (Hot wire) Solar irradiance (Pyranometer SP-212) UV-B (Genicom GUVA-T10GD) A combination of sensor information is necessary for a reliable interpretation of data (false alarm reduction) 7

8 Multihop sensor networks 15 Multihop-network + theoretically no limit in network size + low interference due to short distance communication + power efficient topology especially at large sensor networks if certain data loss is acceptable - complex programming and configuration - Inefficient for event based monitoring - Power consuming if high data reliability is needed Hybrid Star Sensor Network + Easy programming and configuration + Efficient for event based monitoring + most power efficient topology if high data reliability is needed (mote specific duty cycles) - Limited network size 8

9 WSN in a simple application System reliability Data transfer success rate of Sensor [ID] Status 51 43e e e e 35 7e Date 9

10 Modelling & Analysis Aspects: Risk index (example Dew Temperature) Microclimate modelling Salt modelling & measurement Hygrothermal material properties Structural modelling Model coupling Modelling & Analysis Aspects: Risk index (example Dew Temperature) Microclimate modelling Example: dewdegreetime (K-time unit) Calculation of dew temperature according Magnus Tetens Salt modelling & measurement Hygrothermal material properties Structural modelling Model coupling 10

11 Modelling & Analysis Moisture /Salt monitoring & modelling Aspects: Risk index (example ( l D Dew TTemperature) t ) Microclimate modelling Salt modelling & measurement Hygrothermal material properties Structural modelling Model coupling Modelling & Analysis Aspects: Risk index (example ( l D Dew TTemperature) t ) Microclimate modelling Maximum principal stresses under self weight and given displacements Salt modelling & measurement Hygrothermal material properties Structural modelling Model coupling Static and dynamic modelling 2nd mode 11

12 Modelling & Analysis Aspects: Diffusion with damage Risk index (example Dew Temperature) Microclimate modelling Salt modelling & measurement Hygrothermal material properties Structural modelling Model coupling Example: Fine modelling of masonry wall brick-by-brick interactions as interface elements, simulating the mortar joint mechanics and physics, e.g.: damage, friction, diffusion Case studies (3 climate zones) Polychrome Portals of the Holy Cross Minster Schwäbisch Gmünd, Germany Main office of the Province of Bologna, Italy Museums Island, Berlin, Germany Old town of Hebron, Palestinian administered areas Schönbrunn chapel -Schönbrunn Palace, Vienna, Austria 12

13 Conclusions Wireless sensor networks will become accepted, but Their application must be simple (installation, data interpretation, calibration); They must provide integrated data analysis and interpretation (automatized procedures); They must allow remote control and reconfiguration; They should have stable long term behaviour (to be tested in reality) and data reliability must be provable ; They must be open for different sensor technologies (multi sensor platform); They have to be competitive. Thank you for your attention! Combined Workshop of European Collaborative Projects (SMooHS, Climate for Culture, CHIC) & SMooHS Workshop in Berlin, Sep./Oct Details soon available: Ongoing Monitoring Campaigns: Acknowledgements SMooHS Smart monitoring of historic structures is funded by the European Commission under grant # as well as by the Forschungsinitiative Zukunft Bau" of the BBR and the BMVBS of Germany under reference AZ: SF / II 3 F