Inpil Kang

A carbon nanotube strain sensor for structural health monitoring

A carbon nanotube polymer material was used to form a piezoresistive strain sensor for structural health monitoring applications. The polymer improves the interfacial bonding between the nanotubes. Previous single walled carbon nanotube buckypaper sensors produced distorted strain measurements because the van der Waals attraction force allowed axial slipping of the smooth surfaces of the nanotubes. The polymer sensor uses larger multi-walled carbon nanotubes which improve the strain transfer, repeatability and linearity of the sensor. An electrical model of the nanotube strain sensor was derived based on electrochemical impedance spectroscopy and strain testing. The model is useful for designing nanotube sensor systems. A biomimetic artificial neuron was developed by extending the length of the sensor. The neuron is a long continuous strain sensor that has a low cost, is simple to install and is lightweight. The neuron has a low bandwidth and adequate strain sensitivity. The neuron sensor is particularly useful for detecting large strains and cracking, and can reduce the number of channels of data acquisition needed for the health monitoring of large structures.

Structural health monitoring using continuous sensors and neural network analysis

A method for damage detection in a plate structure is presented based on strain waves that are generated by foreign object impact on the structure, or by damage that is propagating in the structure. The response characteristics of continuous sensors, which are long ribbon-like sensors, were studied by simulation of wave propagation in a panel. The advantage of the continuous sensor is to improve damage detection by having a large coverage of sensors on the structure using a small number of channels of data acquisition. Strain responses from the continuous sensors were used to estimate the damage location using a neural network technique. Eight hundred numerical wave propagation simulation runs for a plate were carried out to train the neural network and verify the proposed method for damage localization. The identified damage locations agreed reasonably well with the exact damage locations. Overall, the approach presented is meant to simplify the instrumentation needed for damage detection by using continuous sensors, a small number of channels of data acquisition, and training a neural network to do the work of locating the damage source.

A Study on Way-Point Tracking of AUV using State Feedback

For way-point tracking of an autonomous underwater vehicle, a state feedback controller was designed by using pole placement scheme in discrete time domain. In the controller, 4 state variables were used for regulating the depth of the vehicle in z direction, and 3 state variables, for steering the vehicle in xy plane. Assuming constant speed of AUV, we simplified the design of the way-point tracking system. The proposed controller was simulated by MATLAB/Simulink using 6 degree-of-freedom nonlinear model and its performance of way point tracking was shown to be fulfilled within 1 m, nevertheless the proposed controller is quite simple and easy to implement compared to sliding mode controller.

Multifunctional carbon nanofiber/nanotube smart materials

This paper discusses the development of new multifunctional smart materials based on Carbon Nanofibers (CNF) and Multi-Wall Carbon Nanotubes (MWCNT). The material properties of CNF/MWCNT are a little lower than the properties of Single Wall Carbon Nanotubes (SWCNT). However, the CNF/MWCNT have the potential for more practical applications since their cost is lower. This paper discusses the development of four CNF/MWCNT-based sensors and actuators. These are: (i) an Electrochemical Wet Actuator for use in a liquid electrolyte, (ii) an Electrochemical Dry Actuator for use in a dry environment, (iii) a Bioelectronic sensor; and (iv) a MWCNT neuron for structural health monitoring. These materials are exciting because of their unique properties and many applications.

A Spray-On Carbon Nanotube Artificial Neuron Strain Sensor for Composite Structural Health Monitoring

We present a nanocomposite strain sensor (NCSS) to develop a novel structural health monitoring (SHM) sensor that can be easily installed in a composite structure. An NCSS made of a multi-walled carbon nanotubes (MWCNT)/epoxy composite was installed on a target structure with facile processing. We attempted to evaluate the NCSS sensing characteristics and benchmark compared to those of a conventional foil strain gauge. The response of the NCSS was fairly good and the result was nearly identical to the strain gauge. A neuron, which is a biomimetic long continuous NCSS, was also developed, and its vibration response was investigated for structural damage detection of a composite cantilever. The vibration response for damage detection was measured by tracking the first natural frequency, which demonstrated good result that matched the finite element (FE) analysis.

