1. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory A Programmable Sensor Network Based Structural Health Monitoring System Krishna Kant Chintalapudi Embedded Networking Laboratory, University of Southern California, Los Angeles, USA

2. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Agenda What’s the talk about ? What’s structural health monitoring (SHM)? SHM techniques and their impact on sensor network design Architecture design for sensor network based SHM A prototype – implementation and deployment What next?

3. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory What’s the talk about? A programmable sensor network based system for structural health monitoring What are the requirements of SHM applications? How do we architect a sensor network system to satisfy these requirements? A prototype and its performance

4. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Agenda What’s the talk about ? What’s structural health monitoring (SHM)? SHM techniques and their impact on sensor network design Architecture design for sensor network based SHM A prototype – implementation and deployment What next?

5. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory What Is Structural Health Monitoring (SHM)? Structural integrity assessment for buildings, bridges, offshore rigs, vehicles, aerospace structures etc. Goals of SHM are: – damage detection “is there damage?” – damage localization “where is the damage?” – damage quantification “how severe?” – damage prognosis “future prediction”

6. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory How Are Damages Caused? Extreme stress leading to fatigue in elements – several freeway bridges today bear traffic far exceeding tolerance levels they were originally designed to bear. Rusting and degradation of material properties – leads to change in stress distribution and overloading of certain elements more than others Continuous vibrations/cyclic stresses in the structure – waves shaking offshore oil-rigs, gales shaking bridges. Catastrophes (earthquakes)

7. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory How Do Damages Evolve? Most damages start as tiny cracks caused by metal fatigue (microns-mm). If unattended the cracks creep and grow in size leading to deterioration of the material. If unchecked, it eventually results in an unpredictable, sudden and catastrophic failure. SHM techniques focus on detection and localization of damages as early as possible.

8. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory SHM Today Today SHM is carried out by – collecting sensor data from several locations in the structure and analyzing it on a high end platform – periodic (bi-annual) human inspections (visual/using portable devices), – expensive and dedicated data-acquisition systems (for structures where monitoring is critical). SHM suffers from – human error and inaccessibility of locations within the structure – expensive labor (for inspection), cabling and installation (for data- acquisition systems) – possibility of catastrophic failure between inspections

9. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Agenda What’s the talk about ? What’s structural health monitoring (SHM)? SHM techniques and their impact on sensor network design Architecture design for sensor network based SHM A prototype – implementation and deployment What next?

10. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Local vs. Global Techniques Use sophisticated imaging techniques – 250KHz ultrasound, x-ray, thermal, magnetic etc. Use accelerometers to collect structural response. LOCAL GLOBAL Detect tiny cracks (mm/cm) and small corroded patches. Target larger damages e.g. undermined cables, braces or columns Can detect damages within a few inches of the equipment Detect structural damages in the entire structure

11. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Feasibility of Local SHM Techniques They are expensive, require a lot of power and bulky Demand extremely dense deployments Local SHM techniques are not amenable to sensor network deployments So let us focus on global schemes henceforth

12. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Ambient vs. Forced Excitation Low signal-to-noise ratio. Much higher signal-to-noise ratio. AMBIENTFORCED Rely on ambient sources (wind, passing vehicles, earthquakes) Rely on induced excitation (impact hammer, rotating mass etc.) Unpredictable in nature and timing Pre-meditated and precise. Require continuous monitoring; hard to implement duty cycles. Amenable to extremely low duty cycle functioning.

13. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Recall Our Goal… We want a system that SHM engineers can program … not experts in TinyOS We explore existing SHM schemes to find what SHM engineers want? We design our system based on requirements of SHM schemes.

14. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory What SHM Engineers want? What SHM Engineers want? Structural integrity assessment for buildings, bridges, offshore rigs, vehicles, aerospace structures etc. Today SHM engineers want: – damage detection “is there damage?” – damage localization “where is the damage?” – damage quantification “how severe?” – damage prognosis “future prediction”

15. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Structural Dynamics 101 Structures are no different from strings!!

16. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Structural Dynamics 101… Structural response is the spatio-temporal deformation induced in the structure. The dynamics of a structure are often expressed as, The impulse response is given by v l are mode shapes – normalized structural deformation patterns are modal/resonant frequencies of the structure are the amplitude and phase of the mode induced in the structure

17. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Structural Dynamics 101… mode shapes and frequencies are fundamental to the structure material properties, geometry and assemblage of elements depend on both the sensing and actuating locations mode are global phenomena – may span the entire structure

18. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory How Does Damage Affect Modes? Modal (resonant) frequencies and mode shapes change Modal frequencies decrease Break in symmetry of the structure may lead to splitting of overlapping modes and cause extra modes to appear Non-linearities may introduce new modes.

19. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Some practical aspects Modal frequencies are typically in the range of few tens of Hz Real structures are often heavily damped and decay within a second Most SHM engineers prefer 10 times oversampling Sampling rates desired are around 200-500Hz for most structures.

20. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Literature Review – Damage Detection Model the structural response using ARMA/AR based linear predictors and look for a significant change in coefficients. Look for shifts/changes in modal frequencies through spectral analysis. Look for changes in mode shapes. Use non-linear techniques such as neural networks. Literature is very vast

21. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Literature Review – Damage Localization Significantly more challenging and still a very hot research topic.. Time domain methods, model structure as a LTI system try to solve for A,B,C and D using response from all sensors compute stiffness of elements using A, B, C and D loss of stiffness indicates damage in an element

22. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Damage Localization Techniques… Frequency domain - estimate mode shapes using structural response from all sensors and use mode shapes to estimate stiffness of members ERA (Eigenvalue Realization Algorithm) – perform SVD on the Hankel matrix y is the impulse response vector Select modes corresponding to the high singular values to forma reduced order system, and calculate the modal vector matrix V using,

23. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory What’s common to SHM schemes? Inherently Centralized – Global nature of modes naturally leads to centralized algorithms for detection and localization. Can leverage local computation – Almost none of the schemes uses data in its raw form ARMA/AR models need coefficients Modal frequency based schemes need to use the estimated spectrum Compute these quantities locally and transmit instead of raw data. 40 ARMA coefficients instead of 5000 samples (over 99% savings!!!) Little or no collaboration/aggregation – most algorithms do not require inter-node collaboration (eg SVD is hard to decentralize)

24. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory How many sensors would a typical structure need? Strategies for deploying sensors Deploy a tri-axial sensor at the end of every member (damage localization/member) Divide the structure into sections and deploy a tri-axial sensor at every corner (damage localization/section) Number of sensors determines the granularity of localization (per floor? Per column?) A real structure can have several 100s of members/sections Local computation is absolutely critical

25. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory What are the requirements of SHM schemes? High data rates – 100 sensor will generate a few Mbps of data Reliable Delivery – SHM algorithms do not tolerate sample losses Time Synchronization - Required by most schemes error in time-synchronization manifests as phase error in modes error ~, the higher the modal frequency the more accuracy one needs For 1% error in a 20Hz mode, an accuracy of about 100 Local computation – data acquisition system based solutions will not scale

26. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Agenda What’s the talk about ? What’s structural health monitoring (SHM)? SHM techniques and their impact on sensor network design Architecture design for a programmable sensor network based SHM system A prototype – implementation and deployment What next?

27. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Recall Our Goal… We want a system that SHM engineers can program … in Matlab/C An SHM engineer should be able to write and test variety of algorithms without having to re-program the motes The system should be evolvable – a if better mote platform come, the SHM engineer should not need to rewrite his code

28. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Typical operation of an SHM system Sensors collect noise unless the structure is shaking!!! Ambient Schemes – rely on significant event (heavy wind, passing truck) Forced Schemes – rely on actuators (impact hammers) Structural Response lasts a few seconds!!! Sensors sleep unless an event occurs or the users requests actuators to test Sleep --- test/significant event ---- collect data and locally process --- transmit to central location --- sleep (wake once a day/ once a few hrs) SHM systems will be Triggered Systems

29. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Architecture Design Decisions Two-level Hierarchy – A higher more endowed layer is required to manage the aggregate data rates generated by the motes. Isolate Application code from mote code – Mote class devices provide a generic task interface but no application specific code getSamples(startTime, noSamples, sampFreq, axis) getFFTSamples(startTime,noSamples,sampFreq,a xis,fftSize) actuateStructure(startTime,type, parameters) conveyed to motes as tasking packets by gateway-class devices

30. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory What does code isolation buy us? Reusability – Application programmers can use the generic task interface and write many different SHM applications. Basic SHM library functions can me provided on motes fft, auto-correlation, ARMA coefficient estimation, spectral estimation etc. Evolvability – If a new mote comes along with greater processing power, just add new functionality, no need to rewrite application. Gateway class nodes translate C/Maltab application code into mote tasking commands

31. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Agenda What’s the talk about ? What’s structural health monitoring (SHM)? SHM techniques and their impact on sensor network design Architecture design for a programmable sensor network based SHM system A prototype – implementation and deployment What next?

32. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory We have a prototype function shifts = getModalShiftsFromBuilding() % create a group for sensors gidSensors = NetSHMCreateGroup([1,2,3,4]); %create a group for actuators gidActuators = NetSHMCreateGroup([5]); %actuate after 22 seconds NetSHMCmdActuate(gidActuators,22); %collect structural response starting 20 seconds from now, % 4000 samples at 200Hz,along x-axis only, samples = NetSHMCmdGetSamples(gidSensors,20,200,1,4); %find modal frequencies modes = findModes(samples); %read original modes load OriginalModes; shifts = findModalFreqShifts(modes,OriginalModes); A complete SHM test Matlab API Matlab functions implemented as wrappers over C functions Platform MicaZ and starGates

33. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory The Stacks

34. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory The API Groups – Every task is addressed to a group of sensors/actuators Create, AddNodes, DeleteNodes, ClearGroup etc Create returns a handle to the group Tasks – task(groupId, parameters) getSamples, getFFTSamples, getXCorrSamples, getModalFreqs, actuate etc.

35. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Mote Tasking Library Translates API commands into command packets to motes Uses TimeSynch Module to translate global time to sensor network time Dispatches command packets using the Reliability Layer Delivers results to applications according to API specifications A collection of C and Matlab Mex files

36. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Reliability Layer Transactional Delivery – Application expects results asynchronously Application issues a task Mote Tasking library breaks it up into commands Opens a connection to Reliability layer and sends command packet Reliability layer keeps connection open and forwards result packets to Mote Tasking Lib Mote Tasking Library aggregates results and returns to applications Takes care of out of order delivery Can handle several applications simultaneously OneShot Delivery – Application does not expect any results (e.g. Actuate)

37. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Time Synchronization Use FTSP Small modifications for compatibility with our code We use 28.8Khz timer and get accuracy to a few 100micro-sec All motes are synchronized to a single mote

38. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Routing Does not require any-to-any routing starGates to motes mote to starGates starGates to starGates both communication end points are never motes Routing Modules used starGate to starGate - a distance vector routing scheme, also passes on routes to motes motes to starGates – CENS Extensible Sensing System, starGates to motes – each node periodically transmits list of nodes in its sub-tree to its parent, the parent keeps a pointer on the reverse path We are still investigating better choices for routing

39. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Sensing Hardware MDA400 vibration cards from Crossbow high quality low power vibration sensing 16-bit samples, on board storage (64k) 0-20000Hz sensing 4 simultaneous channels driven by a micaZ Accelerometers high sensitivity (1v/g) low noise Actuators off-the shelf door latch devices motor control board interfaced to micaZ

40. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Deployment Seismic Test Structure Scaled Building Model

41. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Damage Detection and Localization on scaled model Building Details 48 inches high, 4 floors, 60 lbs Floors –1/2 x 12 x 18 aluminum plates steel 1/2 x 1/8 inch steel columns 5.5 lb/inch spring braces 4 actuators on the top floor 8 motes, 2/floor, dual axis, 200Hz, 2 starGates 4 Test Cases braces from floor 4 removed braces from floor 3 removed braces from floor 2 removed braces from floor 2 and 4 removed

42. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Performance Analysis on Seismic Test Structure Structure details Full scale imitation of a hospital ceiling (28’ by 48’) electric lights, drop ceiling, water pipes, fire sprinklers 55,000 lb actuator, 10 inch stroke, manually operated right now 15 micaZ motes, 2 starGates, 200Hz Latency and robustness to failure One starGate carrying most motes killed all samples recovered 3000 samples in about 5 minutes

43. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory Agenda What’s the talk about ? What’s structural health monitoring (SHM)? SHM techniques and their impact on sensor network design Architecture design for a programmable sensor network based SHM system A prototype – implementation and deployment What next?

44. UNIVERSITY OF SOUTHERN CALIFORNIA Embedded Networks Laboratory What next? Develop schemes that allow aggressive local computation for damage localization. Remotely actuate the Seismic Test Structure Developing local actuators for the Seismic Test Structure Damage Detection and Localization on the Seismic Test Structure Experiments on real bridges and structures with large scale deployments