This research aims to develop a unique adhesion mechanism for wall climbing robot to
automate the technology of non-destructive testing (NDT) of large safety critical reinforced
concrete structures such as nuclear power plants, bridge columns, dams etc. This research
work investigates the effect of key design parameters involved in optimizing the adhesion
force achieved from rare earth neodymium magnets. In order to penetrate a nominal
concrete cover to achieve magnetic coupling with buried rebar and generate high enough
adhesion force by using minimum number of permanent magnets, criteria such as distance
between multiple magnets, thickness of flux concentrator are evaluated by implementing
finite element analysis (FEA).
The proposed adhesion module consists of three N42 grade neodymium magnets
arranged in a unique arrangement on a flux concentrator called yoke. The preliminary FEA
results suggest that, using two yoke modules with minimum distance between them
generate 82 N higher adhesion force compared to a single module system with higher forceto-weight
ratio of 4.36. Presence of multiple rebars in a dense mesh setting can assist the
adhesion module to concentrate the magnetic flux along separate rebars. This extended
concentration area has led to higher adhesion force of 135.73 N as well as enabling the
robot to take turns. Results suggest that, having a 50×50 mm rebar meshing can sustain
steep robot rotational movement along it’s centre of gravity where the adhesion force can
fall as low as 150 N. A small, mobile prototype robot with on-board force sensor is built
that exhibited 3600
of manoeuvrability on a 50×50 mm meshed rebars test rig with
maximum adhesion force of 108 N at 35 mm air gap. Both experiment and simulationresults prove that the magnetic adhesion mechanism can generate efficient adhesion force
for the climbing robot to operate on vertical reinforced concrete structures.
In terms of the NDT sensor, an in-depth analysis of the ground penetrating radar (GPR)
is carried out to develop a low cost operational laboratory prototype. A one-dimensional
numerical framework based on finite difference time domain (FDTD) method is developed
to model response behaviour of a GPR. The effects of electrical properties such as dielectric
constant, conductivity of the media are evaluated. A Gaussian shaped pulse is used as
source which propagates through the 1D array grid, and the pulse interactions at different
media interfaces are investigated. A real life application of GPR to detect a buried steel bar
in 1 m thick concrete block is modelled, and the results present 100% accurate detection of
the steel bar along with measured depth of the concrete cover. The developed framework
could be implemented to model multi-layer dielectric blocks with detection capability of
various buried objects. Experimental models are built by utilizing a proposed antenna
miniaturization technique of dipole antenna with additional radiating arms. The resultant
reflection coefficient values indicate a reduction of 55% and 44% in length reduction
compared to a conventional 100 MHz and 200 MHz dipole antenna respectively. The GPR
transmitting pulse generator features an enhanced tuneable feature to make the GPR system
more adaptable to various environmental conditions. The prototype pulse generator circuit
can produce pulses with variable width from 750 ps to 10 ns. The final assembled robotic
GPR system’s performance is validated by its capability of detecting and localizing an
aluminium sheet and a rebar of 12 mm diameter buried under a test rig built of wood to
mimic the concrete structure environment. The final calculations reveal a depth error of
+0.1 m. However, the key focus of this work is to prove the design concept and the error
in measurement can be addressed by utilizing narrower bandwidth pulse that the proposed
pulse generator is capable of generating. In general, the proposed robotic GPR system
developed in this research proves the concept of feasibility of undertaking inspection
procedure on large concrete structures in hazardous environments that may not be
accessible to human inspector