Mimicking the biological neural system using electronic logic circuits

Detecting and locating cracks in structural components and joints that have high feature densities is a challenging problem in the field of Structural Health Monitoring. There have been advances in piezoelectric sensors, actuators, wave propagation, MEMS, and optical fiber sensors. However, few sensor-signal processing techniques have been applied to the monitoring of joints and complex structural geometries. This is in part because maintaining and analyzing a large amount of data obtained from a large number of sensors that may be needed to monitor joints for cracks is difficult. Reliable low cost assessment of the health of structures is crucial to maintain operational availability and productivity, reduce maintenance cost, and prevent catastrophic failure of large structures such as wind turbines, aircraft, and civil infrastructure. Recently, there have also been advances in development of simple passive techniques for health monitoring including a technique based on mimicking the biological neural system using electronic logic circuits. This technique aids in reducing the required number of data acquisition channels by a factor of ten or more and is able to predict the location of a crack within a rectangular grid or within an arbitrarily arranged network of continuous sensors or neurons. The current paper shows results obtained by implementing this method on an aluminum plate and joint. The plates were tested using simulated acoustic emissions and also loading via an MTS machine. The testing indicates that the neural system can monitor complex joints and detect acoustic emissions due to propagating cracks. High sensitivity of the neural system is needed, and further sensor development and testing on different types of joints is required. Also indicated is that sensor geometry, sensor location, signal filtering, and logic parameters of the neural system will be specific to the particular type of joint (material, thickness, geometry) being monitored. Also, a novel piezoresistive carbon nanotube nerve crack sensor is presented that can become a neuron and respond to local crack growth.

Flexible strain sensor based on carbon nanotube rubber composites

Electrically conducting rubber composites (CRC) with carbon nanotubes (CNTs) filler have received much attention as potential materials for sensors. In this work, Ethylene propylene diene M-class rubber (EPDM)/CNT composites as a novel nano sensory material were prepared to develop flexible strain sensors that can measure large deformation of flexible structures. The EPDM/CNT composites were prepared by using a Brabender mixer with multi-walled CNTs and organo-clay. A strain sensor made of EPDM/CNT composite was attached to the surface of a flexible beam and change of resistance of the strain sensor was measured with respect to the beam deflection. Resistance of the sensor was change quite linearly under the bending and compressive large beam deflection. Upon external forces, CRC deformation takes place with the micro scale change of inter-electrical condition in rubber matrix due to the change of contact resistance, and CRC reveals macro scale piezoresistivity. It is anticipated that the CNT/EPDM fibrous strain sensor can be eligible to develop a biomimetic artificial neuron that can continuously sense deformation, pressure and shear force.

A Biomimetic Artificial Neuron Matrix System Based on Carbon Nanotubes for Tactile Sensing of e-Skin

In this study, a carbon nanotube (CNT) flexible strain sensor was fabricated with CNT based epoxy and rubber composites for tactile sensing. The flexible strain sensor can be fabricated as a long fibrous sensor and it also may be able to measure large deformation and contact information on a structure. The long and flexible sensor can be considered to be a continuous sensor like a dendrite of a neuron in the human body and we named the sensor as a biomimetic artificial neuron. For the application of the neuron in biomimetic engineering, an ANMS (Artificial Neuron Matrix System) was developed by means of the array of the neurons with a signal processing system. Moreover, a strain positioning algorithm was also developed to find localized tactile information of the ANMS with Labview for the application of an artificial e-skin.

Carbon Nanotube Smart Materials for Biology and Medicine

This chapter is an overview of potential applications of carbon nanotube smart materials in biology and medicine. Carbon nanotube arrays are forests of aligned nanotubes prepared on a substrate. The nanotubes have multifunctional properties that include high strength, sensing, actuation, and electronic properties. Several prototype smart material devices using nanotube arrays or nanotubes from the array are being developed by various groups that are co-authors of this chapter. The new devices include a biosensor, electrochemical actuator, nanotube probes, and a concept for a future in-body biosensor. Recently, aligned multi-wall carbon nanotube arrays over 1 cm tall were synthesized on large area substrates using a chemical vapor deposition process. The technique for growing nanotubes on large area substrates will open the door for low cost manufacturing of novel sensors, actuators, and devices for biology and medicine.

Direct grafting imidazolium-based poly(ionic liquid) onto multiwalled carbon nanotubes via Diels-Alder “click” reaction

ABSTRACT A facile route for grafting poly(ionic liquid)s (PILs) on to the surface of multi-walled carbon nanotubes (MWNTs) was demonstrated via Diels-Alder (DA) “click” reaction. Firstly, block copolymers of poly(chloromethylstyrene-alt-maleic anhydride) (PCMA) were prepared by the reversible addition-fragmentation chain transfer (RAFT) polymerization. The anhydride units in the copolymer were functionalized with furfuryl amine and then the chloromethyl groups were subsequently tailored with 1-methylimidazole, which afforded imidazolium-based PILs bearing pendent furan moieties. The PILs chains were covalently anchored to the surface of MWNTs, affording PILs/MWNTs by the DA reaction in water under ultrasound assistance. The obtained hybrid materials were characterized by TGA, FT-IR, and TEM analysis. The PILs/MWNTs could be well dispersed in water and organic solvents for several months.