Abstract
Population-based Structural Health Monitoring (PBSHM) considers grouping multiple structures into a single population, thus allowing additional insight to be gained from SHM feature data as a whole, compared to insights gained for any individual structure. Current data storage methodologies for SHM often operate from a single structure point of view. Different types of data can often be stored in different systems, files, structures and languages. This approach means that bespoke methodologies must be developed for any new SHM application, making analysing and processing of SHM data costly. The advantage of the proposed unified approach is the facilitation of information sharing across populations of structures, a key principle in PBSHM. A generic pool of methodologies can then be developed, allowing any set of PBSHM data to be quickly and efficiently analysed and processed, bringing down the total cost of running a system.
In this paper a PBSHM schema is defined to store multiple populations of PBSHM data inside a NoSQL database via a Time First approach. The schema allows a single database that organically grows as more data/knowledge about the population becomes available. As everything is grouped by Time, the approach allows previously unknown data relationships to be easily viewed. In this paper the PBSHM schema is implemented in a MongoDB database and sensor data are added into the system to show the ease of use of a standardised data schema.
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Notes
- 1.
- 2.
Sharding is a method of splitting data across multiple database instances.
- 3.
When using JavaScript to interact with the PBSHM Schema, there will be a loss of accuracy in the timestamps due to JavaScript only supporting 53 bytes in an Int64. This will also affect any interactions within the MongoDB Compass GUI tool as at the time of publishing this paper it is implemented in JavaScript.
- 4.
The file for installation within MongoDB is structure-data-compiled-mongodb.min.json.
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Acknowledgements
The authors of this paper gratefully acknowledge the support of the UK Engineering and Physical Sciences Research Council (EPSRC) through grant references EP/J016942/1, EP/K003836/2 and EP/S001565/1. The authors would also like to thank Vattenfall and Eoghan Maguire for providing the data set used within this paper.
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Appendices
Appendix 1: Non-organic Basic Schema
Please note that the example below uses the MongoDB bsonType instead of the JSON
Appendix 2: Organic Basic Schema
Please note that the example below uses the MongoDB bsonType instead of the JSON
Appendix 3: Accepted Channel Objects Within the v1.0 Schema
Types | Units | Values |
---|---|---|
acceleration | m/s 2, g, v, other | int, double, object |
velocity | m/s, v, other | int, double, object |
displacement | mm, cm, m, km, other | int, double, object |
angularAcceleration | degrees/s 2, radians/s 2, other | int, double, object |
angularVelocity | degrees/s, radians/s, other | int, double, object |
angularDisplacement | degrees, radians, other | int, double, object |
tilt | degrees, radians, other | int, double, object |
strain | nd, other | int, double, object |
tension | fN, pN, nN, μN, mN, cN, dN, N, daN, hN, kN, MN, GN, TN, PN, other | int, double, object |
load | fN, pN, nN, μN, mN, cN, dN, N, daN, hN, kN, MN, GN, TN, PN, other | int, double, object |
structuralPotentialHydrogen | pH, other | int, double, object |
temperature | C, F, K, other | int, double, object |
humidity | %, other | int, double, object |
speed | mph, ft/s, km/h, m/s, kn, other | int, double, object |
direction | degrees, radians, other | int, double, object |
pressure | fPa, pPa, nPa, μPa, mPa, cPa, dPa, Pa, daPa, hPa, kPa, MPa, GPa, TPa, PPa, at, atm, bar, psi, other | int, double, object |
altitude | mm, cm, m, km, feet, other | int, double, object |
pitch | degrees, radians, other | int, double, object |
yaw | degrees, radians, other | int, double, object |
roll | degrees, radians, other | int, double, object |
pitchRate | degrees/s, radians/s, other | int, double, object |
yawRate | degrees/s, radians/s, other | int, double, object |
rollRate | degrees/s, radians/s, other | int, double, object |
current | fA, pA, nA, μA, mA, cA, dA, A, daA, hA, kA, MA, GA, TA, PA, other | int, double, object |
charge | fC, pC, nC, μC, mC, cC, dC, C, daC, hC, kC, MC, GC, TC, PC, other | int, double, object |
power | fW, pW, nW, μW, mW, cW, dW, W, daW, hW, kW, MW, GW, TW, PW, other | int, double, object |
voltage | fV, pV, nV, μV, mV, cV, dV, V, daV, hV, kV, MV, GV, TV, PV, other | int, double, object |
resistance | fΩ, pΩ, nΩ, μ Ω, mΩ, cΩ, dΩ, Ω, daΩ, hΩ, kΩ, MΩ, GΩ, TΩ, PΩ, other | int, double, object |
capacitance | fF, pF, nF, μF, mF, cF, dF, F, daF, hF, kF, MF, GF, TF, PF, other | int, double, object |
inductance | fH, pH, nH, μH, mH, cH, dH, H, daH, hH, kH, MH, GH, TH, PH, other | int, double, object |
frequency | fHz, pHz, nHz, μHz, mHz, cHz, dHz, Hz, daHz, hHz, kHz, MHz, GHz, THz, PHz, other | int, double, object |
conductance | fS, pS, nS, μS, mS, cS, dS, S, daS, hS, kS, MS, GS, TS, PS, other | int, double, object |
magneticFlux | fWb, pWb, nWb, μWb, mWb, cWb, dWb, Wb, daWb, hWb, kWb, MWb, GWb, TWb, PWb, other | int, double, object |
magneticFieldStrength | fT, pT, nT, μT, mT, cT, dT, T, daT, hT, kT, MT, GT, TT, PT, other | int, double, object |
integer | n/a | int |
double | n/a | double |
text | n/a | string |
date | n/a | long |
Appendix 4: PBSHM Schema Installation
An example python script for installing the PBSHM Schema into a collection.
Appendix 5: Single vs Multiple File Channel Data
A JSON example showing equal Channel Data on a single file vs multiple files.
Appendix 6: PBSHM Database Querying
An example python script for querying the PBSHM Database.
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Brennan, D.S., Wickramarachchi, C.T., Cross, E.J., Worden, K. (2022). Implementation of an Organic Database Structure for Population-Based Structural Health Monitoring. In: Grimmelsman, K. (eds) Dynamics of Civil Structures, Volume 2. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-030-77143-0_3
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